Protein interaction probability landscapes for yeast replicative aging

Abstract

We proposed a novel probability landscape approach to map the systems-level profile changes of gene networks during replicative aging in Saccharomyces cerevisiae. This approach enabled us to apply quasi-potentials, the negative logarithm of the probabilities, to calibrate the elevation of the landscapes with young cells as a reference state. Our approach detected opposite landscape changes based on protein abundances from transcript levels, especially for intra-essential gene interactions. We showed that essential proteins play different roles from hub proteins on the age-dependent landscapes. We verified that hub proteins tend to avoid other hub proteins, but essential proteins are attractive to other essential proteins. Overall, we showed that the probability landscape is promising for inferring network profile change during aging and that the essential hub proteins may play an important role in the uncoupling between protein and transcript levels during replicative aging.