{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T23:36:34Z","timestamp":1791329794642,"version":"4.3.1"},"reference-count":48,"publisher":"American Society for Microbiology","issue":"4","license":[{"start":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T00:00:00Z","timestamp":1775520000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T00:00:00Z","timestamp":1775520000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.asm.org\/non-commercial-tdm-license"}],"funder":[{"name":"CAMS Innovation Fund for Medical Sciences","award":["2023-I2M-2-001, 2021-I2M-1-037"],"award-info":[{"award-number":["2023-I2M-2-001, 2021-I2M-1-037"]}]}],"content-domain":{"domain":["journals.asm.org"],"crossmark-restriction":true},"short-container-title":["Microbiol Spectr"],"published-print":{"date-parts":[[2026,4,7]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title\/>\n                    <jats:p>\n                      Tuberculosis remains a leading cause of mortality worldwide. Rapid and accurate diagnosis of active tuberculosis (ATB) is critical for its effective treatment and disease control. However, current sputum-based detection methods have limited diagnostic coverage for ATB, resulting in missed cases and treatment delay. In this study, we performed neutrophil RNA sequencing (RNA-seq) to identify ATB-specific transcriptional signatures. Through integrated analysis of differentially expressed genes (DEGs) across 173 samples (67 ATB, 42 latent tuberculosis infection [LTBI], and 64 healthy controls [HC]), followed by quantitative Real-time polymerase chain reaction (qPCR) validation using 141 samples (31 ATB, 53 LTBI, 57 HC). A novel 4-gene neutrophil-derived tuberculosis signature (neu-TB) was screened by Lasso model prediction, and further evaluation were performed in two independent cohorts (\n                      <jats:italic toggle=\"yes\">n<\/jats:italic>\n                      = 332). The signature achieved exceptional discrimination between ATB and LTBI (area under curve [AUC] = 0.975; 95% confidence interval [CI]: 0.949\u20131.000;\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      &lt; 0.0001), with 96.8% sensitivity and 92.5% specificity. When distinguishing ATB from HC, the performance remained superior (AUC = 0.980, 91.9% sensitivity, 96.5% specificity). Notably, the signature effectively differentiated ATB from other pulmonary diseases (AUC = 0.969, 95% CI: 0.943\u20130.995, 93.0% sensitivity, 87.9% specificity). This study represents the first application of immune cell subset-specific transcriptomic profiling to overcome the technical limitations, which are frequently confounded by heterogeneous cellular backgrounds in whole blood or peripheral blood mononuclear cell (PBMC) analyses. The development of this 4-gene neu-TB signature not only establishes a novel methodology for identifying transcriptomic biomarkers but also demonstrates promising clinical applicability for ATB diagnostics.\n                    <\/jats:p>\n                    <jats:sec>\n                      <jats:title>IMPORTANCE<\/jats:title>\n                      <jats:p>\n                        The most urgent need in pulmonary TB diagnosis is developing a rapid, non-sputum, biomarker-based diagnostic test. Here, we first identified a novel transcriptomic signature and addressed these challenges through two key innovations: (i) cell-type-specific resolution: by focusing on neutrophils\u2014the most abundant immune cell in TB blood signatures and key mediators of host-pathogen interactions\u2014we reduce biological noise and enhance biomarker precision. (ii) Rigorous multi-cohort validation: the 4-gene neutrophil-derived TB signature (neu-TB) was selected via RNA-seq of purified neutrophils (\n                        <jats:italic toggle=\"yes\">n<\/jats:italic>\n                        = 141) and validated by qPCR in two independent cohorts (total\n                        <jats:italic toggle=\"yes\">n<\/jats:italic>\n                        = 332), achieving 93% sensitivity\/88% specificity in distinguishing active TB from latent infection and non-TB controls.\n                      <\/jats:p>\n                    <\/jats:sec>\n                  <\/jats:sec>","DOI":"10.1128\/spectrum.01915-25","type":"journal-article","created":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T13:01:00Z","timestamp":1773320460000},"update-policy":"https:\/\/doi.org\/10.1128\/asmj-crossmark-policy-page","source":"Crossref","is-referenced-by-count":2,"title":["Neutrophil-specific transcriptomic profiling reveals a novel signature for active tuberculosis diagnosis"],"prefix":"10.1128","volume":"14","author":[{"given":"Jie","family":"Hu","sequence":"first","affiliation":[{"name":"NHC Key Laboratory of Systems Biology of Pathogens, National Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College","place":["Beijing, People's Republic of China"]},{"name":"Center for Tuberculosis Research, Chinese Academy of Medical Sciences & Peking Union Medical College","place":["Beijing, People's Republic of China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Song","family":"Liu","sequence":"additional","affiliation":[{"name":"NHC Key Laboratory of Systems Biology of Pathogens, National Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College","place":["Beijing, People's Republic of China"]},{"name":"Center for Tuberculosis Research, Chinese Academy of Medical Sciences & Peking Union Medical College","place":["Beijing, People's Republic of 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