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A novel statistical analysis and interpretation of flow cytometry data.

Banks HT, Kapraun DF, Thompson WC, Peligero C, Argilaguet J, Meyerhans A - J Biol Dyn (2013)

Bottom Line: A recently developed class of models incorporating the cyton model of population generation structure into a conservation-based model of intracellular label dynamics is reviewed.Statistical aspects of the data collection process are quantified and incorporated into a parameter estimation scheme.This scheme is then applied to experimental data for PHA-stimulated CD4+T and CD8+T cells collected from two healthy donors.

View Article: PubMed Central - PubMed

Affiliation: Center for Research in Scientific Computation and Center for Quantitative Sciences in Biomedicine, North Carolina State University, Raleigh, NC 27695-8212, USA. htbanks@ncsu.edu

ABSTRACT
A recently developed class of models incorporating the cyton model of population generation structure into a conservation-based model of intracellular label dynamics is reviewed. Statistical aspects of the data collection process are quantified and incorporated into a parameter estimation scheme. This scheme is then applied to experimental data for PHA-stimulated CD4+T and CD8+T cells collected from two healthy donors. This novel mathematical and statistical framework is shown to form the basis for accurate, meaningful analysis of cellular behaviour for a population of cells labelled with the dye carboxyfluorescein succinimidyl ester and stimulated to divide.

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Histogram data for CD8T cells from Donor 1 (left) and Donor 2 (right). An initially unimodal distribution of fluorescence intensity becomes multimodal as cells divide asynchronously. By day 4, subsequent generations of cells are no longer detectable as fluorescence resulting from CFSE has been diluted to the level of background autofluorescence.
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Figure 2: Histogram data for CD8T cells from Donor 1 (left) and Donor 2 (right). An initially unimodal distribution of fluorescence intensity becomes multimodal as cells divide asynchronously. By day 4, subsequent generations of cells are no longer detectable as fluorescence resulting from CFSE has been diluted to the level of background autofluorescence.

Mentions: When a population of cells is measured, the individual CFSE fluorescence intensity measurements can be placed into a histogram as in Figures 1 and 2. Each ‘peak’ in the histogram represents a cohort of cells having completed the same number of divisions. When such measurements are made sequentially in time, one obtains information on the dynamic response of the population of cells to a stimulus. As such, CFSE-based flow cytometric analysis is a promising tool for the study of cell division and division-linked changes. The ultimate goal for the quantitative analysis of CFSE data (in particular, as it relates to studies of the immune system) is to incorporate fundamental mechanistic modelling of the cellular calculus into a description of population-level behaviour, and thus to obtain a more comprehensive understanding of the immune system, with obvious implications for the study of disease detection, progression, treatment/control, etc. To that end, mathematical modelling provides a quantitative framework with which to analyse and interpret such data.


A novel statistical analysis and interpretation of flow cytometry data.

Banks HT, Kapraun DF, Thompson WC, Peligero C, Argilaguet J, Meyerhans A - J Biol Dyn (2013)

Histogram data for CD8T cells from Donor 1 (left) and Donor 2 (right). An initially unimodal distribution of fluorescence intensity becomes multimodal as cells divide asynchronously. By day 4, subsequent generations of cells are no longer detectable as fluorescence resulting from CFSE has been diluted to the level of background autofluorescence.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3753657&req=5

Figure 2: Histogram data for CD8T cells from Donor 1 (left) and Donor 2 (right). An initially unimodal distribution of fluorescence intensity becomes multimodal as cells divide asynchronously. By day 4, subsequent generations of cells are no longer detectable as fluorescence resulting from CFSE has been diluted to the level of background autofluorescence.
Mentions: When a population of cells is measured, the individual CFSE fluorescence intensity measurements can be placed into a histogram as in Figures 1 and 2. Each ‘peak’ in the histogram represents a cohort of cells having completed the same number of divisions. When such measurements are made sequentially in time, one obtains information on the dynamic response of the population of cells to a stimulus. As such, CFSE-based flow cytometric analysis is a promising tool for the study of cell division and division-linked changes. The ultimate goal for the quantitative analysis of CFSE data (in particular, as it relates to studies of the immune system) is to incorporate fundamental mechanistic modelling of the cellular calculus into a description of population-level behaviour, and thus to obtain a more comprehensive understanding of the immune system, with obvious implications for the study of disease detection, progression, treatment/control, etc. To that end, mathematical modelling provides a quantitative framework with which to analyse and interpret such data.

Bottom Line: A recently developed class of models incorporating the cyton model of population generation structure into a conservation-based model of intracellular label dynamics is reviewed.Statistical aspects of the data collection process are quantified and incorporated into a parameter estimation scheme.This scheme is then applied to experimental data for PHA-stimulated CD4+T and CD8+T cells collected from two healthy donors.

View Article: PubMed Central - PubMed

Affiliation: Center for Research in Scientific Computation and Center for Quantitative Sciences in Biomedicine, North Carolina State University, Raleigh, NC 27695-8212, USA. htbanks@ncsu.edu

ABSTRACT
A recently developed class of models incorporating the cyton model of population generation structure into a conservation-based model of intracellular label dynamics is reviewed. Statistical aspects of the data collection process are quantified and incorporated into a parameter estimation scheme. This scheme is then applied to experimental data for PHA-stimulated CD4+T and CD8+T cells collected from two healthy donors. This novel mathematical and statistical framework is shown to form the basis for accurate, meaningful analysis of cellular behaviour for a population of cells labelled with the dye carboxyfluorescein succinimidyl ester and stimulated to divide.

Show MeSH