Fluorescence-activated cell sorting (FACS) applying flow cytometry to separate cells on a molecular basis is a widespread method. We demonstrate that both fluorescent and unlabeled live cells in a Petri dish observed with a microscope can be automatically recognized by computer vision and picked up by a computer-controlled micropipette. This method can be routinely applied as a FACS down to the single cell level with a very high selectivity. Sorting resolution, i.e., the minimum distance between two cells from which one could be selectively removed was 50-70 micrometers. Survival rate with a low number of 3T3 mouse fibroblasts and NE-4C neuroectodermal mouse stem cells was 66 ± 12% and 88 ± 16%, respectively. Purity of sorted cultures and rate of survival using NE-4C/NE-GFP-4C co-cultures were 95 ± 2% and 62 ± 7%, respectively. Hydrodynamic simulations confirmed the experimental sorting efficiency and a cell damage risk similar to that of normal FACS.
Cell sorting in a Petri dish controlled by computer vision.
利用计算机视觉控制在培养皿中进行细胞分选
阅读:5
作者:Környei Z, Beke S, Mihálffy T, Jelitai M, Kovács K J, Szabó Z, Szabó B
| 期刊: | Scientific Reports | 影响因子: | 3.900 |
| 时间: | 2013 | 起止号: | 2013;3:1088 |
| doi: | 10.1038/srep01088 | 研究方向: | 细胞生物学 |
特别声明
1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。
2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。
3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。
4、投稿及合作请联系:info@biocloudy.com。
