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class="c-article-identifiers" data-test="article-identifier"> <li class="c-article-identifiers__item" data-test="article-category">Article</li> <li class="c-article-identifiers__item"> <a href="https://www.springernature.com/gp/open-research/about/the-fundamentals-of-open-access-and-open-research" data-track="click" data-track-action="open access" data-track-label="link" class="u-color-open-access" data-test="open-access">Open access</a> </li> <li class="c-article-identifiers__item">Published: <time datetime="2024-07-12">12 July 2024</time></li> </ul> <h1 class="c-article-title" data-test="article-title" data-article-title="">Specific CD4<sup>+</sup> T cell phenotypes associate with bacterial control in people who ‘resist’ infection with <i>Mycobacterium tuberculosis</i></h1> <ul class="c-article-author-list c-article-author-list--short" data-test="authors-list" data-component-authors-activator="authors-list"><li class="c-article-author-list__item"><a data-test="author-name" 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href="#Aff1">1</a>,<a href="#Aff5">5</a></sup>, </li><li class="c-article-author-list__item c-article-author-list__item--hide-small-screen"><a data-test="author-name" data-track="click" data-track-action="open author" data-track-label="link" href="#auth-Gerlinde-Obermoser-Aff6" data-author-popup="auth-Gerlinde-Obermoser-Aff6" data-author-search="Obermoser, Gerlinde">Gerlinde Obermoser</a><sup class="u-js-hide"><a href="#Aff6">6</a></sup>, </li><li class="c-article-author-list__item c-article-author-list__item--hide-small-screen"><a data-test="author-name" data-track="click" data-track-action="open author" data-track-label="link" href="#auth-Holden_Terry-Maecker-Aff6" data-author-popup="auth-Holden_Terry-Maecker-Aff6" data-author-search="Maecker, Holden Terry">Holden Terry Maecker</a><span class="u-js-hide"> <a class="js-orcid" href="http://orcid.org/0000-0003-0795-9946"><span class="u-visually-hidden">ORCID: </span>orcid.org/0000-0003-0795-9946</a></span><sup class="u-js-hide"><a 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href="#auth-Neha-Gupta-Aff1-Aff6" data-author-popup="auth-Neha-Gupta-Aff1-Aff6" data-author-search="Gupta, Neha">Neha Gupta</a><span class="u-js-hide"> <a class="js-orcid" href="http://orcid.org/0000-0002-6300-1671"><span class="u-visually-hidden">ORCID: </span>orcid.org/0000-0002-6300-1671</a></span><sup class="u-js-hide"><a href="#Aff1">1</a>,<a href="#Aff6">6</a></sup>, </li><li class="c-article-author-list__item c-article-author-list__item--hide-small-screen"><a data-test="author-name" data-track="click" data-track-action="open author" data-track-label="link" href="#auth-Mary-Rieck-Aff6" data-author-popup="auth-Mary-Rieck-Aff6" data-author-search="Rieck, Mary">Mary Rieck</a><sup class="u-js-hide"><a href="#Aff6">6</a></sup>, </li><li class="c-article-author-list__item c-article-author-list__item--hide-small-screen"><a data-test="author-name" data-track="click" data-track-action="open author" data-track-label="link" href="#auth-Peter-Acs-Aff6" data-author-popup="auth-Peter-Acs-Aff6" data-author-search="Acs, Peter">Peter Acs</a><sup class="u-js-hide"><a href="#Aff6">6</a></sup>, </li><li class="c-article-author-list__item c-article-author-list__item--hide-small-screen"><a data-test="author-name" data-track="click" data-track-action="open author" data-track-label="link" href="#auth-Mustafa-Ghanizada-Aff1-Aff7" data-author-popup="auth-Mustafa-Ghanizada-Aff1-Aff7" data-author-search="Ghanizada, Mustafa">Mustafa Ghanizada</a><span class="u-js-hide"> <a class="js-orcid" href="http://orcid.org/0000-0002-2774-2157"><span class="u-visually-hidden">ORCID: </span>orcid.org/0000-0002-2774-2157</a></span><sup class="u-js-hide"><a href="#Aff1">1</a>,<a href="#Aff7">7</a></sup>, </li><li class="c-article-author-list__item c-article-author-list__item--hide-small-screen"><a data-test="author-name" data-track="click" data-track-action="open author" data-track-label="link" href="#auth-Shin_Heng-Chiou-Aff8" data-author-popup="auth-Shin_Heng-Chiou-Aff8" data-author-search="Chiou, Shin-Heng">Shin-Heng Chiou</a><sup class="u-js-hide"><a href="#Aff8">8</a></sup>, </li><li class="c-article-author-list__item c-article-author-list__item--hide-small-screen"><a data-test="author-name" data-track="click" data-track-action="open author" data-track-label="link" href="#auth-Purvesh-Khatri-Aff1-Aff5-Aff9" data-author-popup="auth-Purvesh-Khatri-Aff1-Aff5-Aff9" data-author-search="Khatri, Purvesh">Purvesh Khatri</a><span class="u-js-hide"> <a class="js-orcid" href="http://orcid.org/0000-0002-4143-4708"><span class="u-visually-hidden">ORCID: </span>orcid.org/0000-0002-4143-4708</a></span><sup class="u-js-hide"><a href="#Aff1">1</a>,<a href="#Aff5">5</a>,<a href="#Aff9">9</a></sup>, </li><li class="c-article-author-list__item c-article-author-list__item--hide-small-screen"><a data-test="author-name" data-track="click" data-track-action="open author" data-track-label="link" href="#auth-W__Henry-Boom-Aff10" data-author-popup="auth-W__Henry-Boom-Aff10" data-author-search="Boom, W. Henry">W. Henry Boom</a><sup class="u-js-hide"><a href="#Aff10">10</a></sup>, </li><li class="c-article-author-list__item c-article-author-list__item--hide-small-screen"><a data-test="author-name" data-track="click" data-track-action="open author" data-track-label="link" href="#auth-Thomas_R_-Hawn-Aff2" data-author-popup="auth-Thomas_R_-Hawn-Aff2" data-author-search="Hawn, Thomas R.">Thomas R. Hawn</a><sup class="u-js-hide"><a href="#Aff2">2</a></sup>, </li><li class="c-article-author-list__item c-article-author-list__item--hide-small-screen"><a data-test="author-name" data-track="click" data-track-action="open author" data-track-label="link" href="#auth-Catherine_M_-Stein-Aff11" data-author-popup="auth-Catherine_M_-Stein-Aff11" data-author-search="Stein, Catherine M.">Catherine M. Stein</a><span class="u-js-hide"> <a class="js-orcid" href="http://orcid.org/0000-0002-9763-5023"><span class="u-visually-hidden">ORCID: </span>orcid.org/0000-0002-9763-5023</a></span><sup class="u-js-hide"><a href="#Aff11">11</a></sup>, </li><li class="c-article-author-list__item c-article-author-list__item--hide-small-screen"><a data-test="author-name" data-track="click" data-track-action="open author" data-track-label="link" href="#auth-Harriet-Mayanja_Kizza-Aff12" data-author-popup="auth-Harriet-Mayanja_Kizza-Aff12" data-author-search="Mayanja-Kizza, Harriet">Harriet Mayanja-Kizza</a><sup class="u-js-hide"><a href="#Aff12">12</a></sup>, </li><li class="c-article-author-list__item c-article-author-list__item--hide-small-screen"><a data-test="author-name" data-track="click" data-track-action="open author" data-track-label="link" href="#auth-Mark_M_-Davis-Aff1-Aff13-Aff14" data-author-popup="auth-Mark_M_-Davis-Aff1-Aff13-Aff14" data-author-search="Davis, Mark M." data-corresp-id="c1">Mark M. Davis<svg width="16" height="16" focusable="false" role="img" aria-hidden="true" class="u-icon"><use xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="#icon-eds-i-mail-medium"></use></svg></a><span class="u-js-hide"> <a class="js-orcid" href="http://orcid.org/0000-0001-6868-657X"><span class="u-visually-hidden">ORCID: </span>orcid.org/0000-0001-6868-657X</a></span><sup class="u-js-hide"><a href="#Aff1">1</a>,<a href="#Aff13">13</a>,<a href="#Aff14">14</a></sup><sup class="u-js-hide"> <a href="#na1">na1</a></sup> & </li><li class="c-article-author-list__show-more" aria-label="Show all 25 authors for this article" title="Show all 25 authors for this article">…</li><li class="c-article-author-list__item"><a data-test="author-name" data-track="click" data-track-action="open author" data-track-label="link" href="#auth-Chetan-Seshadri-Aff2" data-author-popup="auth-Chetan-Seshadri-Aff2" data-author-search="Seshadri, Chetan" data-corresp-id="c2">Chetan Seshadri<svg width="16" height="16" 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data-test="journal-title">Nature Immunology</i></a> <b data-test="journal-volume"><span class="u-visually-hidden">volume</span> 25</b>, <span class="u-visually-hidden">pages </span>1411–1421 (<span data-test="article-publication-year">2024</span>)<a href="#citeas" class="c-article-info-details__cite-as u-hide-print" data-track="click" data-track-action="cite this article" data-track-label="link">Cite this article</a> </p> <div class="c-article-metrics-bar__wrapper u-clear-both"> <ul class="c-article-metrics-bar u-list-reset"> <li class=" c-article-metrics-bar__item" data-test="access-count"> <p class="c-article-metrics-bar__count">8967 <span class="c-article-metrics-bar__label">Accesses</span></p> </li> <li class="c-article-metrics-bar__item" data-test="citation-count"> <p class="c-article-metrics-bar__count">2 <span class="c-article-metrics-bar__label">Citations</span></p> </li> <li class="c-article-metrics-bar__item" data-test="altmetric-score"> <p 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c-status-message--boxed c-status-message--info"> <span class="c-status-message__icon"> <svg class="u-icon" width="18" height="18" aria-hidden="true" focusable="false"> <use xlink:href="#icon-eds-i-info-filled-medium"></use> </svg> </span> <p class="u-mt-0">An <a href="https://doi.org/10.1038/s41590-024-01959-x" class="relation-link" data-track="click" data-track-action="view linked article" data-track-label="link">Author Correction</a> to this article was published on 19 August 2024</p> </div> <div class="u-mb-8 c-status-message c-status-message--boxed c-status-message--info"> <span class="c-status-message__icon"> <svg class="u-icon" width="18" height="18" aria-hidden="true" focusable="false"> <use xlink:href="#icon-eds-i-info-filled-medium"></use> </svg> </span> <p class="u-mt-0">This article has been <a href="#change-history">updated</a></p> </div> </div> <div class="c-article-body"> <section aria-labelledby="Abs1" data-title="Abstract" lang="en"><div class="c-article-section" id="Abs1-section"><h2 class="c-article-section__title js-section-title js-c-reading-companion-sections-item" id="Abs1">Abstract</h2><div class="c-article-section__content" id="Abs1-content"><p>A subset of individuals exposed to <i>Mycobacterium tuberculosis</i> (<i>Mtb</i>) that we refer to as ‘resisters’ (RSTR) show evidence of IFN-γ<sup>−</sup> T cell responses to <i>Mtb</i>-specific antigens despite serially negative results on clinical testing. Here we found that <i>Mtb</i>-specific T cells in RSTR were clonally expanded, confirming the priming of adaptive immune responses following <i>Mtb</i> exposure. RSTR CD4<sup>+</sup> T cells showed enrichment of T<sub>H</sub>17 and regulatory T cell-like functional programs compared to <i>Mtb</i>-specific T cells from individuals with latent <i>Mtb</i> infection. Using public datasets, we showed that these T<sub>H</sub>17 cell-like functional programs were associated with lack of progression to active tuberculosis among South African adolescents with latent <i>Mtb</i> infection and with bacterial control in nonhuman primates. Our findings suggested that RSTR may successfully control <i>Mtb</i> following exposure and immune priming and established a set of T cell biomarkers to facilitate further study of this clinical phenotype.</p></div></div></section> <noscript> </noscript> <section aria-labelledby="inline-recommendations" data-title="Inline Recommendations" class="c-article-recommendations" data-track-component="inline-recommendations"> <h3 class="c-article-recommendations-title" id="inline-recommendations">Similar content being viewed by others</h3> <div class="c-article-recommendations-list"> <div class="c-article-recommendations-list__item"> <article class="c-article-recommendations-card" itemscope itemtype="http://schema.org/ScholarlyArticle"> <div class="c-article-recommendations-card__img"><img src="https://media.springernature.com/w215h120/springer-static/image/art%3A10.1038%2Fs41385-020-0322-6/MediaObjects/41385_2020_322_Fig1_HTML.png" loading="lazy" alt=""></div> <div class="c-article-recommendations-card__main"> <h3 class="c-article-recommendations-card__heading" itemprop="name headline"> <a class="c-article-recommendations-card__link" itemprop="url" href="https://www.nature.com/articles/s41385-020-0322-6?fromPaywallRec=false" data-track="select_recommendations_1" data-track-context="inline recommendations" data-track-action="click recommendations inline - 1" data-track-label="10.1038/s41385-020-0322-6"><i>Mycobacterium tuberculosis</i>-specific CD4 T cells expressing CD153 inversely associate with bacterial load and disease severity in human tuberculosis </a> </h3> <div class="c-article-meta-recommendations" data-test="recommendation-info"> <span class="c-article-meta-recommendations__item-type">Article</span> <span class="c-article-meta-recommendations__access-type">Open access</span> <span class="c-article-meta-recommendations__date">16 July 2020</span> </div> </div> </article> </div> <div class="c-article-recommendations-list__item"> <article class="c-article-recommendations-card" itemscope itemtype="http://schema.org/ScholarlyArticle"> <div class="c-article-recommendations-card__img"><img src="https://media.springernature.com/w215h120/springer-static/image/art%3A10.1038%2Fs41591-022-02110-9/MediaObjects/41591_2022_2110_Fig1_HTML.png" loading="lazy" alt=""></div> <div class="c-article-recommendations-card__main"> <h3 class="c-article-recommendations-card__heading" itemprop="name headline"> <a class="c-article-recommendations-card__link" itemprop="url" href="https://www.nature.com/articles/s41591-022-02110-9?fromPaywallRec=false" data-track="select_recommendations_2" data-track-context="inline recommendations" data-track-action="click recommendations inline - 2" data-track-label="10.1038/s41591-022-02110-9">T cell receptor repertoires associated with control and disease progression following <i>Mycobacterium tuberculosis</i> infection </a> </h3> <div class="c-article-meta-recommendations" data-test="recommendation-info"> <span class="c-article-meta-recommendations__item-type">Article</span> <span class="c-article-meta-recommendations__access-type">Open access</span> <span class="c-article-meta-recommendations__date">05 January 2023</span> </div> </div> </article> </div> <div class="c-article-recommendations-list__item"> <article class="c-article-recommendations-card" itemscope itemtype="http://schema.org/ScholarlyArticle"> <div class="c-article-recommendations-card__img"><img src="https://media.springernature.com/w215h120/springer-static/image/art%3A10.1038%2Fs41467-024-49050-1/MediaObjects/41467_2024_49050_Fig1_HTML.png" loading="lazy" alt=""></div> <div class="c-article-recommendations-card__main"> <h3 class="c-article-recommendations-card__heading" itemprop="name headline"> <a class="c-article-recommendations-card__link" itemprop="url" href="https://www.nature.com/articles/s41467-024-49050-1?fromPaywallRec=false" data-track="select_recommendations_3" data-track-context="inline recommendations" data-track-action="click recommendations inline - 3" data-track-label="10.1038/s41467-024-49050-1">Adolescent BCG revaccination induces a phenotypic shift in CD4<sup>+</sup> T cell responses to <i>Mycobacterium tuberculosis</i> </a> </h3> <div class="c-article-meta-recommendations" data-test="recommendation-info"> <span class="c-article-meta-recommendations__item-type">Article</span> <span class="c-article-meta-recommendations__access-type">Open access</span> <span class="c-article-meta-recommendations__date">18 June 2024</span> </div> </div> </article> </div> </div> </section> <script> window.dataLayer = window.dataLayer || []; window.dataLayer.push({ recommendations: { recommender: 'semantic', model: 'specter', policy_id: 'NA', timestamp: 1732723640, embedded_user: 'null' } }); </script> <div class="main-content"> <section data-title="Main"><div class="c-article-section" id="Sec1-section"><h2 class="c-article-section__title js-section-title js-c-reading-companion-sections-item" id="Sec1">Main</h2><div class="c-article-section__content" id="Sec1-content"><p>Nearly 1.7 billion people who have been exposed to <i>Mycobacterium tuberculosis</i> (<i>Mtb</i>) are clinically asymptomatic but show positive results on tuberculin skin tests (TST) or interferon (IFN)-γ release assays (IGRA), indicating they may harbor a ‘latent’ <i>Mtb</i> infection (referred to here as LTBI)<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 1" title="Houben, R. M. & Dodd, P. J. The global burden of latent tuberculosis infection: a re-estimation using mathematical modelling. PLoS Med. 13, e1002152 (2016)." href="/articles/s41590-024-01897-8#ref-CR1" id="ref-link-section-d4561556e1094">1</a></sup>. We have previously described a cohort of Ugandan household contacts who never developed a positive TST or IGRA, despite a high probability of exposure to <i>Mtb</i>. As these individuals did not develop active tuberculosis (TB) over a median of 9.5 years of follow-up, it was proposed that they ‘resist’ <i>Mtb</i> infection<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 2" title="Lin, P. L. et al. CD4 T cell depletion exacerbates acute Mycobacterium tuberculosis while reactivation of latent infection is dependent on severity of tissue depletion in cynomolgus macaques. AIDS Res Hum. Retroviruses 28, 1693–1702 (2012)." href="/articles/s41590-024-01897-8#ref-CR2" id="ref-link-section-d4561556e1105">2</a></sup> (hereafter referred to as RSTR). Highly exposed individuals with negative TST and/or IGRA were also reported among healthcare workers, miners and other household contact cohorts<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 3" title="Gutierrez, J., Kroon, E. E., Möller, M. & Stein, C. M. Phenotype definition for ‘resisters’ to Mycobacterium tuberculosis infection in the literature-a review and recommendations. Front. Immunol. 12, 619988 (2021)." href="/articles/s41590-024-01897-8#ref-CR3" id="ref-link-section-d4561556e1109">3</a></sup>, even when considering variations in timing and strength of exposure, duration of follow-up and frequency of testing<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 4" title="Verrall, A. J., Netea, M. G., Alisjahbana, B., Hill, P. C. & van Crevel, R. Early clearance of Mycobacterium tuberculosis: a new frontier in prevention. Immunology 141, 506–513 (2014)." href="/articles/s41590-024-01897-8#ref-CR4" id="ref-link-section-d4561556e1113">4</a>,<a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 5" title="Lu, L. L. et al. IFN-γ-independent immune markers of Mycobacterium tuberculosis exposure. Nat. Med. 25, 977–987 (2019)." href="/articles/s41590-024-01897-8#ref-CR5" id="ref-link-section-d4561556e1116">5</a></sup>, but whether these individuals control <i>Mtb</i> infection is unknown.</p><p>Early events following <i>Mtb</i> infection are poorly understood, because most animal models seek to recapitulate active disease. Human TB occurs along a spectrum ranging from clinically apparent disease, asymptomatic infection, and possibly resistance to <i>Mtb</i> infection<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 6" title="Simmons, J. D. et al. Immunological mechanisms of human resistance to persistent Mycobacterium tuberculosis infection. Nat. Rev. Immunol. 18, 575–589 (2018)." href="/articles/s41590-024-01897-8#ref-CR6" id="ref-link-section-d4561556e1132">6</a></sup>. T cells probably mediate resistance to <i>Mtb</i> infection, as several studies have conclusively demonstrated their importance in protecting against disease in humans and animal models<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 2" title="Lin, P. L. et al. CD4 T cell depletion exacerbates acute Mycobacterium tuberculosis while reactivation of latent infection is dependent on severity of tissue depletion in cynomolgus macaques. AIDS Res Hum. Retroviruses 28, 1693–1702 (2012)." href="/articles/s41590-024-01897-8#ref-CR2" id="ref-link-section-d4561556e1139">2</a>,<a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 7" title="Zumla, A., Raviglione, M., Hafner, R. & von Reyn, C. F. Tuberculosis. N. Engl. J. Med. 368, 745–755 (2013)." href="/articles/s41590-024-01897-8#ref-CR7" id="ref-link-section-d4561556e1142">7</a>,<a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 8" title="Mogues, T., Goodrich, M. E., Ryan, L., LaCourse, R. & North, R. J. The relative importance of T cell subsets in immunity and immunopathology of airborne Mycobacterium tuberculosis infection in mice. J. Exp. Med. 193, 271–280 (2001)." href="/articles/s41590-024-01897-8#ref-CR8" id="ref-link-section-d4561556e1145">8</a></sup>. However, the specific role of T cell-derived IFN-γ has been debated. CD4<sup>+</sup> T cells can control <i>Mtb</i> infection even without production of IFN-γ<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 9" title="Gallegos, A. M. et al. A gamma interferon independent mechanism of CD4 T cell mediated control of M. tuberculosis infection in vivo. PLoS Pathog. 7, e1002052 (2011)." href="/articles/s41590-024-01897-8#ref-CR9" id="ref-link-section-d4561556e1155">9</a>,<a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 10" title="Sallin, M. A. et al. Host resistance to pulmonary Mycobacterium tuberculosis infection requires CD153 expression. Nat. Microbiol 3, 1198–1205 (2018)." href="/articles/s41590-024-01897-8#ref-CR10" id="ref-link-section-d4561556e1158">10</a></sup>. Although mendelian defects in IFN-γ-related pathway genes confer susceptibility to mycobacterial disease<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 11" title="Jouanguy, E. et al. Interferon–gamma-receptor deficiency in an infant with fatal bacille Calmette–Guérin infection. N. Engl. J. Med. 335, 1956–1961 (1996)." href="/articles/s41590-024-01897-8#ref-CR11" id="ref-link-section-d4561556e1162">11</a></sup>, human and mice data suggest that mechanisms other than IFN-γ may be important for protection<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 9" title="Gallegos, A. M. et al. A gamma interferon independent mechanism of CD4 T cell mediated control of M. tuberculosis infection in vivo. PLoS Pathog. 7, e1002052 (2011)." href="/articles/s41590-024-01897-8#ref-CR9" id="ref-link-section-d4561556e1166">9</a>,<a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 12" title="Bustamante, J., Boisson-Dupuis, S., Abel, L. & Casanova, J. L. Mendelian susceptibility to mycobacterial disease: genetic, immunological, and clinical features of inborn errors of IFN-γ immunity. Semin. Immunol. 26, 454–470 (2014)." href="/articles/s41590-024-01897-8#ref-CR12" id="ref-link-section-d4561556e1169">12</a></sup>. We identified <i>Mtb</i>-specific IFN-γ- CD4<sup>+</sup> T cells in both RSTR and LTBI that express interleukin (IL)-2, tumor necrosis factor (TNF) and CD154 in the absence of IFN-γ after <i>Mtb</i> exposure<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 5" title="Lu, L. L. et al. IFN-γ-independent immune markers of Mycobacterium tuberculosis exposure. Nat. Med. 25, 977–987 (2019)." href="/articles/s41590-024-01897-8#ref-CR5" id="ref-link-section-d4561556e1182">5</a></sup>.