Cell sorting in a Petri dish controlled by computer vision.

摘要

Fluorescence-activated cell sorting (FACS) applying flow udcytometry to separate cells on a molecular basis is a widespread udmethod. We demonstrate that both fluorescent and unlabeled live udcells in a Petri dish observed with a microscope can be udautomatically recognized by computer vision and picked up by a udcomputer-controlled micropipette. This method can be routinely udapplied as a FACS down to the single cell level with a very udhigh selectivity. Sorting resolution, i.e., the minimum distance udbetween two cells from which one could be selectively removed udwas 50-70 micrometers. Survival rate with a low number of 3T3 udmouse fibroblasts and NE-4C neuroectodermal mouse stem cells was ud66 +/- 12% and 88 +/- 16%, respectively. Purity of sorted udcultures and rate of survival using NE-4C/NE-GFP-4C co-cultures udwere 95 +/- 2% and 62 +/- 7%, respectively. Hydrodynamic udsimulations confirmed the experimental sorting efficiency and a udcell damage risk similar to that of normal FACS.