Network analysis of hyphae forming proteins in Candida albicans identifies important proteins responsible for pathovirulence in the organism

Abstract

Candida albicans causes two types of major infections in humans: superficial infections, such as skin and mucosal infection, and life-threatening systemic infections, like airway and catheter-related blood stream infections. It is a polymorphic fungus with two distinct forms (yeast and hyphal) and the morphological plasticity is strongly associated with many disease causing proteins. In this study, 137 hyphae associated proteins from Candida albicans (C. albicans) were collected from different sources to create a Protein-Protein Interaction (PPI) network. Out of these, we identified 18 hub proteins (Hog1, Hsp90, Cyr1, Cdc28, Pkc1, Cla4, Cdc42, Tpk1, Act1, Pbs2, Bem1, Tpk2, Ras1, Cdc24, Rim101, Cdc11, Cdc10 and Cln3) that were the most important ones in hyphae development. Ontology and functional enrichment analysis of these proteins could categorize these hyphae associated proteins into groups like signal transduction, kinase activity, biofilm formation, filamentous growth, MAPK signaling etc. Functional annotation analysis of these proteins showed that the protein kinase activity to be essential for hyphae formation in Candida. Additionally, most of the proteins from the network were predicted to be localized on cell surface or periphery, suggesting them as the main protagonists in inducing infections within the host. The complex hyphae formation phenomenon of C. albicans is an attractive target for exploitation to develop new antifungals and anti-virulence strategies to combat C. albicans infections. We further tried to characterize few of the most crucial proteins, especially the kinases by their sequence and structural prospects. Therefore, through this article an attempt to understand the hyphae forming protein network analysis has been made to unravel and elucidate the complex pathogenesis processes with the principal aim of systems biological research involving novel Bioinformatics strategies to combat fungal infections.