</p><p>Here, we asked whether <i>Mtb</i>-specific CD4<sup>+</sup> T cells from RSTR expressed unique functional programs compared to LTBI. To address this question, we first analyzed a Ugandan cohort characterized by low <i>Mtb</i> transmission and found that <i>Mtb</i>-specific IFN-γ<sup>−</sup>CD4<sup>+</sup> T cells were not detectable in the absence of <i>Mtb</i> exposure. Next, we identified several functional programs, including T<sub>H</sub>17 cell-like, regulatory T cell and memory T cell phenotypes, that were selectively enriched in <i>Mtb</i>-specific CD4<sup>+</sup> T cells from RSTR compared to LTBI. We also leveraged public datasets to demonstrate an association between these T cell phenotypes and South African adolescents with LTBI who control <i>Mtb</i> infection, as well as the protective efficacy of intravenous Bacillus Calmette–Guérin (BCG) in nonhuman primates (NHPs). Taken together, our results suggest that RSTR might control <i>Mtb</i> after initial exposure by priming an IFN-γ<sup>−</sup>CD4<sup>+</sup> T cell response.</p></div></div></section><section data-title="Results"><div class="c-article-section" id="Sec2-section"><h2 class="c-article-section__title js-section-title js-c-reading-companion-sections-item" id="Sec2">Results</h2><div class="c-article-section__content" id="Sec2-content"><h3 class="c-article__sub-heading" id="Sec3"> <i>Mtb</i>-specific IFN-γ<sup>−</sup>CD4<sup>+</sup> T cells are absent in low-exposure individuals</h3><p>To investigate whether IFN-γ<sup>−</sup>CD4<sup>+</sup> T cell responses were unique to household contacts, we enrolled a cohort of participants from Kampala, Uganda<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 5" title="Lu, L. L. et al. IFN-γ-independent immune markers of Mycobacterium tuberculosis exposure. Nat. Med. 25, 977–987 (2019)." href="/articles/s41590-024-01897-8#ref-CR5" id="ref-link-section-d4561556e1250">5</a></sup> who had low exposure risk based on community TB transmission rates (hereafter low-exposure cohort; Supplementary Tables <a data-track="click" data-track-label="link" data-track-action="supplementary material anchor" href="/articles/s41590-024-01897-8#MOESM3">1</a> and <a data-track="click" data-track-label="link" data-track-action="supplementary material anchor" href="/articles/s41590-024-01897-8#MOESM3">2</a>)<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 13" title="Wobudeya, E., Sekadde-Kasirye, M., Kimuli, D., Mugabe, F. & Lukoye, D. Trend and outcome of notified children with tuberculosis during 2011–2015 in Kampala, Uganda. BMC Public Health 17, 963 (2017)." href="/articles/s41590-024-01897-8#ref-CR13" id="ref-link-section-d4561556e1261">13</a></sup>. The low-exposure cohort contained participants negative for both TST and IGRA (hereafter TST<sup>−</sup>IGRA<sup>−</sup>, <i>n</i> = 17, 9 males and 8 females, aged 18–26 years) (Extended Data Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig7">1a</a>) and sex and age matched TST<sup>+</sup>IGRA<sup>+</sup> individuals (hereafter LTBI, <i>n</i> = 19, 10 males and 9 females, aged 18–42 years). To study <i>Mtb</i>-specific responses, peripheral blood mononuclear cells (PBMC) from TST<sup>−</sup>IGRA<sup>−</sup> and LTBI participants were stimulated for 6 h with overlapping peptide pools targeting the <i>Mtb</i>-specific proteins ESAT6 and CFP10, which are absent in BCG vaccines (Extended Data Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig7">1b</a>). We used intracellular cytokine staining (ICS) to identify IFN-γ<sup>+</sup> and IFN-γ<sup>−</sup>CD4<sup>+</sup> T cell responses and the expression of cytokines IL-2, IL-4/IL-5/IL-13, IL-17A and TNF and we also assessed the expression of the activation and memory markers CD107a and CD154 (Extended Data Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig7">1c</a> and Supplementary Table <a data-track="click" data-track-label="link" data-track-action="supplementary material anchor" href="/articles/s41590-024-01897-8#MOESM3">3</a>)<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 14" title="De Rosa, S. C., Carter, D. K. & McElrath, M. J. OMIP-014: validated multifunctional characterization of antigen-specific human T cells by intracellular cytokine staining. Cytom. A 81, 1019–1021 (2012)." href="/articles/s41590-024-01897-8#ref-CR14" id="ref-link-section-d4561556e1310">14</a></sup>. Four CD4<sup>+</sup> T cell functional profiles were detected using the combinatorial polyfunctionality analysis of antigen-specific T cell subsets (referred to as COMPASS)<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 15" title="Lin, L. et al. COMPASS identifies T-cell subsets correlated with clinical outcomes. Nat. Biotechnol. 33, 610–616 (2015)." href="/articles/s41590-024-01897-8#ref-CR15" id="ref-link-section-d4561556e1316">15</a></sup>, three of which were IFN-γ<sup>+</sup> (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig1">1a,b</a>). TST<sup>−</sup>IGRA<sup>−</sup> participants did not have IFN-γ<sup>−</sup> or polyfunctional IFN-γ<sup>+</sup> T cell responses, while LTBI had both (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig1">1b–e</a>)<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 5" title="Lu, L. L. et al. IFN-γ-independent immune markers of Mycobacterium tuberculosis exposure. Nat. Med. 25, 977–987 (2019)." href="/articles/s41590-024-01897-8#ref-CR5" id="ref-link-section-d4561556e1337">5</a></sup>. Overall, IFN-γ<sup>−</sup>CD4<sup>+</sup> T cells were absent in low-exposure individuals, indicating IFN-γ-independent T cell responses to ESAT6/CFP10 were not observed outside a high-exposure setting, such as household contacts<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 5" title="Lu, L. L. et al. IFN-γ-independent immune markers of Mycobacterium tuberculosis exposure. Nat. Med. 25, 977–987 (2019)." href="/articles/s41590-024-01897-8#ref-CR5" id="ref-link-section-d4561556e1346">5</a></sup>.</p><div class="c-article-section__figure js-c-reading-companion-figures-item" data-test="figure" data-container-section="figure" id="figure-1" data-title="IFN-γ-independent T cell responses are not detected in low-exposure controls."><figure><figcaption><b id="Fig1" class="c-article-section__figure-caption" data-test="figure-caption-text">Fig. 1: IFN-γ-independent T cell responses are not detected in low-exposure controls.</b></figcaption><div class="c-article-section__figure-content"><div class="c-article-section__figure-item"><a class="c-article-section__figure-link" data-test="img-link" data-track="click" data-track-label="image" data-track-action="view figure" href="/articles/s41590-024-01897-8/figures/1" rel="nofollow"><picture><source type="image/webp" srcset="//media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41590-024-01897-8/MediaObjects/41590_2024_1897_Fig1_HTML.png?as=webp"><img aria-describedby="Fig1" src="//media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41590-024-01897-8/MediaObjects/41590_2024_1897_Fig1_HTML.png" alt="figure 1" loading="lazy" width="685" height="366"></picture></a></div><div class="c-article-section__figure-description" data-test="bottom-caption" id="figure-1-desc"><p><b>a</b>, Representative flow cytometry showing the expression of IFN-γ and CD154 in CD4<sup>+</sup> T cells from TST<sup>−</sup>IGRA<sup>−</sup> or LTBI in the low-exposure cohort in response to ESAT6/CFP10 stimulation. <b>b</b>, COMPASS-generated probability heat map of CD4<sup>+</sup> T cell subsets including IFN-γ<sup>−</sup>IL-2<sup>+</sup>CD154<sup>+</sup>, IFN-γ<sup>+</sup>IL-2<sup>−</sup>CD154<sup>+</sup>, IFN-γ<sup>+</sup>IL-2<sup>+</sup>CD154<sup>−</sup> and IFN-γ<sup>+</sup>IL-2<sup>+</sup>CD154<sup>+</sup> cells from TST<sup>−</sup>IGRA<sup>−</sup> or LTBI in the low-exposure cohort in response to ESAT6/CFP10. The depth of purple shading correlates to the probability of a participant-specific response above background for a given cell subset. White, no function; black/gray, presence of a function. IFN-γ<sup>+</sup> cell subsets are noted in gray. <b>c</b>, The frequencies of COMPASS-identified CD4<sup>+</sup> T cell subsets are shown, background corrected by subtracting the frequency of each subset after DMSO stimulation from the frequency after ESAT6/CFP10 stimulation as in <b>b</b>. <b>d</b>, The frequencies of polyfunctional CD4<sup>+</sup> T cells that expressed two or more cytokines in response to ESAT6/CFP10 in CD4<sup>+</sup> T cells as in <b>c</b>. <b>e</b>, Polyfunctionality score of CD4<sup>+</sup> T cells specific to ESAT6/CFP10. In <b>c</b>−<b>e</b>, the statistical significance was calculated using the Wilcoxon rank-sum test. Two-sided <i>P</i> values are shown, while in <b>c</b> the reported <i>P</i> values were adjusted for multiple hypothesis testing using the Bonferroni method.</p></div></div><div class="u-text-right u-hide-print"><a class="c-article__pill-button" data-test="article-link" data-track="click" data-track-label="button" data-track-action="view figure" href="/articles/s41590-024-01897-8/figures/1" data-track-dest="link:Figure1 Full size image" aria-label="Full size image figure 1" rel="nofollow"><span>Full size image</span><svg width="16" height="16" focusable="false" role="img" aria-hidden="true" class="u-icon"><use xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="#icon-eds-i-chevron-right-small"></use></svg></a></div></figure></div><h3 class="c-article__sub-heading" id="Sec4"> <i>Mtb</i>-specific RSTR CD4<sup>+</sup> T cells have unique phenotypes</h3><p>We next profiled the <i>Mtb</i>-specific CD4<sup>+</sup> T cells in a cohort of TB household contacts (hereafter household contact cohort) in Kampala, Uganda, which contained 45 individuals who remained TST<sup>−</sup>IGRA<sup>−</sup> for a median of 9.5 years after exposure<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 5" title="Lu, L. L. et al. IFN-γ-independent immune markers of Mycobacterium tuberculosis exposure. Nat. Med. 25, 977–987 (2019)." href="/articles/s41590-024-01897-8#ref-CR5" id="ref-link-section-d4561556e1479">5</a></sup> (RSTR; 22 males and 23 females, aged 14–67 years) and 45 individuals (23 males and 22 females, age 14–63 years) who were TST<sup>+</sup>IGRA<sup>+</sup> at the initiation of the cohort and did not progress to disease for a median of 9.5 years after exposure<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 5" title="Lu, L. L. et al. IFN-γ-independent immune markers of Mycobacterium tuberculosis exposure. Nat. Med. 25, 977–987 (2019)." href="/articles/s41590-024-01897-8#ref-CR5" id="ref-link-section-d4561556e1488">5</a></sup> (LTBI). Participants were matched for age, sex and exposure risk score (Supplementary Tables <a data-track="click" data-track-label="link" data-track-action="supplementary material anchor" href="/articles/s41590-024-01897-8#MOESM3">4</a> and <a data-track="click" data-track-label="link" data-track-action="supplementary material anchor" href="/articles/s41590-024-01897-8#MOESM3">5</a>). In the discovery phase, we used PBMC collected at a median of 9.5 years after exposure<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 5" title="Lu, L. L. et al. IFN-γ-independent immune markers of Mycobacterium tuberculosis exposure. Nat. Med. 25, 977–987 (2019)." href="/articles/s41590-024-01897-8#ref-CR5" id="ref-link-section-d4561556e1498">5</a></sup> from three RSTR and four LTBI participants (hereafter referred to as the discovery cohort) and performed index sorting and single-cell multiplex targeted transcriptomics on CD69<sup>+</sup>CD154<sup>+</sup> and CD69<sup>+</sup>CD137<sup>+</sup> T cells (hereafter referred to as activated T cells or antigen-specific T cells according to the stimulation antigens) after stimulation of PBMC with ESAT6/CFP10 for 6 h (Extended Data Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig7">1b</a>). This was followed by single-cell whole transcriptomics on clonally expanded activated T cells (the method is hereafter referred to as SELECT-seq<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 16" title="Huang, H. et al. Select sequencing of clonally expanded CD8+ T cells reveals limits to clonal expansion. Proc. Natl Acad. Sci. USA 116, 8995–9001 (2019)." href="/articles/s41590-024-01897-8#ref-CR16" id="ref-link-section-d4561556e1514">16</a></sup>; Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig2">2a</a> and Extended Data Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig8">2a</a>). For T cell phenotyping, index sorting also measured the expression of lineage (CD4 and CD8), memory (CD45RA and CD127) and additional activation (CD25, HLA-DR and CD38) markers, while targeted transcriptomics measured the clonotypic T cell receptor (TCR) ɑ and β sequences, the gene expression of canonical transcription factor usage (<i>TBX21</i> (T-bet), <i>RORC</i> (RORγt), <i>GATA3</i>, <i>FOXP3</i>, <i>RUNX1</i> and <i>RUNX3</i>), and characteristic cytokines (<i>IFNG</i>, <i>IL2</i>, <i>IL17A</i>, <i>GZMB</i>, <i>PERF</i>, <i>IL4</i>, <i>IL5</i>, <i>IL13</i> and <i>TGFB</i>). Using FlowSOM, a tool for clustering and visualizing flow cytometry data, these markers identified 19 cell subsets of ESAT6/CFP10-specific CD4<sup>+</sup> T cells (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig2">2b</a>)<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 17" title="Van Gassen, S. et al. FlowSOM: using self-organizing maps for visualization and interpretation of cytometry data. Cytometry A 87, 636–645 (2015)." href="/articles/s41590-024-01897-8#ref-CR17" id="ref-link-section-d4561556e1578">17</a></sup>. <i>t</i>-Distributed stochastic neighbor embedding (<i>t</i>-SNE) visualization indicated that some subsets, such as <i>RORC</i><sup><i>+</i></sup><i>IL17A</i><sup><i>+</i></sup> cells (cluster 6), were enriched in RSTR, while some subsets, such as <i>RORC</i><sup><i>+</i></sup><i>IFNG</i><sup><i>+</i></sup><i>GZMB</i><sup><i>+</i></sup><i>PERF</i><sup><i>+</i></sup> cells (cluster 11), were abundant in LTBI (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig2">2c</a> and Extended Data Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig8">2b</a>). We also determined the T cell phenotypes in 16 RSTR (8 males and 8 females, aged 14–39 years) and 16 LTBI (9 males and 7 females, aged 15–46 years) after 12 h stimulation with whole <i>Mtb</i> lysate, which contains a broader set of antigens conserved across mycobacteria (Supplementary Tables <a data-track="click" data-track-label="link" data-track-action="supplementary material anchor" href="/articles/s41590-024-01897-8#MOESM3">4</a> and <a data-track="click" data-track-label="link" data-track-action="supplementary material anchor" href="/articles/s41590-024-01897-8#MOESM3">5</a>). Index sorting and targeted transcriptomics did not identify qualitative differences in cluster enrichment in <i>Mtb</i> lysate-specific CD4<sup>+</sup> T cell phenotypes between RSTR and LTBI (Extended Data Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig8">2c</a>). Clonal expansion of ESAT6/CFP10-specific CD4<sup>+</sup> T cells was observed in both RSTR and LTBI participants (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig2">2d,e</a> and Supplementary Tables <a data-track="click" data-track-label="link" data-track-action="supplementary material anchor" href="/articles/s41590-024-01897-8#MOESM3">6</a> and <a data-track="click" data-track-label="link" data-track-action="supplementary material anchor" href="/articles/s41590-024-01897-8#MOESM3">7</a>), which confirmed the IFN-γ<sup>−</sup>CD4<sup>+</sup> T cell recall responses reported previously<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 5" title="Lu, L. L. et al. IFN-γ-independent immune markers of Mycobacterium tuberculosis exposure. Nat. Med. 25, 977–987 (2019)." href="/articles/s41590-024-01897-8#ref-CR5" id="ref-link-section-d4561556e1662">5</a></sup>. Clonally expanded CD4<sup>+</sup> T cells were focused within the <i>IFNG</i><sup><i>+</i></sup> T<sub>H</sub>1* subsets in LTBI (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig2">2f</a>), while they did not dominate in any particular T cell subsets in RSTR (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig2">2f</a>). These data suggested that RSTR harbored <i>Mtb</i>-specific T cell responses with unique functional and phenotypic profiles compared to LTBI.</p><div class="c-article-section__figure js-c-reading-companion-figures-item" data-test="figure" data-container-section="figure" id="figure-2" data-title="Mtb-specific T cells exhibit unique phenotypes and are clonally expanded in RSTR."><figure><figcaption><b id="Fig2" class="c-article-section__figure-caption" data-test="figure-caption-text">Fig. 2: <i>Mtb</i>-specific T cells exhibit unique phenotypes and are clonally expanded in RSTR.</b></figcaption><div class="c-article-section__figure-content"><div class="c-article-section__figure-item"><a class="c-article-section__figure-link" data-test="img-link" data-track="click" data-track-label="image" data-track-action="view figure" href="/articles/s41590-024-01897-8/figures/2" rel="nofollow"><picture><source type="image/webp" srcset="//media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41590-024-01897-8/MediaObjects/41590_2024_1897_Fig2_HTML.png?as=webp"><img aria-describedby="Fig2" src="//media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41590-024-01897-8/MediaObjects/41590_2024_1897_Fig2_HTML.png" alt="figure 2" loading="lazy" width="685" height="673"></picture></a></div><div class="c-article-section__figure-description" data-test="bottom-caption" id="figure-2-desc"><p><b>a</b>, The gating strategy is shown for the sorting of ESAT6/CFP10-specific T cells from RSTR and LTBI in the discovery household contact cohort, based first on the expression of the activation marker CD69 and then CD154 or CD137. <b>b</b>, A heat map showing the median marker expression of ESAT6/CFP10-specific CD4<sup>+</sup> T cell subsets from three RSTR and four LTBI participants in the discovery household contact cohort. Clustering was performed on flow cytometry mean fluorescence intensities and binarized read counts of profiled genes. <b>c</b>, Dimensionality reduction (<i>t</i>-SNE) projection of ESAT6/CFP10-specific CD4<sup>+</sup> T cell subsets, as in <b>b</b>. The arrows highlight cluster 6 and cluster 11, which were preferentially detected in RSTR or LTBI participants, respectively. <b>d</b>, Distribution of clonal expansion based on TCRβ chain from single-cell targeted transcriptomics in ESAT6/CFP10-specific T cells, as in <b>b</b>. Each dot represents a clone as defined by the TCRβ chain CDR3 sequence. The size of the dot is proportional to the frequency, which is also depicted as log<sub>2</sub>(counts) on the <i>y</i> axis. <b>e</b>, A box plot showing the median and interquartile range of frequency of TCRβ clonal expansion in ESAT6/CFP10-specific CD4<sup>+</sup> T cells with whiskers representing minima and maxima. No statistical test was performed due to the small sample sizes. <b>f</b>, A histogram indicating the proportion of clonally expanded cells in ESAT6/CFP10-specific CD4<sup>+</sup> T cell clusters (clusters 1–19), as in <b>b</b>, which were detected more than once in participants among the household contact cohort.</p></div></div><div class="u-text-right u-hide-print"><a class="c-article__pill-button" data-test="article-link" data-track="click" data-track-label="button" data-track-action="view figure" href="/articles/s41590-024-01897-8/figures/2" data-track-dest="link:Figure2 Full size image" aria-label="Full size image figure 2" rel="nofollow"><span>Full size image</span><svg width="16" height="16" focusable="false" role="img" aria-hidden="true" class="u-icon"><use xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="#icon-eds-i-chevron-right-small"></use></svg></a></div></figure></div><h3 class="c-article__sub-heading" id="Sec5">RSTR and LTBI <i>Mtb</i>-specific CD4<sup>+</sup> T cells have a stem memory T (T<sub>SCM</sub>) cell phenotype</h3><p>Next, we applied SELECT-seq<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 16" title="Huang, H. et al. Select sequencing of clonally expanded CD8+ T cells reveals limits to clonal expansion. Proc. Natl Acad. Sci. USA 116, 8995–9001 (2019)." href="/articles/s41590-024-01897-8#ref-CR16" id="ref-link-section-d4561556e1769">16</a></sup> to deeply profile the clonally expanded ESAT6/CFP10-specific CD4<sup>+</sup> T cells. After sequencing quality control filtering, we analyzed 524 CD4<sup>+</sup> T cells (Extended Data Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig9">3a</a>) and found that the major transcriptional variance was between the RSTR and LTBI group (Extended Data Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig9">3b</a>). Differential gene expression analysis identified 582 genes upregulated in RSTR compared to LTBI and 156 genes upregulated in LTBI compared to RSTR (<a data-track="click" data-track-label="link" data-track-action="section anchor" href="/articles/s41590-024-01897-8#Sec10">Methods</a>, Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig3">3a</a> and Supplementary Table <a data-track="click" data-track-label="link" data-track-action="supplementary material anchor" href="/articles/s41590-024-01897-8#MOESM3">8</a>). The top upregulated genes in LTBI were proinflammatory (<i>IFNG</i>, <i>TNF</i> and <i>IL2</i>) and cytotoxic (<i>GZMB</i> and <i>PERF</i>) genes, aligning with an inflammatory response and IFN-γ production identified by Gene Ontology (GO) analysis (Supplementary Tables <a data-track="click" data-track-label="link" data-track-action="supplementary material anchor" href="/articles/s41590-024-01897-8#MOESM3">9</a>–<a data-track="click" data-track-label="link" data-track-action="supplementary material anchor" href="/articles/s41590-024-01897-8#MOESM3">11</a>). The top upregulated genes in RSTR were linked with T cell activation (<i>SASH3</i>, <i>TNFRSF4</i> and <i>IKZF1</i>) and cell membrane receptor (<i>CCR7</i> and <i>ITGAL</i>) (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig3">3a</a>). GO enrichment in RSTR identified translation, cell–cell adhesion, cell movement, mitochondrial electron transport (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig3">3b</a> and Supplementary Tables <a data-track="click" data-track-label="link" data-track-action="supplementary material anchor" href="/articles/s41590-024-01897-8#MOESM3">9</a>–<a data-track="click" data-track-label="link" data-track-action="supplementary material anchor" href="/articles/s41590-024-01897-8#MOESM3">11</a>), a process associated with oxidative phosphorylation and early T cell differentiation<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 18" title="Araki, K. et al. Translation is actively regulated during the differentiation of CD8. Nat. Immunol. 