Signaling Pathways & Transcriptional Regulation in Growth Control and Metabolism
Our laboratory is conducting basic research on the mechanisms of eukaryotic transcriptional regulation in response to nutrients and environmental and cellular stress. We are especially interested in defining the signaling pathways and the mechanisms that regulate transcription of ribosomal components and transfer RNAs since these processes are critically important for controlling cell growth. Deregulation of cell growth control is widely recognized as a key event in cell transformation and tumorigenesis and is relevant to a broad range of human diseases. In addition, as the synthesis of new protein synthetic machinery constitutes >85% of nuclear gene transcription in growing cell populations, the tight coordinate control of this process, which involves all three nuclear RNA polymerases, is considered to be critical for metabolic economy and ultimately for cell survival. Our research programs span genetics, molecular biology, biochemistry and structural biology and utilize budding yeast, mammalian cells and mice as model experimental systems. Much of our current focus is on Maf1, a structurally and functionally novel protein that integrates the outputs of diverse signaling pathways and regulates transcription by all three nuclear RNA polymerases. Maf1 is also being studied because of its potential role as a tumor suppressor and as a regulator of metabolism. The conservation of Maf1 along with its downstream transcriptional targets and the signaling pathways that regulate Maf1 function facilitates the reciprocal translation of knowledge between yeast and mammalian systems and thereby promotes new discoveries.
Genetic Arrays, Gene Networks and Functional Genomics
Synthetic genetic array analysis and other systematic genome-wide genetic approaches such as synthetic dosage lethality and suppression are being applied using a first-of-its-kind robot to produce and replicate high density arrays of yeast. This technology enables the mapping of genetic interaction networks, defines the function of genes and establishes functional relationships between biochemical pathways. These genetic array-based approaches are being applied to a range of biological processes including transcriptional regulation as described above. The robot also serves as a resource to other researchers at AECOM and elsewhere who are working in yeast or in mammalian systems on genes that have homologs in yeast. The integration of genetic interaction data with other large scale datasets such as DNA microarray, ChIP-sequencing and protein-protein interaction data is used to inform testable hypotheses of the systems level behavior of genes and their products.
More Information About Dr. Ian Willis
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Albert Einstein College of Medicine
Jack and Pearl Resnick Campus
1300 Morris Park Avenue
Forchheimer Building, Room 316
Bronx, NY 10461