Identifying mechanisms of apoptotic pore formation with programmatic ensemble modeling

Mitochondrial outer membrane permeabilization is a key step in the apoptotic cell death program, regulating life-death decisions in response to cytotoxic drugs and other forms of cell stress. In this thesis I use mathematical modeling of a reconstituted biochemical system to identify and integrate mechanisms of apoptotic pore formation. A key bottleneck in using mathematical models to characterize mechanisms has been the difficulty of efficiently creating and revising alternative models and evaluating them against data. This problem is addressed through the use of a software framework, PySB, that allows ensembles of models to be transparently described using tools and approaches from computer programming. These alternative hypotheses can then be evaluated against data using methods from Bayesian statistics for discrimination of models with varying numbers of (possibly non-identifiable) parameters. Using this framework, calibration of a set of models to in vitro kinetic measurements of the membrane insertion of Bax identifies a conformational intermediate associated with BH3-only:Bax complex formation and membrane association but not pore formation. Functional measurements of Bax point mutants from tumors show that the pore formation process can be blocked at the transition into or out of this intermediate, preventing mitochondrial permeabilization. In another study, model-based analysis of Bax insertion and permeabilization kinetics across a range of BH3-only, Bax, and liposome concentrations reveals the context-dependence of the mechanisms regulating pore formation. Bax recruitment is shown to depend on liposome concentration kinetically but not stoichiometrically, whereas cBid recruitment is shown to be limited at high cBid:liposome concentrations. I show that Bax distribution among liposomes is dependent on the presence of pre-existing pores, and that pores grow to include large numbers of Bax monomers but have a minimum size of four subunits. More generally, these studies serve as examples of how ensemble modeling can be used to integrate information about complex mechanisms from disparate sets of experimental observations.