18, 1046–1057 (2017)." href="/articles/s41590-024-01897-8#ref-CR18" id="ref-link-section-d4561556e1844">18</a></sup>, as well as T cell activation. Aligning with these, ESAT6/CFP10-specific CD4<sup>+</sup> T cells from RSTR had higher expression of <i>TCF7</i>, <i>FOXP1</i> and <i>CCR7</i>, suggesting a less differentiated and naive-like phenotype, higher <i>ITGAL</i> (encodes LFA1) and <i>ITGA1</i> (VLA1) expression, suggesting higher trafficking mobility and homing to lymph nodes and airways<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 19" title="Zens, K. D. & Farber, D. L. Memory CD4 T cells in influenza. Curr. Top. Microbiol Immunol. 386, 399–421 (2015)." href="/articles/s41590-024-01897-8#ref-CR19" id="ref-link-section-d4561556e1866">19</a>,<a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 20" title="Eckert, I. N. et al. VLA-1 binding to collagen IV controls effector T cell suppression by myeloid-derived suppressor cells in the splenic red pulp. Front. Immunol. 11, 616531 (2020)." href="/articles/s41590-024-01897-8#ref-CR20" id="ref-link-section-d4561556e1869">20</a></sup>, and lacked expression of cytokines such as <i>IFNG</i>, <i>IL2</i> and <i>TNF</i> compared to LTBI (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig3">3c,d</a>). The enrichment of T cell activation genes and the lack of cytokine production after short-term ESAT6/CFP10 stimulation suggested that RSTR ESAT6/CFP10-specific CD4<sup>+</sup> T cells were likely to be T<sub>SCM</sub> cells, rather than naive T cells. The T<sub>SCM</sub> cell phenotype was further supported by the expression of the transcription factor <i>TCF7</i> and an enrichment in genes belonging to the Wnt signaling pathway (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig3">3b,d</a>)<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 21" title="Gattinoni, L. et al. Wnt signaling arrests effector T cell differentiation and generates CD8+ memory stem cells. Nat. Med. 15, 808–813 (2009)." href="/articles/s41590-024-01897-8#ref-CR21" id="ref-link-section-d4561556e1899">21</a></sup>. Overall, SELECT-seq indicated that RSTR CD4<sup>+</sup> T cells were less differentiated, had less inflammatory cytokine activities and more cell trafficking mobility and cell–cell adhesions compared to LTBI, suggesting a CD4<sup>+</sup> T<sub>SCM</sub> cell phenotype.</p><div class="c-article-section__figure js-c-reading-companion-figures-item" data-test="figure" data-container-section="figure" id="figure-3" data-title="Mtb-specific T cells exhibit a TSCM cell-like phenotype in RSTR and LTBI."><figure><figcaption><b id="Fig3" class="c-article-section__figure-caption" data-test="figure-caption-text">Fig. 3: <i>Mtb</i>-specific T cells exhibit a T<sub>SCM</sub> cell-like phenotype in RSTR and LTBI.</b></figcaption><div class="c-article-section__figure-content"><div class="c-article-section__figure-item"><a class="c-article-section__figure-link" data-test="img-link" data-track="click" data-track-label="image" data-track-action="view figure" href="/articles/s41590-024-01897-8/figures/3" rel="nofollow"><picture><source type="image/webp" srcset="//media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41590-024-01897-8/MediaObjects/41590_2024_1897_Fig3_HTML.png?as=webp"><img aria-describedby="Fig3" src="//media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41590-024-01897-8/MediaObjects/41590_2024_1897_Fig3_HTML.png" alt="figure 3" loading="lazy" width="685" height="372"></picture></a></div><div class="c-article-section__figure-description" data-test="bottom-caption" id="figure-3-desc"><p><b>a</b>, A volcano plot depicting DEGs of clonally expanded activated T cells between RSTR (cell number, 231) and LTBI (cell number, 293) from the discovery household contact cohort in response to ESAT6/CFP10 based on SELECT-seq. Red, genes with |log<sub>2</sub>(FC)| >0.5 and <i>P</i> value <0.05. <b>b</b>, GO Biological Process terms related to metabolic and basic activities based on upregulated DEGs from RSTR, as in <b>a</b>. False discovery rate (FDR) was calculated by a modified Fisher’s exact test with FDR correction. <b>c</b>, A heat map displaying the mean expression of genes involved in migration, adhesion or cytokine production in each RSTR and LTBI participant in the discovery household contact cohort. The mean expression level was calculated as the mean of the scaled log-normalized gene counts. <b>d</b>, Violin plots depicting the expression of stem memory like T cell genes (<i>CCR7</i>, <i>FOXP1</i> and <i>TCF7</i>) in RSTR and LTBI, as in <b>c</b>. Statistical significance was calculated using two-sided Wilcoxon rank-sum tests with the Bonferroni method. *Adjusted <i>P</i> value <0.05, **adjusted <i>P</i> value <0.005, ***adjusted <i>P</i> value <0.001. <b>e</b>, Gating strategy for naive-like CD45RA<sup>+</sup>CCR7<sup>+</sup> T cells in ESAT6/CFP10-specific CD4<sup>+</sup> T cells from RSTR (<i>n</i> = 17) and LTBI participants (<i>n</i> = 20) in the validation household contact cohort. <b>f</b>, A box plot showing the median and interquartile range of frequencies of naive-like CD45RA<sup>+</sup>CCR7<sup>+</sup>CD4<sup>+</sup> T cells in ESAT6/CFP10-specific CD4<sup>+</sup> T cells, as in <b>e</b>, with whiskers representing minima and maxima. Statistical significance was determined by the two-sided Wilcoxon rank-sum test, and the unadjusted <i>P</i> value is shown.</p></div></div><div class="u-text-right u-hide-print"><a class="c-article__pill-button" data-test="article-link" data-track="click" data-track-label="button" data-track-action="view figure" href="/articles/s41590-024-01897-8/figures/3" data-track-dest="link:Figure3 Full size image" aria-label="Full size image figure 3" rel="nofollow"><span>Full size image</span><svg width="16" height="16" focusable="false" role="img" aria-hidden="true" class="u-icon"><use xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="#icon-eds-i-chevron-right-small"></use></svg></a></div></figure></div><p>To validate the CD4<sup>+</sup> T<sub>SCM</sub> cell phenotype, we assessed 18 additional RSTR (8 males and 10 females, aged 15–39 years) and 20 LTBI (10 males and 10 females, aged 15–63 years) from the household contact cohort who were not included in the discovery cohort (hereafter referred to as the validation cohort; Supplementary Tables <a data-track="click" data-track-label="link" data-track-action="supplementary material anchor" href="/articles/s41590-024-01897-8#MOESM3">4</a> and <a data-track="click" data-track-label="link" data-track-action="supplementary material anchor" href="/articles/s41590-024-01897-8#MOESM3">5</a>). Flow cytometry (17 RSTR and 20 LTBI) on PBMC from the validation cohort stimulated with ESAT6/CFP10 for 12 h or whole <i>Mtb</i> lysate for 12 h (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig3">3e</a> and Extended Data Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig10">4a</a>) indicated a trend toward a higher proportion of naive-like CD45RA<sup>+</sup>CCR7<sup>+</sup>CD4<sup>+</sup> T cells in RSTR ESAT6/CFP10-specific CD4<sup>+</sup> T cells compared to LTBI (16.85% versus 13.21%, <i>P</i> = 0.069) (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig3">3f</a>), while in the same participants, <i>Mtb</i> lysate-specific CD4<sup>+</sup> T cells had similar frequencies of naIve-like CD45RA<sup>+</sup>CCR7<sup>+</sup>CD4<sup>+</sup> T cells in RSTR (23.11%) versus LTBI (24.01%) (Extended Data Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig10">4b</a>).</p><p>To explore whether the CD45<sup>+</sup>CCR7<sup>+</sup>CD4<sup>+</sup> T cells in RSTR had a naïve or T<sub>SCM</sub> cell phenotype, PBMC from RSTR (<i>n</i> = 12) and LTBI (<i>n</i> = 12) from the validation cohort were stained with carboxyfluorescein succinimidyl ester (CFSE) and stimulated with ESAT6/CFP10 or whole <i>Mtb</i> lysate overnight and activated naive-like CD69<sup>+</sup>CD154<sup>+</sup>CCR7<sup>+</sup>CD45RA<sup>+</sup>CD45RO<sup>−</sup> lymphocytes were sorted by flow cytometry and cultured for 7 days to assess antigen-specific expansion<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 22" title="Gattinoni, L. et al. A human memory T cell subset with stem cell-like properties. Nat. Med. 17, 1290–1297 (2011)." href="/articles/s41590-024-01897-8#ref-CR22" id="ref-link-section-d4561556e2095">22</a></sup> (Extended Data Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig11">5a–c</a> and Supplementary Table <a data-track="click" data-track-label="link" data-track-action="supplementary material anchor" href="/articles/s41590-024-01897-8#MOESM3">3</a>). At the time of sorting, we observed a significantly higher proportion of naive-like CCR7<sup>+</sup>CD45RA<sup>+</sup>CD45RO<sup>−</sup> T cells coexpressing the T<sub>SCM</sub> cell marker CD95 in LTBI compared to RSTR participants, regardless of stimulation (Extended Data Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig11">5d</a>). The frequency of naive-like CD95<sup>+</sup> T cells (hereafter T<sub>SCM</sub> cells)<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 22" title="Gattinoni, L. et al. A human memory T cell subset with stem cell-like properties. Nat. Med. 17, 1290–1297 (2011)." href="/articles/s41590-024-01897-8#ref-CR22" id="ref-link-section-d4561556e2121">22</a></sup> that proliferated in response to whole <i>Mtb</i> lysate or ESAT6/CFP10 was similar in RSTR and LTBI (Extended Data Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig11">5c,e</a>). However, the <i>Mtb</i> lysate-specific T<sub>SCM</sub> cells in both RSTR and LTBI participants preferentially differentiated into CCR7<sup>+</sup>CD45RA<sup>−</sup> central memory T cells, while ESAT6/CFP10-stimulated T<sub>SCM</sub> cells resulted in a higher frequency of CCR7<sup>−</sup>CD45RA<sup>−</sup> effector memory T cells (Extended Data Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig11">5f,g</a>). Taken together, <i>Mtb</i>-specific T<sub>SCM</sub> cells were found at similar frequencies in RSTR and LTBI, and proliferated and differentiated into various memory phenotypes after antigen re-encounter.</p><h3 class="c-article__sub-heading" id="Sec6"> <i>Mtb</i>-specific CD4<sup>+</sup> T cells in RSTR have a T<sub>reg</sub> phenotype</h3><p>Next, we investigated the activation phenotypes of the clonally expanded ESAT6/CFP10-specific CD4<sup>+</sup> T cells identified by SELECT-seq. GO analysis on these T cells identified T cell activation pathways, including MAPK signaling, TCR signaling, TNF signaling and noncanonical NF-κB signaling, that were enriched in RSTR compared to LTBI in the household contact cohort (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig4">4a</a> and Supplementary Tables <a data-track="click" data-track-label="link" data-track-action="supplementary material anchor" href="/articles/s41590-024-01897-8#MOESM3">9</a>–<a data-track="click" data-track-label="link" data-track-action="supplementary material anchor" href="/articles/s41590-024-01897-8#MOESM3">11</a>). Genes encoding costimulatory molecules such as IL2RB, FAS (CD95), TNFRSF4 (OX40), ICOS, CTLA4 and IKZF1 were significantly upregulated in clonally expanded ESAT6/CFP10-specific CD4<sup>+</sup> T cells in RSTR compared to LTBI (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig4">4b</a>). To further explore the CD4 signaling interactions in these RSTR cells, we conducted a protein–protein interaction network analysis on 119 immune-related genes that were upregulated in RSTR compared to LTBI. Three network clusters were identified from the genes upregulated in RSTR: a CD4 activation network centered on <i>CTLA4</i>, which encodes for a T cell checkpoint inhibitor, an innate immunity network, and a lymphocyte trafficking network (Supplementary Tables <a data-track="click" data-track-label="link" data-track-action="supplementary material anchor" href="/articles/s41590-024-01897-8#MOESM3">12</a>–<a data-track="click" data-track-label="link" data-track-action="supplementary material anchor" href="/articles/s41590-024-01897-8#MOESM3">14</a>). The CD4 activation network identified molecules with extensive interactions with other molecules, including <i>CTLA4</i>, <i>IKZF1</i>, <i>CD5</i>, <i>CCR7</i>, <i>IL2RB</i> and <i>BATF</i>, which were defined as key signaling hubs (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig4">4c</a> and Supplementary Tables <a data-track="click" data-track-label="link" data-track-action="supplementary material anchor" href="/articles/s41590-024-01897-8#MOESM3">15</a> and <a data-track="click" data-track-label="link" data-track-action="supplementary material anchor" href="/articles/s41590-024-01897-8#MOESM3">16</a>). Based on the identification of CTLA4 as a key signaling hub in RSTR, we investigated whether the SELECT-seq clonally expanded ESAT6/CFP10-specific CD4<sup>+</sup> T cells exhibited a regulatory T (T<sub>reg</sub>) cell phenotype. We found higher expression of several T<sub>reg</sub> cell-associated genes, including <i>IKZF2</i> (Helios) and <i>TNFRSF18</i> (GITR), in clonally expanded ESAT6/CFP10-specific CD4<sup>+</sup> T cells from RSTR compared to LTBI (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig4">4d</a>)<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 23" title="Zemmour, D. et al. Single-cell gene expression reveals a landscape of regulatory T cell phenotypes shaped by the TCR. Nat. Immunol. 19, 291–301 (2018)." href="/articles/s41590-024-01897-8#ref-CR23" id="ref-link-section-d4561556e2245">23</a></sup>. Targeted transcriptomics also suggested a higher frequency of ESAT6/CFP10-specific <i>FOXP3</i><sup>+</sup> CD25<sup>+</sup> CD4<sup>+</sup> T cells among RSTR compared to LTBI (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig4">4e</a>).</p><div class="c-article-section__figure js-c-reading-companion-figures-item" data-test="figure" data-container-section="figure" id="figure-4" data-title="Mtb-specific T cells exhibit distinct activation phenotypes in RSTR compared to LTBI."><figure><figcaption><b id="Fig4" class="c-article-section__figure-caption" data-test="figure-caption-text">Fig. 4: <i>Mtb</i>-specific T cells exhibit distinct activation phenotypes in RSTR compared to LTBI.</b></figcaption><div class="c-article-section__figure-content"><div class="c-article-section__figure-item"><a class="c-article-section__figure-link" data-test="img-link" data-track="click" data-track-label="image" data-track-action="view figure" href="/articles/s41590-024-01897-8/figures/4" rel="nofollow"><picture><source type="image/webp" srcset="//media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41590-024-01897-8/MediaObjects/41590_2024_1897_Fig4_HTML.png?as=webp"><img aria-describedby="Fig4" src="//media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41590-024-01897-8/MediaObjects/41590_2024_1897_Fig4_HTML.png" alt="figure 4" loading="lazy" width="685" height="625"></picture></a></div><div class="c-article-section__figure-description" data-test="bottom-caption" id="figure-4-desc"><p><b>a</b>, GO terms related to T cell activation in clonally expanded ESAT6/CFP10-specific CD4<sup>+</sup> T cells among RSTR (cell number, 231) compared to LTBI (cell number, 293) from the discovery household contact based on SELECT-seq. <b>b</b>, Expressions of activation and costimulation genes in RSTR and LTBI, as in <b>a</b>. Statistical significance was calculated by two-sided Wilcoxon rank-sum tests with the Bonferroni method. **Adjusted <i>P</i> value <0.005, ***adjusted <i>P</i> value <0.001. <b>c</b>, Interaction network of DEGs related to T cell activation upregulated in RSTR compared to LTBI, as in <b>a</b>. <b>d</b>, Mean expression of T<sub>reg</sub> cell-associated genes within each RSTR and LTBI, as in <b>a</b>. <b>e</b>, A box plot showing the median and interquartile range of frequencies of <i>FOXP3</i><sup>+</sup>CD25<sup>+</sup> T<sub>reg</sub> cells in ESAT6<sup>/</sup>CFP10-specific CD4<sup>+</sup> T cells from the same RSTR (<i>n</i> = 3) and LTBI (<i>n</i> = 4) participants as in <b>a</b> using index sorting and targeted transcriptomics. The whiskers represent minima and maxima. No statistical test was performed due to small sample sizes. <b>f</b>, Gating strategy for CD25<sup>+</sup> T cells and Foxp3<sup>+</sup>CD25<sup>+</sup> T<sub>reg</sub> cells in ESAT6/CFP10-specific CD4<sup>+</sup> T cells from RSTR (<i>n</i> = 17) and LTBI participants (<i>n</i> = 20) in the validation household contact cohort. <b>g</b>, Frequencies of CD25<sup>+</sup>CD4<sup>+</sup> T cells in ESAT6/CFP10-specific CD4<sup>+</sup> T cells are shown as in <b>f</b>. <b>h</b>, Frequencies of Foxp3<sup>+</sup>CD25<sup>+</sup> T<sub>reg</sub> and IL-10<sup>+</sup> CD4<sup>+</sup> T cells in ESAT6<sup>/</sup>CFP10-specific CD4<sup>+</sup> T cells are shown as in <b>f</b>. <b>i</b>, MFIs of IL-10 in supernatants after 48 h ESAT6/CFP10 or 12 h <i>Mtb</i> lysate stimulation based on multiplex cytokine analysis. Significance was determined by two-sided Student’s <i>t</i>-test. Significance in <b>g</b> and <b>h</b> was determined by two-sided Wilcoxon rank-sum tests.</p></div></div><div class="u-text-right u-hide-print"><a class="c-article__pill-button" data-test="article-link" data-track="click" data-track-label="button" data-track-action="view figure" href="/articles/s41590-024-01897-8/figures/4" data-track-dest="link:Figure4 Full size image" aria-label="Full size image figure 4" rel="nofollow"><span>Full size image</span><svg width="16" height="16" focusable="false" role="img" aria-hidden="true" class="u-icon"><use xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="#icon-eds-i-chevron-right-small"></use></svg></a></div></figure></div><p>To assess whether <i>Mtb</i>-specific CD4<sup>+</sup> T<sub>reg</sub> cells were enriched in RSTR compared to LTBI, we performed flow cytometry and multiplex cytokine analysis (ProcartaPlex) on the validation cohort to determine the concentrations of 28 secreted cytokines in conditioned supernatants from cultured PBMC poststimulation with ESAT6/CFP10 or <i>Mtb</i> lysate for 6, 12, 24 and 48 h (Extended Data Figs. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig13">7</a> and <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig14">8</a>). The frequency of CD25<sup>+</sup> cells in total CD4<sup>+</sup> T cells and ESAT6/CFP10-specific CD4<sup>+</sup> T cells was higher in RSTR than in LTBI (total, 17.26% versus 14.94%, <i>P</i> = 0.028; ESAT6/CFP10-specific, 66.83% versus 63.54%, <i>P</i> = 0.065) (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig4">4f,g</a> and Extended Data Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig12">6a</a>). ESAT6/CFP10-specific CD4<sup>+</sup> T cells coexpressing protein markers Foxp3 and CD25 were detectable in both RSTR and LTBI at equal frequencies (25.89% versus 24.00%, <i>P</i> = 0.424) (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig4">4f,h</a>). However, in the same participants, we also observed a higher frequency of both CD25<sup>+</sup>CD4<sup>+</sup> T cells and FoxP3<sup>+</sup>CD25<sup>+</sup>CD4<sup>+</sup> T cells in RSTR compared to LTBI (CD25<sup>+</sup>, 62.98% versus 57.16%, <i>P</i> = 0.052; FoxP3<sup>+</sup>CD25<sup>+</sup>, 19.44% versus 16.13%, <i>P</i> = 0.013) after <i>Mtb</i> lysate stimulation (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig4">4g,h</a>). While the frequency of IL-10<sup>+</sup> cells in ESAT6/CFP10-specific CD4<sup>+</sup> T cells was comparable between RSTR and LTBI using flow cytometry (0.37% versus 0.33%, <i>P</i> = 0.532), the concentration of IL-10 in conditioned supernatants post-ESAT6/CFP10 stimulation was higher in LTBI compared to RSTR (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig4">4h,i</a>). Within the same participants, IL-10 concentrations in supernatants after <i>Mtb</i> lysate stimulation trended higher in RSTR than LTBI (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig4">4i</a>). The concentration of TGF-β in supernatants post-ESAT6/CFP10 stimulation was similar between RSTR and LTBI (Extended Data Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig12">6b</a>). Finally, the ratio of anti-inflammatory FoxP3<sup>+</sup>CD25<sup>+</sup> T<sub>reg</sub> cell fraction to proinflammatory T cell fraction, which included RORγt<sup>+</sup>T-bet<sup>+</sup> T<sub>H</sub>1* cells, RORγt<sup>+</sup>T-bet<sup>−</sup> T<sub>H</sub>17 cells and RORγt<sup>−</sup>T-bet<sup>+</sup> T<sub>H</sub>1 cells, was significantly higher in RSTR than LTBI (Extended Data Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig12">6c</a>). Together, these data indicated that RSTR <i>Mtb</i>-specific T cells exhibited a distinct activation profile, enriched for a T<sub>reg</sub> cell phenotype, compared to LTBI.</p><h3 class="c-article__sub-heading" id="Sec7"> <i>Mtb</i>-specific RSTR CD4<sup>+</sup> T cells have a T<sub>H</sub>17 cell-like phenotype</h3><p>Next, we investigated the polarization of ESAT6/CFP10-specific CD4<sup>+</sup> T cell functions in PBMC from RSTR from the discovery household contact cohort. Targeted transcriptomics revealed that <i>RORC</i><sup>+</sup><i>TBX21</i><sup>+</sup> T<sub>H</sub>1* or <i>RORC</i><sup>−</sup><i>TBX21</i><sup>+</sup> T<sub>H</sub>1 CD4<sup>+</sup> T cells were more abundant in ESAT6/CFP10-specific CD4<sup>+</sup> T cells among LTBI than RSTR (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig5">5a</a>), which is consistent with known LTBI phenotypes<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 24" title="Lindestam Arlehamn, C. S. et al. Memory T cells in latent Mycobacterium tuberculosis infection are directed against three antigenic islands and largely contained in a CXCR3+CCR6+ Th1 subset. PLoS Pathog. 9, e1003130 (2013)." href="/articles/s41590-024-01897-8#ref-CR24" id="ref-link-section-d4561556e2589">24</a></sup>, while <i>RORC</i><sup>+</sup><i>TBX21</i><sup>−</sup> T<sub>H</sub>17 CD4<sup>+</sup> T cells were enriched in RSTR (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig5">5a</a> and Extended Data Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig9">3c</a>). SELECT-seq showed increased expression of several T<sub>H</sub>17 cell-associated genes, including <i>BATF</i>, <i>RORA</i> and <i>STAT3</i>, in clonally expanded ESAT6/CFP10-specific CD4<sup>+</sup> T cells from RSTR compared to LTBI (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig5">5b,c</a>; <a href="http://amigo.geneontology.org/amigo/term/GO:0072539">GO:0072539</a> from MSigDB database)<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 25" title="Sopel, N., Graser, A., Mousset, S. & Finotto, S. The transcription factor BATF modulates cytokine-mediated responses in T cells. Cytokine Growth Factor Rev. 30, 39–45 (2016)." href="/articles/s41590-024-01897-8#ref-CR25" id="ref-link-section-d4561556e2635">25</a>,<a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 26" title="Arlehamn, C. L. et al. Transcriptional profile of tuberculosis antigen-specific T cells reveals novel multifunctional features. J. Immunol. 