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 journalArticlepeer-review

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

Fingerprint

Dive into the research topics of 'Automated cell identification and tracking using nanoparticle moving-light-displays'. Together they form a unique fingerprint.

Cite this