期刊论文详细信息
BMC Systems Biology
Estimating cell diffusivity and cell proliferation rate by interpreting IncuCyte ZOOM™ assay data using the Fisher-Kolmogorov model
Matthew J. Simpson2  D. L. Sean McElwain1  Lisa K. Chopin2  Esha T. Shah2  Stuart T. Johnston1 
[1] School of Mathematical Sciences, Queensland University of Technology (QUT), Brisbane 4001, Australia;Ghrelin Research Group, Translational Research Institute, Institute of Health and Biomedical Innovation and APCRC-Q, QUT, 37 Kent St, Woolloongabba 4102, Australia
关键词: Wound healing;    Cancer;    Leading edge detection;    Scratch assay;    Cell proliferation;    Cell motility;   
Others  :  1230654
DOI  :  10.1186/s12918-015-0182-y
 received in 2015-01-29, accepted in 2015-06-23,  发布年份 2015
【 摘 要 】

Background

Standard methods for quantifying IncuCyte ZOOM™ assays involve measurements that quantify how rapidly the initially-vacant area becomes re-colonised with cells as a function of time. Unfortunately, these measurements give no insight into the details of the cellular-level mechanisms acting to close the initially-vacant area. We provide an alternative method enabling us to quantify the role of cell motility and cell proliferation separately. To achieve this we calibrate standard data available from IncuCyte ZOOM™ images to the solution of the Fisher-Kolmogorov model.

Results

The Fisher-Kolmogorov model is a reaction-diffusion equation that has been used to describe collective cell spreading driven by cell migration, characterised by a cell diffusivity, D, and carrying capacity limited proliferation with proliferation rate, λ, and carrying capacity density, K. By analysing temporal changes in cell density in several subregions located well-behind the initial position of the leading edge we estimate λ and K. Given these estimates, we then apply automatic leading edge detection algorithms to the images produced by the IncuCyte ZOOM™ assay and match this data with a numerical solution of the Fisher-Kolmogorov equation to provide an estimate of D. We demonstrate this method by applying it to interpret a suite of IncuCyte ZOOM™ assays using PC-3 prostate cancer cells and obtain estimates of D, λ and K. Comparing estimates of D, λ and K for a control assay with estimates of D, λ and K for assays where epidermal growth factor (EGF) is applied in varying concentrations confirms that EGF enhances the rate of scratch closure and that this stimulation is driven by an increase in D and λ, whereas K is relatively unaffected by EGF.

Conclusions

Our approach for estimating D, λ and K from an IncuCyte ZOOM™ assay provides more detail about cellular-level behaviour than standard methods for analysing these assays. In particular, our approach can be used to quantify the balance of cell migration and cell proliferation and, as we demonstrate, allow us to quantify how the addition of growth factors affects these processes individually.