193, 2931–2940 (2014)." href="/articles/s41590-024-01897-8#ref-CR26" id="ref-link-section-d4561556e2638">26</a></sup>, while the expression of T<sub>H</sub>1 and T<sub>H</sub>1* cell-associated genes <i>IL2</i>, <i>TBX21</i> and <i>CXCR3</i> was increased in LTBI (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig5">5b,c</a>).</p><div class="c-article-section__figure js-c-reading-companion-figures-item" data-test="figure" data-container-section="figure" id="figure-5" data-title="Enrichment of Mtb-specific TH17-like cells among RSTR."><figure><figcaption><b id="Fig5" class="c-article-section__figure-caption" data-test="figure-caption-text">Fig. 5: Enrichment of <i>Mtb</i>-specific T<sub>H</sub>17-like cells among RSTR.</b></figcaption><div class="c-article-section__figure-content"><div class="c-article-section__figure-item"><a class="c-article-section__figure-link" data-test="img-link" data-track="click" data-track-label="image" data-track-action="view figure" href="/articles/s41590-024-01897-8/figures/5" rel="nofollow"><picture><source type="image/webp" srcset="//media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41590-024-01897-8/MediaObjects/41590_2024_1897_Fig5_HTML.png?as=webp"><img aria-describedby="Fig5" src="//media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41590-024-01897-8/MediaObjects/41590_2024_1897_Fig5_HTML.png" alt="figure 5" loading="lazy" width="685" height="570"></picture></a></div><div class="c-article-section__figure-description" data-test="bottom-caption" id="figure-5-desc"><p><b>a</b>, Box plots showing the median and interquartile range of frequencies of <i>RORC</i><sup>+</sup><i>TBX21</i><sup>+</sup>, <i>RORC</i><sup>+</sup><i>TBX21</i><sup>−</sup>, <i>RORC</i><sup>−</sup><i>TBX21</i><sup>+</sup> and <i>RORC</i><sup>−</sup><i>TBX21</i><sup>−</sup> cells in ESAT6/CFP10-specific CD4<sup>+</sup> T cells in RSTR (<i>n</i> = 3) and LTBI (<i>n</i> = 4) in the discovery household contact cohort using targeted transcriptomics. The whiskers represent minima and maxima. Statistical testing was not performed due to small sample sizes. <b>b</b>, SELECT-seq showing the mean expression of genes associated with T<sub>H</sub>1 or T<sub>H</sub>17 phenotypes from <a href="http://amigo.geneontology.org/amigo/term/GO:0072539">GO:0072539</a> in the MSigDB database in clonally expanded ESAT6/CFP10-specific CD4<sup>+</sup> T cells within both RSTR and LTBI in the household contact cohort as in <b>a</b>. <b>c</b>, Expressions of T<sub>H</sub>1 or T<sub>H</sub>17 cell-associated genes in RSTR and LTBI in the household contact cohort, as shown in <b>a</b>. Significance was determined using two-sided Wilcoxon rank-sum tests with the Bonferroni method. ***Adjusted <i>P</i> value <0.001. <b>d</b>, Representative flow cytometry showing the expression of RORγt and T-bet in ESAT6/CFP10-specific CD4<sup>+</sup> T cells from RSTR (<i>n</i> = 17) and LTBI participants (<i>n</i> = 20) in the validation household contact cohort. <b>e</b>, Frequencies of RORγ<sup>+</sup>T-bet<sup>+</sup>, RORγt<sup>+</sup>T-bet<sup>−</sup>, RORγt<sup>−</sup>T-bet<sup>+</sup> and RORγt<sup>−</sup>T-bet<sup>−</sup>cells in ESAT6/CFP10-specific CD4<sup>+</sup> T cells or <i>Mtb</i> lysate-specific CD4<sup>+</sup> T cells from RSTRs and LTBI, as in <b>d</b>. <b>f</b>, Frequencies of IL-17A<sup>+</sup> cells in ESAT6/CFP10-specific CD4<sup>+</sup> T cells or <i>Mtb</i> lysate-specific CD4<sup>+</sup> T cells from RSTRs and LTBI as in <b>d</b>. <b>g</b>, MFIs of IL-17A or IL-23 in supernatants of PBMC are shown after 24 h or 6 h stimulation, respectively, with <i>Mtb</i> lysate. Significance was determined by two-sided Student’s <i>t</i>-test. Significance in <b>e</b> and <b>f</b> was determined by two-sided Wilcoxon rank-sum tests.</p></div></div><div class="u-text-right u-hide-print"><a class="c-article__pill-button" data-test="article-link" data-track="click" data-track-label="button" data-track-action="view figure" href="/articles/s41590-024-01897-8/figures/5" data-track-dest="link:Figure5 Full size image" aria-label="Full size image figure 5" rel="nofollow"><span>Full size image</span><svg width="16" height="16" focusable="false" role="img" aria-hidden="true" class="u-icon"><use xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="#icon-eds-i-chevron-right-small"></use></svg></a></div></figure></div><p>To test whether <i>Mtb</i>-specific T<sub>H</sub>17-like cells were enriched in RSTR compared to LTBI, we performed flow cytometry and multiplex cytokine analysis on the validation cohort. After ESAT6/CFP10 stimulation, we found an increased frequency of RORγt<sup>+</sup>T-bet<sup>+</sup> or CXCR3<sup>+</sup>CCR6<sup>+</sup> T<sub>H</sub>1* and RORγt<sup>−</sup>T-bet<sup>+</sup> T<sub>H</sub>1 cells in LTBI <i>Mtb</i>-specific CD4<sup>+</sup> T cells compared to RSTR (RORγt<sup>+</sup>T-bet<sup>+</sup>, 15.6% versus 12.9%, <i>P</i> = 0.020; CXCR3<sup>+</sup>CCR6<sup>+</sup>, 16.7% versus 12.3%, <i>P</i> < 0.001; and RORγt<sup>−</sup>T-bet<sup>+</sup>, 41.9% versus 30.22%, <i>P</i> < 0.001) compared to RSTR (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig5">5d,e</a> and Extended Data Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig15">9a,b</a>)<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 24" title="Lindestam Arlehamn, C. S. et al. Memory T cells in latent Mycobacterium tuberculosis infection are directed against three antigenic islands and largely contained in a CXCR3+CCR6+ Th1 subset. PLoS Pathog. 9, e1003130 (2013)." href="/articles/s41590-024-01897-8#ref-CR24" id="ref-link-section-d4561556e2893">24</a></sup>. Conversely, we detected an increased frequency of RORγt<sup>+</sup>T-bet<sup>−</sup> T<sub>H</sub>17 T cells in RSTR compared to LTBI (5.86% versus 2.36%, <i>P</i> < 0.001) (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig5">5e</a>). Similarly, after <i>Mtb</i> lysate stimulation, the frequency of RORγt<sup>+</sup>T-bet<sup>+</sup> or CXCR3<sup>+</sup>CCR6<sup>+</sup> T<sub>H</sub>1* CD4<sup>+</sup> T cells was higher in LTBI (RORγt<sup>+</sup>T-bet<sup>+</sup>, 20.3% versus 15.3%, <i>P</i> = 0.039 and CXCR3<sup>+</sup>CCR6<sup>+</sup>, 20.2% versus 13.5%, <i>P</i> = 0.003), while the frequency of RORγt<sup>+</sup>T-bet<sup>−</sup> T<sub>H</sub>17 CD4<sup>+</sup> T cells was higher in RSTR (2.66% versus 1.72%, <i>P</i> = 0.011) (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig5">5e</a> and Extended Data Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig15">9b</a>). ICS and multiplex cytokine analysis found higher production of IFN-γ in PBMC from LTBI than RSTR after both stimulations (Extended Data Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig13">7</a>, <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig14">8</a> and <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig15">9b</a>). IL-17A<sup>+</sup> cells trended higher in RSTR <i>Mtb</i>-specific CD4<sup>+</sup> T cells compared to LTBI after both stimulations, although this was not statistically significant (ESAT6/CFP10,1.24% versus 0.95%, <i>P</i> = 0.104 and <i>Mtb</i> lysate, 1.39% versus 1.20%, <i>P</i> = 0.209) (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig5">5f</a>). Multiplex cytokine analysis showed that expression of IL-17A increased in both RSTR and LTBI after ESAT6/CFP10 and <i>Mtb</i> lysate stimulations (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig5">5g</a> and Extended Data Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig13">7</a>). We also noted higher amounts of the T<sub>H</sub>17 cell-promoting cytokine IL-23 in RSTR conditioned supernatants post-<i>Mtb</i> lysate stimulation than LTBI (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig5">5g</a>). Thus, RSTR <i>Mtb</i>-specific T cells were biased toward a T<sub>H</sub>17 cell-like functional program, rather than the T<sub>H</sub>1* cell program observed in LTBI.</p><h3 class="c-article__sub-heading" id="Sec8"> <i>Mtb</i>-specific RSTR CD4<sup>+</sup> T cell phenotypes associate with bacterial control</h3><p>To further contextualize our findings, we analyzed public data from cohorts with clinically relevant endpoints. We leveraged data from the Adolescent Cohort Study (ACS), a longitudinal study of LTBI adolescents in South Africa, in which blood was collected every 6 months over 2 years to identify blood correlates of TB risk<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 27" title="Mahomed, H. et al. TB incidence in an adolescent cohort in South Africa. PLoS ONE 8, e59652 (2013)." href="/articles/s41590-024-01897-8#ref-CR27" id="ref-link-section-d4561556e3028">27</a>,<a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 28" title="Zak, D. E. et al. A blood RNA signature for tuberculosis disease risk: a prospective cohort study. Lancet 387, 2312–2322 (2016)." href="/articles/s41590-024-01897-8#ref-CR28" id="ref-link-section-d4561556e3031">28</a></sup>. To determine whether the T cell transcriptional programs identified in RSTR were associated with a lack of progression to active TB disease, we studied 144 ACS participants who had whole-blood transcriptomic data, among which 43 participants progressed to microbiologically confirmed TB (progressors) and 101 did not develop TB (nonprogressors), and calculated gene module scores across all time points as the mean expression level of functional associated genes. A ‘T<sub>N</sub>_T<sub>SCM</sub> module score’ composed of seven genes related to the naive-like (T<sub>N</sub>) or T<sub>SCM</sub> cell phenotype we describe here, including <i>CCR7</i> and <i>TCF7</i> (<a data-track="click" data-track-label="link" data-track-action="section anchor" href="/articles/s41590-024-01897-8#Sec10">Methods</a>)<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 29" title="Galletti, G. et al. Two subsets of stem-like CD8+ memory T cell progenitors with distinct fate commitments in humans. Nat. Immunol. 21, 1552–1562 (2020)." href="/articles/s41590-024-01897-8#ref-CR29" id="ref-link-section-d4561556e3053">29</a></sup>, was higher in nonprogressors than progressors up to 180 days before the onset of TB disease (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig6">6a</a>). There was a trend toward a higher score in nonprogressors compared to progressors as far back as 2 years before disease onset (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig6">6a</a>). A ‘T cell activation module score’, composed of 24 genes identified through network analysis<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 30" title="Szklarczyk, D. et al. The STRING database in 2023: protein–protein association networks and functional enrichment analyses for any sequenced genome of interest. Nucleic Acids Res. 51, D638–D646 (2023)." href="/articles/s41590-024-01897-8#ref-CR30" id="ref-link-section-d4561556e3064">30</a></sup> in clonally expanded ESAT6/CFP10-specific CD4<sup>+</sup> T cells among RSTR (<a data-track="click" data-track-label="link" data-track-action="section anchor" href="/articles/s41590-024-01897-8#Sec10">Methods</a>, Supplementary Tables <a data-track="click" data-track-label="link" data-track-action="supplementary material anchor" href="/articles/s41590-024-01897-8#MOESM3">15</a> and <a data-track="click" data-track-label="link" data-track-action="supplementary material anchor" href="/articles/s41590-024-01897-8#MOESM3">16</a> and Supplementary Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig4">4c</a>), including <i>CTLA4</i>, <i>IL2RB</i> and <i>IKZF1</i>, was enriched in nonprogressors compared to progressors up to 180 days before disease onset (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig6">6b</a>). This association was also significant up to 2 years before disease onset (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig6">6b</a>). Thus, we found an enrichment of naive-like and T cell activation transcriptional programs among a subset of South African adolescents with LTBI who did not progress to active TB disease compared to those who did progress.</p><div class="c-article-section__figure js-c-reading-companion-figures-item" data-test="figure" data-container-section="figure" id="figure-6" data-title="RSTR CD4+ T cell phenotypes associate with lack of progression to active TB in the ACS cohort and bacterial control in NHPs."><figure><figcaption><b id="Fig6" class="c-article-section__figure-caption" data-test="figure-caption-text">Fig. 6: RSTR CD4<sup>+</sup> T cell phenotypes associate with lack of progression to active TB in the ACS cohort and bacterial control in NHPs.</b></figcaption><div class="c-article-section__figure-content"><div class="c-article-section__figure-item"><a class="c-article-section__figure-link" data-test="img-link" data-track="click" data-track-label="image" data-track-action="view figure" href="/articles/s41590-024-01897-8/figures/6" rel="nofollow"><picture><source type="image/webp" srcset="//media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41590-024-01897-8/MediaObjects/41590_2024_1897_Fig6_HTML.png?as=webp"><img aria-describedby="Fig6" src="//media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41590-024-01897-8/MediaObjects/41590_2024_1897_Fig6_HTML.png" alt="figure 6" loading="lazy" width="685" height="674"></picture></a></div><div class="c-article-section__figure-description" data-test="bottom-caption" id="figure-6-desc"><p><b>a</b>,<b>b</b>, Box plots showing the median and interquartile range of RSTR-associated T<sub>N</sub>_T<sub>SCM</sub> cell module (<b>a</b>) or T cell activation module scores (<b>b</b>) from whole-blood bulk transcriptomics at serial time points before TB diagnosis among nonprogressors (<i>n</i> = 101) and progressors (<i>n</i> = 43) in the ACS (GSE79362) (ref. <sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 28" title="Zak, D. E. et al. A blood RNA signature for tuberculosis disease risk: a prospective cohort study. Lancet 387, 2312–2322 (2016)." href="/articles/s41590-024-01897-8#ref-CR28" id="ref-link-section-d4561556e3135">28</a></sup>). The whiskers represent minima and maxima. Scores were computed as geometric mean of gene expressions. Significance was determined by two-sided Student’s <i>t</i>-test. <b>c</b>, Frequencies of <i>Mtb</i>-specific CD4<sup>+</sup> T cells expressing <i>RORC</i> and/or <i>TBX21</i> or <i>FOXP3</i> among TB nonprogressors (<i>n</i> = 35) and progressors (<i>n</i> = 35) in ACS<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 31" title="Musvosvi, M. et al. T cell receptor repertoires associated with control and disease progression following Mycobacterium tuberculosis infection. Nat. Med. 29, 258–269 (2023)." href="/articles/s41590-024-01897-8#ref-CR31" id="ref-link-section-d4561556e3167">31</a></sup> using single-cell targeted transcriptomics. Significance was determined by two-sided Wilcoxon rank-sum tests. <b>d</b>,<b>e</b>, Heat maps showing the mean expression of the top 15 enriched genes in a stem-like T cell subset (<b>d</b>) and a T1–T17 cell subset (<b>e</b>) identified in granulomas from cynomolgus macaques in clonally expanded ESAT6/CFP10-specific CD4<sup>+</sup> T cells in RSTR (cell number, 231) and LTBI (cell number, 293) in the household contact cohort. <b>f</b>, Stem-like T cell- and T1–T17 T cell-associated gene module scores as in <b>d</b>. <b>g</b>, RSTR-associated T<sub>H</sub>17 cell gene module score from whole-blood bulk transcriptomics in rhesus macaques at day 0 (W0), day 2 (D2), week 2 (W2), week 4 (W4) and week 12 (W12), postintravenous vaccination with BCG. <b>h</b>, Flow cytometry showing cell count and frequency of IFNγ<sup>−</sup>IL-2<sup>−</sup>IL-17<sup>+</sup>TNF<sup>−</sup> T<sub>H</sub>17 CD4<sup>+</sup> cells in the bronchoalveolar lavage of BCG-vaccinated rhesus macaques as in <b>g</b>. For <b>c</b> and <b>f</b>–<b>h</b>, significance was calculated using the two-sided Wilcoxon rank-sum tests.</p></div></div><div class="u-text-right u-hide-print"><a class="c-article__pill-button" data-test="article-link" data-track="click" data-track-label="button" data-track-action="view figure" href="/articles/s41590-024-01897-8/figures/6" data-track-dest="link:Figure6 Full size image" aria-label="Full size image figure 6" rel="nofollow"><span>Full size image</span><svg width="16" height="16" focusable="false" role="img" aria-hidden="true" class="u-icon"><use xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="#icon-eds-i-chevron-right-small"></use></svg></a></div></figure></div><p>As the associations within whole-blood transcriptomes did not necessarily implicate T cells directly, we analyzed the frequency of CD4<sup>+</sup> T cell subsets using publicly available targeted transcriptomic data<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 31" title="Musvosvi, M. et al. T cell receptor repertoires associated with control and disease progression following Mycobacterium tuberculosis infection. Nat. Med. 29, 258–269 (2023)." href="/articles/s41590-024-01897-8#ref-CR31" id="ref-link-section-d4561556e3239">31</a></sup> from the ACS cohort in response to stimulation with whole <i>Mtb</i> lysate (35 progressors and 35 nonprogressors, with all time points collapsed). The frequency of <i>RORC</i><sup>+</sup><i>TBX21</i><sup>+</sup> T<sub>H</sub>1* or <i>RORC</i><sup>−</sup><i>TBX21</i><sup>+</sup> T<sub>H</sub>1 cells in <i>Mtb</i>-specific CD4<sup>+</sup> T cells was similar between progressors and nonprogressors (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig6">6c</a>). However, the frequencies of <i>RORC</i><sup>+</sup><i>TBX21</i><sup>−</sup> T<sub>H</sub>17 and <i>FOXP3</i><sup>+</sup> T<sub>reg</sub> were higher in nonprogressors than progressors (T<sub>H</sub>17, 16.0% versus 13.3%, <i>P</i> = 0.01 and T<sub>reg</sub>, 3.01% versus 2.40%, <i>P</i> = 0.07) (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig6">6c</a>), indicating that RSTR-defined T<sub>reg</sub> cell-like and T<sub>H</sub>17 cell-like phenotypes were enriched in South African adolescents with LTBI who did not progress to active TB disease.</p><p>Finally, we sought to examine whether RSTR CD4<sup>+</sup> T cell phenotypes were associated with bacterial control by analyzing published NHP studies in which the <i>Mtb</i> burden was quantified after natural infection or experimental vaccination. We first leveraged a study of 26 granulomas from four cynomolgus macaques assessed at 10 weeks after low-dose infection with <i>Mtb</i> (<10 colony forming units (c.f.u.)) using single-cell RNA sequencing (RNA-seq)<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 32" title="Gideon, H. P. et al. Multimodal profiling of lung granulomas in macaques reveals cellular correlates of tuberculosis control. Immunity 55, 827–846.e810 (2022)." href="/articles/s41590-024-01897-8#ref-CR32" id="ref-link-section-d4561556e3319">32</a></sup> in which several T cell clusters, including <i>GZMB</i><sup>+</sup><i>S100A10</i><sup>+</sup> cytotoxic, <i>MKI67</i><sup>+</sup> proliferating, <i>CCR7</i><sup>+</sup><i>TCF7</i><sup>+</sup> stem-like and <i>TXNIP</i><sup>+</sup><i>CCR6</i><sup>+</sup> T1–T17 cell populations, were associated with reduced bacterial burden<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 32" title="Gideon, H. P. et al. Multimodal profiling of lung granulomas in macaques reveals cellular correlates of tuberculosis control. Immunity 55, 827–846.e810 (2022)." href="/articles/s41590-024-01897-8#ref-CR32" id="ref-link-section-d4561556e3350">32</a></sup>. We found higher expression of the top genes in the macaque stem-like cell subset (such as <i>CCR7</i> and <i>TCF7</i>; Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig6">6d</a>) and T1–T17 population 1 subset genes (such as <i>CCR6</i> and <i>TXNIP</i>; Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig6">6e</a>) in clonally expanded activated CD4<sup>+</sup> T cells in RSTR compared to LTBI. The associated gene module scores composed of the top 15 genes from each subset were significantly higher in RSTR than LTBI (<a data-track="click" data-track-label="link" data-track-action="section anchor" href="/articles/s41590-024-01897-8#Sec10">Methods</a> and Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig6">6f</a>). We also examined the blood transcriptomes and T cell phenotypes in 34 rhesus macaques that were vaccinated intravenously with BCG, challenged with <i>Mtb</i> 24 weeks postvaccination, and assessed for <i>Mtb</i> burden by necropsy at 36 weeks postvaccination or upon development of humane endpoint clinical signs (c.f.u. <100 designated as protected and c.f.u. >100 nonprotected) to identify correlates of protective immunity<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 33" title="Liu, Y. E. et al. Blood transcriptional correlates of BCG-induced protection against tuberculosis in rhesus macaques. Cell Rep. Med 4, 101096 (2023)." href="/articles/s41590-024-01897-8#ref-CR33" id="ref-link-section-d4561556e3388">33</a>,<a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 34" title="Darrah, P. A. et al. Airway T cells are a correlate of i.v. Bacille Calmette–Guerin-mediated protection against tuberculosis in rhesus macaques. Cell Host Microbe 31, 962–977.e968 (2023)." href="/articles/s41590-024-01897-8#ref-CR34" id="ref-link-section-d4561556e3391">34</a></sup>. Expression of a T<sub>H</sub>17 cell gene module based on genes enriched in clonally expanded activated CD4<sup>+</sup> T cells from RSTR in Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig5">5b</a> (<i>CCR6</i>, <i>RORA</i>, <i>CCR4</i> and <i>BATF</i>) was higher in protected macaques than nonprotected ones (<a data-track="click" data-track-label="link" data-track-action="section anchor" href="/articles/s41590-024-01897-8#Sec10">Methods</a> and Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig6">6g</a>). Similarly, the absolute number, but not the frequency of purified protein derivative (PPD)-specific IFN-γ<sup>−</sup>IL-2<sup>−</sup>TNF<sup>−</sup>IL-17<sup>+</sup> CD4<sup>+</sup> T cells in bronchoalveolar lavage was higher in protected macaques than nonprotected ones (Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig6">6h</a>). As such, T<sub>H</sub>17 cell-like functional programs that were enriched in <i>Mtb</i>-specific T cells in RSTR were also associated with the control of <i>Mtb</i> infection in NHP models.