Deniz Koyuncu, Thomas Tavolara, Daniel M Gatti, Adam C Gower, Melanie L Ginese, Igor Kramnik, Bülent Yener, Usama Sajjad, Muhammad Khalid Khan Niazi, Metin Gurcan, Anas Alsharaydeh, Gillian Beamer
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Here, we identified features of asymptomatic <i>M. tuberculosis</i> infection by applying computational and statistical approaches to multimodal data sets. Cytokines and anti-<i>M</i>. <i>tuberculosis</i> cell wall antibodies discriminated progressors vs controllers with chronic pulmonary TB but could not classify mice with asymptomatic infection. However, a novel deep-learning neural network trained on lung granuloma images was able to accurately classify asymptomatically infected lungs vs acute pulmonary TB in progressors vs chronic pulmonary TB in controllers, and discrimination was based on perivascular and peribronchiolar lymphocytes. Because the discriminatory lesion was rich in lymphocytes and CD4 T cell-mediated immunity is required for resistance, we expected CD4 T-cell genes would be elevated in asymptomatic infection. However, the significantly different, highly expressed genes were from B-cell pathways (e.g., <i>Bank1</i>, <i>Cd19</i>, <i>Cd79</i>, <i>Fcmr</i>, <i>Ms4a1</i>, <i>Pax5</i>, and <i>H2-Ob</i>), and CD20+ B cells were enriched in the perivascular and peribronchiolar regions of mice with asymptomatic <i>M. tuberculosis</i> infection. Together, these results indicate that genetically controlled B-cell responses are important for establishing asymptomatic <i>M. tuberculosis</i> lung infection.</p>","PeriodicalId":13541,"journal":{"name":"Infection and Immunity","volume":" ","pages":"e0026323"},"PeriodicalIF":2.9000,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11238564/pdf/","citationCount":"0","resultStr":"{\"title\":\"B cells in perivascular and peribronchiolar granuloma-associated lymphoid tissue and B-cell signatures identify asymptomatic <i>Mycobacterium tuberculosis</i> lung infection in Diversity Outbred mice.\",\"authors\":\"Deniz Koyuncu, Thomas Tavolara, Daniel M Gatti, Adam C Gower, Melanie L Ginese, Igor Kramnik, Bülent Yener, Usama Sajjad, Muhammad Khalid Khan Niazi, Metin Gurcan, Anas Alsharaydeh, Gillian Beamer\",\"doi\":\"10.1128/iai.00263-23\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Because most humans resist <i>Mycobacterium tuberculosis</i> infection, there is a paucity of lung samples to study. 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However, a novel deep-learning neural network trained on lung granuloma images was able to accurately classify asymptomatically infected lungs vs acute pulmonary TB in progressors vs chronic pulmonary TB in controllers, and discrimination was based on perivascular and peribronchiolar lymphocytes. Because the discriminatory lesion was rich in lymphocytes and CD4 T cell-mediated immunity is required for resistance, we expected CD4 T-cell genes would be elevated in asymptomatic infection. However, the significantly different, highly expressed genes were from B-cell pathways (e.g., <i>Bank1</i>, <i>Cd19</i>, <i>Cd79</i>, <i>Fcmr</i>, <i>Ms4a1</i>, <i>Pax5</i>, and <i>H2-Ob</i>), and CD20+ B cells were enriched in the perivascular and peribronchiolar regions of mice with asymptomatic <i>M. tuberculosis</i> infection. 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引用次数: 0
摘要
由于大多数人都能抵抗结核分枝杆菌的感染,因此可供研究的肺部样本很少。为了填补这一空白,我们用结核分枝杆菌感染了多样性杂交小鼠,并对不同疾病状态下的小鼠肺部进行了研究。在低剂量气溶胶感染后,进展期小鼠会在 60 天内死于急性炎症性肺病,而控制期小鼠则会在至少 60 天内保持无症状感染,然后发展为慢性肺结核(TB),持续数月至 1 年以上。在这里,我们通过对多模态数据集应用计算和统计方法,确定了无症状结核杆菌感染的特征。细胞因子和抗结核细胞壁抗体能区分慢性肺结核进展者和控制者,但不能对无症状感染的小鼠进行分类。然而,根据肺肉芽肿图像训练的新型深度学习神经网络却能准确地将无症状感染肺与急性肺结核进展者与慢性肺结核控制者进行分类,并且根据血管周围和支气管周围淋巴细胞进行区分。由于辨别病灶的淋巴细胞丰富,而抵抗力需要 CD4 T 细胞介导的免疫力,我们预计 CD4 T 细胞基因在无症状感染中会升高。然而,明显不同的高表达基因来自 B 细胞通路(如 Bank1、Cd19、Cd79、Fcmr、Ms4a1、Pax5 和 H2-Ob),CD20+ B 细胞富集在无症状结核杆菌感染小鼠的血管周围和支气管周围区域。这些结果表明,基因控制的 B 细胞反应对建立无症状结核杆菌肺部感染非常重要。
B cells in perivascular and peribronchiolar granuloma-associated lymphoid tissue and B-cell signatures identify asymptomatic Mycobacterium tuberculosis lung infection in Diversity Outbred mice.
Because most humans resist Mycobacterium tuberculosis infection, there is a paucity of lung samples to study. To address this gap, we infected Diversity Outbred mice with M. tuberculosis and studied the lungs of mice in different disease states. After a low-dose aerosol infection, progressors succumbed to acute, inflammatory lung disease within 60 days, while controllers maintained asymptomatic infection for at least 60 days, and then developed chronic pulmonary tuberculosis (TB) lasting months to more than 1 year. Here, we identified features of asymptomatic M. tuberculosis infection by applying computational and statistical approaches to multimodal data sets. Cytokines and anti-M. tuberculosis cell wall antibodies discriminated progressors vs controllers with chronic pulmonary TB but could not classify mice with asymptomatic infection. However, a novel deep-learning neural network trained on lung granuloma images was able to accurately classify asymptomatically infected lungs vs acute pulmonary TB in progressors vs chronic pulmonary TB in controllers, and discrimination was based on perivascular and peribronchiolar lymphocytes. Because the discriminatory lesion was rich in lymphocytes and CD4 T cell-mediated immunity is required for resistance, we expected CD4 T-cell genes would be elevated in asymptomatic infection. However, the significantly different, highly expressed genes were from B-cell pathways (e.g., Bank1, Cd19, Cd79, Fcmr, Ms4a1, Pax5, and H2-Ob), and CD20+ B cells were enriched in the perivascular and peribronchiolar regions of mice with asymptomatic M. tuberculosis infection. Together, these results indicate that genetically controlled B-cell responses are important for establishing asymptomatic M. tuberculosis lung infection.
期刊介绍:
Infection and Immunity (IAI) provides new insights into the interactions between bacterial, fungal and parasitic pathogens and their hosts. Specific areas of interest include mechanisms of molecular pathogenesis, virulence factors, cellular microbiology, experimental models of infection, host resistance or susceptibility, and the generation of innate and adaptive immune responses. IAI also welcomes studies of the microbiome relating to host-pathogen interactions.