Research Summary

Our lab is interested in understanding the system-level architecture of genetic networks and the interplay between their design and the evolutionary process. We are combining theoretical and experimental approaches to study epistasis networks - networks that describe how perturbations (mutations or drugs) in a given biological system are combined to aggravate or alleviate the phenotypic consequences of each other. Such epistatic interactions, fundamental in a range of evolutionary processes, may also help elucidating the functional organization of complex genetic architectures. We are developing quantitative automated experimental tools based on bioluminescence and fluorescence measurements to achieve en mass, yet very accurate, quantification of epistatic interaction networks in bacteria and yeast. Using a novel bioluminescence measurement technique, we have performed a systematic study of epistasis between mutations and environmental stresses in Escherichia coli (Kishony & Leibler, 2003). In contrast to the perception that stresses always reduce the organism's ability to tolerate mutations, our measurements identified stresses that do the opposite - that is they alleviate the average effect of deleterious mutations. More recently, we have used the computational method of flux balance analysis (FBA) to study the epistasis network of yeast metabolism (Segre' et al, 2004). Our results show that the epistasis network posses a very special property, which we term "monochromaticity", whereby functional gene modules interact with each other with purely aggravating or purely alleviating epistatic links. This property extends the concept of epistasis from the gene-gene level to the system level. The new definition for identifying functional modules is implemented in a classification algorithm that we developed - the Prism algorithm.