</p></div></div></section><section data-title="Discussion"><div class="c-article-section" id="Sec9-section"><h2 class="c-article-section__title js-section-title js-c-reading-companion-sections-item" id="Sec9">Discussion</h2><div class="c-article-section__content" id="Sec9-content"><p>Here, we showed that <i>Mtb</i>-specific IFN-γ<sup>−</sup> T cell responses to the <i>Mtb</i> antigens ESAT6/CFP10 were not detectable in a low-exposure cohort in Uganda, but were clonally expanded in individuals in a household contact cohort who ‘resist’ <i>Mtb</i> infection, indicating the IFN-γ<sup>−</sup> T cell functional profile may be a reliable measure of <i>Mtb</i> exposure and adaptive immune priming. RSTR <i>Mtb</i>-specific T cells expressed T<sub>reg</sub> cell and T<sub>H</sub>17 cell-like phenotypes compared to LTBI, who were characterized by T<sub>H</sub>1 and T<sub>H</sub>1* phenotypes. T<sub>H</sub>17-like and T<sub>reg</sub> cell transcriptional programs were also observed in a publicly available cohort of adolescent LTBI nonprogressors, suggesting an association with protection along the clinical spectrum of human TB. Finally, The T<sub>H</sub>17 cell-like functional programs enriched in RSTRs were also associated with early <i>Mtb</i> control in natural and experimental infections in NHP models. Our findings suggest that RSTR may control <i>Mtb</i> after initial exposure and define a set of T cell biomarkers that could be used to identify RSTR in other populations after high-intensity exposure to <i>Mtb</i>.</p><p>Our data support an important role for <i>Mtb</i>-specific T cells expressing IL-17 in the absence of IFN-γ. Studies in mice that received an ESAT6 subunit vaccine indicated a role for IL-17A-producing CD4<sup>+</sup> T cells in recruiting T<sub>H</sub>1 cells, which directly restricted bacterial growth<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 35" title="Khader, S. A. et al. IL-23 and IL-17 in the establishment of protective pulmonary CD4+ T cell responses after vaccination and during Mycobacterium tuberculosis challenge. Nat. Immunol. 8, 369–377 (2007)." href="/articles/s41590-024-01897-8#ref-CR35" id="ref-link-section-d4561556e3507">35</a></sup>. Consistent with this, <i>RORC</i> loss-of-function mutations in humans result in impaired IFN-γ response to mycobacteria<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 36" title="Okada, S. et al. Impairment of immunity to Candida and Mycobacterium in humans with bi-allelic RORC mutations. Science 349, 606–613 (2015)." href="/articles/s41590-024-01897-8#ref-CR36" id="ref-link-section-d4561556e3515">36</a></sup>. A longitudinal study of <i>Mtb</i>-exposed household contacts in Peru found a reduction in T<sub>H</sub>17-like effector cells in individuals who previously developed active TB disease compared to those who did not<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 37" title="Nathan, A. et al. Multimodally profiling memory T cells from a tuberculosis cohort identifies cell state associations with demographics, environment and disease. Nat. Immunol. 22, 781–793 (2021)." href="/articles/s41590-024-01897-8#ref-CR37" id="ref-link-section-d4561556e3524">37</a></sup>. In a repeated limiting-dose challenge model in NHPs, mucosal T<sub>H</sub>17 cells correlated with protective immunity<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 38" title="Dijkman, K. et al. Prevention of tuberculosis infection and disease by local BCG in repeatedly exposed rhesus macaques. Nat. Med. 25, 255–262 (2019)." href="/articles/s41590-024-01897-8#ref-CR38" id="ref-link-section-d4561556e3530">38</a></sup>. Group 3 innate lymphoid cells mediated protection against <i>Mtb</i> through IL-17 and IL-22 induction of CXCL13 and the formation of lymphoid follicles within granulomas<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 39" title="Ardain, A. et al. Group 3 innate lymphoid cells mediate early protective immunity against tuberculosis. Nature 570, 528–532 (2019)." href="/articles/s41590-024-01897-8#ref-CR39" id="ref-link-section-d4561556e3538">39</a></sup>. Here, we found an expansion of T<sub>H</sub>17 cell-like transcriptional program in LTBI adolescents who did not to progress to active TB over 2 years of observation compared to progressors in a South African cohort. These data support the notion that LTBI is heterogeneous and consists of individuals at risk for and individuals protected from <i>Mtb</i> disease. Future work may help replace the terms RSTR and LTBI, which are defined by IFN-γ<sup>+</sup> immunity, with more clinically informative definitions.</p><p>Our results are not inconsistent with a model in which <i>Mtb</i> is recognized and eliminated without the assistance of T cells at the earliest stages of exposure. Alveolar macrophages are among the first airway immune cells to encounter <i>Mtb</i> and are generally permissive to <i>Mtb</i> growth<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 40" title="Cohen, S. B. et al. Alveolar macrophages provide an early Mycobacterium tuberculosis niche and initiate dissemination. Cell Host Microbe 24, 439–446.e434 (2018)." href="/articles/s41590-024-01897-8#ref-CR40" id="ref-link-section-d4561556e3561">40</a></sup>. Studies of blood-derived myeloid cells have revealed differences in the transcriptional response between RSTR and LTBIs in household contacts in Uganda<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 41" title="Simmons, J. D. et al. Monocyte metabolic transcriptional programs associate with resistance to tuberculin skin test/interferon-γ release assay conversion. J. Clin. Invest. 131, e140073 (2021)." href="/articles/s41590-024-01897-8#ref-CR41" id="ref-link-section-d4561556e3565">41</a>,<a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 42" title="Seshadri, C. et al. Transcriptional networks are associated with resistance to Mycobacterium tuberculosis infection. PLoS ONE 12, e0175844 (2017)." href="/articles/s41590-024-01897-8#ref-CR42" id="ref-link-section-d4561556e3568">42</a></sup> and a cohort of miners in South Africa<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 43" title="Chihota, V. N. et al. Resistance to Mycobacterium tuberculosis infection among highly TB exposed South African gold miners. PLoS ONE 17, e0265036 (2022)." href="/articles/s41590-024-01897-8#ref-CR43" id="ref-link-section-d4561556e3573">43</a></sup>. A study of <i>Mtb</i>-exposed household contacts in Indonesia reported higher IL-6 concentrations after in vitro stimulation with <i>Escherichia</i> <i>coli</i> among those who remained persistently IGRA<sup>−</sup> compared to those who became IGRA<sup>+</sup><sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 44" title="Verrall, A. J. et al. Early clearance of Mycobacterium tuberculosis is associated with increased innate immune responses. J. Infect. Dis. 221, 1342–1350 (2020)." href="/articles/s41590-024-01897-8#ref-CR44" id="ref-link-section-d4561556e3590">44</a></sup>. Notably, IL-6 and TGF-β are required to prime T<sub>H</sub>17 responses<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 45" title="Bhaumik, S. & Basu, R. Cellular and molecular dynamics of Th17 differentiation and its developmental plasticity in the intestinal immune response. Front. Immunol. 8, 254 (2017)." href="/articles/s41590-024-01897-8#ref-CR45" id="ref-link-section-d4561556e3596">45</a></sup>. These data support a model whereby differences in the early innate immune response to <i>Mtb</i> infection might result in differences in T cell priming. Antibodies also contribute to bacterial control through a variety of mechanisms, including activating antibacterial programs within macrophages<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 46" title="Lu, L. L. et al. A functional role for antibodies in tuberculosis. Cell 167, 433–443.e414 (2016)." href="/articles/s41590-024-01897-8#ref-CR46" id="ref-link-section-d4561556e3603">46</a></sup>. Monoclonal antibodies derived from TST<sup>−</sup> <i>Mtb</i>-exposed healthcare workers confer protection against <i>Mtb</i> challenge in mice<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 47" title="Li, H. et al. Latently and uninfected healthcare workers exposed to TB make protective antibodies against Mycobacterium tuberculosis. Proc. Natl Acad. Sci. USA 114, 5023–5028 (2017)." href="/articles/s41590-024-01897-8#ref-CR47" id="ref-link-section-d4561556e3616">47</a></sup>. Thus, non-T cell mechanisms may act in concert to reduce the bacterial load and tune the inflammatory environment to prime the T cell phenotypes that we observed.</p><p><i>Mtb</i>-specific IFN-γ<sup>+</sup> CD4 T cells may be a reliable proxy for established infection with <i>Mtb</i>. The concentration of IFN-γ in IGRA supernatants is associated with progression to active TB<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 48" title="Andrews, J. R. et al. The dynamics of QuantiFERON-TB gold in-tube conversion and reversion in a cohort of South African adolescents. Am. J. Respir. Crit. Care Med. 191, 584–591 (2015)." href="/articles/s41590-024-01897-8#ref-CR48" id="ref-link-section-d4561556e3630">48</a>,<a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 49" title="Andrews, J. R. et al. Serial QuantiFERON testing and tuberculosis disease risk among young children: an observational cohort study. Lancet Respir. Med. 5, 282–290 (2017)." href="/articles/s41590-024-01897-8#ref-CR49" id="ref-link-section-d4561556e3633">49</a></sup>. The frequency of <i>Mtb</i>-specific IFN-γ<sup>+</sup> CD4 T cells increases along the spectrum of IGRA nonconverters (persistently IGRA<sup>−</sup>), reverters (previously IGRA<sup>+</sup>, but now IGRA<sup>−</sup>) and persistently IGRA<sup>+</sup> South African adolescents<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 50" title="Mpande, C. A. M. et al. Mycobacterium tuberculosis-specific T cell functional, memory, and activation profiles in QuantiFERON-reverters are consistent with controlled infection. Front Immunol. 12, 712480 (2021)." href="/articles/s41590-024-01897-8#ref-CR50" id="ref-link-section-d4561556e3651">50</a></sup>. Our study characterized the phenotypes of T cells targeting ESAT6/CFP10, which are specific for <i>Mtb</i> and incorporated into IGRA and whole <i>Mtb</i> lysates, which contain many more antigens that are shared across many mycobacterial species. However, we did not identify the additional antigens present in <i>Mtb</i> lysate driving this T cell response. In a study of <i>Mtb</i>-infected mice and BCG-vaccinated humans, <i>Mtb</i> infection drove ESAT6-specific T cells to become more differentiated than T cells specific for Ag85B, consistent with the observation that <i>Mtb</i> restricts expression of Ag85B, but not ESAT6, during chronic infection<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" title="Moguche, A. O. et al. Antigen availability shapes T cell differentiation and function during tuberculosis. Cell Host Microbe 21, 695–706.e695 (2017)." href="#ref-CR51" id="ref-link-section-d4561556e3674">51</a>,<a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" title="Rogerson, B. J. et al. Expression levels of Mycobacterium tuberculosis antigen-encoding genes versus production levels of antigen-specific T cells during stationary level lung infection in mice. Immunology 118, 195–201 (2006)." href="#ref-CR52" id="ref-link-section-d4561556e3674_1">52</a>,<a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 53" title="Shi, L., North, R. & Gennaro, M. L. Effect of growth state on transcription levels of genes encoding major secreted antigens of Mycobacterium tuberculosis in the mouse lung. Infect. Immun. 72, 2420–2424 (2004)." href="/articles/s41590-024-01897-8#ref-CR53" id="ref-link-section-d4561556e3677">53</a></sup>. The LTBI nonprogressors that we studied here were shown to preferentially target PE13 and CFP10 when compared to progressors<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 31" title="Musvosvi, M. et al. T cell receptor repertoires associated with control and disease progression following Mycobacterium tuberculosis infection. Nat. Med. 29, 258–269 (2023)." href="/articles/s41590-024-01897-8#ref-CR31" id="ref-link-section-d4561556e3682">31</a></sup>. Similar efforts may define antigens present in Mtb lysate that are preferentially targeted by RSTR compared to LTBI.</p></div></div></section><section data-title="Methods"><div class="c-article-section" id="Sec10-section"><h2 class="c-article-section__title js-section-title js-c-reading-companion-sections-item" id="Sec10">Methods</h2><div class="c-article-section__content" id="Sec10-content"><h3 class="c-article__sub-heading" id="Sec11">Low-exposure cohort</h3><p>The low-exposure cohort was enrolled from a low TB incidence district that was identified by the Kampala Capital City Authority based on low TB transmission rates<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 13" title="Wobudeya, E., Sekadde-Kasirye, M., Kimuli, D., Mugabe, F. & Lukoye, D. Trend and outcome of notified children with tuberculosis during 2011–2015 in Kampala, Uganda. BMC Public Health 17, 963 (2017)." href="/articles/s41590-024-01897-8#ref-CR13" id="ref-link-section-d4561556e3698">13</a></sup>. Subjects were screened and enrolled for health assessment and blood draws between 2017 and 2018 in Uganda (Extended Data Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig7">1</a>). All healthy, nonpregnant participants were eligible. A total of 247 individuals were approached in this district, of which 230 consented and were screened for previous TB treatment, pregnancy, medications and serious illnesses. A total of 220 healthy, nonpregnant individuals were enrolled, and 211 of the enrolled participants were found to be noninfected with human immundeficiency virus (HIV). All participants reported no known contact with a TB case. Based on TST and IGRA (QuantiFERON-TB (QFT) Gold) concordance, we were able to classify 196 HIV-noninfected individuals as either TST<sup>+</sup>IGRA<sup>+</sup> concordant, TST<sup>+</sup>IGRA<sup>−</sup> discordant, TST<sup>−</sup>IGRA<sup>−</sup> concordant or TST<sup>−</sup>IGRA<sup>+</sup> discordant. For the present study, we selected 17 TST<sup>−</sup>IGRA<sup>−</sup> subjects (mean age of 21.59 years; 9 males and 8 females) and 19 TST<sup>+</sup>IGRA<sup>+</sup> (LTBI) subjects (mean age of 24.47 years; 10 males and 9 females) after matching for age and sex.</p><h3 class="c-article__sub-heading" id="Sec12">Household contact cohort</h3><p>The full details of this cohort have been previously published<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 54" title="Stein, C. M. et al. Long-term stability of resistance to latent Mycobacterium tuberculosis infection in highly exposed tuberculosis household contacts in Kampala, Uganda. Clin. Infect. Dis. 68, 1705–1712 (2019)." href="/articles/s41590-024-01897-8#ref-CR54" id="ref-link-section-d4561556e3739">54</a></sup>. Initially, household contacts of sputum culture-positive cases of pulmonary TB were enrolled between 2002 and 2012 as part of the Kawempe Community Health Study. At baseline, individuals who had no active <i>Mtb</i> infection determined by sputum culture and radiology were enrolled. Upon enrollment, individuals were longitudinally screened during a 2-year follow-up period by TST (Mantoux method, 0.1 ml of 5 tuberculin units of PPD, Tubersol; Connaught Laboratories), in which a positive TST was defined as an induration of >10 mm for individuals noninfected with HIV and >5 mm for individuals infected with HIV. In this initial study, a total of 2,585 individuals were enrolled in the household contact cohort. Of these individuals, 198 (10.7%) remained persistently TST negative over the 2-year follow-up period upon their enrollment.</p><p>Between 2014 and 2017, 691 household contacts from the initial study were identified as eligible for retracing according to the epidemiologic risk score criteria previously published<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 54" title="Stein, C. M. et al. Long-term stability of resistance to latent Mycobacterium tuberculosis infection in highly exposed tuberculosis household contacts in Kampala, Uganda. Clin. Infect. Dis. 68, 1705–1712 (2019)." href="/articles/s41590-024-01897-8#ref-CR54" id="ref-link-section-d4561556e3749">54</a></sup>. Of these individuals, 441 (63.8%) were enrolled in a subsequent longitudinal follow-up retracing study. The mean time between enrollment in the initial study and completion of the retracing study was 9.5 years. During the retracing study, individuals completed three QFT assays over 2 years. On their final visit, individuals also underwent the TST (positive TST defined above). RSTR were classified as such if all TST assays (five from the initial study and one at the end of the retracing study) and the three QFTs from the retracing study were concordantly negative, while LTBI participants were classified as such if all TST and QFT assays were positive. PBMC were isolated from whole blood collected during the retracing study by Ficoll–Hypaque density centrifugation and cryopreserved until use.</p><p>For the present study, we selected PBMC from a subset of 45 LTBI (mean age of 23.9 years; 23 males and 22 females) and 45 RSTR (mean age of 22.8 years; 22 males and 23 females) subjects from the retracing study after matching for age, sex, exposure risk score and documented lack of HIV co-infection (Supplementary Tables <a data-track="click" data-track-label="link" data-track-action="supplementary material anchor" href="/articles/s41590-024-01897-8#MOESM3">4</a> and <a data-track="click" data-track-label="link" data-track-action="supplementary material anchor" href="/articles/s41590-024-01897-8#MOESM3">5</a>). No power calculations were performed to predetermine sample sizes, but our sample sizes are similar to those reported in our published studies of this cohort<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 5" title="Lu, L. L. et al. IFN-γ-independent immune markers of Mycobacterium tuberculosis exposure. Nat. Med. 25, 977–987 (2019)." href="/articles/s41590-024-01897-8#ref-CR5" id="ref-link-section-d4561556e3762">5</a>,<a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 41" title="Simmons, J. D. et al. Monocyte metabolic transcriptional programs associate with resistance to tuberculin skin test/interferon-γ release assay conversion. J. Clin. Invest. 131, e140073 (2021)." href="/articles/s41590-024-01897-8#ref-CR41" id="ref-link-section-d4561556e3765">41</a></sup>. All study subjects gave written, informed consent, approved by the National AIDS Research Committee, the Uganda National Council for Science and Technology and the institutional review board at University Hospitals Cleveland Medical Center.</p><h3 class="c-article__sub-heading" id="Sec13">ACS</h3><p>The ACS is a published cohort that followed healthy adolescents (<i>n</i> = 6,363; aged 12–18 years) from South Africa and monitored them for progression from latent TB infection to active disease over 2 years<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 28" title="Zak, D. E. et al. A blood RNA signature for tuberculosis disease risk: a prospective cohort study. Lancet 387, 2312–2322 (2016)." href="/articles/s41590-024-01897-8#ref-CR28" id="ref-link-section-d4561556e3780">28</a></sup>. We obtained publicly available bulk RNA-seq data measured in whole-blood samples every 6 months for 2 years from 144 individuals (aged 12–18 years; 48 males and 96 females)<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 28" title="Zak, D. E. et al. A blood RNA signature for tuberculosis disease risk: a prospective cohort study. Lancet 387, 2312–2322 (2016)." href="/articles/s41590-024-01897-8#ref-CR28" id="ref-link-section-d4561556e3784">28</a>,<a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 31" title="Musvosvi, M. et al. T cell receptor repertoires associated with control and disease progression following Mycobacterium tuberculosis infection. Nat. Med. 29, 258–269 (2023)." href="/articles/s41590-024-01897-8#ref-CR31" id="ref-link-section-d4561556e3787">31</a></sup>. At baseline, adolescents were diagnosed with LTBI by a positive QFT assay (>0.35 IU ml<sup>−1</sup>) and/or a positive TST (>10 mm). Progression to active TB was determined by evidence of intrathoracic disease (two positive sputum smears or one positive Mycobacteria Growth Indicator Tube liquid culture). Of these 144 individuals, 43 progressed to active TB (referred to here as progressors), while the remaining 101 did not develop active TB during the study period (referred to here as nonprogressors). Progressors only include individuals who developed active TB over 6 months after enrollment (or the first positive TST or positive QFT assay) to exclude early asymptomatic disease. From the same study, we also obtained publicly available data on single-cell targeted transcriptomics performed on sorted CD4<sup>+</sup> T cells of PBMC after stimulation with <i>Mtb</i> lysate obtained at the same time points mentioned above, in which there were 70 participants with 35 progressors and 35 nonprogressors<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 31" title="Musvosvi, M. et al. T cell receptor repertoires associated with control and disease progression following Mycobacterium tuberculosis infection. Nat. Med. 29, 258–269 (2023)." href="/articles/s41590-024-01897-8#ref-CR31" id="ref-link-section-d4561556e3799">31</a></sup>. All individuals were HIV-uninfected.</p><h3 class="c-article__sub-heading" id="Sec14">NHPs</h3><p>We obtained publicly available gene sets from single-cell sequencing data of granuloma homogenate from cynomolgus macaques (<i>n</i> = 4; mean age of 7 years, 3 males and 1 female)<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 32" title="Gideon, H. P. et al. Multimodal profiling of lung granulomas in macaques reveals cellular correlates of tuberculosis control. Immunity 55, 827–846.e810 (2022)." href="/articles/s41590-024-01897-8#ref-CR32" id="ref-link-section-d4561556e3814">32</a></sup>. The cynomolgus macaques were infected with low-dose <i>Mtb</i> via bronchoscopic instillation (<10 c.f.u., Erdman strain). Infection was confirmed at 4 weeks by positron emission tomography computed tomography and monitored until necropsy 10-weeks postinfection by clinical and radiographic examinations. We utilized gene sets from single-cell sequencing data obtained from 26 granulomas sampled 10-weeks postinfection at necropsy.</p><p>Additionally, we obtained whole-blood transcriptome data and flow cytometry data of bronchoalveolar lavage fluid from rhesus macaques (<i>n</i> = 34; median age of 4.4 years, 16 males and 18 females)<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 33" title="Liu, Y. E. et al. Blood transcriptional correlates of BCG-induced protection against tuberculosis in rhesus macaques. Cell Rep. Med 4, 101096 (2023)." href="/articles/s41590-024-01897-8#ref-CR33" id="ref-link-section-d4561556e3827">33</a>,<a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 34" title="Darrah, P. A. et al. Airway T cells are a correlate of i.v. Bacille Calmette–Guerin-mediated protection against tuberculosis in rhesus macaques. Cell Host Microbe 31, 962–977.e968 (2023)." href="/articles/s41590-024-01897-8#ref-CR34" id="ref-link-section-d4561556e3830">34</a></sup>. The rhesus macaques were randomized into six vaccine groups (based on birth colony, gender and prevaccination CD4 T cell responses to <i>Mtb</i> PPD) and received intravenous BCG vaccination of varying doses (4.5–7.5 log<sub>10</sub> c.f.u. in half-log increments). The rhesus macaques received <i>Mtb</i> challenge via bronchoscope (average 12 c.f.u., Erdman strain) 24 weeks postvaccination. We analyzed bulk RNA-seq data from whole blood collected at baseline, 2 days, 2 weeks, 4 weeks and 12 weeks postvaccination. We analyzed flow cytometry data from bronchoalveolar lavage fluid collected at baseline, 2 weeks, 4 weeks, 8 weeks and 12 weeks postvaccination. The rhesus macaques were euthanized either 36 weeks postvaccination or when they developed clinical signs of humane endpoints, and total <i>Mtb</i> c.f.u. was measured upon necropsy.