Hepatic transcriptome of pulmonary TB infection.
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ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE273691 | GEO | 2024/09/17
REPOSITORIES: GEO
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Project description:: Pulmonary tuberculosis (TB) generates chronic systemic inflammation and metabolic dysregulation. The liver is the master regulator of metabolism and to determine the impact of pulmonary TB on this organ we undertook unbiased mRNA and protein analyses of the liver in mice with TB.
2024-09-19 | PXD055781 | Pride
Project description:Most individuals infected with Mycobacterium tuberculosis can control the infection by forming and maintaining TB granulomas at the local infection foci. However, when the chronic infection (also known as latency) becomes active, the caseous center of TB granuloma enlarges, and it liquefies and cavitates, ultimately releasing bacilli into airway. Deciphering how genes are regulated within TB granulomas will help to understand the granuloma biology. Therefore, we performed genome-wide microarray on caseous human pulmonary TB granulomas and compared with normal lung tissues.
2010-06-02 | GSE20050 | GEO
Project description:Most individuals infected with Mycobacterium tuberculosis can control the infection by forming and maintaining TB granulomas at the local infection foci. However, when the chronic infection (also known as latency) becomes active, the caseous center of TB granuloma enlarges, and it liquefies and cavitates, ultimately releasing bacilli into airway. Deciphering how genes are regulated within TB granulomas will help to understand the granuloma biology. Therefore, we performed genome-wide microarray on caseous human pulmonary TB granulomas and compared with normal lung tissues. Laser capture microdissection (LCM) was used to dissect out caseous granulomas from TB patients' lung tissues, excluding uninvolved areas. Total RNA were isolated from LCM-derived materials and used for microarray. As a control, parenchyma from normal lung tissues was prepared in the same manner as caseous granulomas. Sample GSM501252, Caseum 2-C, is missing a CEL file.
2010-06-08 | E-GEOD-20050 | biostudies-arrayexpress
Project description:Background: Mycobacterium tuberculosis infection is a leading cause of infectious death worldwide. Gene-expression microarray studies profiling the blood transcriptional response of tuberculosis (TB) patients have been undertaken in order to better understand the host immune response as well as to identify potential biomarkers of disease. To date most of these studies have focused on pulmonary TB patients with gene-expression profiles of extra-pulmonary TB patients yet to be compared to those of patients with pulmonary TB or sarcoidosis. Methods A novel cohort of patients with extra-pulmonary TB and sarcoidosis was recruited and the transcriptional response of these patients compared to those with pulmonary TB using a variety of transcriptomic approaches including testing a previously defined 380 gene meta-signature of active TB. Results The 380 meta-signature broadly differentiated active TB from healthy controls in this new dataset consisting of pulmonary and extra-pulmonary TB. The top 15 genes from this meta-signature had a lower sensitivity for differentiating extra-pulmonary TB from healthy controls as compared to pulmonary TB. We found the blood transcriptional responses in pulmonary and extra-pulmonary TB to be heterogeneous and to reflect the extent of symptoms of disease. Conclusions The transcriptional signature in extra-pulmonary TB demonstrated heterogeneity of gene expression reflective of symptom status, while the signature of pulmonary TB was distinct, based on a higher proportion of symptomatic individuals. These findings are of importance for the rational design and implementation of mRNA based TB diagnostics.
2016-11-04 | GSE83456 | GEO
Project description:Identification of blood transcriptional biomarkers linked to different phases of tuberculosis. The discovery of a transcriptional signature that distinguishes subclinical TB from incipient TB at baseline could lead to tuberculosis interventions that combat the tuberculosis epidemic in the context of household contacts.
2023-01-10 | GSE193777 | GEO
Project description:The aim of this study was to compare the transcriptional response to TB in regions of different incidence / prevalence. Experimental Design: Whole blood collected in tempus tubes from patients with different spectra of TB disease. All patients were sampled prior to the initiation of any antimycobacterial therapy. Active Pulmonary TB: PTB - All patients confirmed by isolation of Mycobacterium Tuberculosis on culture of sputum. Latent TB: LTB - All patients were screened at a tuberculosis clinic. All were positive by Interferon-Gamma Release assay(IGRA); specifically Quantiferon Gold In-Tube Assay (Cellestis, Australia). Latent patients had no clinical, or microbiological evidence of active infection and were asymptomatic. Experimental Variables: Patient group: Active PTB; Latent TB. There are no healthy controls in this dataset as it was being used for validation only. Controls: Latent TB individuals are used as a control for PTB in this dataset since there are few to no unexposed adult controls in Cape Town.
2010-08-11 | E-GEOD-19442 | biostudies-arrayexpress
Project description:116 Whole Genome Sequencing (WGS) samples from the TB-DAR study, which consists of a cohort of adult pulmonary tuberculosis patients recruited in Dar es Salaam, Tanzania.
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Project description:Tuberculosis (TB) is a chronic granulomatous disease caused by the pathogen Mycobacterium tuberculosis. The success of M. tuberculosis can be attributed to its ability to evade protective host immune responses and its recalcitrance to antimicrobial chemotherapy. Detailed understanding of protective host immune response to TB is still lacking and there are limited reports that characterize host responses to TB at the site of disease. Furthermore, although cure of the majority of patients treated with the standard 6-month multidrug regimen indicates that treatment is highly effective, approximately 4-10% of clinically cured patients will develop recurrent disease within the first 12 months after completing therapy. We therefore analyzed BALF supernatant proteomes from pulmonary TB patients and patients at the end of standard anti-TB treatment to gain a better understanding of the host response at the site of disease. This would not only aid our understanding of localised host responses during TB disease, but could allow us to identify protein signatures associated with active TB disease or clinical cure.
2021-11-03 | PXD018907 | Pride
Project description:Understanding the immune response to tuberculosis requires greater knowledge of humoral responses. To characterize antibody targets and the effect of disease parameters on target recognition, we developed a systems immunology approach that integrated detection of antibodies against the entire Mycobacterium tuberculosis proteome, bacterial metabolic and regulatory pathway information, and patient data. Probing ~4,000 M. tuberculosis proteins with sera from >500 suspected tuberculosis patients worldwide revealed that antibody responses recognized ~10% of the bacterial proteome. This result defines the immunoproteome of M. tuberculosis, which is rich in membrane-associated and extracellular proteins. Most serum reactivity during active tuberculosis focused onto ~0.5% of the proteome. Within this pool, which is selectively enriched for extracellular proteins (but not for membrane-associated proteins), relative target preference varied among patients. The shift in relative M. tuberculosis protein reactivity observed with active tuberculosis defines the evolution of the humoral immune response during M. tuberculosis infection and disease. Peripheral blood was collected from prospectively enrolled TB suspects among subjects seeking care for pulmonary symptoms at clinics associated with national TB control programs in 11 countries. M. tuberculosis proteome microarrays representing 4099 bacterial protein spots were probed with sera from 561 TB suspects. Based on the final diagnosis, they belonged to two classes: TB (n=254) and Non-TB Disease (n=307). In addition, healthy individuals negative to Latent TB Infection (LTBI neg, n=64) were also tested (negative control sera). Each serum was tested with a single array and no replicate experiments were performed. The reactivity of a serum to an M. tuberculosis protein (reactivity call) was defined based on the distribution of negative control sera intensity for that protein using Z-statistics. Based on the distribution of reactivity calls, 27 outlier samples reacting with more than 20 proteins were excluded from further analysis. The association of reactivity calls of each protein with TB/NTBD status of TB suspects was determined by estimating odds ratio and 95% confidence interval.
2010-07-13 | E-GEOD-19433 | biostudies-arrayexpress