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Tailleux, L.

Publications and source records attributed to Tailleux, L..

2 recordsLinked to original sources

Gene activation precedes DNA demethylation in response to infection in human dendritic cells

DNA methylation is considered to be a relatively stable epigenetic mark. Yet, a growing body of evidence indicates that DNA methylation levels can change rapidly, for example, in innate immune cells facing an infectious agent. Nevertheless, the causal relationship between changes in DNA methylation and gene expression during infection remains to be elucidated. Here, we generated time-course data on DNA methylation, gene expression, and chromatin accessibility patterns during infection of human dendritic cells with Mycobacterium tuberculosis. We found that the immune response to infection is accompanied by active demethylation of thousands of CpG sites overlapping distal enhancer elements. However, virtually all changes in gene expression in response to infection occur prior to detectable changes in DNA methylation, indicating that the observed losses in methylation are a downstream consequence of transcriptional activation. Footprinting analysis revealed that immune-related transcription factors (TF), such as NF-{kappa}B/Rel, are recruited to enhancer elements prior to the observed losses in methylation, suggesting that DNA demethylation is mediated by TF binding to cis-acting elements. Collectively, our results show that DNA demethylation is not required for the establishment of the core regulatory program engaged upon infection.

genomics

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

Tuberculosis (TB) is a deadly infectious disease, which kills millions of people every year. The causative pathogen, Mycobac-terium tuberculosis (MTB), is estimated to have infected up to a third of the worlds 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 decent 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.

genomics