</p><h3 class="c-article__sub-heading" id="Sec15">Antigens</h3><p>Overlapping peptide pools targeting ESAT6 and CFP10 were used to stimulate T cells for these studies (BEI Resources). Peptides were 15 or 16 mers with 11 or 12 amino acid overlaps for ESAT6 protein and 11 amino acid overlaps for CFP10. <i>Mtb</i> whole-cell lysate from H37Rv was also used to stimulate T cells (BEI Resources). Dimethyl sulfoxide (DMSO) (Sigma-Aldrich) was used as a negative control. <i>Staphylococcus enterotoxin</i> B (List Biological Laboratories) was used as a positive control for the low-exposure cohort.</p><h3 class="c-article__sub-heading" id="Sec16">ICS</h3><p>ICS was performed on samples from the low-exposure cohort as we have previously described<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 5" title="Lu, L. L. et al. IFN-γ-independent immune markers of Mycobacterium tuberculosis exposure. Nat. Med. 25, 977–987 (2019)." href="/articles/s41590-024-01897-8#ref-CR5" id="ref-link-section-d4561556e3869">5</a></sup>. The same ICS assay and flow cytometry acquisition method was performed on samples from the household contacts with minor modifications. Before staining, samples from the household contacts were divided in half to be analyzed using two multiparameter flow cytometry panels, one for the analysis of T<sub>reg</sub> subsets and one for T<sub>H</sub> subsets (panel details in Supplementary Table <a data-track="click" data-track-label="link" data-track-action="supplementary material anchor" href="/articles/s41590-024-01897-8#MOESM3">3</a>). Cells were permeabilized and underwent intracellular staining using the eBioscience Foxp3/Transcription Factor Staining Buffer Set (eBioscience) according to the manufacturer’s directions to allow for the analysis of transcription factors. In the household contacts data, PBMC from two RSTR subjects were excluded from data acquisition and analysis due to bacterial contamination of the samples after overnight rest. The investigators were blinded to group allocation during acquisition of flow cytometry data in the validation household contact cohort.</p><h3 class="c-article__sub-heading" id="Sec17">SELECT-seq on <i>Mtb</i>-reactive T cells</h3><p>We conducted single-cell whole transcriptomics using the SELECT-seq protocol, which includes stimulation and sorting procedures<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 16" title="Huang, H. et al. Select sequencing of clonally expanded CD8+ T cells reveals limits to clonal expansion. Proc. Natl Acad. Sci. USA 116, 8995–9001 (2019)." href="/articles/s41590-024-01897-8#ref-CR16" id="ref-link-section-d4561556e3892">16</a>,<a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 31" title="Musvosvi, M. et al. T cell receptor repertoires associated with control and disease progression following Mycobacterium tuberculosis infection. Nat. Med. 29, 258–269 (2023)." href="/articles/s41590-024-01897-8#ref-CR31" id="ref-link-section-d4561556e3895">31</a></sup>. In brief, PBMC from RSTR and LTBI samples were stimulated as described in the ICS methods above. Notably, before the stimulation, the cells were cultured in 1 μg ml<sup>−1</sup> anti-CD154 antibody for 30 min to prevent CD154 downregulation. After stimulation, cells were first stained (Supplementary Table <a data-track="click" data-track-label="link" data-track-action="supplementary material anchor" href="/articles/s41590-024-01897-8#MOESM3">3</a>) and index sorted on live CD3<sup>+</sup>/TCRαβ<sup>+</sup> cells positive for CD69 and CD154 and/or CD137 on a BD FACSAria Fusion. These antigen-specific T cells were fluorescence-activated cell sorted (FACS) into individual wells of a 96-well PCR plate with lysis buffers. To assess the technical variability, we mixed the lysis buffers with the external RNA control—ERCC RNA Spike-In (a final estimate of ~5,000 molecules per well, Thermo Fisher Scientific). We used the modified Smart-seq2 protocol (Clontech Laboratories) to generate the complementary DNA library. From the library, we took a small aliquot (1 μl) for the nested PCR to amplify and sequence 15 targeted RNAs (<i>TBX21</i>, <i>RORC</i>, <i>GATA3</i>, <i>FOXP3</i>, <i>RUNX1</i>, <i>RUNX3</i>, <i>IFNG</i>, <i>IL2</i>, <i>IL17A</i>, <i>GZMB</i>, <i>PERF</i>, <i>IL4</i>, <i>IL5</i>, <i>IL13</i> and <i>TGFB</i>) and the CDR3 regions of both TCRα and TCRβ chains. Based on the TCR sequences, the Smart-seq2-generated complementary DNAs of the clonally expanded activated T cells were manually selected only on the ESAT6/CFP10-reactive cells for the high-coverage in-depth single-cell full transcriptomic sequencing. We applied the tagmentation and indexing protocol as in the Smart-seq2 protocol and amplified the tagmented DNA. The final pooled library was prepared using the Nextera XT library prep kit (96 index primers; Illumina) protocol and was sequenced on an Illumina HiSeq 2500.</p><h3 class="c-article__sub-heading" id="Sec18">T cell proliferation assay</h3><p>PBMC from RSTR (<i>n</i> = 12) and LTBI (<i>n</i> = 12) were thawed and enumerated as described above. After resting the samples for 2 h, the cells were washed with cold CFSE buffer (PBS supplemented with 5% FBS) and adjusted to 5 × 10<sup>6</sup> cells ml<sup>−1</sup>. The samples were then stained with 5 µM CFSE (BioTracker 488 Green CSFE Cell Proliferation Kit; Sigma-Aldrich) for 5 min at room temperature (RT), followed by three successive washes using CFSE buffer. After the third wash, the cells were reconstituted in media and incubated with anti-CD154 (1 µg ml<sup>−1</sup>) (Miltenyi) for 30 min at 37 °C to prevent internalization of surface CD154. The cells were then stimulated overnight with DMSO, the whole <i>Mtb</i> lysate (100 µg ml<sup>−1</sup>) or ESAT6/CFP10 peptide pool (1 µg ml<sup>−1</sup>). Following stimulation, the cells were stained with LIVE/DEAD Fixable Aqua (Thermo Fisher Scientific) for 15 min at RT. Next, the cells were washed with FACS buffer and stained with CCR7 (phycoerythrin (PE)) for 30 min at 37 °C. The cells were centrifuged and washed with FACS buffer and stained with CD154 (BV711), CD69 (BV450), CD95 (PE–Dazzle 594), CD45RA (PE–Cyanine7) and CD45RO (PerCP-Cyanine5.5) (panel details in Supplementary Table <a data-track="click" data-track-label="link" data-track-action="supplementary material anchor" href="/articles/s41590-024-01897-8#MOESM3">3</a>) for 30 min at 4 °C. The live CD154<sup>+</sup>/CD69<sup>+</sup>CCR7<sup>+</sup>CD45RA<sup>+</sup>CD45RO<sup>−</sup> populations were sorted into 5-ml FACS tubes using a BD FACSAria III Cell Sorter. These cells were then transferred to a 96-well U-bottom plate (Corning) and cultured in sterile-filtered RPMI 1640 (Gibco) supplemented with 10% FBS (HyClone) and 50 units ml<sup>−1</sup> recombinant human IL-2 (Prometheus Pharmaceuticals through UWMC Clinical Pharmacy) at 37 °C. After 7 days in culture, the cells were stained with LIVE/DEAD Fixable Aqua (Thermo Fisher Scientific) for 15 min at RT. Next, the cells were washed and stained with CCR7 (PE) for 30 min at 37 °C. The cells were then washed and stained with additional phenotypic markers (Supplementary Table <a data-track="click" data-track-label="link" data-track-action="supplementary material anchor" href="/articles/s41590-024-01897-8#MOESM3">3</a>) for 30 min at 4 °C. Finally, the cells were fixed using 1% paraformaldehyde (Electron Microscopy Sciences) for 15 min at 4 °C and acquired using a BD LSRFortessa Cell Analyzer. Data were analyzed using FlowJo version 10.10.00 (BD Biosciences).</p><h3 class="c-article__sub-heading" id="Sec19">Multiplex cytokine analysis and ELISA</h3><p>Cytokine profiles were assessed for 18 RSTR and 20 LTBI participants from the household contact cohort using custom 27-plex ProcartaPlex Panel kits (Invitrogen) and enzyme-linked immunosorbent assy (ELISA). Briefly, 100 μl of supernatant from PBMC stimulated with DMSO or ESAT6/CFP10 peptide pool for 6, 12, 24 and 48 h was collected and stored at −80 °C for downstream analyses. For assessment via multiplex cytokine analysis, 50 μl of undiluted culture supernatant was incubated with magnetic capture beads conjugated to analyte-specific antibodies in 96-well plates. The plates were then washed, and the wells containing samples and beads were incubated with detection antibodies followed by streptavidin conjugated to phycoerythrin. Cytokine secretion data (Granulocyte-macrophage colony-stimulating factor (GM-CSF), IFN-α, IFN-γ, IL-1α, IL-1β, IL-10, IL-12p70, IL-13, IL-15, IL-17A, IL-18, IL-1RA, IL-2, IL-21, IL-22, IL-23, IL-27, IL-3, IL-4, IL-5, IL-6, IL-7, IL-8, IL-9, IP-10, TNF-α and TNF-β) were then acquired using the Bio-Plex 200 suspension array system (Bio-Rad). Only samples with bead counts >50 were considered. Due to the concentration of several analytes falling outside the linear range of their respective standard curve, the mean fluorescence intensity (MFI) value for each cytokine per sample was extracted and analyzed in R.</p><p>Due to incompatibility with ProcartaPlex chemistry, TGFβ-1 was detected separately via ELISA. Briefly, 96-well high-binding ELISA plates (Millipore) were coated overnight with mouse anti-human TGFβ-1 IgG (BioLegend) in carbonate coating buffer at 4 °C. Then, the plates were washed and blocked using 2% BSA in PBS for 3 h at 37 °C. After blocking, the plates were washed, 50 μl of the experimental sample or TGFβ-1 standard was added to each well, and the plates were incubated overnight at 4 °C. The supernatant was collected, the plates were washed and 50 μl of biotinylated mouse anti-human TGFβ-1 IgG (BioLegend) was added to each well, and the plates were incubated at 37 °C for 3 h. Next, the plates were washed, and 50 μl of streptavidin conjugated to horseradish peroxidase (BD Biosciences) was added to each well. The plates were incubated at room temperature for 30 min and then washed, and 50 μl of substrate buffer (<i>o</i>-phenylenediamine dihydrochloride (Thermo Fisher Scientific) and Pierce Stable Peroxide Buffer) was added to each well. The plates were developed for 10–15 min at RT before plate absorbance was read at 450 nm using a CLARIOstar Plus Microplate Reader (BMG LabTech).</p><h3 class="c-article__sub-heading" id="Sec20">Computation/statistics</h3><h4 class="c-article__sub-heading c-article__sub-heading--small" id="Sec21">Flow cytometry</h4><p>ICS data were compensated and gated using FlowJo (v9.9.6) (BD Biosciences). Representative gating trees of the low-exposure controls and the household contacts are shown in Extended Data Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig8">2</a>. The data were then processed using the OpenCyto framework (V2.16.1) in the R programming environment (V4.1.2)<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 55" title="Finak, G. et al. OpenCyto: an open source infrastructure for scalable, robust, reproducible, and automated, end-to-end flow cytometry data analysis. PLoS Comput. Biol. 10, e1003806 (2014)." href="/articles/s41590-024-01897-8#ref-CR55" id="ref-link-section-d4561556e4032">55</a></sup>. With the data from the low-exposure controls COMPASS (V1.19.4) was used to achieve a comprehensive and unbiased analysis of the activation profiles of antigen-specific T cells as previously described<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 5" title="Lu, L. L. et al. IFN-γ-independent immune markers of Mycobacterium tuberculosis exposure. Nat. Med. 25, 977–987 (2019)." href="/articles/s41590-024-01897-8#ref-CR5" id="ref-link-section-d4561556e4036">5</a>,<a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 15" title="Lin, L. et al. COMPASS identifies T-cell subsets correlated with clinical outcomes. Nat. Biotechnol. 33, 610–616 (2015)." href="/articles/s41590-024-01897-8#ref-CR15" id="ref-link-section-d4561556e4039">15</a></sup>. For a given subject, COMPASS was also used to compute a polyfunctionality score that summarizes the entire functionality profile into a single number in which greater weight is given to subsets with more than one function. COMPASS was performed on data from the antigen stimulations for CD4<sup>+</sup> T cells to assess T cell subsets expressing IFN-γ, IL-17A, IL-4/5/13, CD107a, TNF, IL-2 and CD154. Poor-quality samples were identified by low CD3 (<10,000 cells) or CD4 (<3,000 cells) counts and were excluded from downstream analysis. The R package ComplexHeatmap (V1.15.1) was used to visualize COMPASS posterior probabilities of response<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 56" title="Gu, Z., Eils, R. & Schlesner, M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics 32, 2847–2849 (2016)." href="/articles/s41590-024-01897-8#ref-CR56" id="ref-link-section-d4561556e4045">56</a></sup>. For all flow cytometry data, magnitudes of T cell responses were calculated as the proportion of gated events. We used Wilcoxon rank-sum tests to compare magnitudes of T cell responses between sample groups.</p><h4 class="c-article__sub-heading c-article__sub-heading--small" id="Sec22">Index sort and targeted RNA-seq</h4><p>The index sort flow cytometry MFI and targeted RNA-seq count dataset were analyzed in R using the packages FlowSOM (V2.1.11)<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 17" title="Van Gassen, S. et al. FlowSOM: using self-organizing maps for visualization and interpretation of cytometry data. Cytometry A 87, 636–645 (2015)." href="/articles/s41590-024-01897-8#ref-CR17" id="ref-link-section-d4561556e4057">17</a></sup> and CATALYST (V1.14.1)<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 57" title="Chevrier, S. et al. Compensation of signal spillover in suspension and imaging mass cytometry. Cell Syst. 6, 612–620.e615 (2018)." href="/articles/s41590-024-01897-8#ref-CR57" id="ref-link-section-d4561556e4061">57</a></sup>. First, all MFI values were shifted by a minimal constant to ensure they were above zero. The non-negative MFI values helped prevent the data overspill. Next, the MFIs underwent an arcsinh5 transformation. The RNA-seq count data were binarized with a cutoff of 5 due to its binary property<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 58" title="Han, A., Glanville, J., Hansmann, L. & Davis, M. M. Linking T-cell receptor sequence to functional phenotype at the single-cell level. Nat. Biotechnol. 32, 684–692 (2014)." href="/articles/s41590-024-01897-8#ref-CR58" id="ref-link-section-d4561556e4065">58</a></sup>. The combined transformed data matrix was standardized to have a mean of 0 and a standard deviation of 1 within each marker across all cells. The CATALYST workflow conducted two series of clustering for the computational efficiency with many cells. The cells were clustered by FlowSOM into 100 groups with a grid size of 15. These 100 groups were meta-clustered by the agglomerative hierarchical clustering to a preset cluster number 40 to identify rare subsets, such as T<sub>reg</sub> and T<sub>H</sub>1*. We visualized these cell phenotypes in the <i>t</i>-SNE plot calculated in CATALYST. Next, we manually merged and annotated these cell phenotype clusters. We used Wilcoxon rank-sum tests to compare the cell phenotype subset composition between the two groups and corrected for multiple hypothesis testing using the Bonferroni method.</p><h4 class="c-article__sub-heading c-article__sub-heading--small" id="Sec23">Full transcriptomic scRNA-seq</h4><p>Python (V3.9) was used for preprocessing of raw sequencing data. To convert the sequencing read fastq files into single-cell count tables, we used STAR<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 59" title="Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013)." href="/articles/s41590-024-01897-8#ref-CR59" id="ref-link-section-d4561556e4085">59</a></sup> to align with the reference GRCh38.genome.ERCC.fa and an index length of 150 bp, and featureCounts<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 60" title="Liao, Y., Smyth, G. K. & Shi, W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923–930 (2014)." href="/articles/s41590-024-01897-8#ref-CR60" id="ref-link-section-d4561556e4089">60</a></sup> to calculate the count tables. The single-cell count tables were imported as a Seurat object using the Seurat package (V4) in R (V4.1.2) for downstream analysis. We filtered cells with unique featureCounts over 4,000, total counts below 5 × 10<sup>5</sup> and mitochondrial counts >5% for doublets, dropouts and dying cells (Extended Data Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig10">4a</a>). CD8<sup>+</sup> T cells were removed due to a low cell number. We gated CD4<sup>+</sup> T cells based on their CD4 and CD8 flow MFIs. The principal component analysis reduced the expressed genes into 30 components. To study cell phenotypic heterogeneity, these CD4<sup>+</sup> T cells were clustered using the graphical-based clustering method and visualized in the Uniform Manifold Approximation and Projection plot. To identify significantly differentially expressed genes (DEGs) between the two groups, we used the Wilcoxon rank-sum test with cutoffs of 0.05 in the Benjamini–Hochberg-adjusted <i>P</i> values and 0.5 in the absolute log<sub>2</sub> of fold change (FC) of the average expression between the two groups. The significantly upregulated genes in RSTR were used to run the GO analysis using DAVID GO<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 61" title="Sherman, B. T. et al. DAVID: a web server for functional enrichment analysis and functional annotation of gene lists (2021 update). Nucleic Acids Res. 50, W216–W221 (2022)." href="/articles/s41590-024-01897-8#ref-CR61" id="ref-link-section-d4561556e4110">61</a>,<a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 62" title="Huang, D. W., Sherman, B. T. & Lempicki, R. A. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protoc. 4, 44–57 (2009)." href="/articles/s41590-024-01897-8#ref-CR62" id="ref-link-section-d4561556e4113">62</a></sup>. For the network analysis, we screened the immune-related genes (GO0002376: immune_system_process) and ran the STRINGdb (V2.16.4) network clustering algorithm in R<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 30" title="Szklarczyk, D. et al. The STRING database in 2023: protein–protein association networks and functional enrichment analyses for any sequenced genome of interest. Nucleic Acids Res. 51, D638–D646 (2023)." href="/articles/s41590-024-01897-8#ref-CR30" id="ref-link-section-d4561556e4117">30</a></sup>. The gene regulatory network inference and motif discovery were conducted using SCENIC (V1.1.2)<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 63" title="Van de Sande, B. et al. A scalable SCENIC workflow for single-cell gene regulatory network analysis. Nat. Protoc. 15, 2247–2276 (2020)." href="/articles/s41590-024-01897-8#ref-CR63" id="ref-link-section-d4561556e4122">63</a></sup>.</p><h4 class="c-article__sub-heading c-article__sub-heading--small" id="Sec24">Mutiplex cytokine analysis and ELISA</h4><p>The multiplex cytokine and TGFβ ELISA data were exported as comma-separated value (CSV) files from the Bio-Plex 200 CLARIOstar Plus Microplate Reader, respectively. All the cytokine data were merged, cleaned and analyzed in R. Due to the low concentration of cytokines detectable by the Procartaplex kit, the MFI data for each cytokine were extracted and assessed. Background-corrected signals were computed by subtracting the signal from the DMSO condition from the antigen stimulation condition. To choose the precise time points with which to compare protein secretion (measured by ProcartaPlex and ELISA) between the RSTR and LTBI groups, we identified samples exhibiting the most favorable signal-to-noise ratio in response to stimulation (ESAT6/CFP10 or <i>Mtb</i> lysate) versus DMSO. This selection was based on applying the <i>t</i>-statistic at each time point assessed. Subsequently, statistical testing between the two groups was performed on a single time point for each analyte using the Student’s <i>t</i>-test (Extended Data Figs. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig13">7</a> and <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig14">8</a>). <i>P</i> values less than 0.05 were considered significant. Data distribution was assumed to be normal but this was not formally tested.</p><h4 class="c-article__sub-heading c-article__sub-heading--small" id="Sec25">ACS cohort analysis</h4><p>We summarized a 7-gene differentiation module (<i>CCR7</i>, <i>SELL</i>, <i>LEF1</i>, <i>TCF7</i>, <i>FOXP1</i>, <i>IL7R</i> and <i>CD27</i>) and the 24-gene activation module (<i>CTLA4</i>, <i>IKZF1</i>, <i>CD5</i>, <i>IL2RB</i>, <i>BATF</i>, <i>TNFRSF4</i>, <i>CXCR4</i>, <i>ICOS</i>, <i>JAK3</i>, <i>TNFRSF18</i>, <i>FAS</i>, <i>JAK1</i>, <i>UBASH3A</i>, <i>S1PR4</i>, <i>NFKB2</i>, <i>PIK3CD</i>, <i>PRKCQ</i>, <i>ETS1</i>, <i>AHR</i>, <i>RASGRP1</i>, <i>SASH3</i>, <i>POU2F2</i>, <i>TTC7A</i> and <i>RFTN1</i>) as the geometric mean of the module gene expression level, and we evaluated whether these modules were differentially expressed between progressors and nonprogressors at all time points before sputum conversion<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 28" title="Zak, D. E. et al. A blood RNA signature for tuberculosis disease risk: a prospective cohort study. Lancet 387, 2312–2322 (2016)." href="/articles/s41590-024-01897-8#ref-CR28" id="ref-link-section-d4561556e4260">28</a></sup>. The phenotypic CD4<sup>+</sup> T cell fractions were calculated from the non-mucosal-associated invariant T (MAIT) CD4<sup>+</sup> T cells previously published<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 31" title="Musvosvi, M. et al. T cell receptor repertoires associated with control and disease progression following Mycobacterium tuberculosis infection. Nat. Med. 29, 258–269 (2023)." href="/articles/s41590-024-01897-8#ref-CR31" id="ref-link-section-d4561556e4268">31</a></sup>. The targeted transcriptional profiling count data were binarized with a cutoff of 5 as we have done previously<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 36" title="Okada, S. et al. Impairment of immunity to Candida and Mycobacterium in humans with bi-allelic RORC mutations. Science 349, 606–613 (2015)." href="/articles/s41590-024-01897-8#ref-CR36" id="ref-link-section-d4561556e4273">36</a></sup> to study cells expressing <i>RORC</i>, <i>TBX21</i> and <i>FOXP3</i>.