People
The people in our Genome Canada funded program can be divided into three interrelated scientific groups:
Project Leader
Brenda Andrews
The Andrews lab is using functional genomics to study cell cycle transcription factor pathways and mechanisms of cell cycle regulation. In eukaryotic cells, cell division is primarily controlled in G1 phase of the cell cycle at a regulatory nexus called the restriction point or Start. Cell cycle transitions, including Start, are controlled by cyclin-dependent kinases (Cdks) whose activation requires association with regulatory subunits called cyclins. The importance of understanding Start and other cell cycle transitions is underscored by the observation that perturbations of cell cycle regulators appear to be a universal feature of cancer cells. Using a synthetic dosage suppression screen, we have produced an intriguing roster of putative kinase substrates. High through put fluorescence microscopy has also become a powerful tool in our lab to look for substrates and to map cell cycle transcription factor pathways. To this end, we are currently optimizing a screening procedure that detects changes in the steady-state levels or subcellular distribution of GFP-tagged proteins in yeast strains that harbour mutations at kinase-encoding loci. These, and other functional genomics approaches including DNA microarrays and systematic proteomics, are being applied both to specific projects in the lab and also to a larger effort to map genetic networks controlling cell cycle progression and cell polarity in yeast.
Cheryl Arrowsmith
Research in the Arrowsmith lab focuses on the structural and biochemical characterization of proteins involved in cancer pathways. The goals of our research are to understand at the molecular level the origin of protein-DNA and protein-protein interactions and how these processes are modulated by cofactors, phosphorylation and protein dynamics. We use primarily Nuclear Magnetic Resonance (NMR) Spectroscopy in conjunction with other physical and biochemical techniques to study the three-dimensional (3D) structure, dynamics and biochemical properties of proteins, protein-DNA and protein-protein complexes in solution. Knowledge of a protein's structure often illustrates the mechanism by which it recognizes other molecules, catalyzes enzymatic reactions, and how oncogenic mutations alter these functions. In addition, the structures may also form the basis for the design of drugs which can reverse the oncogenic effects of defective or overexpressed oncoproteins. We are also using structural biology as a tool in functional genomics because protein function derives directly from its 3D structure, and can often be inferred from structural data when sequence information alone is insufficient. Structural Proteomics involves the large scale, high throughput cloning, expression and structure determination (using both X-ray and NMR).
Aled Edwards
The completion and near completion of the sequencing phase of genome projects has ushered in the age of proteomics, the study of all gene products in an organism. This flood of sequence information coupled with recent advances in molecular and structural biology have led to the concept of 'structural genomics'. Research in the Edwards lab is directed to genome-scale studies of the structure and function of proteins and of protein families in model organisms. The main goal of our research is to determine three-dimensional structures, using X-ray crystallography, of protein families that can not be predicted from existing protein structure data (PDB). This approach should lead to completion of the protein folding space and elucidation of the function of these proteins. Our technological aims are to identify effective valid protein targets in sequenced genomes, develop highly parallel and cost-effective methods to clone, express and purify proteins for structural studies, create more effective crystallization screens and accelerate the 3D protein structure solving process. Our long term goal is to determine experimental structures for all proteins because subtle differences in protein structure contribute to the diversity and complexity of life. Our highly collaborative group has projects in structural proteomics, chemical proteomics, protein degradation in yeast and the proteomics of nuclear receptors in Drosophila. We also study viral liver disease using DNA microarrays.
Andrew Emili
The Emili lab is interested in comprehensive analysis of the gene products (proteins) expressed by the genomes of eukaryotic organisms using sophisticated, comprehensive, and complimentary proteomics methodologies. Our research aims to understand the function and integration of the complex biological circuitry that underlies cell growth and proliferation, with a particular focus on DNA replication, DNA repair and cell division pathways. Researchers in the Emili lab have been isolating and characterizing protein complexes using efficient affinity methods. The components of these complexes are then carefully characterized by mass spectrometry in order to provide a wiring diagram of the cell. Each of the purified complexes is being analysed by SDS-PAGE and individual bands are being identified by MALDI-TOF mass spectrometry. Isolated protein complexes are also subject to gel-free HPLC coupled tandem mass spectrometric identification of all associated proteins. The comprehensive identification and quantification of cellular proteins and their post-translational modifications by mass spectrometry will also help describe the cellular responses to mutations or extra cellular signals and will help identify functional changes arising from physiological responses to stimuli, developmental cues or disease processes.
