Towards Fully Automated Phototransfection
Title: Towards Fully Automated Phototransfection
Author(s) name and affiliations:
David J. Cappelleri, Mechanical Engineering, Stevens Institute of Technology
Adam Halasz, Mathematics, West Virginia University
Jai-Yoon Sul, Tae Kyung Kim, and James Eberwine, Pharmacology, University of Pennsylvania
Vijay Kumar, Mechanical Engineering and Applied Mechanics, University of Pennsylvania
Flexible automation technologies have been applied to the manual phototransfection procedure on fibroblast and astrocyte cells. We have designed and implemented a framework for increased throughput of the entire process. Integrated image processing, laser target position calculation, and stage movements show a throughput increase of >23X over the current manual method while the potential for even greater throughput improvements (> 110X) is described. A software tool for automated single cell morphological measurements has also been constructed and shown to be able quantify changes in the cell before and after the process, successfully characterizing them, using metrics such as cell perimeter, area, major and minor axis length, and eccentricity values.