Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1177198 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR31099200_1.fastq.gz | Fastqsanger.gz | |||
| SRR31099300_1.fastq.gz | Fastqsanger.gz | |||
| SRR31099201_1.fastq.gz | Fastqsanger.gz | |||
| SRR31099301_1.fastq.gz | Fastqsanger.gz | |||
| SRR31099202_1.fastq.gz | Fastqsanger.gz |
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Project description:①Background:Tuberculosis is mainly a respiratory tract infection caused by mycobacterium tuberculosis and one of the leading causes of death worldwide. According to the Global Tuberculosis Report in 2021, About a quarter of the world's population is infected with Mycobacterium tuberculosis and China is the second highest burden of TB. Although TB diagnosis and prevention techniques have become more mature, the number of TB cases is still increasing, mainly due to: the prevalence of drug-resistant tuberculosis bacteria, tuberculosis and HIV co-infection, long incubation time of mycobacterium tuberculosis difficult to early diagnosis and so on. Therefore, it is of great significance to study the pathogenesis of mycobacterium tuberculosis infection.②Method: THP-1 cells were treated with 50ng/ml PMA for 24 hours, so that THP-1 cell can be induced into macrophages. After that THP-1 macrophages were infected with mycobacterium tuberculosis H37Rv(MOI=1), which were collected and applied to RNA-sequencing. The constructed sequencing library was sequenced using an Illumina Novaseq 6000 system.
2022-08-31 | GSE203261 | GEO
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:Efforts to eradicate TB are largely threatened by drug-resistant tuberculosis, particularly, multidrug-resistant tuberculosis (MDR-TB). It is imperative to find one or more specific biomarkers for diagnosing MDR-TB earlier and declining the incidence. Growing evidences have showed lncRNAs are widely expressed and take part in the genesis and development of many diseases, including tuberculosis. Therefore, to screen the differential lncRNAs among MDR-TB, drug-sensitive tuberculosis(DS-TB) and healthy controls(HCs) is a good strategy to acquire potential biomarkers for MDR-TB diagnosis and partly describe the mechanism of MDR-TB. Here, the present study aimed to investigate the differential expression profile of lncRNAs in serum among patients with MDR-TB ,DS-TB and HCs using lncRNA microarray
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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.
2010-08-11 | GSE22098 | 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.
2010-08-11 | E-GEOD-22098 | biostudies-arrayexpress
Project description:Background Accurate assessment of treatment efficacy would facilitate clinical trials of new anti-tuberculosis drugs. TB patients exhibit altered peripheral immunity which reverts during successful treatment. We hypothesised that these changes could be observed in whole blood transcriptome profiles. Methods Ex vivo blood samples from 27 pulmonary TB patients were assayed at diagnosis and during conventional treatment. RNA was processed and hybridised to Affymetrix GeneChips, to determine expression of over 47,000 transcripts. Findings There were significant changes in expression of over 4,000 genes during treatment. Rapid, large scale changes were detected, with down-regulated expression of ~1,000 genes within the first week, including inflammatory markers such as the complement components C1q and C2. This was followed by slower changes in expression of different networks of genes, including a later increase in expression of B cell markers, transcription factors and signalling molecules. Interpretation The expression of many genes is drastically altered during TB disease, with components of the humoral immune response being markedly affected. The treatment-induced restoration reflects the simultaneous suppression and activation of different immune responses in TB. The rapid initial down-regulation of expression of inflammatory mediators coincides with rapid killing of actively dividing bacilli, whereas slower delayed changes occur as drugs act on dormant bacilli and as lung pathology resolves. Measurement of biosignatures during clinical trials of new drugs could be useful predictors of rapid bactericidal or sterilizing drug activity. Ex vivo blood samples analysed for 27 first episode pulmonary TB patients, at diagnosis and after 1, 2, 4 and 26 weeks of treatment.
2012-08-09 | E-GEOD-31348 | biostudies-arrayexpress
Project description:Background Accurate assessment of treatment efficacy would facilitate clinical trials of new anti-tuberculosis drugs. TB patients exhibit altered peripheral immunity which reverts during successful treatment. We hypothesised that these changes could be observed in whole blood transcriptome profiles. Methods Ex vivo blood samples from 27 pulmonary TB patients were assayed at diagnosis and during conventional treatment. RNA was processed and hybridised to Affymetrix GeneChips, to determine expression of over 47,000 transcripts. Findings There were significant changes in expression of over 4,000 genes during treatment. Rapid, large scale changes were detected, with down-regulated expression of ~1,000 genes within the first week, including inflammatory markers such as the complement components C1q and C2. This was followed by slower changes in expression of different networks of genes, including a later increase in expression of B cell markers, transcription factors and signalling molecules. Interpretation The expression of many genes is drastically altered during TB disease, with components of the humoral immune response being markedly affected. The treatment-induced restoration reflects the simultaneous suppression and activation of different immune responses in TB. The rapid initial down-regulation of expression of inflammatory mediators coincides with rapid killing of actively dividing bacilli, whereas slower delayed changes occur as drugs act on dormant bacilli and as lung pathology resolves. Measurement of biosignatures during clinical trials of new drugs could be useful predictors of rapid bactericidal or sterilizing drug activity. Ex vivo blood samples analysed during TB treatment. These samples are from 9 successfully cured patients at diagnosis and end-of-treatment at 26 weeks.
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Project description:Mycobacterium tuberculosis (Mtb) antigen-specific cellular response is promising for detectionof Mtb infection, but not efficient for diagnosis of TB. We firstly identified 16 TB disease-specific protein markers measured in the culture supernatant of Mtb-stimulated whole blood using a 640 human proteins array, the highest throughput antibody-based protein array available at the time when we did this study. Potential TB-related proteins were then analyzed across three different patient cohorts comprised of healthy controls, LTBI, non-TB pneumonia, and TB patients to evaluate how the biomarkers performed in diagnosing TB in the real clinical setting. The data finally reveal an eight-protein biosignature of TB.
2019-12-12 | GSE141848 | GEO
Project description:Mycobacterium tuberculosis (Mtb) antigen-specific cellular response is promising for detectionof Mtb infection, but not efficient for diagnosis of TB. We firstly identified 16 TB disease-specific protein markers measured in the culture supernatant of Mtb-stimulated whole blood using a 640 human proteins array, the highest throughput antibody-based protein array available at the time when we did this study. Potential TB-related proteins were then analyzed across three different patient cohorts comprised of healthy controls, LTBI, non-TB pneumonia, and TB patients to evaluate how the biomarkers performed in diagnosing TB in the real clinical setting. The data finally reveal an eight-protein biosignature of TB.
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2021-03-05 | GSE168247 | GEO