Abstract
An estimated one-third of the world's population is currently latently infected with Mycobacterium tuberculosis. Latent M. tuberculosis infection (LTBI) progresses into active tuberculosis (TB) disease in ~5 to 10% of infected individuals. Diagnostic and prognostic biomarkers to monitor disease progression are urgently needed to ensure better care for TB patients and to decrease the spread of TB. Biomarker development is primarily based on transcriptomics. Our understanding of biology combined with evolving technical advances in high-throughput techniques led us to investigate the possibility of additional platforms (epigenetics and proteomics) in the quest to (i) understand the biology of the TB host response and (ii) search for multiplatform biosignatures in TB. We engaged in a pilot study to interrogate the DNA methylome, transcriptome, and proteome in selected monocytes and granulocytes from TB patients and healthy LTBI participants. Our study provides first insights into the levels and sources of diversity in the epigenome and proteome among TB patients and LTBI controls, despite limitations due to small sample size. Functionally the differences between the infection phenotypes (LTBI versus active TB) observed in the different platforms were congruent, thereby suggesting regulation of function not only at the transcriptional level but also by DNA methylation and microRNA. Thus, our data argue for the development of a large-scale study of the DNA methylome, with particular attention to study design in accounting for variation based on gender, age, and cell type. IMPORTANCE: DNA methylation modifies the transcriptional program of cells. We have focused on two major populations of leukocytes involved in immune response to infectious diseases, granulocytes and monocytes, both of which are professional phagocytes that engulf and kill bacteria. We have interrogated how DNA methylation, gene expression, and protein translation differ in these two cell populations between healthy individuals and patients suffering from TB. To better understand the underlying biologic mechanisms, we harnessed a statistical enrichment analysis, taking advantage of predefined and well-characterized gene sets. Not only were there clear differences on various levels between the two populations, but there were also differences between TB patients and healthy controls in the transcriptome, proteome, and, for the first time, DNA methylome in these cells. Our pilot study emphasizes the value of a large-scale study of the DNA methylome taking into account our findings.