Reliable Protein Interactomes for Infectious Diseases

Participants: Michal Wozniak, Chern Han Yong, Hufeng Zhou, Jinyan Li, Jerzy Tiuryn, Limsoon Wong.


There is a critical need to address the emergence of drug resistant varieties of pathogens for several infectious diseases. For example, drug-resistant tuberculosis has continued to spread internationally and is now approaching critical proportions. Approaches to counter drug resistance have so far achieved limited success. It has been proposed that this lack of success is due to a lack of understanding of how resistance emerges in bacterial upon drug treatment and that a systems-level analysis of the proteins and interactions involved is essential to gaining insights into routes required for drug resistance.

The premise of such an analysis is the existence of a comprehensive protein interactome of the relevant pathogen. For example, let us assume that a comprehensive protein interactome of Mycobacterium tuberculosis is available. Then one could identify a minimal set of proteins (or protein interactions) whose inhibition would disconnect all essential pathways in M. tuberculosis. Alternatively, one could trace the interaction route of the known targets of a drug to various effluxpump proteins and drug-modifying enzyme proteins.


This project proposes a system-based approach to analyze and counter drug resistance in pathogens, with M. tuberculosis (MTB) as a test case. The following 4 issues are to be dealt with in the course of the project:
  1. Unreliability of MTB interactome maps.
  2. Paucity of MTB interactome maps.
  3. Prediction of novel protein interactions and protein complexes in MTB.
  4. Identification candidate mutations and pathways to drug resistance in MTB.

Wrt 1., we have developed a methodology to assess the reliability of protein interactome maps and have applied it to the first high-throughput protein-protein interaction dataset produced on MTB. In the process, we have shown that this experimental dataset is very unreliable and should be used by researchers with extreme caution. We have further identified reliable subsets that can be used safely.

Wrt 2., we have developed a methodology to unify pathway and protein interaction data from multiple heterogeneous distributed data sources, and have used it to build a database (IntPath) of integrated pathway information for MTB and several other model organisms. IntPath is one of the most comprehensive unified pathway resource on MTB H37rv and several other organisms.

Wrt 3., we have developed methods for predicting host-pathogen protein interaction and applied them on the human-MTB system. These methods are significantly more advanced than earlier methods. In addition, we have also made discovery and methodological development in analyzing antibody-antigen binding interfaces.

Wrt 4., we have developed methods for comparative analysis and cleansing of closely related genomes; a method for identifying mutations associated with drug resistance; and methods for identifying a minimal subset of proteins that, when inhibited, have a high likelihood to simultaneous disrupt a maximum number of pathways and complexes.

Selected Publications


Selected Presentations


This project is supported in part by two NGS scholarships (Yong: 1/09 -, Zhou: 9/09 -), a Singapore Ministry of Education Tier-2 grant MOE2009-T2-2-004 (Wozniak, Li, Wong: 4/10 - 3/13), and a Polish Ministry of Science and Higher Education grant N N301 065236 (Wozniak, Tiuryn).

Last updated: 15/1/2018, Limsoon Wong.