Jack Greenblatt
The Greenblatt Lab is focusing on four distinct areas: transcriptional regulation, bacterial proteomics, human protein interactions and yeast proteomics. As part of the Proteomics Research Center, we are using cutting edge technologies such as mass spectrometry, microarray analyses and polytene chromosome immuno-localization to interrogate cellular biology. The focus and long-term objectives of the Proteomics Research Center (PRC), are to develop a fully integrated experimental framework for researchers to systematically address the complexities of protein function and cellular networks using advanced and complimentary experimental approaches and technologies. We are motivated by a common interest to analyze biological problems through a synergy of methodologies and biological perspectives. As much as possible, we aim to foster cross-communication and transfer the various research skills among all the members of collaborating laboratories, and this will obviously benefit the nascent proteomics field by providing training for a new breed of principle investigators, postdoctoral and postgraduate researchers who will disseminate these skills around the world. Today, several disciplines, in particular bioinformatics, genomics, and proteomics, are converging in efforts to annotate, exploit and extend newly-available genome sequence information. The goal of our research efforts are to increase understanding of the function(s) and relationships of the many thousands of genes and proteins present in living cells, with the implicit expectation that this understanding will lead to dramatic progress in uncovering the fundamental principles that govern biology and evolution.
Alexander Yakunin
In all sequenced genomes, a large fraction of predicted genes (up to 50% in some genomes) encodes proteins of unknown biochemical function. Many global strategies are already being used to infer function (protein-protein interaction, gene expression analysis, structural studies). As an additional approach to discover protein function, Alexander’s group has developed a series of general enzymatic assays with which to test purified unknown proteins for catalytic activity. These assays are designed to be of broad substrate specificity to enable the identification of the sub-class or sub-subclass of enzymes (esterases, phosphatases, proteases, nucleases, dehydrogenases) to which the specific protein belongs. Proteins that have detectable activity are further characterized using more specific assays. Specifically: phosphatases are screened for activity against a panel of 57 physiological substrates, phosphodiesterases/nucleases – with 10 substrates, and esterases/lipases – with 9 substrates. The spectrophotometric assays are developed for 96-well plates, can be performed quickly and require only a few micrograms of protein. Using these general assays, we have detected catalytic activity in three dozens of purified bacterial proteins produced by our structural proteomics group or our collaborators. Most of them are phosphatases, phosphodiesterases and esterases. To characterize their cellular role, we are using additional approaches (gene knock-outs, etc) as well as collaborations with established laboratories.
Brenda Andrews
The Andrews lab is using functional genomics to study cell cycle transcription factor pathways and mechanisms of cell cycle regulation. In eukaryotic cells, cell division is primarily controlled in G1 phase of the cell cycle at a regulatory nexus called the restriction point or Start. Cell cycle transitions, including Start, are controlled by cyclin-dependent kinases (Cdks) whose activation requires association with regulatory subunits called cyclins. The importance of understanding Start and other cell cycle transitions is underscored by the observation that perturbations of cell cycle regulators appear to be a universal feature of cancer cells. Using a synthetic dosage suppression screen, we have produced an intriguing roster of putative kinase substrates. High through put fluorescence microscopy has also become a powerful tool in our lab to look for substrates and to map cell cycle transcription factor pathways. To this end, we are currently optimizing a screening procedure that detects changes in the steady-state levels or subcellular distribution of GFP-tagged proteins in yeast strains that harbour mutations at kinase-encoding loci. These, and other functional genomics approaches including DNA microarrays and systematic proteomics, are being applied both to specific projects in the lab and also to a larger effort to map genetic networks controlling cell cycle progression and cell polarity in yeast.
Charles Boone
The Boone lab is focused on the development and application of functional genomics techniques to address a number of biological problems. To this end, we are developing and applying functional genomics approaches for mapping genetic, chemical-genetic, protein-protein interactions using a yeast model system. The ultimate goal is to place all yeast genes and their corresponding products in a functional network. Systematic phenotypic and genetic analysis with the yeast S. cerevisiae deletion mutant collection has proven incredibly powerful as it enables researchers to examine mutations in each gene for specific phenotypes comprehensively. To facilitate a functional genomics approach to cell biological problems, we are also combining our automated form of yeast genetics, SGA methodology with a powerful cell biological screening system, the High Throughput Microplate Imaging System (HTMIS). The integration of SGA technology with HTMIS should increase the resolution of the SGA system such that all double mutants are examined for numerous morphological synergistic phenotypes, not just the rare synthetic lethal combinations, enabling the detailed molecular investigation of numerous biological processes. Genomic approaches in yeast have also pioneered a new era in biology and they have enable technologies with a direct application to the field of natural/synthetic chemical products. We are applying yeast chemical-genetics approaches to gain insights into the mechanism of drug action. Perhaps the most powerful approach is the chemical-genetic information obtained from scoring each of the ~5000 viable deletion mutant strains for sensitivity to a specific compound using a parallel growth assay and barcode microarray readout.
