Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA138233 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Tuberculosis (TB) is responsible for the majority of mortality and morbidity associated with infectious diseases worldwide. The characterization of exact molecular components of immune response associated with protection against TB may help design more effective therapeutic interventions. In this study, we aimed to characterize the immune signature of memory T cells associated with active versus latent infection with Mycobacterium tuberculosis. Transcriptomic profiling using RNA sequencing was performed on memory CD4 T cells isolated from individuals with active TB (at diagnosis and 2 months post treatment), latent TB, as well as from TB negative healthy controls. Overall, we found specific gene signatures for each cohort that could successfully discriminate between individuals with active TB at diagnosis, treated active TB, latent TB and healthy controls.
2021-05-11 | GSE161829 | GEO
Project description:Tuberculosis (TB) is responsible for the majority of mortality and morbidity associated with infectious diseases worldwide. The characterization of exact molecular components of immune response associated with protection against TB may help design more effective therapeutic interventions. In this study, we aimed to characterize the immune signature of memory T cells associated with latent infection with Mycobacterium tuberculosis. Transcriptomic profiling using RNA sequencing was performed on memory CD4 T cells isolated from individuals with latent tuberculosis, as well as from tuberculosis negative healthy controls. Overall, we found specific gene signatures in each cell subset that could successfully discriminate between individuals with latent tuberculosis and healthy controls.
2018-06-14 | GSE99373 | GEO
Project description:Tuberculosis (TB) is responsible for the majority of mortality and morbidity associated with infectious diseases worldwide. The characterization of exact molecular components of immune response associated with protection against TB may help design more effective therapeutic interventions. In this study, we aimed to characterize the immune signature of memory T cells associated with latent infection with Mycobacterium tuberculosis. Transcriptomic profiling using RNA sequencing was performed on memory CD8 T cells isolated from individuals with latent tuberculosis, as well as from tuberculosis negative healthy controls. Overall, we found specific gene signatures in each cell subset that could successfully discriminate between individuals with latent tuberculosis and healthy controls.
2020-05-26 | GSE99374 | GEO
Project description:Tuberculosis (TB) is responsible for the majority of mortality and morbidity associated with infectious diseases worldwide. The characterization of exact molecular components of immune response associated with protection against TB may help design more effective therapeutic interventions. In this study, we aimed to characterize the immune signature of memory T cells associated with latent infection with Mycobacterium tuberculosis. Transcriptomic profiling using RNA sequencing was performed on memory CD4 and CD8 T cells isolated from individuals with latent tuberculosis, as well as from tuberculosis negative healthy controls. Overall, we found specific gene signatures in each cell subset that could successfully discriminate between individuals with latent tuberculosis and healthy controls.
2019-06-12 | GSE84445 | GEO
Project description:Tuberculosis (TB) is responsible for the majority of mortality and morbidity associated with infectious diseases worldwide. The characterization of exact molecular components of immune response associated with protection against TB may help design more effective therapeutic interventions. In this study, we aimed to characterize the immune signature of monocyte subsets associated with active versus latent infection with Mycobacterium tuberculosis. Transcriptomic profiling using RNA sequencing was performed on classical (CD14+CD16-), intermediate (CD14+CD16+) and non-classical (CD14-CD16+) monocytes isolated from individuals with active TB (at diagnosis and 2 months post treatment), latent TB, as well as from TB negative healthy controls. Overall, we found specific gene signatures for each monocyte subset that could successfully discriminate between individuals with active TB at diagnosis, treated active TB, latent TB and healthy controls.
2023-01-03 | GSE185372 | GEO
Project description:For further identify the differentiation between latent and clinical tuberculosis (TB), we employed whole genome microarray expression profiling to study genes with significant expression change in peripheral CD4+T cells between healthy control, latent tuberculosis (LTB) and clinical tuberculosis (TB). Our experiment included 4 groups: healthy donor (HD), latent TB1 (LTB1) with low IFN-gamma release level, latent TB2 (LTB2) with high IFN-gamma release level, and tuberculosis (TB) with high IFN-gamma release level. Human peripheral blood mononuclear cells were collected, from which CD4+T cells were isolated. Total RNA of each individuals of each group was extracted from peripheral CD4+T cells. One μg of RNA mixture, pooled equivalently by each individual total RNA of each group, was administrated microarray test. Compared with HD, through analyzing enriched-Gene Ontology (GO) terms and KEGG pathways of each group, we found peripheral CD4+T cells might had different ability for mycobacterium tuberculosis infection in LTB1, LTB2 and TB. Finally we detected that TNFSF13/APRIL and TNFSF13B/BAFF was significant up-regulation in both CD4+T cells and serum of TB by real time PCR and ELISA, respectively.
