GSE60398
Model-driven mapping of transcriptional networks reveals the circuitry and dynamics of virulence regulation
Purpose: Key steps in understanding a biological process include identifying genes that are involved and determining how they are regulated. We developed a novel method for identifying TFs involved in a specific process and used it to map regulation of the key virulence factor of Cryptococcus neoformans, its capsule. Results: The map, built from expression profiles of 41 TF mutants, includes 20 TFs not previously known to regulate virulence attributes. It also reveals a hierarchy comprising executive, mid-level, and “foreman” TFs. When grouped by temporal expression pattern, these TFs explain much of the transcriptional dynamics of capsule induction. Phenotypic analysis of 41 TF deletion mutants revealed complex relationships among virulence factors and virulence in mice. Conclusions: These data resources and analyses provide the first integrated, systems level view of capsule regulation and biosynthesis. Our methods dramatically improve the efficiency with which transcriptional networks can be analyzed, making genomic approaches accessible to labs focused on specific physiological processes. Overall design: A total of 288 expression profiles were generated by RNA-Seq analysis of Mutant and wildtype cells grown in capsule inducing conditions for 90 minutes. In addition, 3 replicate expression profiles were generated for wildtype cells grown in : a capsule non-inducing condition, a capsule inducing condition for 180 minutes, a capsule inducing condition for 480 minutes, and a capsule inducing condition for 1440 minutes.  In addition, ChIP-seq of NRG1(CNAG_05222) in capsule inducing conditions, and USV101(CNAG_05420) in both capsule inducing and non-inducing conditions were generated.