Epigenetics and proteomics join transcriptomics in the quest for tuberculosis biomarkers

Esterhuyse, Maria M. ; Weiner, January ; Caron, Etienne ; Loxton, Andre G. ; Iannaccone, Marco ; Wagman, Chandre ; Saikali, Philippe ; Stanley, Kim ; Wolski, Witold E. ; Mollenkopf, Hans-Joachim ; Schick, Matthias ; Aebersold, Ruedi ; Linhart, Heinz ; Walzl, Gerhard ; Kaufmann, Stefan H. E. (2015-09-15)

CITATION: Esterhuyse, M. M. et al. 2015. Epigenetics and proteomics join transcriptomics in the quest for tuberculosis biomarkers. mBio, 6(5):e01187-15, doi:10.1128/mBio.01187-15.

The original publication is available at http://mbio.asm.org


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.

Please refer to this item in SUNScholar by using the following persistent URL: http://hdl.handle.net/10019.1/99817
This item appears in the following collections: