Transcriptome analysis of mycobacteria in sputum samples of pulmonary tuberculosis patients
Ontology highlight
ABSTRACT:
OTHER RELATED OMICS DATASETS IN: GSE93316
PROVIDER: PRJNA360604 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Sputum expectorated by the pulmonary tuberculosis patients still remains a primary diagnostic specimen. The expression pattern of mycobacteria in sputum will lead to an insight of bacterial adaptation at the most highly transmissible stage of infection and can also help in identifying newer diagnostic as well as drug targets. Further, the identification of crossreactive gene targets from the sputum samples of other lung diseases will help to find the diagnostic candidates which will be highly specific to pulmonary tuberculosis.
2017-04-18 | GSE93316 | GEO
Project description: Not available
| S-EPMC5345810 | biostudies-literature
Project description:Bacille Calmette Guerin (BCG) is the only licensed vaccine against Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB) disease. However, BCG has limited efficacy, necessitating the development of better vaccines. Non-tuberculous mycobacteria (NTM), a distinct lineage from Mtb, are opportunistic pathogens present in the environment. TB endemic countries experience higher exposure to NTM, but previous studies have not elucidated the relationship between NTM exposure and BCG efficacy. Therefore, we developed a mouse model (BCG+NTM) that mimics human BCG vaccination at an early stage and continuous NTM exposure via the oral route, including during TB infection. Our results show that BCG+NTM mice had improved protection against pulmonary TB correlating with increased pulmonary influx of B-cells, higher titers of anti-Mtb IgA and IgG antibodies in serum and airways, compared to mice vaccinated with BCG alone. Notably, the lungs of BCG+NTM mice developed B-cell aggregates expressing markers of germinal center formation as determined by spatial transcriptomics. We conclude a direct correlation between NTM exposure and protection from TB, with B-cells playing a crucial role.
2022-10-23 | GSE203037 | GEO
Project description:Purpose: Accurate diagnosis of complete inactivation of tuberculosis lesions is still a challenge with respect to sputum-negative tuberculosis. RNA-sequencing was conducted to uncover potential lncRNA indicators of metabolic activity in tuberculosis lesions. Methods: Lung tissues with high metabolic activity (PET-high) and low metabolic activity (PET-low) demonstrated by fluorine-18-fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) were collected from five sputum-negative tuberculosis patients for RNA-sequencing. Differentially expressed mRNAs and lncRNAs were identified, and their correlations were evaluated to constructed lncRNA-mRNA co-expression network. Afterwards, cis- or trans-targets of differentially expressed lncRNAs were predicted, followed by establishing lncRNA-target-pathway network, in which lncRNAs and mRNAs with high degrees were measured by quantitative real-time PCR using samples collected from 11 patients. Prediction efficiencies of lncRNA indicators were assessed by receiver operating characteristic curve analysis, Bioinformatics analysis was performed for potential lncRNAs. Results: In total, 386 mRNAs and 44 lncRNAs were identified to be differentially expressed. Differentially expressed mRNAs in lncRNA-mRNA co-expression network were significantly associated with the fibrillar collagen, platelet-derived growth factor binding, and leukocyte migration involved in inflammatory response. One cis-target gene and 440 trans-target genes were predicted for differentially expressed lncRNAs. Seven genes (C1QB, CD68, CCL5, CCL19, MMP7, HLA-DMB, and CYBB) and two lncRNAs (ENST00000429730.1 and MSTRG.93125.4) were validated to be significantly up-regulated. The area under the curve of ENST00000429730.1 and MSTRG.93125.4 was 0.750 and 0.813, respectively. Conclusion: Two lncRNAs ENST00000429730.1 and MSTRG.93125.4 might be considered as potential indicators of metabolic activity in tuberculosis lesions for sputum-negative tuberculosis.
2020-09-30 | GSE158767 | GEO
Project description:These are sputum samples collected from 8 individuals with cystic fibrosis during the course of routine clinical care. They were initially stored at 4C for up to 24 hours then stored at -80C. No processing has been done to the sputum prior to freezing. For each individual there are sputum samples collected both before and after the individual had his or her first positive sputum culture for nontuberculous mycobacteria (NTM). The individuals experienced different clinical courses after their infection.
2017-06-19 | ST000711 | MetabolomicsWorkbench
Project description:Pulmonary tuberculosis metagenome
| PRJNA664352 | ENA
Project description:Pulmonary tuberculosis is a multigene disease, and some of the genes affect the development of Pulmonary tuberculosis. The study wants to find different expression genes in blood from Pulmonary tuberculosis patient and normal people who have genetic relationship wtih each other. We used microarrays to detail the global programme of gene expression in the blood between Pulmonary tuberculosis patient's and normal people's who have genetic relationship wtih each other.
2017-12-06 | GSE107731 | GEO
Project description:Little is known about the lung microbiome dynamics and host-microbiome interactions in relation to chronic obstructive pulmonary disease (COPD) exacerbations and in patient subgroups based on smoking status and disease severity. Here we performed a 16S ribosomal RNA survey on sputum microbiome from 16 healthy and 43 COPD subjects. For COPD subjects, a longitudinal sampling was performed from stable state to exacerbations, at two and six weeks post-exacerbations and at six months from first stable visit. Host sputum transcriptome were characterized for a subset of COPD patient samples.
2021-03-21 | GSE112165 | GEO
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:Despite more than a century fighting against tuberculosis, the World Health Organisation has estimated that around 1.7 million people died of tuberculosis in 2016 and over a quarter of the world’s population is infected. One of the critical hurdles for stopping tuberculosis transmission is early and effective diagnosis of patients with the active pulmonary disease. Although important innovations in molecular diagnosis have been recently developed (e.g. Xpert MTB/RIF, Cepheid Inc., USA), there are no suitable tests for population screening at point-of-care. The current tuberculosis diagnosis pipeline presents a highly variable performance and requires access to reference laboratory facilities. A non-sputum based rapid test with high specificity and sensitivity could save ~400,000 lives per year. Therefore, new biomarkers for diagnosis are urgently required for identifying patients with early symptoms and to expedite treatment. Variable sensitivity and specificity can be overcome using a combination of multiple biomarkers (5). Proteins, as ultimate biological effectors, are ideal candidates for diagnostic biomarkers; consequently, proteomic studies are a crucial platform for biomarker discovery in tuberculosis. This work aims to develop a multi-marker panel for tuberculosis diagnosis with high performance capable of differentiating tuberculosis patients from relevant controls. Quantitative Multidimensional Protein Identification Technology (qMudPIT) is applied for biomarker discovery identifying candidates for early diagnosis of tuberculosis. The multidimensional method optimised in this work led to the identification of 5022 plasma proteins and 3577 quantified proteins using iTRAQ labelling. Known and completely novel markers for active tuberculosis in plasma were identified including a peptide derived from Mycobacterium tuberculosis. Complementary statistical and bioinformatic analysis were applied to prioritise candidates for validation in one or two independent cohorts. The plasma proteomic profile here described represents a power strategy for biomarker discovery and the panel proposed has the potential to be translated to a rapid test and which might contribute to tuberculosis control.
2021-09-09 | PXD020212 | Pride