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

Research output: Contribution to journalArticle

11 Scopus citations

Abstract

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.

Original languageEnglish (US)
Article numbere40835
JournalPLoS ONE
Volume7
Issue number7
DOIs
StatePublished - Jul 19 2012

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)
  • General

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