Research Interests:

Our lab is interested in understanding the system-level architecture of genetic networks and the interplay between their design and the evolutionary process.

Gene and Drug Networks
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, also helps elucidate 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. In a systematic study of epistasis between mutations and environmental stresses in Escherichia coli we found that, in contrast to the perception that stress generally reduces the organism's ability to tolerate mutations, there exist 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. This new definition for identifying functional modules is implemented in a classification algorithm that we developed - the Prism algorithm. In drug networks, the same conceptual method could be applied to cluster drugs by their mechanism of actions based only on the properties of their mutual interactions.

Evolutionary Adaptation
Our evolution research is concentrating on adaptation in asexual organisms. We have demonstrated a simple equivalence principle which, at the limit of high mutation rates and population size, provides a projection of the complex adaptation process onto a simple two-dimensional parameter space of an effective mutational size and an effective mutational rate.

Selected Publications:

R. Kishony and S. Leibler (2003). Environmental stresses can alleviate the average deleterious effect of mutations. Journal of Biology 2, p. 14.

D. Segrè, A. DeLuna, G. M. Church, R. Kishony (2005). Modular epistasis in yeast metabolism. Nature Genetics 3, 77.

M. Hegreness, N. Shoresh, D. Hartl, R. Kishony (2006). An Equivalence Principle for the Incorporation of Favorable Mutations in Asexual Populations. Science 311, p. 1615.

P. Yeh, A. Tschumi, R. Kishony (2006). Functional classification of drugs by properties of their pair-wise interactions. Nature Genetics 38, 489.