A Unified Model of Gene Regulatory Circuit Evolution

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DESCRIPTION (provided by applicant): Cells control the timing and expression levels of their genes using special regulatory genes that interact in complex circuits to activate or repress the transcription of protein-coding DNA. We have little understanding of how complex transcriptional circuits evolve. The goal of this project is to combine multiple approaches - genomics, biochemistry, molecular evolution, ancestral reconstruction, and computational modeling - to learn the evolutionary mechanisms underlying complex regulatory circuits. The applicant, Dr. Victor Hanson-Smith, will use the yeast species Candida albicans as a model organism for studying this problem. C. albicans form surface-associated biofilms on implanted medical devices in humans; device-associated biofilms serve as reservoirs for chronic infection and life-threatening illness. C. albicans control biofilm formation using a complex circuit with six master-regulator genes and thousands of downstream target genes. It is not known how biofilm formation evolved, or if the C. albicans biofilm network is one evolutionary solution among many alternatives. Dr. Hanson-Smith will study the evolution of the biofilm gene circuit using a new quantitative model that incorporates unprecedented detail about gene regulation. His approach is to learn empirically- derived parameter values for this model from molecular experimentation in C. albicans, and then use simulation studies to test models for the evolution of biofilm formation. Dr. Hanson-Smith's approach differs from many other types of evolutionary simulations as it is based on real properties of the relevant molecules involved rather the abstract parameters of gene regulation. Since this is a F32 training award, a major component of this project is the training of Dr. Hanson-Smith in the techniques of genome sequencing and assaying gene expression levels. At the end of this project, Dr. Hanson-Smith will have received outstanding training in the molecular systems governing gene regulation, and therefore - combined with his computational background -- he will be well positioned to establish and direct his own research lab. Scientifically, this project will shed light on the evolutionary pathway by which C. albicans acquired biofilm formation; it may also reveal novel ways of controlling biofilm formation in the clinic, and general principles of how future pathogens might be expected to evolve. More broadly, this project will provide a framework for understanding, and even predicting, the types of evolutionary trajectories that lead to the development of complex physiological traits across the tree of life.