E-MTAB-8163
Ontology highlight
ABSTRACT:
PROVIDER: E-MTAB-8163 | ExpressionAtlas | 2025-01-16
REPOSITORIES: ExpressionAtlas
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| E-MTAB-8163-analysis-methods.tsv | Tabular | |||
| E-MTAB-8163-analytics.tsv | Tabular | |||
| E-MTAB-8163-apply_fixes_zooma_mappings.done | Other | |||
| E-MTAB-8163-atlasExperimentSummary.Rdata | Rdata | |||
| E-MTAB-8163-configuration.xml | Xml |
Items per page: 5 1 - 5 of 24 |
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Project description:Transcriptional profiling of the tuberculin skin test in individuals cured of active tuberculosis disease (RNA-Seq)
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Project description:Whole genome transcriptional profiling of punch biopsies from the site of 2U intradermal tuberculin or equivalent volume of saline injection at 48 hours after injection in individuals that have been cured of active tuberculosis disease.
2021-05-05 | E-MTAB-8163 | biostudies-arrayexpress
Project description:Tuberculosis (TB) is a serious infectious disease, but current methods of detection require improvement in sensitivity, efficiency or specificity. We conducted a microarray experiment, comparing the gene expression profiles in peripheral blood mononuclear cells among individuals with active TB, latent infection, and healthy conditions in a Taiwanese population. These differentially expressed genes may be potential biomarkers that can differentiate between active TB and latent infection. We isolated total RNA from the PBMC from 7 active TB, 7 latent infection, and 7 healthy individuals and profiled their transcriptional profiles to identify signficantly differentially expressed geens that differ among these three groups
2014-10-21 | E-GEOD-62525 | biostudies-arrayexpress
Project description:Human infection with Mycobacterium tuberculosis results in a continuum of ill-defined, clinical manifestations with stable latent M. tuberculosis infection (LTBI) and severe active disease at the ends. Identifying different states of infection is of importance to tuberculosis (TB) control since risk of developing active disease varies among different asymptomatic states while infectiousness varies among patients with different bacterial burden. We investigated changes in proteome-scale antibody responses during disease progression in a non-human primate model of tuberculosis. We probed M. tuberculosis proteome microarrays with serial sera collected from three infection-outcome groups (active, reactivation, and latent). We found that each infection outcome is associated with characteristic changes in the antibody levels and number of antigenic targets, which suggested an association between antibody responses and bacillary burden. Additional proteome-scale serological profiling of > 400 human TB suspects established that antibody responses are positively associated with bacterial load. Thus tuberculosis-specific antibody levels and number of antigenic targets increases with disease progression. Serum samples collected from adult patients with suspected tuberculosis during a multi-site study was used to probe whole proteome microarrays. Subject recruitment was conducted under uniform protocols approved by the institutional ethics committee at each site. Final diagnosis of active TB was based on positive M. tuberculosis culture results. The active TB patients were further subdivided into smear-positive and negative disease based on results of Ziehl-Neelsen staining of sputum smears for acid fast bacilli. Active TB was excluded as a diagnosis (Non-TB Disease [NTBD] patients) based on having negative M. tuberculosis culture and smear results and on having an alternate diagnosis. All subjects were presumably negative for HIV infection given the very low incidence of HIV infection in the study sites. Sera from 169 TB and 242 NTBD patients were selected for microarray probing. The control sera (n = 14) which was used to generate negative control distribution for each protein were negative to latent M. tuberculosis infection, as indicated by negative results to tuberculin skin test.
