Machine vision based stochastic analysis of cancer cell mitochondrial dysfunction induced by a BH3 domain

Abstract

We have developed a versatile and rapid method for the quantitative estimation of cell death kinetics, following direct single-shot activation of the mitochondrial death pathway by a cell permeable BH3 activator peptide (D-R(8)BH3(BID)). This approach employs timelapse epifluorescent imaging of live cells and a machine- vision based feature extraction algorithm, to measure unidirectional stochastic transitions associated with mitochondrial inner membrane potential depolarization and/or permeability transition, at single cell resolution. This data is transformed to enable construction of a right step-wise survival function using the product limit estimator, and estimation of a median latency parameter (lambda), defined for the entire imaged cell population. Estimates of lambda computed for cells exhibiting two-colour fluorescence can be compared statistically using the Mantel-Hansel test. This general method has been applied to measure the kinetics and temporal ordering of BH3 domain induced mitochondrial depolarization and inner membrane permeabilization in cancer cells, and demonstrates the robustness of this technique in resolving temporally distinct intracellular events within individual cells.