PLoS ONE (Jan 2012)

Automated cell identification and tracking using nanoparticle moving-light-displays.

  • James A Tonkin,
  • Paul Rees,
  • Martyn R Brown,
  • Rachel J Errington,
  • Paul J Smith,
  • Sally C Chappell,
  • Huw D Summers

DOI
https://doi.org/10.1371/journal.pone.0040835
Journal volume & issue
Vol. 7, no. 7
p. e40835

Abstract

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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.