Numerical modelling of label-structured cell population growth using CFSE distribution data

Luzyanina, Tatyana; Roose, Dirk; Schenkel, Tim; Sester, Martina; Ehl, Stephan; Meyerhans, Andreas; Bocharov, Gennady

doi:10.1186/1742-4682-4-26

Cited by 55 publications

(99 citation statements)

References 39 publications

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“…The label-structured model (3.15) has been shown to provide an excellent fit to histogram data [21,79] and the model has been generalized (3.16) to permit the direct computation of cell numbers and division-specific division and death rates [23,46,74,79]. Though some comparison of the two different modeling approaches (describing cell numbers and fitting histogram data) has been done [56], it has not been immediately clear how to directly compare the distinct approaches in an impartial manner. Fortunately, the recent work on a 'division and label-structured population model' [46,74] has demonstrated how model (3.17) can be viewed as a unifying link between models of cell numbers and models of label dynamics (and thus histogram data).…”

Section: Discussionmentioning

confidence: 99%

“…The use of such a nonphysiological structure variable was suggested as early as 2000 for BrdU-based assays [30], and was first explored in the context of CFSE-based assays in [56]. More recent work [8,21,22,55,79] has consistently demonstrated that the label-structured PDE framework can accurately model the observed histogram data from a CFSE-based proliferation assay.…”

Section: Label-structured Pde Modelsmentioning

confidence: 99%

“…It has also been shown [23,79] that variability (among all cells in the population) in the autofluorescence parameter x a is a significant physical feature of an accurate mathematical model and can be accurately modeled with a lognormal distribution [23,46,79]. The best-fit solution to model (3.16) for a particular data set (data originally from [56]) is shown in Figure 8 and demonstrates the suitability of the given model in describing data from CFSE-based proliferation assays. A slightly different form of the model (3.16) has also been formulated in [46,74] and this leads to significant computational benefits.…”

Section: Label-structured Pde Modelsmentioning

confidence: 99%

“…Typical histogram representation of data from a CFSE-based proliferation assay. Originally from [56].…”

Section: Flow Cytometry and Cfse Datamentioning

confidence: 99%

“…Thus, there seems to be an advantage in the direct mathematical modeling of CFSE histogram data. To this end, structured population models have been proposed [21,22,55,56,79]. Such partial differential equation (PDE) models have long been discussed in the context of cell populations [28] and can be structured by age [1,27,39,44], cyclin content [27], size [40,44,45,68] or DNA-content [26], or any number of other physiological variables [62].…”

Section: Label-structured Pde Modelsmentioning

confidence: 99%

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Mathematical Models of Dividing Cell Populations: Application to CFSE Data

Banks

Thompson

2012

Math. Model. Nat. Phenom.

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Abstract. Flow cytometric analysis using intracellular dyes such as CFSE is a powerful experimental tool which can be used in conjunction with mathematical modeling to quantify the dynamic behavior of a population of lymphocytes. In this survey we begin by providing an overview of the mathematically relevant aspects of the data collection procedure. We then present an overview of the large body of mathematical models, along with their assumptions and uses, which have been proposed to describe the dynamics of proliferating cell populations. While much of this body of work has been aimed at modeling the generation structure (cells per generation) of the proliferating population, several recent models have considered the more fundamental task of modeling CFSE histogram data directly. Such models are analyzed and recent results are discussed. Finally, directions for future research are suggested.

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Section: Discussionmentioning

confidence: 99%

Section: Label-structured Pde Modelsmentioning

confidence: 99%

Section: Label-structured Pde Modelsmentioning

confidence: 99%

“…Typical histogram representation of data from a CFSE-based proliferation assay. Originally from [56].…”

Section: Flow Cytometry and Cfse Datamentioning

confidence: 99%

Section: Label-structured Pde Modelsmentioning

confidence: 99%

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Mathematical Models of Dividing Cell Populations: Application to CFSE Data

Banks

Thompson

2012

Math. Model. Nat. Phenom.

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Tracking antigen‐driven responses by flow cytometry: Monitoring proliferation by dye dilution

Wallace

Tario

Fisher³

et al. 2008

Cytometry Pt A

140

146

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Cell-tracking reagents such as the green-fluorescent protein labeling dye CFSE and the red-fluorescent lipophilic membrane dye PKH26 are commonly used to monitor cell proliferation by flow cytometry in heterogeneous cell populations responding to immune stimuli. Both reagents stain cells with a bright homogeneous fluorescence, which is partitioned between daughter cells during each cell division. Because daughter cell fluorescence intensities are approximately halved after each division, the intensity of a cell relative to its intensity at the time of staining provides information about how many divisions it has undergone. Knowing how many rounds of division have occurred and the relative number of cells in each daughter generation, one can back-calculate the number of cells in the original population (i.e., cells present at the time of stimulus) that went on to respond by proliferating. Using this information, the precursor cell frequencies and extent of expansion to a specific antigen or mitogen of interest can be calculated. Concurrently, the phenotype of the cells can be determined, as well as their ability to bind antigen or synthesize cytokines, providing more detailed characterization of all cells responding to the antigen, not just effector cells. In multiparameter flow cytometric experiments to simultaneously analyze antigen-specific tetramer binding, cytokine production and T-cell proliferation, we found that only approximately half of the cells that exhibited specific binding to influenza tetramer also proliferated, as measured by dye dilution, and synthesized IFNc in response to antigen. We expect the advent of new cell tracking dyes emitting from the violet to the near infrared combined with the increasing number of lasers and detectors on contemporary flow cytometers to further expand the usefulness of this approach to characterization of complex antigendriven immunological responses. '

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Quantitative analysis of cell proliferation by a dye dilution assay: Application to cell lines and cocultures

et al. 2017

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Cell proliferation represents one of the most fundamental processes in biological systems, thus the quantitative analysis of cell proliferation is important in many biological applications such as drug screening, production of biologics, and assessment of cytotoxicity. Conventional proliferation assays mainly quantify cell number based on a calibration curve of a homogeneous cell population, and therefore are not applicable for the analysis of cocultured cells. Moreover, these assays measure cell proliferation indirectly, based on cellular metabolic activity or DNA content. To overcome these shortcomings, a dye dilution assay employing fluorescent cell tracking dyes that are retained within cells was applied and was diluted proportionally by subsequent cell divisions. Here, it was demonstrated that this assay could be implemented to quantitatively analyze the cell proliferation of different types of cell lines, and to concurrently analyze the proliferation of two types of cell lines in coculture by utilizing cell tracking dyes with different spectral characteristics. The mean division time estimated by the dye dilution assay is compared with the population doubling time obtained from conventional methods and values from literature. Additionally, dye transfer between cocultured cells was investigated and it was found that it is a characteristic of the cells rather than a characteristic of the dye. It was suggested that this method can be easily combined with other flow cytometric analyses of cellular properties, providing valuable information on cell status under diverse conditions. © 2017 International Society for Advancement of Cytometry.

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Numerical modelling of label-structured cell population growth using CFSE distribution data

Cited by 55 publications

References 39 publications

Mathematical Models of Dividing Cell Populations: Application to CFSE Data

Mathematical Models of Dividing Cell Populations: Application to CFSE Data

Tracking antigen‐driven responses by flow cytometry: Monitoring proliferation by dye dilution

Quantitative analysis of cell proliferation by a dye dilution assay: Application to cell lines and cocultures

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