Experimental and Computational Methods for Identifying Death-Regulatory Genes from Chemo-Genetic Profiles

Abstract

A common approach to understanding how drugs induce their therapeutic effect is identifying the genetic determinants of drug sensitivity. This can be achieved following systematic loss- or gain-of-function genetic perturbations with CRISPR/Cas9. Because these “chemo-genetic profiles” are generally performed in a pooled format, inference of gene function is subject to several confounding influences, including variation in growth rates between clones or variation in the degree of coordination between growth and death. To overcome these issues, we developed an analysis method called MEDUSA (Method for Evaluating Death Using a Simulation-assisted Approach). MEDUSA uses time-resolved measurements and model driven constraints to reveal the combination of growth and death rates that generated the drug-treated clonal abundance. We find that MEDUSA is uniquely effective at identifying death regulatory genes, and we apply MEDUSA to determine how DNA damage-induced lethality varies in the presence and absence of p53. We find that loss of p53 switches the mechanism of DNA damage-induced death from apoptosis to a non-apoptotic form of death called MPT-driven necrosis. We find that activation of MPT by DNA damage requires high respiration, and that cell death can be exacerbated by modulating NAD+ in p53-deficient cells. These findings demonstrate the accuracy and utility of MEDUSA, both for determining the genetic dependencies of lethality and for revealing opportunities to promote the lethality of chemotherapies in a cancer specific manner.