Modeling the transcriptional regulatory network that controls the early hypoxic response in Candida albicans

Eukaryot Cell. 2014 May;13(5):675-90. doi: 10.1128/EC.00292-13. Epub 2014 Mar 28.

Abstract

We determined the changes in transcriptional profiles that occur in the first hour following the transfer of Candida albicans to hypoxic growth conditions. The impressive speed of this response is not compatible with current models of fungal adaptation to hypoxia that depend on the depletion of sterol and heme. Functional analysis using Gene Set Enrichment Analysis (GSEA) identified the Sit4 phosphatase, Ccr4 mRNA deacetylase, and Sko1 transcription factor (TF) as potential regulators of the early hypoxic response. Cells mutated in these and other regulators exhibit a delay in their transcriptional responses to hypoxia. Promoter occupancy data for 29 TFs were combined with the transcriptional profiles of 3,111 in vivo target genes in a Network Component Analysis (NCA) to produce a model of the dynamic and highly interconnected TF network that controls this process. With data from the TF network obtained from a variety of sources, we generated an edge and node model that was capable of separating many of the hypoxia-upregulated and -downregulated genes. Upregulated genes are centered on Tye7, Upc2, and Mrr1, which are associated with many of the gene promoters that exhibit the strongest activations. The connectivity of the model illustrates the high redundancy of this response system and the challenges that lie in determining the individual contributions of specific TFs. Finally, treating cells with an inhibitor of the oxidative phosphorylation chain mimics most of the early hypoxic profile, which suggests that this response may be initiated by a drop in ATP production.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Candida albicans / genetics*
  • Candida albicans / metabolism
  • Fungal Proteins / genetics
  • Fungal Proteins / metabolism
  • Gene Expression Regulation, Fungal*
  • Gene Regulatory Networks*
  • Models, Genetic*
  • Oxidative Phosphorylation
  • Oxygen / metabolism*
  • Transcription Factors / genetics
  • Transcription Factors / metabolism

Substances

  • Fungal Proteins
  • Transcription Factors
  • Oxygen