</p><h4 class="c-article__sub-heading c-article__sub-heading--small" id="Sec26">NHP cohort analysis</h4><p>We derived the gene expression patterns identified in 26 granulomas from 4 cynomolgus macaques obtained 10 weeks after low-dose <i>Mtb</i> infection and analyzed using single-cell RNA-seq<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 32" title="Gideon, H. P. et al. Multimodal profiling of lung granulomas in macaques reveals cellular correlates of tuberculosis control. Immunity 55, 827–846.e810 (2022)." href="/articles/s41590-024-01897-8#ref-CR32" id="ref-link-section-d4561556e4297">32</a></sup>. We selected the top 15 enriched genes in each of the stem-like cell subset and T1–T17 population 1 cell subset and calculated their mean expression using scaled log-normalized gene counts in RSTR and LTBI subjects using the SELECT-seq dataset. Genes that were not expressed or not found were excluded from the analysis. We used the AddModuleScore function from Seurat to calculate the associated gene module scores.</p><p>We examined the expression of the T<sub>H</sub>17 gene module in the whole-blood transcriptome of 34 rhesus macaques from a dose-ranging study of intravenous BCG vaccination followed by <i>Mtb</i> challenge. Data collection and preprocessing have been described in detail previously<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 33" title="Liu, Y. E. et al. Blood transcriptional correlates of BCG-induced protection against tuberculosis in rhesus macaques. Cell Rep. Med 4, 101096 (2023)." href="/articles/s41590-024-01897-8#ref-CR33" id="ref-link-section-d4561556e4309">33</a></sup>. We calculated the RSTR-associated T<sub>H</sub>17 module score using the geometric mean of genes identified in Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig5">5b</a> that could be mapped to the rhesus macaque genome (<i>CCR6</i>, <i>CCR4</i>, <i>BATF</i> and <i>RORA</i>). We then compared this module score across all time points between macaques that were protected (<i>n</i> = 18) versus not protected (<i>n</i> = 16) against <i>Mtb</i> challenge, as determined by total <i>Mtb</i> c.f.u. upon necropsy, using the two-sided Wilcoxon rank-sum test. Flow cytometry was performed on freshly collected bronchoalveolar lavage fluid obtained from these same macaques<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 34" title="Darrah, P. A. et al. Airway T cells are a correlate of i.v. Bacille Calmette–Guerin-mediated protection against tuberculosis in rhesus macaques. Cell Host Microbe 31, 962–977.e968 (2023)." href="/articles/s41590-024-01897-8#ref-CR34" id="ref-link-section-d4561556e4344">34</a></sup>. From these data, we extracted the IL-17-monofunctional T cell phenotype measured by IFNγ<sup>−</sup>IL-2<sup>−</sup>IL-17<sup>+</sup>TNF<sup>−</sup> among CD4<sup>+</sup> T cells after PPD stimulation.</p><h3 class="c-article__sub-heading" id="Sec27">Reporting summary</h3><p>Further information on research design is available in the <a data-track="click" data-track-label="link" data-track-action="supplementary material anchor" href="/articles/s41590-024-01897-8#MOESM1">Nature Portfolio Reporting Summary</a> linked to this article.</p></div></div></section> </div> <div> <section data-title="Data availability"><div class="c-article-section" id="data-availability-section"><h2 class="c-article-section__title js-section-title js-c-reading-companion-sections-item" id="data-availability">Data availability</h2><div class="c-article-section__content" id="data-availability-content"> <p>All the validation flow cytometry data are available for download via ImmPort at <a href="https://www.immport.org">https://www.immport.org</a> under study accession number <a href="https://www.immport.org/shared/study/SDY2277">SDY2277</a> and via Fairdomhub at <a href="https://fairdomhub.org/studies/1179">https://fairdomhub.org/studies/1179</a>. The processed Seurat object generated from the SELECT-seq data is available via Zenodo at <a href="https://zenodo.org/records/7946277">https://zenodo.org/records/7946277</a> (ref. <sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 64" title="Sun, M. et al. Specific CD4+ T cell phenotypes associate with bacterial control in people who ‘resist’ infection with Mycobacterium tuberculosis. Zenodo 
 https://zenodo.org/records/7946277
 
 (2023)." href="/articles/s41590-024-01897-8#ref-CR64" id="ref-link-section-d4561556e4506">64</a></sup>). The raw and processed SELECT-seq data is available at Gene Expression Omnibus (GEO; accession number <a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE267774">GSE267774</a>). The gene sets <a href="http://amigo.geneontology.org/amigo/term/GO:0072539">GO:0072539</a> and <a href="http://amigo.geneontology.org/amigo/term/GO:0002376">GO:0002376</a> from MSigDB were used to analyze SELECT-seq data. From the ACS cohort, whole-blood bulk transcriptomics data is available at GEO (accession number <a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE79362">GSE79362</a>)<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 28" title="Zak, D. E. et al. A blood RNA signature for tuberculosis disease risk: a prospective cohort study. Lancet 387, 2312–2322 (2016)." href="/articles/s41590-024-01897-8#ref-CR28" id="ref-link-section-d4561556e4539">28</a></sup> and single-cell targeted transcriptomics data can be found in supplementary materials in the published study from Musvosvi et al.<sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 31" title="Musvosvi, M. et al. T cell receptor repertoires associated with control and disease progression following Mycobacterium tuberculosis infection. Nat. Med. 29, 258–269 (2023)." href="/articles/s41590-024-01897-8#ref-CR31" id="ref-link-section-d4561556e4543">31</a></sup>.</p> </div></div></section><section data-title="Code availability"><div class="c-article-section" id="code-availability-section"><h2 class="c-article-section__title js-section-title js-c-reading-companion-sections-item" id="code-availability">Code availability</h2><div class="c-article-section__content" id="code-availability-content"> <p>Code to complete multiplex cytokine and flow cytometry analyses can be found via GitHub at <a href="https://github.com/seshadrilab/cd4-phenotypes-sun-2024-procartaplex">https://github.com/seshadrilab/cd4-phenotypes-sun-2024-procartaplex</a> and <a href="https://github.com/seshadrilab/cd4-phenotypes-sun-2024-flow">https://github.com/seshadrilab/cd4-phenotypes-sun-2024-flow</a>. Code to complete SELECT-seq analysis and analyses of ACS and NHP cohort data can be found via GitHub at <a href="https://github.com/ttsunmeng/TB_RSTR_ESAT6CFP10_SelectSeq_analysis_pipeline">https://github.com/ttsunmeng/TB_RSTR_ESAT6CFP10_SelectSeq_analysis_pipeline</a>.</p> </div></div></section><section data-title="Change history"><div class="c-article-section" id="change-history-section"><h2 class="c-article-section__title js-section-title js-c-reading-companion-sections-item" id="change-history">Change history</h2><div class="c-article-section__content" id="change-history-content"><ul class="c-article-change-list"><li class="c-article-change-list__item u-mb-24" id="chg1"><ins datetime="2024-08-19"><h3 class="c-article-change-list__heading u-h3 u-pr-8 u-display-inline">19 August 2024</h3><div class="c-article-change-list__details"><p>A Correction to this paper has been published: <a href="https://doi.org/10.1038/s41590-024-01959-x">https://doi.org/10.1038/s41590-024-01959-x</a></p></div></ins></li></ul></div></div></section><div id="MagazineFulltextArticleBodySuffix"><section aria-labelledby="Bib1" data-title="References"><div class="c-article-section" id="Bib1-section"><h2 class="c-article-section__title js-section-title js-c-reading-companion-sections-item" id="Bib1">References</h2><div class="c-article-section__content" id="Bib1-content"><div data-container-section="references"><ol class="c-article-references" data-track-component="outbound reference" data-track-context="references section"><li class="c-article-references__item js-c-reading-companion-references-item" data-counter="1."><p class="c-article-references__text" id="ref-CR1">Houben, R. 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Specific CD4+ T cell phenotypes associate with bacterial control in people who ‘resist’ infection with Mycobacterium tuberculosis. <i>Zenodo</i> <a href="https://zenodo.org/records/7946277" data-track="click_references" data-track-action="external reference" data-track-value="external reference" data-track-label="https://zenodo.org/records/7946277">https://zenodo.org/records/7946277</a> (2023)<i>.</i></p></li></ol><p class="c-article-references__download u-hide-print"><a data-track="click" data-track-action="download citation references" data-track-label="link" rel="nofollow" href="https://citation-needed.springer.com/v2/references/10.1038/s41590-024-01897-8?format=refman&flavour=references">Download references<svg width="16" height="16" focusable="false" role="img" aria-hidden="true" class="u-icon"><use xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="#icon-eds-i-download-medium"></use></svg></a></p></div></div></div></section></div><section data-title="Acknowledgements"><div class="c-article-section" id="Ack1-section"><h2 class="c-article-section__title js-section-title js-c-reading-companion-sections-item" id="Ack1">Acknowledgements</h2><div class="c-article-section__content" id="Ack1-content"><p>We acknowledge the invaluable contribution made by the Kawempe study team’s medical officers, health visitors, laboratory and data personnel in Uganda and the USA. The present study would not have been possible without the generous participation of the Ugandan TB patients and their families. We thank D. Lauffenberger from MIT in collaborating to analyze the intravenous BCG data. We thank members of the Human Immune Monitoring Center for facilitating this work, especially A. Cheruku. Furthermore, we thank J. Wilhelmy, A. McSween, Q. Xia and C. Wang from the Davis lab for their input on assay development and data analysis. Cell sorting/flow cytometry analysis for this project was done on instruments in the Stanford Shared FACS Facility. We thank the Hi-IMPAcTB Data Management team for organizing the data associated with this project for FAIR sharing, namely C. Demurjian, E. Koo, S. Levine (MIT BioMicro Center) and D. Mugahid (Harvard School of Public Health). This work was supported by the US National Institutes of Health (R01-AI124348 to W.H.B., C.M.S. and T.R.H.; U01-AI115642 to W.H.B., T.R.H., C.M.S. and H.M.-K.; K24-AI137310 to T.R.H.; R01-AI125189 and R01-AI146072 to C.S.; and 75N93019C00071 to C.S. and W.H.B.), the Bill and Melinda Gates Foundation (OPP1151836 and OPP1109001 to W.H.B., T.R.H., C.M.S. and H.M.-K. and OPP1113682 Center for Human Systems Immunology award to M.M.D.) and the Howard Hughes Medical Institute (M.M.D.). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. Additionally, we acknowledge E.D. Layton for technical assistance. Finally, we would like to thank E. Nemes and K. Urdahl for providing critical feedback on the paper before submission.</p></div></div></section><section aria-labelledby="author-information" data-title="Author information"><div class="c-article-section" id="author-information-section"><h2 class="c-article-section__title js-section-title js-c-reading-companion-sections-item" id="author-information">Author information</h2><div class="c-article-section__content" id="author-information-content"><span class="c-article-author-information__subtitle u-visually-hidden" id="author-notes">Author notes</span><ol class="c-article-author-information__list"><li class="c-article-author-information__item" id="na1"><p>These authors contributed equally: Meng Sun, Jolie M. Phan, Nathan S. Kieswetter, Mark M. Davis, Chetan Seshadri.</p></li></ol><h3 class="c-article__sub-heading" id="affiliations">Authors and Affiliations</h3><ol class="c-article-author-affiliation__list"><li id="Aff1"><p class="c-article-author-affiliation__address">Institute for Immunity, Transplantation and Infection, School of Medicine, Stanford University, Stanford, CA, USA</p><p class="c-article-author-affiliation__authors-list">Meng Sun, Huang Huang, Yiran E. Liu, Sanjana Gupta, Neha Gupta, Mustafa Ghanizada, Purvesh Khatri & Mark M. Davis</p></li><li id="Aff2"><p class="c-article-author-affiliation__address">Department of Medicine, University of Washington School of Medicine, Seattle, WA, USA</p><p class="c-article-author-affiliation__authors-list">Jolie M. Phan, Nathan S. Kieswetter, Krystle K. Q. Yu, Malisa T. Smith, Thomas R. Hawn & Chetan Seshadri</p></li><li id="Aff3"><p class="c-article-author-affiliation__address">Department of Epidemiology and Population Health, School of Medicine, Stanford University, Stanford, CA, USA</p><p class="c-article-author-affiliation__authors-list">Yiran E. Liu</p></li><li id="Aff4"><p class="c-article-author-affiliation__address">Department of Immunology and Microbiology, University of Colorado, Anschutz Medicine Campus, Aurora, CO, USA</p><p class="c-article-author-affiliation__authors-list">Chuangqi Wang</p></li><li id="Aff5"><p class="c-article-author-affiliation__address">Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, CA, USA</p><p class="c-article-author-affiliation__authors-list">Sanjana Gupta & Purvesh Khatri</p></li><li id="Aff6"><p class="c-article-author-affiliation__address">Human Immune Monitoring Center, Institute for Immunity, Transplantation and Infection, School of Medicine, Stanford University, Stanford, CA, USA</p><p class="c-article-author-affiliation__authors-list">Gerlinde Obermoser, Holden Terry Maecker, Akshaya Krishnan, Sundari Suresh, Neha Gupta, Mary Rieck & Peter Acs</p></li><li id="Aff7"><p class="c-article-author-affiliation__address">Department of Immunology and Microbiology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark</p><p class="c-article-author-affiliation__authors-list">Mustafa Ghanizada</p></li><li id="Aff8"><p class="c-article-author-affiliation__address">Division of Medical Oncology, Rutgers Cancer Institute of New Jersey, Department of Medicine, Rutgers Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, USA</p><p class="c-article-author-affiliation__authors-list">Shin-Heng Chiou</p></li><li id="Aff9"><p class="c-article-author-affiliation__address">Department of Biomedical Data Sciences, School of Medicine, Stanford University, Stanford, CA, USA</p><p class="c-article-author-affiliation__authors-list">Purvesh Khatri</p></li><li id="Aff10"><p class="c-article-author-affiliation__address">Department of Medicine, Case Western Reserve University, Cleveland, OH, USA</p><p class="c-article-author-affiliation__authors-list">W. Henry Boom</p></li><li id="Aff11"><p class="c-article-author-affiliation__address">Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA</p><p class="c-article-author-affiliation__authors-list">Catherine M. Stein</p></li><li id="Aff12"><p class="c-article-author-affiliation__address">Department of Medicine, Makerere University School of Medicine, Kampala, Uganda</p><p class="c-article-author-affiliation__authors-list">Harriet Mayanja-Kizza</p></li><li id="Aff13"><p class="c-article-author-affiliation__address">Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA, USA</p><p class="c-article-author-affiliation__authors-list">Mark M. Davis</p></li><li id="Aff14"><p class="c-article-author-affiliation__address">Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA, USA</p><p class="c-article-author-affiliation__authors-list">Mark M. Davis</p></li></ol><div class="u-js-hide u-hide-print" data-test="author-info"><span class="c-article__sub-heading">Authors</span><ol class="c-article-authors-search u-list-reset"><li id="auth-Meng-Sun-Aff1"><span class="c-article-authors-search__title u-h3 js-search-name">Meng Sun</span><div class="c-article-authors-search__list"><div class="c-article-authors-search__item c-article-authors-search__list-item--left"><a href="/search?author=Meng%20Sun" class="c-article-button" data-track="click" data-track-action="author link - publication" data-track-label="link" rel="nofollow">View author publications</a></div><div class="c-article-authors-search__item c-article-authors-search__list-item--right"><p class="search-in-title-js c-article-authors-search__text">You can also search for this author in <span class="c-article-identifiers"><a class="c-article-identifiers__item" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=search&term=Meng%20Sun" data-track="click" data-track-action="author link - pubmed" data-track-label="link" rel="nofollow">PubMed</a><span class="u-hide"> </span><a class="c-article-identifiers__item" href="http://scholar.google.co.uk/scholar?as_q=&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_sauthors=%22Meng%20Sun%22&as_publication=&as_ylo=&as_yhi=&as_allsubj=all&hl=en" data-track="click" data-track-action="author link - scholar" data-track-label="link" rel="nofollow">Google Scholar</a></span></p></div></div></li><li id="auth-Jolie_M_-Phan-Aff2"><span class="c-article-authors-search__title u-h3 js-search-name">Jolie M. 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M.S., J.M.P. and N.S.K. performed the experiments, analyzed the data, and generated the figures and tables. M.T.S., H.H., S.G., S.-H.C., M.G. and P.K. facilitated computational analyses. K.K.Q.Y., G.O., H.T.M., A.K., S.S., N.G., M.R. and P.A. facilitated SELECT-seq experiments at the Stanford Human Immune Monitoring Core. C.M.S., H.M.-K., T.R.H. and W.H.B. contributed to epidemiologic analyses and established the clinical cohorts. Y.E.L., C.W. and P.K. contributed the analyses in the NHP study. M.S., J.M.P., N.S.K. and C.S. wrote the paper with contributions from all authors. C.M.S. and W.H.B. facilitated access to biospecimens. C.M.S., W.H.B., T.R.H., M.M.D. and CS provided funding and oversight for the work. All authors read and approved the final paper.</p><h3 class="c-article__sub-heading" id="corresponding-author">Corresponding authors</h3><p id="corresponding-author-list">Correspondence to <a id="corresp-c1" href="mailto:mmdavis@stanford.edu">Mark M. Davis</a> or <a id="corresp-c2" href="mailto:seshadri@uw.edu">Chetan Seshadri</a>.</p></div></div></section><section data-title="Ethics declarations"><div class="c-article-section" id="ethics-section"><h2 class="c-article-section__title js-section-title js-c-reading-companion-sections-item" id="ethics">Ethics declarations</h2><div class="c-article-section__content" id="ethics-content"> <h3 class="c-article__sub-heading" id="FPar4">Competing interests</h3> <p>The authors declare no competing interests.</p> </div></div></section><section data-title="Peer review"><div class="c-article-section" id="peer-review-section"><h2 class="c-article-section__title js-section-title js-c-reading-companion-sections-item" id="peer-review">Peer review</h2><div class="c-article-section__content" id="peer-review-content"> <h3 class="c-article__sub-heading" id="FPar3">Peer review information</h3> <p><i>Nature Immunology</i> thanks Fatoumatta Darboe and Jayne Sutherland for their contribution to the peer review of this paper. Primary Handling Editor: Ioana Staicu, in collaboration with the <i>Nature Immunology</i> team. <a data-track="click" data-track-label="link" data-track-action="supplementary material anchor" href="/articles/s41590-024-01897-8#MOESM2">Peer reviewer reports</a> are available.</p> </div></div></section><section data-title="Additional information"><div class="c-article-section" id="additional-information-section"><h2 class="c-article-section__title js-section-title js-c-reading-companion-sections-item" id="additional-information">Additional information</h2><div class="c-article-section__content" id="additional-information-content"><p><b>Publisher’s note</b> Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></div></div></section><section data-title="Extended data"><div class="c-article-section" id="Sec29-section"><h2 class="c-article-section__title js-section-title js-c-reading-companion-sections-item" id="Sec29">Extended data</h2><div class="c-article-section__content" id="Sec29-content"><div data-test="supplementary-info"><div id="figshareContainer" class="c-article-figshare-container" data-test="figshare-container"></div><div class="c-article-supplementary__item js-c-reading-companion-figures-item" data-test="supp-item" id="Fig7"><h3 class="c-article-supplementary__title u-h3"><a class="print-link" data-track="click" data-track-action="view supplementary info" data-test="supp-info-link" data-track-label="extended data fig. 1 enrollment of low exposure co" href="/articles/s41590-024-01897-8/figures/7" data-supp-info-image="//media.springernature.com/lw685/springer-static/esm/art%3A10.1038%2Fs41590-024-01897-8/MediaObjects/41590_2024_1897_Fig7_ESM.jpg">Extended Data Fig. 1 Enrollment of low exposure cohort, study schema and gating strategy.</a></h3><div class="c-article-supplementary__description" data-component="thumbnail-container"><p><b>(a)</b> Screening and enrollment of low exposure cohort participants for health assessment and blood draw. Enrollment took place in Uganda from July 2017 to March 2018. All healthy non-pregnant participants were eligible. TB, tuberculosis; HIV, human immunodeficiency virus; TST, tuberculin skin test; IGRA, IFN-γ release assay. <b>(b)</b> Schematic of the low exposure cohort, containing 19 LTBI and 17 TST<sup>−</sup>IGRA<sup>−</sup> participants, and the household contact cohort, containing 45 RSTR and 45 LTBI participants. T cell responses to ESAT6/CFP10 or whole <i>Mtb</i> lysate were assessed using intracellular cytokine staining, targeted transcriptomics and SELECT-seq, and validated using flow cytometry and multiplex cytokine analysis on independent samples. <b>(c)</b> Flow cytometry gating strategy for CD4<sup>+</sup> T cell subsets with cytokine and activation marker expressions from PBMCs in the low exposure control cohort stimulated with ESAT6/CFP10 peptide pool for 6 hours.</p></div></div><div class="c-article-supplementary__item js-c-reading-companion-figures-item" data-test="supp-item" id="Fig8"><h3 class="c-article-supplementary__title u-h3"><a class="print-link" data-track="click" data-track-action="view supplementary info" data-test="supp-info-link" data-track-label="extended data fig. 2 the composition of mtb-specif" href="/articles/s41590-024-01897-8/figures/8" data-supp-info-image="//media.springernature.com/lw685/springer-static/esm/art%3A10.1038%2Fs41590-024-01897-8/MediaObjects/41590_2024_1897_Fig8_ESM.jpg">Extended Data Fig. 2 The composition of <i>Mtb</i>-specific T cell subsets.