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The CU School of Medicine is top-ranked in primary care, pediatrics and family and rural medicine. We offer degrees in doctor of medicine, physical therapy, physician assistant, medical science in anesthesiology, genetic counseling, modern human anatomy.

Molecular Biology Program
 

Mark Johnston, Professor and Chair

Ph.D. (1980), University of California, Berkeley


 

 

 

 

Contact Info:

Molecular Biology
University of Colorado

Mark Johnston, Ph.D.  Research One South
(RC1-South), Room 10100
Mark.Johnston@ucdenver.edu Phone: 303-724-3203

 

Glucose sensing and signaling in yeasts

Glucose fuels life. It is the preferred carbon and energy source of most cells and the only source for some cells (e.g., brain cells). Because of this, cells have evolved sophisticated mechanisms for sensing glucose and responding to it appropriately. This is especially apparent in the yeast S. cerevisiae, which has several highly evolved regulatory mechanisms for sensing and utilizing the widely varying amounts of glucose it encounters during its lifetime. These regulatory mechanisms determine the distinctive fermentative metabolism of yeast, a lifestyle it shares with many kinds of tumor cells, and which humans have long exploited for production of food (bread) and my favorite beverage (beer). Our long-term goal is to understand how yeast cells sense and respond to glucose.

 

 

 

Comparative and Functional Genomics

A true understanding of cellular function will require knowledge of how the cell integrates many signals into its regulatory network and responds with a coordinated output. An important piece of this puzzle is identification of the proteins that regulate gene expression and the DNA sequences they recognize. We can identify potential regulatory sequences by comparative genomics and we can test these hypotheses with functional genomics. We are developing and implementing high throughput genetic and biochemical strategies for this purpose. Armed with the catalogue of regulatory proteins and their binding sites, we expect to be able to contribute to a comprehensive understanding of the regulatory network of this reference eukaryotic cell. This project offers opportunities to couple training in computational biology with experimental work.

 

 

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