Grant: Foundation Grant

Automated Imaging; Cell Cycle Regulation; Functional Genomics; Gene Expression; Genetic Interactions; Genetic Networks; Molecular Biology; Phenomics; Systems Biology; Yeast Genomics

<html> <body> <p>The ultimate goal of my Foundation Grant is to couple technological innovation with cutting-edge molecular and computational biology to generate a comprehensive and integrated view of the eukaryotic cell. We exploit the budding yeast system to produce quantitative data that yield the spatio-temporal resolution of dynamic biological processes required to model complex systems. Our projects will produce a rich view of the cell, allowing us to discover unanticipated connections between biological pathways, many of which are relevant to human disease.<br> We have five broad aims:<br> <b>Aim 1. Phenomics of subcellular morphology</b>. We implemented two experimental pipelines that combine array-based genetics and automated microscopy for quantitative cell biological screens. Our first pipeline enables the introduction of fluorescent markers of subcellular compartments of interest into genome-wide yeast mutant collections. We plan to produce comprehensive cell biological datasets that will reveal all genes that influence the function of fundamental cell compartments and structures in a model eukaryotic cell.<br> <b>Aim 2. Quantitative cell biological analysis of the proteome.</b> Our second phenomics pipeline involves a high-content screening approach designed to rapidly survey proteome dynamics in living cells, and to define proteome flux using a computational image-based method. We will assess proteome response to an array of genetic and environmental perturbations, as well as during important biological processes, such as cell division and aging. Our project provides a proof-of-principle for both a technical and conceptual platform that we intend to adapt to other systems.<br> <b>Aim 3. Using yeast phenomics to explore transcription networks</b>. We developed a method called Reporter Synthetic Genetic Array that automates the introduction of reporters of transcription pathways into arrays of yeast mutants. We are generating a dataset covering 27 cell cycle-regulated promoters, which we have analysed to survey the effects of genetic perturbation. Integration of these data with our phenomics experiments will be used to discover new pathways regulating cell cycle progression, a process which is subverted in many diseases, notably cancer.<br> <b>Aim 4. Open Access and Generalized Cell Biology Classifiers</b>. We are developing computational methods for biological image analysis that we aim to make adaptable to a variety of datasets, including mammalian cell images. We plan to make our computational systems available to the community for their data analysis through a web interface.<br> <b>Aim 5. Comparative Phenomics</b>. We will leverage our yeast datasets to design genome-wide cell biological screens in mammalian cells. In general, we aim to continue to incorporate a full-genome cross-species approach into our research program, to maximize the impact of our results and to reveal conserved aspects of eukaryotic cell biology.<br> <br> Our core expertise in yeast functional genomics, and the infrastructure available for combined automated genetics and microscopy, is arguably unparalleled internationally. The biomedical research environment is changing at a remarkable pace, which means training environments must also be dynamic and responsive to the availability of new technologies and ideas. I aspire to provide an inspiring training program that stresses technological innovation and provides trainees with a broad appreciation of the scientific process and the foundation to achieve their career goals.</p> </body> </html>