</a></h3><div class="c-article-supplementary__description" data-component="thumbnail-container"><p><b>(a)</b> Gating strategy of ESAT6/CFP10-specific CD4<sup>+</sup> T cells among PBMCs from the household contact cohort using index sort. T cells were identified as CD3<sup>+</sup>CD14<sup>−</sup>/CD19<sup>−</sup>. T cells positive for the TCRɑβ marker were gated on and separated into CD4<sup>+</sup> or CD8<sup>+</sup> subsets. Activated CD3<sup>+</sup>TCRαβ<sup>+</sup> T cells were gated on using CD69, CD137, and CD154 markers. <b>(b)</b> Box plots showing the median and interquartile range of frequencies of ESAT6/CFP10-specific CD4<sup>+</sup> T cell clusters defined in Fig. <a data-track="click" data-track-label="link" data-track-action="figure anchor" href="/articles/s41590-024-01897-8#Fig2">2b</a> among RSTR (n = 3) and LTBI (n = 4) donors in the household contact cohort using index sort and targeted transcriptomics. Whiskers represent minima and maxima. Statistical testing was not performed due to the small sample sizes. <b>(c)</b> Dimensionality reduction (t-SNE) projection of activated CD4<sup>+</sup> T cell subsets sorted from PBMCs among the household contact cohort after stimulation with <i>Mtb</i> lysate for 12 hours.</p></div></div><div class="c-article-supplementary__item js-c-reading-companion-figures-item" data-test="supp-item" id="Fig9"><h3 class="c-article-supplementary__title u-h3"><a class="print-link" data-track="click" data-track-action="view supplementary info" data-test="supp-info-link" data-track-label="extended data fig. 3 quality control filtering and" href="/articles/s41590-024-01897-8/figures/9" data-supp-info-image="//media.springernature.com/lw685/springer-static/esm/art%3A10.1038%2Fs41590-024-01897-8/MediaObjects/41590_2024_1897_Fig9_ESM.jpg">Extended Data Fig. 3 Quality control filtering and key T cell transcriptional factor gene visualization of the SELECT-Seq data.</a></h3><div class="c-article-supplementary__description" data-component="thumbnail-container"><p><b>(a)</b> Filtered cell number by quality control parameters, including the number of unique expressed genes, total gene counts, and percentage of mitochondrial (MT) gene expression, from the whole transcriptomic data of clonally expanded ESAT6/CFP10-specific CD4<sup>+</sup> T cells in the household contact cohort. <b>(b)</b> Dimensionality reduction (UMAP) projection of these clonally expanded CD4<sup>+</sup> T cells showing group, subject, sex, sequencing batches, and subset clusters. <b>(c)</b> Expression of transcriptional factor genes essential for T cell polarization on these clonally expanded CD4<sup>+</sup> T cells. The expression levels were calculated as the log-normalized gene counts from the whole transcriptomic data.</p></div></div><div class="c-article-supplementary__item js-c-reading-companion-figures-item" data-test="supp-item" id="Fig10"><h3 class="c-article-supplementary__title u-h3"><a class="print-link" data-track="click" data-track-action="view supplementary info" data-test="supp-info-link" data-track-label="extended data fig. 4 gating strategy for th panel " href="/articles/s41590-024-01897-8/figures/10" data-supp-info-image="//media.springernature.com/lw685/springer-static/esm/art%3A10.1038%2Fs41590-024-01897-8/MediaObjects/41590_2024_1897_Fig10_ESM.jpg">Extended Data Fig. 4 Gating strategy for T<sub>H</sub> panel and naïve-like <i>Mtb</i> lysate-specific cell frequency in the validation cohort.</a></h3><div class="c-article-supplementary__description" data-component="thumbnail-container"><p><b>(a)</b> Flow cytometry gating strategy for cells expressing memory markers, transcriptional factors and intracellular cytokines associated with T<sub>H</sub>1 and T<sub>H</sub>17 among the validation household contact cohort in response to stimulation with ESAT6/CFP10. A time gate was applied to exclude events affected by sample acquisition aberrations, followed by T cell identification by lymphocyte size, CD3, CD14, and CD19 markers. A singlet gate was then applied, followed by the identification of viable cells and a second lymphocyte gate. A secondary gate was applied to identify IL-17A<sup>+</sup> cells due to spillover spreading. The same gating strategy was applied to samples stimulated with whole <i>Mtb</i> lysate (not shown). <b>(b)</b> Flow cytometry showing the median and interquartile range of frequencies of CD45RA<sup>+</sup>CCR7<sup>+</sup> naïve-like cells in <i>Mtb</i> lysate-specific CD4<sup>+</sup> T cells among validation household contact cohort RSTR (n = 17) and LTBI (n = 20). Whiskers represent minima and maxima. Statistical significance was determined by the two-sided Wilcoxon rank-sum test.</p></div></div><div class="c-article-supplementary__item js-c-reading-companion-figures-item" data-test="supp-item" id="Fig11"><h3 class="c-article-supplementary__title u-h3"><a class="print-link" data-track="click" data-track-action="view supplementary info" data-test="supp-info-link" data-track-label="extended data fig. 5 rstr tscm cells proliferate s" href="/articles/s41590-024-01897-8/figures/11" data-supp-info-image="//media.springernature.com/lw685/springer-static/esm/art%3A10.1038%2Fs41590-024-01897-8/MediaObjects/41590_2024_1897_Fig11_ESM.jpg">Extended Data Fig. 5 RSTR T<sub>SCM</sub> cells proliferate similarly to LTBI T<sub>SCM</sub> cells in response to <i>Mtb</i> antigen.</a></h3><div class="c-article-supplementary__description" data-component="thumbnail-container"><p><b>(a)</b> Schematic of T<sub>SCM</sub> study where RSTR (n = 12) and LTBI (n = 12) PBMC from the household contact cohort were thawed, rested for 2 hours, stained with 5 µM CFSE, and stimulated with ESAT6/CFP10 or <i>Mtb</i> lysate overnight. <b>(b)</b> Gating strategy of activated naive-like CD69<sup>+</sup>CD154<sup>+</sup>CCR7<sup>+</sup>CD45RA<sup>+</sup>CD45RO<sup>−</sup>lymphocytes. <b>(c)</b> Representative flow cytometry showing sorted T<sub>SCM</sub> cells from RSTR and LTBI expressing the proliferation marker CFSE after 7-day culture. Representive CD45RA and CCR7 staining of the CFSE<sup>low</sup> population in response to ESAT6/CFP10 and <i>Mtb</i> lysate 7-day post-stimulation <b>(d)</b> Box plots showing the median and interquartile range of frequencies of T<sub>SCM</sub> cells (CD95<sup>+</sup>CCR7<sup>+</sup>CD45RA<sup>+</sup>CD45RO<sup>−</sup>) at the time of sorting from PBMC stimulated with <i>Mtb</i> lysate or ESAT6/CFP10. Whiskers represent minima and maxima. <b>(e)</b> Frequencies of CFSE<sup>low</sup>CD95<sup>+</sup> CD4<sup>+</sup> T<sub>SCM</sub> cells after 7-day culture. <b>(f-g)</b> Frequencies of proliferated cells in response to <b>(f)</b> <i>Mtb</i> lysate and <b>(g)</b> ESAT6/CFP10 stimulation. CM, central memory; EM, effector memory. Significance in <b>d-g</b> was calculated using the two-sided Wilcoxon rank-sum tests.</p></div></div><div class="c-article-supplementary__item js-c-reading-companion-figures-item" data-test="supp-item" id="Fig12"><h3 class="c-article-supplementary__title u-h3"><a class="print-link" data-track="click" data-track-action="view supplementary info" data-test="supp-info-link" data-track-label="extended data fig. 6 gating strategy of treg and i" href="/articles/s41590-024-01897-8/figures/12" data-supp-info-image="//media.springernature.com/lw685/springer-static/esm/art%3A10.1038%2Fs41590-024-01897-8/MediaObjects/41590_2024_1897_Fig12_ESM.jpg">Extended Data Fig. 6 Gating strategy of T<sub>reg</sub> and its functional profiles.</a></h3><div class="c-article-supplementary__description" data-component="thumbnail-container"><p><b>(a)</b> Flow cytometry gating strategy for cells expressing T<sub>reg</sub> cell- and activation- associated markers, transcriptional factors and intracellular cytokines among the validation household contact cohort in response to stimulation with ESAT6/CFP10. A time gate was applied to exclude events affected by sample acquisition aberrations, followed by T cell identification by lymphocyte size, CD3, CD14, and CD19 markers. A singlet gate was then applied, followed by the identification of viable cells and a second lymphocyte gate. The same gating strategy was applied to samples stimulated with whole <i>Mtb</i> lysate (not shown). <b>(b)</b> ELISA showing the median and interquartile range of background-corrected absorbance level of TGF-β in conditioned supernatants from PBMCs in response to ESAT6/CFP10 stimulation among RSTR (n = 18) and LTBI (n = 20) in the validation household contact cohort. Whiskers represent minima and maxima. <b>(c)</b> Ratio of anti-inflammatory FoxP3<sup>+</sup>CD25<sup>+</sup> T<sub>reg</sub> cell frequency to pro-inflammatory CD4 T cell frequency, including RORγt<sup>-</sup>T-bet<sup>+</sup> T<sub>H</sub>1, RORγt<sup>+</sup>T-bet<sup>−</sup>T<sub>H</sub>17, and RORγt<sup>+</sup>T-bet<sup>+</sup> T<sub>H</sub>1* cells, among validation donors in response to ESAT6/CFP10 (left) or <i>Mtb</i> lysate (right) from flow cytometry data. Significance in <b>b</b>,<b>c</b> was determined by the two-sided Wilcoxon rank-sum tests.</p></div></div><div class="c-article-supplementary__item js-c-reading-companion-figures-item" data-test="supp-item" id="Fig13"><h3 class="c-article-supplementary__title u-h3"><a class="print-link" data-track="click" data-track-action="view supplementary info" data-test="supp-info-link" data-track-label="extended data fig. 7 cytokine secretion from ltbi " href="/articles/s41590-024-01897-8/figures/13" data-supp-info-image="//media.springernature.com/lw685/springer-static/esm/art%3A10.1038%2Fs41590-024-01897-8/MediaObjects/41590_2024_1897_Fig13_ESM.jpg">Extended Data Fig. 7 Cytokine secretion from LTBI and RSTR PBMC following ESAT6/CFP10 stimulation.</a></h3><div class="c-article-supplementary__description" data-component="thumbnail-container"><p><b>(a)</b> Heatmap showing paired t-statistic of cytokine expression levels between ESAT6/CFP10 and DMSO stimulations from supernatants among RSTR (n = 18) and LTBI (n = 20) donors at 6, 12, 24, and 48 hours after stimulation. <b>(b)</b> Box plots showing the median and interquartile range of cytokine mean fluorescence intensities at the timepoint that exhibited the highest signal identified as in <b>a</b>. Whiskers represent minima and maxima. Significance was calculated by two-sided student’s t-test. n.s. (not significant), p-value > 0.05; *, p-value < 0.05; **, p-value < 0.01; ***, p-value < 0.001.</p></div></div><div class="c-article-supplementary__item js-c-reading-companion-figures-item" data-test="supp-item" id="Fig14"><h3 class="c-article-supplementary__title u-h3"><a class="print-link" data-track="click" data-track-action="view supplementary info" data-test="supp-info-link" data-track-label="extended data fig. 8 cytokine secretion from ltbi " href="/articles/s41590-024-01897-8/figures/14" data-supp-info-image="//media.springernature.com/lw685/springer-static/esm/art%3A10.1038%2Fs41590-024-01897-8/MediaObjects/41590_2024_1897_Fig14_ESM.jpg">Extended Data Fig. 8 Cytokine secretion from LTBI and RSTR PBMC following <i>Mtb</i> lysate stimulation.</a></h3><div class="c-article-supplementary__description" data-component="thumbnail-container"><p><b>(a)</b> Heatmap showing paired t-statistic of cytokine expression levels between <i>Mtb</i> lysate and DMSO stimulations from supernatants among RSTR (n = 18) and LTBI (n = 20) donors at 6, 12, 24, and 48 hours after stimulation. <b>(b)</b> Box plots showing the median and interquartile range of cytokine mean fluorescence intensities at the timepoint that exhibited the highest signal identified as in <b>a</b>. Whiskers represent minima and maxima. Significance was calculated by two-sided student’s t-test. n.s. (not significant), p-value > 0.05; *, p-value < 0.05; **, p-value < 0.01; ***, p-value < 0.001.</p></div></div><div class="c-article-supplementary__item js-c-reading-companion-figures-item" data-test="supp-item" id="Fig15"><h3 class="c-article-supplementary__title u-h3"><a class="print-link" data-track="click" data-track-action="view supplementary info" data-test="supp-info-link" data-track-label="extended data fig. 9 representative staining of cx" href="/articles/s41590-024-01897-8/figures/15" data-supp-info-image="//media.springernature.com/lw685/springer-static/esm/art%3A10.1038%2Fs41590-024-01897-8/MediaObjects/41590_2024_1897_Fig15_ESM.jpg">Extended Data Fig. 9 Representative staining of CXCR3<sup>+</sup>CCR6<sup>+</sup> TH1 cells and IFN-γ<sup>+</sup> CD4<sup>+</sup> T cell frequencies.</a></h3><div class="c-article-supplementary__description" data-component="thumbnail-container"><p><b>(a)</b> Representative staining for CXCR3<sup>+</sup>CCR6<sup>+</sup> T<sub>H</sub>1 cells in ESAT6/CFP10-specific CD4<sup>+</sup> T cells from a participant in the validation household contact cohort. <b>(b)</b> Median and interquartile range of frequencies of CXCR3<sup>+</sup>CCR6<sup>+</sup> T<sub>H</sub>1 and IFN-γ<sup>+</sup> CD4<sup>+</sup> T cells in ESAT6/CFP10-specific CD4<sup>+</sup> T cells or Mtb lysate-specific CD4<sup>+</sup> T cells among RSTR (n = 17) and LTBI (n = 20). Whiskers represent minima and maxima. Significance was determined by two-sided Wilcoxon rank-sum tests.</p></div></div></div></div></div></section><section data-title="Supplementary information"><div class="c-article-section" id="Sec30-section"><h2 class="c-article-section__title js-section-title js-c-reading-companion-sections-item" id="Sec30">Supplementary information</h2><div class="c-article-section__content" id="Sec30-content"><div data-test="supplementary-info"><div class="c-article-supplementary__item" data-test="supp-item" id="MOESM1"><h3 class="c-article-supplementary__title u-h3"><a class="print-link" data-track="click" data-track-action="view supplementary info" data-test="supp-info-link" data-track-label="reporting summary" href="https://static-content.springer.com/esm/art%3A10.1038%2Fs41590-024-01897-8/MediaObjects/41590_2024_1897_MOESM1_ESM.pdf" data-supp-info-image="">Reporting Summary</a></h3></div><div class="c-article-supplementary__item" data-test="supp-item" id="MOESM2"><h3 class="c-article-supplementary__title u-h3"><a class="print-link" data-track="click" data-track-action="view supplementary info" data-test="supp-info-link" data-track-label="peer review file" href="https://static-content.springer.com/esm/art%3A10.1038%2Fs41590-024-01897-8/MediaObjects/41590_2024_1897_MOESM2_ESM.pdf" data-supp-info-image="">Peer Review File</a></h3></div><div class="c-article-supplementary__item" data-test="supp-item" id="MOESM3"><h3 class="c-article-supplementary__title u-h3"><a class="print-link" data-track="click" data-track-action="view supplementary info" data-test="supp-info-link" data-track-label="supplementary tables" href="https://static-content.springer.com/esm/art%3A10.1038%2Fs41590-024-01897-8/MediaObjects/41590_2024_1897_MOESM3_ESM.xlsx" data-supp-info-image="">Supplementary Tables</a></h3><div class="c-article-supplementary__description" data-component="thumbnail-container"><p>Supplementary Table 1. Summary of clinical and demographic characteristics of low exposure cohort. Data presented here include all participants of the wider study cohort. Samples used in this study are from a subset of the concordant positive (TST<sup>+</sup>IGRA<sup>+</sup>; LTBI) and concordant negative (TST<sup>−</sup>IGRA<sup>−</sup>) subjects, and all subjects included in this study were HIV-negative adults. Categorization was done based on TST and IGRA results, examining quantitative responses. Any subjects that were not clearly TST<sup>+</sup> and/or IGRA<sup>+</sup> based on quantitative QFT were included in the ‘unevaluable’ category. Means are presented as indicated. BCG scar indicates prior vaccination with BCG. Clinical and demographic characteristics are shown for each individual where available. *Eleven subjects had TST readings between 5 and 10 mm, two had indeterminate QFT results and two had missing TST readings. **QFT results >10 were capped at 10. HIV, human immunodeficiency virus; TST, tuberculin skin test; IGRA, IFN-γ release assay; QFT, QuantiFERON-TB Gold test; BMI, body mass index. Supplementary Table 2. Clinical and demographic characteristics of low-exposure cohort. Raw data used to generate the values shown in Supplementary Table 1 are presented here. Data presented here represent the subjects included in the ICS assay of the low exposure cohort, which are a subset of the concordant positive (TST<sup>+</sup>IGRA<sup>+</sup>; LTBI) and concordant negative (TST<sup>−</sup>IGRA<sup>−</sup>) subjects presented in Supplementary Table 1. All subjects included in this study were HIV-negative adults. Clinical and demographic characteristics are shown for each individual where available. BMI, body mass index. Supplementary Table 3. Multiparameter flow cytometry panels. The results reported in Figs. 1–5 and Extended Data Fig. 5 utilized four different multiparameter flow cytometry panels to analyze T cells following in vitro simulation. Details regarding the antibodies used for these experiments are provided here. The ICS results in Fig. 1 utilized the ‘LEC’ (low-exposure cohort) panel, the index sort results in Fig. 2 utilized the ‘Index sort’ panel, the flow cytometry results in Figs. 3 and 5 utilized the ‘T<sub>h</sub>’ panel, the flow cytometry results in Fig. 4 utilized the ‘T<sub>reg</sub>’ panel and the flow cytometry results in Extended Data Fig. 5 utilized the ‘T<sub>scm</sub>’ panel. Supplementary Table 4. Summary of clinical and demographic characteristics of household contact cohort. Subjects presented here are demographically representative of the wider study cohort and consist of individuals included in the discovery and validation phases of this study. Means are presented as indicated. The risk score is determined as previously described<sup>54</sup>. HIV, human immunodeficiency virus. Supplementary Table 5. Clinical and demographic characteristics of household contact cohort. Raw data used to generate the values shown in Supplementary Table 4 are presented here. Data presented here represent the subjects from the household contact cohort included for SELECT-seq, flow cytometry, multiplex cytokine analysis and ELISA. Clinical and demographic characteristics are shown for each individual where available. FULLIDNO, subject identification number; RS_SUB_ACCESSION_NO, sample accession number; M0_KCVAGE, age at study baseline visit for initial 24 months follow-up; KCHCA_AGE_YR_CURRENT, age at substudy retrace visit; ADULT_RISK_TBINF, adult risk score; CURRENT_HIVSTAT, current HIV status. Supplementary Table 6. TCR sequencing of RSTR ESAT6/CFP10-specific T cells. The TCR sequencing data from three RSTR using the SELECT-seq approach was analyzed to calculate the clonally expanded T cells. Supplementary Table 7. TCR sequencing of LTBI ESAT6/CFP10-specific T cells. The TCR sequencing data from four LTBI using the SELECT-seq approach was analyzed to calculate the clonally expanded T cells. Supplementary Table 8. DEGs between RSTR and LTBI. The DEGs between RSTR and LTBI were identified from the whole transcriptomic data in the SELECT-seq. The adjusted <i>P</i> values were calculated using the Wilcoxon rank-sum test. The average log<sub>2</sub> FC was calculated as the difference in mean log-normalized expression levels between RSTR and LTBI cells. A positive log<sub>2</sub>(FC) indicates higher mean expression levels in the RSTR group compared to the LTBI group. Supplementary Table 9. Pathway analyses of RSTR DEGs. GO Biological Process (BP) analysis was performed to analyze the DEGs. The false discovery rate (FDR) was calculated to quantify the significance of each GO BP term in the RSTR group. Supplementary Table 10. Pathway analyses of LTBI DEGs. GO BP analysis was performed to analyze the DEGs. The FDR was calculated to quantify the significance of each GO BP term in the LTBI group. Supplementary Table 11. Gene set enrichment analysis of DEGs between RSTR and LTBI. The DEGs found in RSTR and LTBI groups were analyzed using gene set enrichment analysis (GSEA). Supplementary Table 12. Network analysis of upregulated DEGs in RSTR using STRINGdb: cluster 1. The upregulated DEGs related to the immune system process in RSTR were analyzed using the STRINGdb network clustering algorithm. The analysis yielded three distinct clusters, where each gene was a node in a network cluster. The network properties of each gene node in cluster 1 were calculated and presented. Supplementary Table 13. Network analysis of upregulated DEGs in RSTR using STRINGdb: cluster 2. The upregulated DEGs related to the immune system process in RSTR were analyzed using the STRINGdb network clustering algorithm. The analysis yielded three distinct clusters, where each gene was a node in a network cluster. The network properties of each gene node in cluster 2 were calculated and presented. Supplementary Table 14. Network analysis of upregulated DEGs in RSTR using STRINGdb: cluster 3. The upregulated DEGs related to the immune system process in RSTR were analyzed using the STRINGdb network clustering algorithm. The analysis yielded three distinct clusters, where each gene was a node in a network cluster. The network properties of each gene node in cluster 3 were calculated and presented. Supplementary Table 15. Gene regulatory network analysis of RSTR in the household contact cohort. The whole transcriptomic data of the SELECT-seq was used to conduct the gene regulatory network analysis. The enrichment score of each transcription factor was calculated separately for the RSTR group. Supplementary Table 16. Gene regulatory network analysis of LTBI in the household contact cohort. The whole transcriptomic data of the SELECT-seq was used to conduct the gene regulatory network analysis. The enrichment score of each transcription factor was calculated separately for the LTBI group.</p></div></div></div></div></div></section><section data-title="Rights and permissions"><div class="c-article-section" id="rightslink-section"><h2 class="c-article-section__title js-section-title js-c-reading-companion-sections-item" id="rightslink">Rights and permissions</h2><div class="c-article-section__content" id="rightslink-content"> <p><b>Open Access</b> This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. 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id="citeas">Cite this article</h3><p class="c-bibliographic-information__citation">Sun, M., Phan, J.M., Kieswetter, N.S. <i>et al.</i> Specific CD4<sup>+</sup> T cell phenotypes associate with bacterial control in people who ‘resist’ infection with <i>Mycobacterium tuberculosis</i>. <i>Nat Immunol</i> <b>25</b>, 1411–1421 (2024). https://doi.org/10.1038/s41590-024-01897-8</p><p class="c-bibliographic-information__download-citation u-hide-print"><a data-test="citation-link" data-track="click" data-track-action="download article citation" data-track-label="link" data-track-external="" rel="nofollow" href="https://citation-needed.springer.com/v2/references/10.1038/s41590-024-01897-8?format=refman&flavour=citation">Download citation<svg width="16" height="16" focusable="false" role="img" aria-hidden="true" class="u-icon"><use xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="#icon-eds-i-download-medium"></use></svg></a></p><ul class="c-bibliographic-information__list" 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