Computational inference of the transcriptional regulatory network of Candida glabrata

Candida glabrata is a major cause of candidiasis and the second most frequent opportunistic yeast pathogen. Its infectious and antifungal mechanisms are globally regulated by the transcription systems of pathogenic fungi. In this study, we reconstructed the genome-scale transcriptional regulatory network (TRN) of C. glabrata, consisting of 6634 interactive relationships between 145 transcription factors and 3230 target genes, based on genomic and transcriptomic data. The C. glabrata TRN was found to have a typical topological structure and significant network cohesiveness. Moreover, this network could be functionally divided into several sub-networks, including networks involving carbon, nitrogen, growth-associated metabolic profiles, stress response to acidity, hyperosmosis, peroxidation, hypoxia and virulence. Furthermore, by integrating the genome-scale metabolic model of C. glabrata, six essential metabolites and eight related enzymes were systematically selected as drug targets. Overall, elucidation of the genome-scale TRN of C. glabrata has expanded our knowledge of the contents and structures of microbial regulatory networks and improved our understanding of the regulatory behaviors of growth, metabolism and gene expression programs in response to environmental stimuli.