Dataset Information

Predicting susceptibility to tuberculosis based on gene expression profiling in dendritic cells.

ABSTRACT: Tuberculosis (TB) is a deadly infectious disease, which kills millions of people every year. The causative pathogen, Mycobacterium tuberculosis (MTB), is estimated to have infected up to a third of the world's population; however, only approximately 10% of infected healthy individuals progress to active TB. Despite evidence for heritability, it is not currently possible to predict who may develop TB. To explore approaches to classify susceptibility to TB, we infected with MTB dendritic cells (DCs) from putatively resistant individuals diagnosed with latent TB, and from susceptible individuals that had recovered from active TB. We measured gene expression levels in infected and non-infected cells and found hundreds of differentially expressed genes between susceptible and resistant individuals in the non-infected cells. We further found that genetic polymorphisms nearby the differentially expressed genes between susceptible and resistant individuals are more likely to be associated with TB susceptibility in published GWAS data. Lastly, we trained a classifier based on the gene expression levels in the non-infected cells, and demonstrated reasonable performance on our data and an independent data set. Overall, our promising results from this small study suggest that training a classifier on a larger cohort may enable us to accurately predict TB susceptibility.

SUBMITTER: Blischak JD

PROVIDER: S-EPMC5516010 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

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Predicting susceptibility to tuberculosis based on gene expression profiling in dendritic cells.

Blischak John D JD Tailleux Ludovic L Myrthil Marsha M Charlois Cécile C Bergot Emmanuel E Dinh Aurélien A Morizot Gloria G Chény Olivia O Platen Cassandre Von CV Herrmann Jean-Louis JL Brosch Roland R Barreiro Luis B LB Gilad Yoav Y

Scientific reports 20170718 1

Tuberculosis (TB) is a deadly infectious disease, which kills millions of people every year. The causative pathogen, Mycobacterium tuberculosis (MTB), is estimated to have infected up to a third of the world's population; however, only approximately 10% of infected healthy individuals progress to active TB. Despite evidence for heritability, it is not currently possible to predict who may develop TB. To explore approaches to classify susceptibility to TB, we infected with MTB dendritic cells (DC ...[more]

PMID: 28720766

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Project description:Cordyceps sinensis (CS) has been commonly used as herbal medicine and a health supplement in China for over two thousand years. Although previous studies have demonstrated that CS has benefits in immunoregulation and anti-inflammation, the precise mechanism by which CS affects immunomodulation is still unclear. In this study, we exploited duplicate sets of loop-design microarray experiments to examine two different batches of CS and analyze the effects of CS on dendritic cells (DCs), in different physiology stages: naïve stage and inflammatory stage. Immature DCs were treated with CS, lipopolysaccharide (LPS), or LPS plus CS (LPS/CS) for two days, and the gene expression profiles were examined using cDNA microarrays. The results of two loop-design microarray experiments showed good intersection rates. The expression level of common genes found in both loop-design microarray experiments was consistent, and the correlation coefficients (Rs), were higher than 0.96. Through intersection analysis of microarray results, we identified 295 intersecting significantly differentially expressed (SDE) genes of the three different treatments (CS, LPS, and LPS/CS), which participated mainly in the adjustment of immune response and the regulation of cell proliferation and death. Genes regulated uniquely by CS treatment were significantly involved in the regulation of focal adhesion pathway, ECM-receptor interaction pathway, and hematopoietic cell lineage pathway. Unique LPS regulated genes were significantly involved in the regulation of Toll-like receptor signaling pathway, systemic lupus erythematosus pathway, and complement and coagulation cascades pathway. Unique LPS/CS regulated genes were significantly involved in the regulation of oxidative phosphorylation pathway. These results could provide useful information in further study of the pharmacological mechanisms of CS. This study also demonstrates that with a rigorous experimental design, the biological effects of a complex compound can be reliably studied by a complex system like cDNA microarray.

Project description:BACKGROUND: Staphylococcus aureus is a major pathogen of humans and animals and emerging antibiotic-resistant strains have further increased the concern of this health issue. Host genetics influence susceptibility to S. aureus infections, and the genes determining the outcome of infections should be identified to find alternative therapies to treatment with antibiotics. Here, we used outbred animals from a divergent selection based on susceptibility towards Staphylococcus infection to explore host immunogenetics. METHODOLOGY/PRINCIPAL FINDINGS: We investigated how dendritic cells respond to heat-inactivated S. aureus and whether dendritic cells from animals showing different degrees of susceptibility had distinct gene expression profiles. We measured gene expression levels of in vitro S. aureus-stimulated bone marrow-derived dendritic cells at three different time points (0, 3 and 8 hrs) by using 15 k ovine Agilent microarrays. Furthermore, differential expression of a selected number of genes was confirmed by RT-qPCR. Gene signatures of stimulated DCs were obtained and showed that genes involved in the inflammatory process and T helper cell polarization were highly up-regulated upon stimulation. Moreover, a set of 204 genes were statistically differentially expressed between susceptible and resistant animals, and grouped them according to their predisposition to staphylococcal infection. Interestingly, over-expression of the C1q and Ido1 genes was observed in the resistant line and suggested a role of classical pathway of complement and early regulation of inflammation pathways, respectively. On the contrary, over expression of genes involved in the IL1R pathway was observed in susceptible animals. Furthermore, the leucocyte extravasation pathway was also found to be dominant in the susceptible line. CONCLUSION/SIGNIFICANCE: We successfully obtained Staphylococcus aureus associated gene expression of ovine BM-DC in an 8-hour kinetics experiment. The distinct transcriptional profiles of dendritic cells obtained from resistant and susceptible animals may explain susceptibility towards S. aureus infections in a broader context.

Project description:Tuberculosis (TB) is a serious infectious disease in that 90% of those latently infected with Mycobacterium tuberculosis present no symptoms, but possess a 10% lifetime chance of developing active TB. To prevent the spread of the disease, early diagnosis is crucial. However, current methods of detection require improvement in sensitivity, efficiency or specificity. In the present study, we conducted a microarray experiment, comparing the gene expression profiles in the peripheral blood mononuclear cells among individuals with active TB, latent infection, and healthy conditions in a Taiwanese population.Bioinformatics analysis revealed that most of the differentially expressed genes belonged to immune responses, inflammation pathways, and cell cycle control. Subsequent RT-PCR validation identified four differentially expressed genes, NEMF, ASUN, DHX29, and PTPRC, as potential biomarkers for the detection of active and latent TB infections. Receiver operating characteristic analysis showed that the expression level of PTPRC may discriminate active TB patients from healthy individuals, while ASUN could differentiate between the latent state of TB infection and healthy condidtion. In contrast, DHX29 may be used to identify latently infected individuals among active TB patients or healthy individuals. To test the concept of using these biomarkers as diagnostic support, we constructed classification models using these candidate biomarkers and found the Naïve Bayes-based model built with ASUN, DHX29, and PTPRC to yield the best performance.Our study demonstrated that gene expression profiles in the blood can be used to identify not only active TB patients, but also to differentiate latently infected patients from their healthy counterparts. Validation of the constructed computational model in a larger sample size would confirm the reliability of the biomarkers and facilitate the development of a cost-effective and sensitive molecular diagnostic platform for TB.

Dataset Information

Predicting susceptibility to tuberculosis based on gene expression profiling in dendritic cells.

Publications

Predicting susceptibility to tuberculosis based on gene expression profiling in dendritic cells.

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