Guri Giaever
The primary interests of the Giaever lab are to screen known and novel antiproliferatives to understand precise mechanisms of drug action, identify potential new chemotherapeutics targets and to identify an inhibitory chemical probe for as many essential gene products as possible for use as rapid, reversible laboratory tools. To accomplish these goals we are employing a validated chemogenomic assay, HaploInsufficiency Profiling (HIP), based on our observation that lowering the dosage of a single gene from two copies to one copy in diploid yeast results in a heterozygote that is sensitized to any compound that acts on the product of this gene. In our assay, a complete collection of heterozygous deletion strains is pooled, grown in the presence of compound and sampled as a function of time. Molecular bar-codes incorporated into each strain allow parallel analysis and relative strain fitness to be quantitatively assessed by hybridization to oligonucleotide arrays. Strains most sensitive to drug often carry deletions in genes that interact directly with the test compounds and inhibit cell proliferation. In this way, all ~6,000 yeast proteins are screened simultaneously. This approach is distinguished from other genomic approaches because 1) it is a cellular in vivo assay and 2) it allows ranking of genes most important for survival to compound that can be rapidly confirmed biologically. The results of this assay typically identify the drug target. Moreover, because such probes act in a reversible fashion, they can be employed to further understand the effects of inhibiting essential biological pathways. Once the primary mechanism has been uncovered, further pathway specific synthetic genetic effects of a particular compound on a pathway can be uncovered using HOP (Homozygous deletion Profiling) screening. By assessing the effects of these chemical probes on the nonessential fraction of the genome, we will uncover genes that buffer inhibition of the target pathway and that will ultimately assist in deconvolution of involved pathways.
Jack Greenblatt
The Greenblatt Lab is focusing on four distinct areas: transcriptional regulation, bacterial proteomics, human protein interactions and yeast proteomics. As part of the Proteomics Research Center, we are using cutting edge technologies such as mass spectrometry, microarray analyses and polytene chromosome immuno-localization to interrogate cellular biology. The focus and long-term objectives of the Proteomics Research Center (PRC), are to develop a fully integrated experimental framework for researchers to systematically address the complexities of protein function and cellular networks using advanced and complimentary experimental approaches and technologies. We are motivated by a common interest to analyze biological problems through a synergy of methodologies and biological perspectives. As much as possible, we aim to foster cross-communication and transfer the various research skills among all the members of collaborating laboratories, and this will obviously benefit the nascent proteomics field by providing training for a new breed of principle investigators, postdoctoral and postgraduate researchers who will disseminate these skills around the world. Today, several disciplines, in particular bioinformatics, genomics, and proteomics, are converging in efforts to annotate, exploit and extend newly-available genome sequence information. The goal of our research efforts are to increase understanding of the function(s) and relationships of the many thousands of genes and proteins present in living cells, with the implicit expectation that this understanding will lead to dramatic progress in uncovering the fundamental principles that govern biology and evolution.
Timothy Hughes
In virtually all organisms, the genome functions as a highly-encoded self-extracting program. The combined action of the gene products not only directs the molecular reactions that form the organism, but also serves to interpret the genome itself. In the human genome alone, genome sequencing and comparative genomics have revealed thousands of new genes, including hundreds of potential DNA-binding proteins, and roughly a million conserved noncoding elements with no known function, many of which are likely to be regulatory features. These observations underscore the complexity of gene regulation, but also provide a starting point for describing how genomes function on a global basis to orchestrate biology at the molecular and cellular level. We are employing diverse technologies to identify, study and map properties and relationships among individual functional units in the genome. Projects in the lab encompass gene expression studies in organisms ranging from yeast to mouse, experimental identification of functional units in genome sequence, global analysis of DNA binding and RNA processing activities, and genome-scale characterization of proteins via the construction of extensive reagent collections. Most of our work utilizes microarray technology and involves computational data analysis.
