Systems cell biology knowledge created from high content screening

Abstract

High content screening (HCS), the large-scale automated analysis of the temporal and spatial changes in cells and cell constituents in arrays of cells, has the potential to create enormous systems cell biology knowledge bases. HCS is being employed along with the continuum of the early drug discovery process, including lead optimization where new knowledge is being used to facilitate the decision-making process. We demonstrate methodology to build new systems cell biology knowledge using a multiplexed HCS assay, designed with the aid of knowledge-mining tools, to measure the phenotypic response of a panel of human tumor cell types to a panel of natural product-derived microtubule-targeted anticancer agents and their synthetic analogs. We show how this new systems cell biology knowledge can be used to design a lead compound optimization strategy for at least two members of the panel, (-)-laulimalide and (+)-discodermolide, that exploits cell killing activity while minimally perturbing the regulation of the cell cycle and the stability of microtubules. Furthermore, this methodology can also be applied to basic biomedical research on cells.