Automated cell identification and tracking using nanoparticle moving-light-displays
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...
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| Veröffentlicht in: | PloS one 2012-07, Vol.7 (7), p.e40835 |
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| creator | Tonkin, James A Rees, Paul Brown, Martyn R Errington, Rachel J Smith, Paul J Chappell, Sally C Summers, Huw D |
| description | 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. |
| doi_str_mv | 10.1371/journal.pone.0040835 |
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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.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0040835</identifier><identifier>PMID: 22829889</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Algorithms ; Automation ; Biology ; Cadmium Compounds - chemistry ; Cadmium tellurides ; Cell growth ; Cell Line, Tumor ; Cell Proliferation ; Clustering ; Computer applications ; Displays ; Drug dosages ; Endocytosis ; Engineering ; Fluorescence ; Humans ; Identification ; Light ; Light sources ; Lung cancer ; Lung diseases ; Materials Science ; Microscopy ; Models, Theoretical ; Motion capture ; Motion detection ; Nanoparticles ; Nanoparticles - chemistry ; Nanotechnology - methods ; Optics ; Particle tracking ; Pattern recognition ; Quantum Dots ; Sulfides - chemistry ; Technology application ; Tellurium - chemistry ; Theory ; Time series ; Vector quantization ; Visual perception ; Zinc Compounds - chemistry ; Zinc sulfide ; Zinc sulfides</subject><ispartof>PloS one, 2012-07, Vol.7 (7), p.e40835</ispartof><rights>COPYRIGHT 2012 Public Library of Science</rights><rights>2012 Tonkin et al. 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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. 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| subjects | Algorithms Automation Biology Cadmium Compounds - chemistry Cadmium tellurides Cell growth Cell Line, Tumor Cell Proliferation Clustering Computer applications Displays Drug dosages Endocytosis Engineering Fluorescence Humans Identification Light Light sources Lung cancer Lung diseases Materials Science Microscopy Models, Theoretical Motion capture Motion detection Nanoparticles Nanoparticles - chemistry Nanotechnology - methods Optics Particle tracking Pattern recognition Quantum Dots Sulfides - chemistry Technology application Tellurium - chemistry Theory Time series Vector quantization Visual perception Zinc Compounds - chemistry Zinc sulfide Zinc sulfides |
| title | Automated cell identification and tracking using nanoparticle moving-light-displays |
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