2012-07-05 | E-GEOD-30722 | biostudies-arrayexpress
Project description:C1q expression increases significantly in the peripheral blood of patients with active tuberculosis compared to healthy controls and individuals with latent TB infection. The percentage of C1q-expressing CD14 positive cells is significantly increased in active TB patients. C1q expression in the peripheral blood correlates with sputum smear positivity in tuberculosis patients and is reduced after anti-tuberculosis chemotherapy. Notably, receiver operating characteristic analysis showed that C1qC mRNA levels in peripheral blood efficiently discriminate active from latent tuberculosis infection and healthy controls. Additionally, C1qC protein level in pleural effusion shows improved power in discriminating tuberculosis from non-tuberculosis pleurisy when compared to other inflammatory markers, such as IL-6 and TNF-α C1q expression correlates with active disease in human tuberculosis. C1q could be a potential diagnostic marker to discriminate active tuberculosis from latent tuberculosis infection as well as tuberculosis pleurisy from non-tuberculosis pleurisy. Complement gene expression in peripheral blood mononuclear cells of tuberculosis patients and controls were determined using whole genome transcriptional microarray assays. The mRNA and protein levels of three C1q components, C1qA, C1qB, and C1qC, were further validated by qRT-PCR and enzyme-linked immunosorbent assay, respectively. The percentages of C1q expression in CD14 positive cells were determined by flow cytometry. Finally, C1qC protein level was quantified in the pleural fluid of tuberculosis and non-tuberculosis pleurisy.
2014-02-15 | E-GEOD-54992 | biostudies-arrayexpress
Project description:Kilian2024 - Immune cell dynamics in Cue-Induced Extended Human Colitis Model
Single-cell technologies such as scRNA-seq and flow cytometry provide critical insights into immune cell behavior in inflammatory bowel disease (IBD). However, integrating these datasets into computational models for dynamic analysis remains challenging. Here, Kilian et al., (2024) developed a deterministic ODE-based model that incorporates these technologies to study immune cell population changes in murine colitis. The model parameters were optimized to fit experimental data, ensuring an accurate representation of immune cell behavior over time. It was then validated by comparing simulations with experimental data using Pearson’s correlation and further tested on independent datasets to confirm its robustness. Additionally, the model was applied to clinical bulk RNA-seq data from human IBD patients, providing valuable insights into immune system dynamics and potential therapeutic strategies.
Figure 4c, obtained from the simulation of human colitis model is highlighted here.
This model is described in the article:
Kilian, C., Ulrich, H., Zouboulis, V.A. et al. Longitudinal single-cell data informs deterministic modelling of inflammatory bowel disease. npj Syst Biol Appl 10, 69 (2024). https://doi.org/10.1038/s41540-024-00395-9
Abstract:
Single-cell-based methods such as flow cytometry or single-cell mRNA sequencing (scRNA-seq) allow deep molecular and cellular profiling of immunological processes. Despite their high throughput, however, these measurements represent only a snapshot in time. Here, we explore how longitudinal single-cell-based datasets can be used for deterministic ordinary differential equation (ODE)-based modelling to mechanistically describe immune dynamics. We derived longitudinal changes in cell numbers of colonic cell types during inflammatory bowel disease (IBD) from flow cytometry and scRNA-seq data of murine colitis using ODE-based models. Our mathematical model generalised well across different protocols and experimental techniques, and we hypothesised that the estimated model parameters reflect biological processes. We validated this prediction of cellular turnover rates with KI-67 staining and with gene expression information from the scRNA-seq data not used for model fitting. Finally, we tested the translational relevance of the mathematical model by deconvolution of longitudinal bulk mRNA-sequencing data from a cohort of human IBD patients treated with olamkicept. We found that neutrophil depletion may contribute to IBD patients entering remission. The predictive power of IBD deterministic modelling highlights its potential to advance our understanding of immune dynamics in health and disease.
This model was curated during the Hackathon hosted by BioMed X GmbH in 2024.
2025-03-07 | MODEL2502180001 | BioModels
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:C1q expression increases significantly in the peripheral blood of patients with active tuberculosis compared to healthy controls and individuals with latent TB infection. The percentage of C1q-expressing CD14 positive cells is significantly increased in active TB patients. C1q expression in the peripheral blood correlates with sputum smear positivity in tuberculosis patients and is reduced after anti-tuberculosis chemotherapy. Notably, receiver operating characteristic analysis showed that C1qC mRNA levels in peripheral blood efficiently discriminate active from latent tuberculosis infection and healthy controls. Additionally, C1qC protein level in pleural effusion shows improved power in discriminating tuberculosis from non-tuberculosis pleurisy when compared to other inflammatory markers, such as IL-6 and TNF-α C1q expression correlates with active disease in human tuberculosis. C1q could be a potential diagnostic marker to discriminate active tuberculosis from latent tuberculosis infection as well as tuberculosis pleurisy from non-tuberculosis pleurisy.
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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: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.
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