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Deriving Quantitative Cell Biological Information from Dye-Dilution Lymphocyte Proliferation Experiments.

Koushik Roy1, Maxim Nikolaievich Shokhirev2, Simon Mitchell1

  • 1Department of Microbiology, Immunology, and Molecular Genetics, Institute for Quantitative and Computational Biosciences, University of California, Box 951570, 570 Boyer Hall, Los Angeles, CA, 90095, USA.

Methods in Molecular Biology (Clifton, N.J.)
|February 2, 2018
PubMed
Summary

Quantitative analysis of lymphocyte expansion dynamics is possible using dye-dilution assays. This method, combined with the FlowMax software, provides objective cell biological insights with confidence measures.

Keywords:
B cellCFSE assayCell biological parameterFlowMaxLymphocyteLymphocyte dynamicsProliferationQuantitative dye dilution

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Area of Science:

  • Immunology
  • Cell Biology
  • Computational Biology

Background:

  • Lymphocyte expansion dynamics are crucial for adaptive immunity.
  • Dye-dilution assays offer a method to track cell proliferation.
  • Quantitative analysis of these assays can yield valuable cell biological parameters.

Purpose of the Study:

  • To describe a method for generating quantitative cell biological insights from dye-dilution experiments.
  • To detail experimental methods for murine lymphocyte dye-dilution data generation.
  • To present a computational data analysis workflow using the FlowMax software.

Main Methods:

  • Performing time-course dye-dilution experiments with murine lymphocytes.
  • Utilizing the FlowMax software package for computational data analysis.
  • Integrating experimental data with computational analysis for quantitative insights.

Main Results:

  • The combined approach allows for the quantification of cell division percentage, division timing, and cell death.
  • Objective interpretation of dye-dilution data is achieved through computational analysis.
  • Confidence in reported cell biological parameters is dependent on data quality and quantity.

Conclusions:

  • Dye-dilution assays, when coupled with computational analysis like FlowMax, provide a robust method for studying lymphocyte expansion.
  • This approach enables the objective and quantitative determination of key cell biological parameters.
  • The reliability of these parameters is directly linked to the quality and volume of the generated data.