Chris Hittinger

Credentials: Genetics Department

Position title: Evolution of carbon-responsive gene networks, yeast biodiversity, industrial brewing and biofuel applications

Email: cthittinger@wisc.edu

Address:
Carbon metabolism is the energy superhighway of life. We study the diversity and evolution of yeast carbon metabolism, which is controlled by a complex system of interacting genes that respond to different carbon sources and determine the organism’s energy-use strategy. Some yeasts readily ferment sugars into ethanol, even in the presence of oxygen, but most organisms (including many yeast species) prefer respiration. The biofuel industry currently exploits the highly refined trait of aerobic fermentation or Crabtree-Warburg Effect in Saccharomyces cerevisiae to produce ethanol. However, the yeasts currently in use are not able to convert some common sugars like xylose into ethanol efficiently enough to compete in the energy market. By understanding how evolution has sculpted and rewired yeast gene networks to meet their different ecological needs, we can better determine how to engineer complex biological systems to meet our energy needs.

Since carbon-utilization traits are highly variable in yeast, both within and between species, they make an excellent model for understanding how the gene networks that control them have changed in response to recent selection and over the long arc of evolution. Our research uses next-generation sequencing, precise manipulation of yeast gene networks, functional genomics, and evolutionary genomics to study:

1. Evolution of aerobic fermentation (an unusual, derived trait that Saccharomyces yeasts share with some cancer cells and that is exploited by the brewing, wine, and biofuel industries).
2. Utilization of alternative and novel carbon sources (like galactose and xylose).
3. Rewiring of transcriptional regulatory networks.
4. How variation in gene networks is maintained and evolves.
5. Yeast biodiversity, ecology, and evolution.
6. Developing next-generation sequencing methods for non-model systems.