Cargando…

Reconstruction of cell population dynamics using CFSE

BACKGROUND: Quantifying cell division and death is central to many studies in the biological sciences. The fluorescent dye CFSE allows the tracking of cell division in vitro and in vivo and provides a rich source of information with which to test models of cell kinetics. Cell division and death have...

Descripción completa

Detalles Bibliográficos
Autores principales: Yates, Andrew, Chan, Cliburn, Strid, Jessica, Moon, Simon, Callard, Robin, George, Andrew JT, Stark, Jaroslav
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1929124/
https://www.ncbi.nlm.nih.gov/pubmed/17565685
http://dx.doi.org/10.1186/1471-2105-8-196
_version_ 1782134264859459584
author Yates, Andrew
Chan, Cliburn
Strid, Jessica
Moon, Simon
Callard, Robin
George, Andrew JT
Stark, Jaroslav
author_facet Yates, Andrew
Chan, Cliburn
Strid, Jessica
Moon, Simon
Callard, Robin
George, Andrew JT
Stark, Jaroslav
author_sort Yates, Andrew
collection PubMed
description BACKGROUND: Quantifying cell division and death is central to many studies in the biological sciences. The fluorescent dye CFSE allows the tracking of cell division in vitro and in vivo and provides a rich source of information with which to test models of cell kinetics. Cell division and death have a stochastic component at the single-cell level, and the probabilities of these occurring in any given time interval may also undergo systematic variation at a population level. This gives rise to heterogeneity in proliferating cell populations. Branching processes provide a natural means of describing this behaviour. RESULTS: We present a likelihood-based method for estimating the parameters of branching process models of cell kinetics using CFSE-labeling experiments, and demonstrate its validity using synthetic and experimental datasets. Performing inference and model comparison with real CFSE data presents some statistical problems and we suggest methods of dealing with them. CONCLUSION: The approach we describe here can be used to recover the (potentially variable) division and death rates of any cell population for which division tracking information is available.
format Text
id pubmed-1929124
institution National Center for Biotechnology Information
language English
publishDate 2007
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-19291242007-07-21 Reconstruction of cell population dynamics using CFSE Yates, Andrew Chan, Cliburn Strid, Jessica Moon, Simon Callard, Robin George, Andrew JT Stark, Jaroslav BMC Bioinformatics Research Article BACKGROUND: Quantifying cell division and death is central to many studies in the biological sciences. The fluorescent dye CFSE allows the tracking of cell division in vitro and in vivo and provides a rich source of information with which to test models of cell kinetics. Cell division and death have a stochastic component at the single-cell level, and the probabilities of these occurring in any given time interval may also undergo systematic variation at a population level. This gives rise to heterogeneity in proliferating cell populations. Branching processes provide a natural means of describing this behaviour. RESULTS: We present a likelihood-based method for estimating the parameters of branching process models of cell kinetics using CFSE-labeling experiments, and demonstrate its validity using synthetic and experimental datasets. Performing inference and model comparison with real CFSE data presents some statistical problems and we suggest methods of dealing with them. CONCLUSION: The approach we describe here can be used to recover the (potentially variable) division and death rates of any cell population for which division tracking information is available. BioMed Central 2007-06-12 /pmc/articles/PMC1929124/ /pubmed/17565685 http://dx.doi.org/10.1186/1471-2105-8-196 Text en Copyright © 2007 Yates et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Yates, Andrew
Chan, Cliburn
Strid, Jessica
Moon, Simon
Callard, Robin
George, Andrew JT
Stark, Jaroslav
Reconstruction of cell population dynamics using CFSE
title Reconstruction of cell population dynamics using CFSE
title_full Reconstruction of cell population dynamics using CFSE
title_fullStr Reconstruction of cell population dynamics using CFSE
title_full_unstemmed Reconstruction of cell population dynamics using CFSE
title_short Reconstruction of cell population dynamics using CFSE
title_sort reconstruction of cell population dynamics using cfse
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1929124/
https://www.ncbi.nlm.nih.gov/pubmed/17565685
http://dx.doi.org/10.1186/1471-2105-8-196
work_keys_str_mv AT yatesandrew reconstructionofcellpopulationdynamicsusingcfse
AT chancliburn reconstructionofcellpopulationdynamicsusingcfse
AT stridjessica reconstructionofcellpopulationdynamicsusingcfse
AT moonsimon reconstructionofcellpopulationdynamicsusingcfse
AT callardrobin reconstructionofcellpopulationdynamicsusingcfse
AT georgeandrewjt reconstructionofcellpopulationdynamicsusingcfse
AT starkjaroslav reconstructionofcellpopulationdynamicsusingcfse