Nevan J. Krogan
Functional Insights from Protein-Protein and Genetic Interaction Maps
Our research focuses on the development of tools that allow for the generation, analysis and visualization of large-scale, quantitative genetic and physical interaction maps with the ultimate goal of further understanding cell physiology. Our work has been targeted towards simpler systems (e.g. S. cerevisiae, S. pombe and E. coli) but we plan to eventually apply these approaches to multiple-cellular organisms.
In the past, we have used an affinity purification/mass spectrometry strategy to try to comprehensively define the physical interactome of S. cerevisiae. Recently developed algorithms have allowed us to define a relatively comprehensive, high-quality protein-protein interaction dataset for budding yeast. We are employing similar strategies to create protein-protein interaction maps for other organisms including S. pombe, M. tuberculosis as well as an HIV-host physical map.
However, even knowledge of the stoichiometry, affinity, and lifetime of every protein-protein interaction would not reveal the functional relationships between and within such complexes. Genetic interactions can provide functional information that is largely invisible to protein-protein interaction datasets. In collaboration with Jonathan Weissman, we have developed an approach, termed E-MAP (epistatic miniarray profile), which can provide information on genetic interactions. E-MAPs comprise comprehensive and quantitative measurements of genetic interactions between pairs of mutations from a set of genes that are functionally related. Since this analysis is quantitative, both negative (i.e. SSL) and positive interactions can be identified. Positive interactions include cases where the double mutant grows better (suppression) or no worse than the sickest single mutant. Such positive interactions would result, for example, if loss of one protein suppressed the growth defect caused by loss of a second protein or if two proteins are part of a pathway whose function is completely dependent on the presence of both components. We have used the E-MAP approach to genetically interrogate sets of genes involved in the early secretory pathway and chromosome function, which includes transcriptional regulation, DNA repair/replication and chromatid segregation. We are presently generating E-MAPs that focus on other biological processes and developing E-MAP technology for other organisms.
Finally, and most importantly, we attempt to integrate the physical and genetic interaction data in a biologically meaningful way so that hypotheses about specific biological phenomenon can be generated and ultimately tested.
Awarded as a Keck Distinguished Young Scholar, W. M. Keck Foundation, 2009-2014