A Bridging Centrality Plugin for GEPHI and a Case Study for Mycobacterium Tuberculosis H37Rv

Area of Science:

• Graph theory and network analysis
• Computational biology and bioinformatics
• Systems biology

Background:

• Bridging Centrality (BriCe) is a valuable metric for identifying nodes that connect distinct clusters within networks.
• Existing implementations of BriCe were not readily available for popular graph analysis software like GEPHI.
• A need existed for an accessible tool to apply BriCe analysis in graph-based studies.

Purpose of the Study:

• To introduce and provide an open-source Bridging Centrality (BriCe) plugin for the GEPHI software.
• To offer a user-friendly tool for analyzing complex networks and uncovering bridging nodes.
• To demonstrate the utility of the BriCe plugin through a biological network analysis.

Main Methods:

• Development of an open-source Bridging Centrality (BriCe) plugin integrated directly into the GEPHI software interface.
• Application of the BriCe plugin to analyze the protein-protein interaction network of Mycobacterium tuberculosis H37Rv.
• Integration of predicted subcellular localization data with BriCe values for biological interpretation.

Main Results:

• Successful implementation and release of the BriCe plugin for GEPHI, requiring no separate installation.
• Identification of proteins with high BriCe values in the Mycobacterium tuberculosis network.
• Formulation of a novel hypothesis linking glycosyltransferase proteins and the type VII Secretion System in lipopolysaccharide export, supported by BriCe analysis.

Conclusions:

• The BriCe plugin for GEPHI provides an accessible and effective tool for network analysis.
• The plugin facilitates the discovery of novel biological insights by identifying critical bridging elements in complex networks.
• The study highlights the potential of BriCe analysis in generating new hypotheses in systems biology, exemplified by the Mycobacterium tuberculosis case study.