Integrative proteomics and network biology approach to identify potential urine based biomarkers for tuberculosis.

Urine based biomarker discovery employing proteomics platform has been successfully attempted for multiple diseases. Urine is an excellent source of biomarker discovery but its potential is not fully tapped in tuberculosis (TB) diagnostics. In the present study, proteomic profiling of urine samples from thirty five subjects (Mean age=41 years (15-76), M/F=28/7) belonging to active TB, latent TB, lung cancer, chronic obstructive pulmonary disorders (COPD) and healthy subjects were carried out employing a robust multiplex technique. We identified 131 proteins out of which 16 molecules showed at least two-fold change in TB. The study identified a signature of three putative markers, leucine-rich alpha-2-glycoprotein (up-regulated), roundabout homolog 4 and isoform 2 of prostatic acid phosphatase (down-regulated) that could differentiate active TB from other pulmonary diseases. Besides, we investigated whether a network based approach can be efficiently used to expand dynamic coverage, gain a comprehensive view of underlying perturbed functions during the infection and to discover potential biomarkers. While comparing the functionally associated sub-networks of active TB with healthy urine proteome, we identified 54 proteins from the discriminative TB sub-network, some of which are known to be involved in the infection process. Few examples in this study like serpin peptidase inhibitor and catenin that has not been identified in the experiment but detected in the difference network demonstrate that proteomic profiling when integrated with network biology method could be a holistic approach to expand the dynamic range and identify potential candidate biomarkers and also provide a broad overview of perturbed functions during the infection.