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Fractional proliferation: a method to deconvolve cell population dynamics from single-cell data

Nature Methods volume 9, pages 923–928 (2012)Cite this article

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Abstract

We present an integrated method that uses extended time-lapse automated imaging to quantify the dynamics of cell proliferation. Cell counts are fit with a quiescence-growth model that estimates rates of cell division, entry into quiescence and death. The model is constrained with rates extracted experimentally from the behavior of tracked single cells over time. We visualize the output of the analysis in fractional proliferation graphs, which deconvolve dynamic proliferative responses to perturbations into the relative contributions of dividing, quiescent (nondividing) and dead cells. The method reveals that the response of 'oncogene-addicted' human cancer cells to tyrosine kinase inhibitors is a composite of altered rates of division, death and entry into quiescence, a finding that challenges the notion that such cells simply die in response to oncogene-targeted therapy.

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Figure 1: The fractional proliferation methodology.
Figure 2: The quiescence-growth model explains nonlinear proliferation.
Figure 3: Interpretation of tracked single-cell data with mathematical models.
Figure 4: Application of fractional proliferation to a model of oncogene-addicted tumor cells.

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Acknowledgements

We would like to thank J. Hao and A. Udyavar for technical assistance, E. Pham and R. Feroze for assistance in manual image analysis, G. Ostheimer for assistance with flow cytometry and A. Weaver, G. Webb, B. Rexer, K. Dahlman, W. Yarbrough and L. Estrada for reviewing the manuscript and providing stimulating discussions. We acknowledge the generous gift of primary squamous cell carcinoma and SQ20B cells from W. Yarbrough and PC9 cells from W. Pao (both at Vanderbilt University School of Medicine). We also acknowledge A. Miyawaki (RIKEN Brain Science Institute) for the mAG-geminin plasmid and Gideon Bollag (Plexxikon) for the generous gift of PLX-4720. This work was supported by the US National Institutes of Health/National Cancer Institute Integrative Cancer Biology Program (5U54 CA113007-07). Flow cytometry experiments were performed in the Vanderbilt Medical Center Flow Cytometry Shared Resource, which is supported by the Vanderbilt Ingram Cancer Center (P30 CA68485) and the Vanderbilt Digestive Disease Research Center (DK058404). In addition, the project described was partially supported by the National Center for Research Resources (UL1 RR024975-01) and is now at the National Center for Advancing Translational Sciences (2 UL1 TR000445-06).

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Authors and Affiliations

  1. Department of Cancer Biology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA

    Darren R Tyson, Shawn P Garbett, Peter L Frick & Vito Quaranta

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  1. Darren R Tyson
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Contributions

D.R.T. conceived of the approach, D.R.T. and P.L.F. cultured, treated and imaged cells, D.R.T. analyzed images, S.P.G. and D.R.T. developed the mathematical models, D.R.T. and S.P.G. fit model parameters to data, and D.R.T. and V.Q. cowrote the paper.

Corresponding author

Correspondence to Darren R Tyson.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–10, Supplementary Tables 1–3 and Supplementary Notes 1–3 (PDF 9666 kb)

Supplementary Software 1

Mathematica CDF file to interactively explore solutions to the quiescence-growth model and visualize the alterations in curve shape caused by modulating parameters individually or simultaneously. This file can be opened and manipulated using the freely available Wolfram CDF Player (http://www.wolfram.com/products/player/) (TXT 16 kb)

Supplementary Software 2

Text file containing cut-and-paste R code to produce the fractional proliferation graphs shown in Figure 3d (identical to code in Supplementary Note 2). (TXT 3 kb)

Example of a typical fluorescence image stack with manual cell tracking labels.

This movie shows the response of PC9 cells to 96 h in 1 μM erlotinib followed by 72 h in fresh medium without erlotinib (two medium changes). Data shown in this video were used to generate Supplementary Figure 9. (MOV 5033 kb)

41592_2012_BFnmeth2138_MOESM309_ESM.mov

Fluorescence microscopy image stack with manual cell tracking labels of CA1d cells treated with 16 μM erlotinib for 96 h used to generate Figure 3d. (MOV 8126 kb)

Fluorescence microscopy image stack of primary cultured cells (human squamous cell carcinoma of the tongue) transiently labeled with H2BmRFP using CellLight Nucleus (Invitrogen).

Data shown in this video were used to generate Supplementary Figure 10. (MOV 27815 kb)

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Tyson, D., Garbett, S., Frick, P. et al. Fractional proliferation: a method to deconvolve cell population dynamics from single-cell data. Nat Methods 9, 923–928 (2012). https://doi.org/10.1038/nmeth.2138

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