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Yener, B.

Publications and source records attributed to Yener, B..

2 recordsLinked to original sources

Systems genetics uncover new loci containing functional gene candidates in Mycobacterium tuberculosis-infected Diversity Outbred mice.

Mycobacterium tuberculosis, the bacillus that causes tuberculosis (TB), infects 2 billion people across the globe, and results in 8-9 million new TB cases and 1-1.5 million deaths each year. Most patients have no known genetic basis that predisposes them to disease. We investigated the complex genetic basis of pulmonary TB by modelling human genetic diversity with the Diversity Outbred mouse population. When infected with M. tuberculosis, one-third develop early onset, rapidly progressive, necrotizing granulomas and succumb within 60 days. The remaining develop non-necrotizing granulomas and survive longer than 60 days. Genetic mapping using clinical indicators of disease, granuloma histopathological features, and immune response traits identified five new loci on mouse chromosomes 1, 2, 4, 16 and three previously identified loci on chromosomes 3 and 17. Quantitative trait loci (QTLs) on chromosomes 1, 16, and 17, associated with multiple correlated traits and had similar patterns of allele effects, suggesting these QTLs contain important genetic regulators of responses to M. tuberculosis. To narrow the list of candidate genes in QTLs, we used a machine learning strategy that integrated gene expression signatures from lungs of M. tuberculosis-infected Diversity Outbred mice with gene interaction networks, generating functional scores. The scores were then used to rank candidates for each mapped trait in each locus, resulting in 11 candidates: Ncf2, Fam20b, S100a8, S100a9, Itgb5, Fstl1, Zbtb20, Ddr1, Ier3, Vegfa, and Zfp318. Importantly, all 11 candidates have roles in infection, inflammation, cell migration, extracellular matrix remodeling, or intracellular signaling. Further, all candidates contain single nucleotide polymorphisms (SNPs), and some but not all SNPs were predicted to have deleterious consequences on protein functions. Multiple methods were used for validation including (i) a statistical method that showed Diversity Outbred mice carrying PWH/PhJ alleles on chromosome 17 QTL have shorter survival; (ii) quantification of S100A8 protein levels, confirming predicted allele effects; and (iii) infection of C57BL/6 mice deficient for the S100a8 gene. Overall, this work demonstrates that systems genetics using Diversity Outbred mice can identify new (and known) QTLs and new functionally relevant gene candidates that may be major regulators of granuloma necrosis and acute inflammation in pulmonary TB.

genetics↗

Perivascular and peribronchiolar granuloma-associated lymphoid tissue and B-cell gene expression pathways identify asymptomatic Mycobacterium tuberculosis lung infection in Diversity Outbred mice{-}{-}{-}

Humans are highly genetically diverse, and most are resistant to Mycobacterium tuberculosis. However, lung tissue from genetically resistant humans is not readily available to identify potential mechanisms of resistance. To address this, we model M. tuberculosis infection in Diversity Outbred mice. Like humans, Diversity Outbred mice also exhibit genetically determined susceptibility to M. tuberculosis infection: Progressors who succumb within 60 days of a low dose aerosol infection due to acute necrotizing granulomas, and Controllers who maintain asymptomatic infection for at least 60 days, and then develop chronic pulmonary TB with occasional necrosis and cavitation, over months to greater than 1 year. Here, we identified specific regions of granuloma-associated lymphoid tissue (GrALT) and B-cell gene expression pathways as key features of asymptomatic lung infection using cytokine, antibody, granuloma image, and gene expression datasets. Cytokines and anti-M. tuberculosis cell wall antibodies discriminated acute vs chronic pulmonary TB but not asymptomatic lung infection. To find unique features of asymptomatic lung infection, we trained a weakly supervised, deep-learning neural network on lung histology images. The neural network accurately produced an interpretable imaging biomarker: perivascular and bronchiolar lymphocytic cuffs, a type of GrALT. We expected CD4 T cell genes would be highly expressed in asymptomatic lung infection. However, the significantly different, highly expressed genes in lungs of asymptomatically infected Diversity Outbred mice corresponded to B-cell activation, proliferation, and antigen-receptor signaling, including Fcrl1, Cd79, Pax5, Cr2, and Ms4a1. Overall, our results suggest that genetically controlled B-cell responses are important for establishing asymptomatic M. tuberculosis lung infection.

pathology↗