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Using a large consortium of undergraduate students in an organized program at the University of California, Los Angeles (UCLA), we have undertaken a functional genomic screen in the Drosophila eye. In addition to the educational value of discovery-based learning, this article presents the first comprehensive genomewide analysis of essential genes involved in eye development. The data reveal the surprising result that the X chromosome has almost twice the frequency of essential genes involved in eye development as that found on the autosomes.

Live cell imaging has improved our ability to measure phenotypic heterogeneity. However, bottlenecks in imaging and image processing often make it difficult to differentiate interesting biological behavior from technical artifact. Thus there is a need for new methods that improve data quality without sacrificing throughput. Here we present a 3-step workflow to improve dynamic phenotype measurements of heterogeneous cell populations. We provide guidelines for image acquisition, phenotype tracking, and data filtering to remove erroneous cell tracks using the novel Tracking Aberration Measure (TrAM). Our workflow is broadly applicable across imaging platforms and analysis software. By applying this workflow to cancer cell assays, we reduced aberrant cell track prevalence from 17% to 2%. The cost of this improvement was removing 15% of the well-tracked cells. This enabled detection of significant motility differences between cell lines. Similarly, we avoided detecting a false change in translocation kinetics by eliminating the true cause: varied proportions of unresponsive cells. Finally, by systematically seeking heterogeneous behaviors, we detected subpopulations that otherwise could have been missed, including early apoptotic events and pre-mitotic cells. We provide optimized protocols for specific applications and step-by-step guidelines for adapting them to a variety of biological systems.

Background: Recent studies suggest that the spatio-temporal dynamics of critical signaling molecules can mediate heterogeneous response to therapeutic intervention. Here, we set out to apply live cell imaging of single cells in high throughput to correlate the dynamics of androgen receptor (AR) with response to taxane chemotherapy in heterogeneous prostate cancer (PCa) cell populations. Methods: We previously developed a 3-step high throughput imaging and data analysis workflow to improve measurements of the dynamic phenotype in heterogeneous populations. We treated PCa cells stably expressing GFP-AR with AR ligand and quantified nuclear/cytoplasmic GFP intensity to measure nuclear translocation of AR over a 30 min time course. Then we treated cells with paclitaxel and tracked cells' response for 24h. Results: Applied to PCa cell lines stably expressing GFP-AR, we measured considerable heterogeneity of AR translocation in response to ligand stimulation. We quantified populations of non-responders and classified responding cells based on the dynamics of AR. Evaluation of cell morphology revealed a fraction of relatively large cells to be exclusively slow responders to AR ligand. We measured heterogeneous response to treatment with paclitaxel that correlated with cell phenotype. Conclusion: We conclude that cell morphology features in heterogeneous PCa cell populations correlate with AR translocation dynamics and drug response. Future experiments will include expression of the constitutively active AR variant AR-v7 to analyze its effect on the dynamics of wild-type AR and on single cell response to paclitaxel chemotherapy. Note: This abstract was not presented at the conference. Citation Format: Katherin Patsch, Anjana Soundararajan, Mark Engeln, Mitchell E. Gross, Shannon M. Mumenthaler, Daniel Ruderman. Heterogeneity of androgen receptor dynamics and drug response in prostate cancer cells. [abstract]. In: Proceedings of the AACR Special Conference on Engineering and Physical Sciences in Oncology; 2016 Jun 25-28; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2017;77(2 Suppl):Abstract nr A29.