Evolution of the complex transcription network controlling biofilm formation in Candida species

We examine how a complex transcription network composed of seven “master” regulators and hundreds of target genes evolved over a span of approximately 70 million years. The network controls biofilm formation in several Candida species, a group of fungi that are present in humans both as constituents of the microbiota and as opportunistic pathogens. The ability to form biofilms is crucial for microbial colonization of different host niches, particularly when an implanted medical device is present. We examined and compared the network underlying biofilm formation across four Candida species (C. albicans, C. dubliniensis, C. tropicalis, and C. parapsilosis), all of which form biofilms composed of multiple cell types. To describe the salient features of the network across different species, we employed four approaches: (1) we phenotypically characterized the biofilms formed by these species using a variety of methods; (2) we knocked out — one by one — the master regulators identified in C. albicans in the four species and monitored their effect on biofilm formation; (3) we identified the target genes of 18 master regulator orthologs across the four species by performing ChIP-seq experiments; and (4) we carried out transcriptional profiling across each species during biofilm formation. Additional network information was obtained by analyzing an interspecies hybrid formed between the two most closely related species, C. albicans and C. dubliniensis. We observed two major types of changes that have occurred in the biofilm circuit since the four species last shared a common ancestor. Master regulator “substitutions” occurred over relatively long evolutionary times, resulting in different species having overlapping, but different sets of master regulators of biofilm formation. Second, massive changes in the connections between the master regulators and their target genes occurred over much shorter timescales. Both types of change are crucial to account for the structures of the biofilm networks in extant species. We believe this analysis is the first detailed, empirical description of how a complex transcription network has evolved.