Flowmax: A Computational Lymphocyte Phenotyping Tool For Deriving Cell Biological Insights From CFSE Flow Cytometry Time Courses (2012-234)
- 詳細技術說明
- A researcher from UC San Diego has developed an improved methodology and a corresponding graphical computational tool for analysis of cell proliferation time courses to reduce misinterpretation. This integrated modeling and analysis tool fits mathematical models to measured flow cytometry dye dilution experiments to model cellular biological processes (e.g. propensity of cells to respond, interdivision time, survival time) that describe the measured population dynamics. The computational tool consists of three main parts. First, it offers a graphical user friendly environment for basic analysis of flow cytometry data, which allows users to construct fluorescence histograms of viable cells for multiple experimental time points.Second, the tool trains two computational models on the experimental data using an optimized non-linear approach. The first model is used as an adaptor to facilitate optimal fitting of a second cell population model. The second step is repeated numerous times and each solution is subjected to parameter sensitivity analysis as part of a final confidence estimation step.A clustering approach is then used to derive the minimal set of unique solutions and the parameter confidence. Furthermore, numerous solution analysis tools were integrated to help analyze the statistical significance of solutions, as well as to visualize and deconstruct all solutions in terms of cellular and population phenotypes. In summary, this novel approach integrates modeling and analysis and allows for the estimation of parameter sensitivity and uniqueness, enabling useful solution comparisons. The tool has been used to discern novel immunological signaling phenotypes in a laboratory setting and can be directly applied to facilitate improved immunological and cancer screening in clinics.
- *Abstract
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Lymphocyte population dynamics within the mammalian immune response have been extensively studied, as they are a predictor of vaccine efficacy, while their misregulation may lead to cancers or autoimmunity.
A current experimental approach for tracking lymphocyte population dynamics involves flow cytometry of carboxyfluorescein succimidyl ester (CFSE)-stained cells. First introduced in 1990, CFSE tracking relies on the fact that CFSE is irreversibly bound to proteins in cells, resulting in progressive halving of cellular fluorescence with each cell division. By measuring the fluorescence of thousands of cells at various points in time after stimulation, fluorescence histograms with peaks representing generations of divided cells can be obtained. However, interpreting CFSE data confronts two challenges. In addition to intrinsic biological complexity arising from generation- and cell age-dependent variability in cellular processes, fluorescence signals for a specific generation are not truly uniform due to heterogeneity in (i) staining of founder population, (ii) dye partitioning during division, and (iii) dye clearance from cells over time. Thus, while high-throughput experimental approaches enable population- level measurements, deconvolution of CFSE time courses into biologically-intuitive cellular parameters is susceptible to misinterpretation.
- *Principal Investigation
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Name: Maxim Shokhirev
Department:
- 其他
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Intellectual Property Info
This patent-pending technology and software is available for commercial development.
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Tech ID/UC Case
25024/2012-841-0
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2012-841-0
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