Perivascular and peribronchiolar granuloma-associated lymphoid tissue and B-cell gene expression pathways identify asymptomatic Mycobacterium tuberculosis lung infection in Diversity Outbred mice
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ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE266564 | GEO | 2024/06/15
REPOSITORIES: GEO
Similar Datasets
Project description: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.
2024-06-15 | GSE266563 | GEO
Project description: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.
2024-06-15 | GSE266562 | GEO
Project description:Perivascular and peribronchiolar granuloma-associated lymphoid tissue and B-cell gene expression pathways identify asymptomatic Mycobacterium tuberculosis lung infection in Diversity Outbred mice
| PRJNA1107591 | ENA
Project description:Perivascular and peribronchiolar granuloma-associated lymphoid tissue and B-cell gene expression pathways identify asymptomatic Mycobacterium tuberculosis lung infection in Diversity Outbred mice (dataset 1)
| PRJNA1107589 | ENA
Project description:Perivascular and peribronchiolar granuloma-associated lymphoid tissue and B-cell gene expression pathways identify asymptomatic Mycobacterium tuberculosis lung infection in Diversity Outbred mice (dataset 2)
| PRJNA1107592 | ENA
Project description:BackgroundMachine learning sustains successful application to many diagnostic and prognostic problems in computational histopathology. Yet, few efforts have been made to model gene expression from histopathology. This study proposes a methodology which predicts selected gene expression values (microarray) from haematoxylin and eosin whole-slide images as an intermediate data modality to identify fulminant-like pulmonary tuberculosis ('supersusceptible') in an experimentally infected cohort of Diversity Outbred mice (n=77).MethodsGradient-boosted trees were utilized as a novel feature selector to identify gene transcripts predictive of fulminant-like pulmonary tuberculosis. A novel attention-based multiple instance learning model for regression was used to predict selected genes' expression from whole-slide images. Gene expression predictions were shown to be sufficiently replicated to identify supersusceptible mice using gradient-boosted trees trained on ground truth gene expression data.FindingsThe model was accurate, showing high positive correlations with ground truth gene expression on both cross-validation (n = 77, 0.63 ≤ ρ ≤ 0.84) and external testing sets (n = 33, 0.65 ≤ ρ ≤ 0.84). The sensitivity and specificity for gene expression predictions to identify supersusceptible mice (n=77) were 0.88 and 0.95, respectively, and for an external set of mice (n=33) 0.88 and 0.93, respectively.ImplicationsOur methodology maps histopathology to gene expression with sufficient accuracy to predict a clinical outcome. The proposed methodology exemplifies a computational template for gene expression panels, in which relatively inexpensive and widely available tissue histopathology may be mapped to specific genes' expression to serve as a diagnostic or prognostic tool.FundingNational Institutes of Health and American Lung Association.
| S-EPMC8138606 | biostudies-literature
Project description:Mycobacterium tuberculosis, the causative agent of tuberculosis (TB), induces formation of granulomas, structures in which immune cells and bacteria colocalize. Macrophages are among the most abundant cell types in granulomas and have been shown to serve as both critical bactericidal cells and targets for M. tuberculosis infection and proliferation throughout the course of infection. Very little is known about how these processes are regulated, what controls macrophage microenvironment-specific polarization and plasticity, or why some granulomas control bacteria and others permit bacterial dissemination. We take a computational-biology approach to investigate mechanisms that drive macrophage polarization, function, and bacterial control in granulomas. We define a "macrophage polarization ratio" as a metric to understand how cytokine signaling translates into polarization of single macrophages in a granuloma, which in turn modulates cellular functions, including antimicrobial activity and cytokine production. Ultimately, we extend this macrophage ratio to the tissue scale and define a "granuloma polarization ratio" describing mean polarization measures for entire granulomas. Here we coupled experimental data from nonhuman primate TB granulomas to our computational model, and we predict two novel and testable hypotheses regarding macrophage profiles in TB outcomes. First, the temporal dynamics of granuloma polarization ratios are predictive of granuloma outcome. Second, stable necrotic granulomas with low CFU counts and limited inflammation are characterized by short NF-κB signal activation intervals. These results suggest that the dynamics of NF-κB signaling is a viable therapeutic target to promote M1 polarization early during infection and to improve outcome.