2012-08-07 | GSE27882 | GEO
Project description:For further identify the differentiation between latent and clinical tuberculosis (TB), we employed whole genome microarray expression profiling to study genes with significant expression change in peripheral CD4+T cells between healthy control, latent tuberculosis (LTB) and clinical tuberculosis (TB). Our experiment included 4 groups: healthy donor (HD), latent TB1 (LTB1) with low IFN-gamma release level, latent TB2 (LTB2) with high IFN-gamma release level, and tuberculosis (TB) with high IFN-gamma release level. Human peripheral blood mononuclear cells were collected, from which CD4+T cells were isolated. Total RNA of each individuals of each group was extracted from peripheral CD4+T cells. One ?g of RNA mixture, pooled equivalently by each individual total RNA of each group, was administrated microarray test. Compared with HD, through analyzing enriched-Gene Ontology (GO) terms and KEGG pathways of each group, we found peripheral CD4+T cells might had different ability for mycobacterium tuberculosis infection in LTB1, LTB2 and TB. Finally we detected that TNFSF13/APRIL and TNFSF13B/BAFF was significant up-regulation in both CD4+T cells and serum of TB by real time PCR and ELISA, respectively. Peripheral CD4+ T cells were purified by positive selection using magnetic beads (BD IMagTM anti-human CD4 Particles-DM, BD Biosciences). Total RNA was extracted from CD4+ T cells (CD4-RNA) of LTB1, LTB2 and TB patients and healthy controls by RNeasy Mini Kit (QIAGEN).Then, RNA quality was checked and mixed with an equal quantity of each individual. The number of included-individuals in each group was 11 for HD, 11 for LTB1, 12 for LTB2 and 11 for TB.
2012-08-06 | E-GEOD-27882 | biostudies-arrayexpress
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:Tuberculosis (TB) remains one of the world’s major infectious diseases affecting nations with limited public health resources. Multidrug resistance development has seriously compromised therapeutic treatment choices. The pathology of latent TB shows evidence of a reservoir of Mycobacterium tuberculosis (Mtb) in the lungs of affected individuals. If the pathogen is contained by the immune system, no overt disease symptoms occur. The environmental and internal triggers leading to disease reactivation are not well understood. Proteomic investigations of blood plasma and sputum derived from subjects with active TB versus latent TB versus healthy individuals may yield new biomarkers and, when surveying larger longitudinally monitored cohorts, may discriminate infection outcomes in an endemic setting.
2021-05-26 | PXD012412 | Pride
Project description:Tuberculosis (TB), caused by infection with Mycobacterium tuberculosis (M. tuberculosis), is a major cause of morbidity and mortality worldwide and efforts to control TB are hampered by difficulties with diagnosis, prevention and treatment. Most people infected with M. tuberculosis remain asymptomatic, termed latent TB, with a 10% lifetime risk of developing active TB disease, but current tests cannot identify which individuals will develop disease. The immune response to M. tuberculosis is complex and incompletely characterized, hindering development of new diagnostics, therapies and vaccines. The goals of this study include: 1. Identify a transcript signature for active TB in intermediate and high burden settings, correlating with radiological extent of disease and reverting to that of healthy controls following treatment; 2. Identify a specific transcript signature that discriminated active TB from other inflammatory and infectious diseases; 3. Classify TB signature using modular and pathway analysis tools. Three milliliters of whole blood was collected in Tempus tubes from 12 pediatric streptococcus, 40 pediatric staphylococcus, 31 still’s disease, 82 pediatric systemic lupus erythematosus (SLE) and 28 adult SLE patients. RNA was extracted and globin reduced. Labeled cRNA was hybridized to Illumina Human HT-12 Beadchips. Healthy controls were included to match patients’ demographic data. Genespring software was used to analyze active TB transcript signatures, comparing with healthy controls and other inflammatory and infectious diseases.
2010-08-11 | E-GEOD-22098 | biostudies-arrayexpress