molecular, cellular and genetic analysis of cell structure and division in eukaryotes
Michael Snyder, Ph.D.

Michael Snyder, Ph.D.

Lewis B. Cullman Professor of Molecular, Cellular and Developmental Biology and Professor of Molecular Biophysics and Biochemistry;
Director of the Yale Center for Genomics and Proteomics
Phone (203) 432 6139; Fax (203) 432 6161
Lab Web site

B.A. University of Rochester 1977; Ph.D. California Institute of Technology 1983

Probing of Yeast Protein Microarrays
Probing of Yeast Protein Microarrays: A. GST-fused yeast proteins overexpressed in yeast were purified using glutathione agarose, and spotted in duplicates on glass slides. To assess the quality of printing a slide was probed with a-GST antibody, followed by a fluorescent secondary antibody; B & C. Protein microarray probed with dsDNA fluorescent probes containing a WT Rap1 DNA motif (B) and a mutated Rap1 DNA motif (C). A specific interaction with Rap1 protein is detected when a WT DNA probe is used, whereas none is detected when the mutated probe is applied (yellow underlined spots in B & C respectively).

Hierarchical clustering of microarray data
Hierarchical clustering of microarray data Each gene is represented by 48 individual hybridization measurements or probe intensities across the five tissues. The probe intensities were normalized within a chip to the median intensity of all probes on that array (intra-chip normalization). The median value of the 48 normalized probe intensities (i.e. the global median) thus serves as a reference to compare the expression of each gene across experiments (inter-chip comparisons). Probe intensities above and below the global median are denoted by shades of red or blue, respectively; those at the global median are colored yellow. B) As expected, expression profiles from a given tissue clustered tightly together, whereas expression profiles across different tissues exhibited wider variation. Genes demonstrating tissue specific expression were representative of the normal physiology of the tissue in which they are expressed, thus confirming the biological accuracy of our data.

Our laboratory uses global approaches to explore protein function and dissect regulatory networks. Several of our areas of research are:

  1. Control of Cell Division and Cell Morphogenesis in Yeast
  2. Characterization of Proteomes
  3. Analysis of Regulatory Circuits in Yeast
  4. Characterization of the Human Genome
  5. Sex-specific Gene Expression in Mammals

1) Control of Cell Division and Cell Morphogenesis in Yeast. Understanding how cell cycle progression is regulated is critical for understanding how cellular events proceed in a orderly fashion. Much attention has been devoted to understanding how nuclear processes, such as DNA replication, are coordinated with cell cycle progression, but whether and how peripheral cytoskeletal events are monitored and controlled by the cell cycle machinery is not known. We have found a novel cytoskeletal checkpoint in which the organization of the septin cytoskeleton is coordinated with nuclear division. Septins are highly conserved cytoskeletal elements in involved in septation (cytokinesis). A highly conserved protein kinase cascade regulates this event. One key enzyme in this cascade is the protein kinase Hsl1 which is activated upon septin polymerization. To learn about how Hsl1 functions we using genomic approaches to identify its substrates.

2) Characterization of Proteomes. We have developed a number of novel approaches to characterize protein function in yeast and humans. A novel protein microarray technology was invented for analyzing large numbers of proteins. Nearly all yeast proteins were overexpressed and purified and deposited on a microscope slide. The chips have been used for a variety of applications including interactions with proteins, lipids, DNA and small molecules. Using this technology we have discovered that a metabolic enzyme, Arg5,6 associates with DNA to regulate gene expression in yeast. We are using this technology to develop a protein phosphorylation map for yeast. We are also extending this technology to humans as well as employing other novel methods for analyzing protein function in humans.

3) Analysis of Regulatory Circuits in Yeast. In collaboration with Dr. P. Brown (Stanford), we have developed a novel method, called chIP chip, to identify all of the targets of transcription factors. DNA is prepared from chromatin that has been immunoprecipitated with antibodies to a specific transcription factor and is used to probe a microarray of intergenic region DNA. All regions of the genome that are bound by the transcription factor are then deduced. We have been employing this methodology to dissect the transcriptional circuitry in yeast and understand how regulatory circuits evolve between related species.

4) Characterization of the Human Genome. We have constructed tiling arrays for large segments of the human genome and used these discover new coding regions and regulatory elements in the human genome. By probing the arrays with liver and placental RNAs we have discovered thousands of new transcribed segments in the human genomes. Using ChIP chip and these arrays we have mapped the binding sites of NF-KappaB, CREB and STAT1 to discover new gene targets for each of these regulatory factors. This information is being using to assemble gene regulatory networks for humans, and is expected to help us dissect the complex regulation of human gene expression during development and in disease states.

5) Sex-specific Gene Expression in Mammals. To better understand the molecular differences between adult males and females in mammals we have analyzed gene expression in kidney, liver, brain and reproductive tissues in mice and brain tissues in human. We have found little sex specific gene expression in the hypothalamus, but significant differences in gene expression in the reproductive tissues (as expected). We also found a number of differences in gene expression in male and female liver and kidney. The majority of differentially expressed genes are involved in drug metabolism and osmotic regulation; the latter is important for controlling hypertension. These results have important implications in understanding the different physiology of males and females and how they lead to different sex specific difference in human health and its control.

Selected Publications

Rinn JL, Rozowsky JS, Laurenzi IJ, Petersen PH, Zou K, Zhong W, Gerstein M, Snyder M. (2004) Major molecular differences between mammalian sexes are involved in drug metabolism & renal function. Dev Cell. 6:791-800.

Smith MG, Des Etages SG, Snyder M. (2004) Microbial synergy via an ethanol-triggered pathway. Mol Cell Biol. 24:3874-84.

Euskirchen G, Royce TE, Bertone P, Martone R, Rinn JL, Nelson FK, Sayward F, Luscombe NM, Miller P, Gerstein M, Weissman S, Snyder M. (2004) CREB binds to multiple loci on human chromosome 22. Mol Cell Biol. 24:3804-14.

Bidlingmaier S, Snyder M. (2004) Regulation of polarized growth initiation and termination cycles by the polarisome and Cdc42 regulators. J Cell Biol. 164:207-18

Extensive sex-specific expression in the kidney.
Extensive sex-specific expression in the kidney.
A) Twenty-seven genes were differentially expressed by sex in the kidney. One-quarter, 7, of these genes are drug and steroid metabolism genes. The rest are mainly comprised of osmo-regulation genes or genes with yet unresolved cellular roles. Shades of blue represent the degree to which expression in the male is lower than the female median expression level (female specific expression). Shades of red indicate the degree to which expression in the male is above the female median expression level (male specific expression). The brightness of the color represents the amount of expression. P values of differential expression between sexes are also listed. B) We independently verified the expression of 7 genes in the kidney using quantitative-real-time PCR. Each reaction was performed in triplicate. DRT represents the amount of pooled cDNA was amplified in the reaction per cycle. 100% of the randomly selected genes demonstrated the same sex-specific expression pattern observed in the microarray data.



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