| S-EPMC4288886 | biostudies-literature
Project description:Mycobacterium tuberculosis infects two billion people across the globe, and results in 8-9 million new tuberculosis (TB) cases and 1-1.5 million deaths each year. Most patients have no known genetic basis that predisposes them to disease. Here, we investigate 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 immune and inflammatory mediators; and clinical, microbiological, and granuloma correlates of disease identified five new loci on mouse chromosomes 1, 2, 4, 16; and three known loci on chromosomes 3 and 17. Further, multiple positively correlated traits shared loci on chromosomes 1, 16, and 17 and had similar patterns of allele effects, suggesting these loci contain critical genetic regulators of inflammatory responses to M. tuberculosis. To narrow the list of candidate genes, we used a machine learning strategy that integrated gene expression signatures from lungs of M. tuberculosis-infected Diversity Outbred mice with gene interaction networks to generate scores representing functional relationships. The scores were used to rank candidates for each mapped trait, resulting in 11 candidate genes: Ncf2, Fam20b, S100a8, S100a9, Itgb5, Fstl1, Zbtb20, Ddr1, Ier3, Vegfa, and Zfp318. Although all candidates have roles in infection, inflammation, cell migration, extracellular matrix remodeling, or intracellular signaling, and all contain single nucleotide polymorphisms (SNPs), SNPs in only four genes (S100a8, Itgb5, Fstl1, Zfp318) are predicted to have deleterious effects on protein functions. We performed methodological and candidate validations to (i) assess biological relevance of predicted allele effects by showing that Diversity Outbred mice carrying PWH/PhJ alleles at the H-2 locus on chromosome 17 QTL have shorter survival; (ii) confirm accuracy of predicted allele effects by quantifying S100A8 protein in inbred founder strains; and (iii) infection of C57BL/6 mice deficient for the S100a8 gene. Overall, this body of work demonstrates that systems genetics using Diversity Outbred mice can identify new (and known) QTLs and functionally relevant gene candidates that may be major regulators of complex host-pathogens interactions contributing to granuloma necrosis and acute inflammation in pulmonary TB.
2024-06-15 | GSE267006 | GEO
Project description:The BCG vaccine is ineffective against adult tuberculosis. Hence, new antituberculosis vaccines are needed. Correlates of protection against tuberculosis are not known. We studied the effects of BCG vaccination on gene expression in tuberculosis granulomas using macaques.Macaques were BCG-vaccinated or sham-vaccinated and then challenged with virulent Mycobacterium tuberculosis. Lung lesions were used for comparative transcriptomics.Vaccinated macaques were protected with lower bacterial burden and immunopathology. Lesions from BCG-vaccinated nonhuman primates (NHPs) showed a better balance of ?- and ?-chemokine gene expression with higher levels of ?-chemokine expression relative to nonvaccinated animals. Consistent with this, sham-vaccinated macaques recruited fewer macrophages relative to neutrophils in their lungs. The expression of indoleamine 2,3-dioxygenase (IDO), a known immunosuppressor, was significantly higher in both week 5 and 10 lesions from sham-vaccinated, relative to BCG-vaccinated, NHPs. IDO expression was primarily limited to the nonlymphocytic region of the lesions, within the inner ring structure surrounding the central necrosis.Our study defines lung gene expression correlates of protective response against tuberculosis, relative to disease, which can potentially be employed to assess the efficacy of candidate antituberculosis vaccines. Mycobacterium tuberculosis may modulate protective immune responses using diverse mechanisms, including increased recruitment of inflammatory neutrophils and the concomitant use of IDO to modulate inflammation.
| S-EPMC3633457 | biostudies-literature
Project description:Protective immunity and latent Mycobacterium tuberculosis infection in humans are associated with the formation of mature protective granulomas within the lung. Unfortunately, understanding the importance of such structures has been hindered by the lack of small-animal models that can develop mature granulomas. In this article, we describe for the first time, to our knowledge, the formation of mature, fibrotic M. tuberculosis-containing pulmonary granulomas in a mouse model of IL-10 deficiency (CBA/J IL-10(-/-)). Long-term control of M. tuberculosis infection in the absence of IL-10 was also associated with an early and enhanced capacity for Ag presentation and a significant increase in the generation of multifunctional T cells. Although IL-10 deficiency is known to enhance Th1 immune responses in general, we demonstrate in this study using transient anti-IL-10R treatment that it is the presence of IL-10 in vivo during the first month of M. tuberculosis infection that plays a definitive role in the inhibition of optimum protective immunity that can establish the environment for mature granuloma formation. Although the importance of IL-10 during M. tuberculosis infection has been debated, our data demonstrate that in CBA/J mice, IL-10 plays a significant early inhibitory role in preventing the development of protective immunity associated with containment of M. tuberculosis infection.
| S-EPMC3594073 | biostudies-literature