Automated cell identification and tracking using nanoparticle moving-light-displays.
Automated cell identification and tracking using nanoparticle moving-light-displays.
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DOI：
10.1371/journal.pone.0040835
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发表时间：
2012
期刊：
影响因子：
3.7
通讯作者：
Summers HD
中科院分区：
文献类型：
--
作者：
Tonkin JA;Rees P;Brown MR;Errington RJ;Smith PJ;Chappell SC;Summers HD
An automated technique for the identification, tracking and analysis of biological cells is presented. It is based on the use of nanoparticles, enclosed within intra-cellular vesicles, to produce clusters of discrete, point-like fluorescent, light sources within the cells. Computational analysis of these light ensembles in successive time frames of a movie sequence, using k-means clustering and particle tracking algorithms, provides robust and automated discrimination of live cells and their motion and a quantitative measure of their proliferation. This approach is a cytometric version of the moving light display technique which is widely used for analyzing the biological motion of humans and animals. We use the endocytosis of CdTe/ZnS, core-shell quantum dots to produce the light displays within an A549, epithelial, lung cancer cell line, using time-lapse imaging with frame acquisition every 5 minutes over a 40 hour time period. The nanoparticle moving light displays provide simultaneous collection of cell motility data, resolution of mitotic traversal dynamics and identification of familial relationships allowing construction of multi-parameter lineage trees.
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