Igor Stagljar
The Stagljar lab uses a combination of molecular, cellular, genetic, genomic and proteomic approaches to study the function of many yeast and human membrane proteins as well as proteins involved in the maintenance of genome stability in humans. Current projects within the lab focus on four critical areas. The membrane protein interactome project involves the development of a yeast-based genetic technology for the in vivo detection of membrane protein interactions, called the split-ubiquitin membrane yeast two-hybrid (MYTH) system. Our current efforts are directed to identify, characterize and perturb focused collections of membrane proteins in an effort to understand complex biological processes such as cell signaling and membrane transportl. Protein interaction technologies in our lab include the development of a novel assay, called Cross-and-Capture, that allows a rapid analysis of protein-protein interactions by using differentially tagged yeast arrays in the two haploid yeast mating types. Another goal of our research is to identify novel drugs against the selected P. aeruginosa proteins using the newly developed yeast-based phenotypic assays, and to examine the biological activities of these drugs in vivo and in vitro. Our approach is comprised of a rapid cloning assay for the transfer of selected P. aeruginosa ORFs into yeast expression vector under control of the inducible promoter, a robotics-based method to select for P. aeruginosa genes causing the growth inhibition in yeast and a chemical genomics approach in which yeast strains expressing the"leathal" P. aeruginosa ORFs are used to screen for chemical compounds that relieve the lethality caused by the heterologous expression of a particular P. aeruginosa ORF. These kinds of assays (which in principle could be derived from any set of heterologous genes, including man or any other human pathogens) allow identification of small molecules as potential compounds for drug development and as tools to better understand gene function of a certain organism. Finally, our lab is studying the involvement of DNA helicases in the maintenance of genome stablility. Specifically, we are studying the RecQ family of helicases using human cells as a model to characterize their roles in preserving the genome stability and onset of cancer.
Gary Bader
The Bader lab is studying the organization and evolution of biological systems using computational biology and bioinformatics techniques. We seek to accurately predict links, such as specific molecular interactions, in eukaryotic cell signaling systems using comprehensive genomics data like genome sequence and transcript profiles. We are interested to find how these links are rewired by mutations to cause disease. This work is supported through the development of open-source biological pathway and network databases and visualization and analysis software.
Michael Brudno
Research in the Brudno lab centers around the development of efficient computational approaches for the analysis of large biological datasets. Biological datasets can be extremely diverse, and vary depending on experimental approach; similarly, they are often noisy, and the exact nature of the noise varies from experiment to experiment. While a one-size-fits-all solution may be the second best approach to solving several biological problems, we believe that the best method for a particular problem will usually be specific. Most of our previous work has centred on comparisons of genomic sequences in order to understand the evolution of a genome and to elucidate the functional elements within genomic sequences. In the future, we look forward to applying innovative algorithmic approaches to analyzing genomes as well as other types of biological data.
Quaid Morris
The focus of research in the Morris lab is the development and application of adaptive algorithms for analysing large-scale biological datasets. We are currently working in the areas of gene function prediction and modeling gene regulatory networks. Using supervised learning algorithms to predict the biological function of a gene based on its expression profile, we have predicted the function of essential and non-essential yeast genes. Moreover, we have recently shown that this approach can be used to make precise predictions about gene function in mammals and, in doing so, we have assigned annotations to more than a thousand unannotated mouse genes. We have used a similar approach to assign functions to novel mouse microRNAs and we are currently working on improving the accuracy and coverage of functional predictions using probabilistic generative models which model the dependencies between GO-BP categories and the uncertainty in the gene expression measurements. Projects in our laboratory also include the use of principled statistical models to closely examine microarray expression data, the development of a microarray-based system to quantify alternative splicing levels on a genome-wide scale as well as probablistic algorithms to detect cis-acting elements that transcription and splicing factors bind to in yeast and mouse. Finally, we are doing a large-scale exon tiling microarray study to detect new mouse genes.
Zhaolei Zhang
The Zhang lab is currently pursuing a variety of bioinformatics and genomics topics including comparative genomics, evolutionary bioinformatics, analysis of regulatory elements and cellular databases. First, we are interested in using computational and experimental approaches to identify and characterize functional sequences and motifs in the intergenic regions of the genome. We are particularly interested in the primate-specific noncoding RNA transcripts, i.e. those that only arose after the human-mouse split. The recent whole-genome tiling microarray experiments have revealed many of these candidate transcript regions in the human genome. Using these datasets as starting point, we applied a number of filtering procedures such as probability of forming stable secondary structures to derive a set of candidate regions in the human genome. The next step is to re-sequence their synthetic homologs in other primate species, so as to reveal their evolutionary history and shed lights on their cellular function. Second, we are interested in studying the evolutionary history of genes, genomes, transcriptomes, and biological networks. Having the advantage of working closely with colleagues who are producing large amount of genomics and proteomics data, we hope to be able to elucidate some of the fundamental questions in evolutionary biology and genomics. Third, we are developing new algorithms to improve existing TF binding sites prediction methods. Specifically, we are trying to characterize structural information and positional co-variations that are hidden in the traditional Positional Specific Weight Matrix (PSWM) approaches. We demonstrated that the structural properties of the double-helix as shown below are important for DNA-protein recognition and likely are the “hidden code” for the degenerate weight matrices. Finally, we are developing a database (CellFrame) to collect cell perturbation data from the literature. We will apply existing tools and also develop our own method to analyze these data and reconstruct cellular pathways.