【 授权许可】

   
2015 Johnston et al.

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【 参考文献 】
  • [1]Maini PK, McElwain DLS, Leavesley D: Travelling waves in a wound healing assay. Appl Math Lett 2004, 17(5):575-80.
  • [2]Maini PK, McElwain DLS, Leavesley DI: Traveling wave model to interpret a wound-healing cell migration assay for human peritoneal mesothelial cells. Tissue Eng 2004, 10(3-4):475-82.
  • [3]Cai AQ, Landman KA, Hughes BD: Multi-scale modeling of a wound-healing cell migration assay. J Theor Biol 2007, 245(3):576-94.
  • [4]Tremel A, Cai A, Tirtaatmadja N, Hughes BD, Stevens GW, Landman KA, et al.: Cell migration and proliferation during monolayer formation and wound healing. Chem. Eng. Sci 2009, 64(2):247-53.
  • [5]Johnston ST, Simpson MJ, McElwain DLS: How much information can be obtained from tracking the position of the leading edge in a scratch assay? J R Soc Interface 2014, 11(97):20140325.
  • [6]Johnston ST, Simpson MJ, McElwain DLS, Binder BJ, Ross JV: Interpreting scratch assays using pair density dynamics and approximate Bayesian computation. Open Biol 2014, 4:140097.
  • [7]Kharait S, Hautaniemi S, Wu S, Iwabu A, Lauffenburger DA, Wells A: Decision tree modeling predicts effects of inhibiting contractility signaling on cell motility. BMC Syst Biol 2007, 1(1):9. BioMed Central Full Text
  • [8]Khain E, Katakowski M, Hopkins S, Szalad A, Zheng X, Jiang F, et al.: Collective behavior of brain tumor cells: the role of hypoxia. Physical Review E 2011, 83(3):031920.
  • [9]Khain E, Katakowski M, Charteris N, Jiang F, Chopp M: Migration of adhesive glioma cells: Front propagation and fingering. Physical Review E 2012, 86(1):011904.
  • [10]Charteris N, Khain E: Modeling chemotaxis of adhesive cells: Stochastic lattice approach and continuum description. New Journal of Physics 2014, 16:025002.
  • [11]Liang CC, Park AY, Guan JL: In vitro scratch assay: a convenient and inexpensive method for analysis of cell migration in vitro. Nat Protoc 2007, 2(2):329-33.
  • [12]EssenBioScience: IncuCyte ZOOM live cell imaging. http://www.essenbioscience.com/essen-products/incucyte/ (Accessed: January 2015).
  • [13]Gujral TS, Chan M, Peshkin L, Sorger PK, Kirschner MW, MacBeath G: A noncanonical frizzled2 pathway regulates epithelial-mesenchymal transition and metastasis. Cell 2014, 159:844-56.
  • [14]Salomon C, Kobayashi M, Ashman K, Sobrevia L, Mitchell MD, Rice GE: Hypoxia-induced changes in the bioactivity of cytotrophoblast-derived exosomes. PLOS ONE 2013, 8(11):79636.
  • [15]Salomon C, Torres MJ, Kobayashi M, Scholz-Romero K, Sobrevia L, Dobierzewska A, et al.: A gestational profile of placental exosomes in maternal plasma and their effects on endothelial cell migration. PLOS ONE 2014, 9(6):98667.
  • [16]Kaighn ME, Narayan KS, Ohnuki Y, Lechner JF, Jones LW: Establishment and characterization of a human prostatic carcinoma cell line (PC-3). Invest. Urol 1979, 17:16-23.
  • [17]Jarrard DF, Blitz BF, Smith RC, Patai BL, Rukstalis DB: Effect of epidermal growth factor on prostate cancer cell line PC3 growth and invasion. Prostate 1994, 24:46-53.
  • [18]Treloar KK, Simpson MJ, Haridas P, Manton KJ, Leavesley DI, McElwain DLS, et al.: Multiple types of data are required to identify the mechanisms influencing the spatial expansion of melanoma cell colonies. BMC Syst Biol 2013, 7(1):137. BioMed Central Full Text
  • [19]Harris RC, Chung E, Coffey RJ: EGF receptor ligands. Exp Cell Res 2003, 284:2-13.
  • [20]Herbst RS: Review of epidermal growth factor receptor biology. Int J Radiat Oncol Biol Phys 2004, 59:21-6.
  • [21]Simpson MJ, Treloar KK, Binder BJ, Haridas P, Manton KJ, Leavesley DI, et al.: Quantifying the roles of cell motility and cell proliferation in a circular barrier assay. J R Soc Interface 2013, 10(82):20130007.
  • [22]Treloar KK, Simpson MJ, McElwain DLS, Baker RE: Are in vitro estimates of cell diffusivity and cell proliferation rate sensitive to assay geometry? J Theor Biol 2014, 356:71-84.
  • [23]Mathworks: Image Processing Toolbox User Guide R2013b. http://www.mathworks.com.au/help/images/index.html (Accessed: January 2015).
  • [24]Treloar KK, Simpson MJ: Sensitivity of edge detection methods for quantifying cell migration assays. PLOS ONE 2013, 8(6):67389.
  • [25]Canny J: A computational approach to edge detection. IEEE Trans Pattern Anal Mach Intell 1986, 6:679-698.
  • [26]Fisher RA: The wave of advance of advantageous genes. Ann Eugen 1937, 7(4):355-69.
  • [27]Kolmogorov A, Petrovsky A, Piscounov N: Etude de lequation de la diffusion avec croissance de la quantite de matiere et son application a unprobleme biologique. Moscow Univ Math Bull 1937, 1:1-25.
  • [28]Murray JD: Mathematical Biology vol. 1: An introduction. Springer, New York; 2002.
  • [29]Sengers BG, Please CP, Oreffo RO: Experimental characterization and computational modelling of two-dimensional cell spreading for skeletal regeneration. J R Soc Interface 2007, 4(17):1107-17.
  • [30]Savla U, Olson LE, Waters CM: Mathematical modeling of airway epithelial wound closure during cyclic mechanical strain. J Appl Physiol 2004, 96:566-74.
  • [31]Sheardown H, Cheng YL: Mechanisms of corneal epithelial wound healing. Chem Eng Sci 1996, 51(19):4517-529.
  • [32]Baldock AL, Ahn S, Rockne R, Johnston S, Neal M, Corwin D, et al.: Patient-specific metrics of invasiveness reveal significant prognostic benefit of resection in a predictable subset of gliomas. PLOS ONE 2014, 9(10):99057.
  • [33]Rockne RC, Trister AD, Jacobs J, Hawkins-Daarud AJ, Neal ML, Hendrickson K, et al.: A patient-specific computational model of hypoxia-modulated radiation resistance in glioblastoma using 18F-FMISO-PET. J R Soc Interface 2014, 12:20141174.
  • [34]Sherratt JA, Murray JD: Models of epidermal wound healing. Proc R Soc London, Ser B 1990, 241:29-36.
  • [35]Habbal A, Barelli H, Malandin G: Assessing the ability of the 2D Fisher-KPP equation to model cell-sheet wound closure. Math. Biosci 2014, 252:45-59.
  • [36]Swanson KR, Bridge C, Murray JD, Alvord Jr EC: Virtual and real brain tumors: using mathematical modeling to quantify glioma growth and invasion. J Neurol Sci 2003, 216(1):1-10.
  • [37]Scott JG, Basanta D, Anderson ARA, Gerlee P: A mathematical model of tumour self-seeding reveals secondary metastatic deposits as drivers of primary tumour growth. J R Soc Interface 2013, 10:20130011.
  • [38]Simpson MJ: Depth-averaging errors in reactive transport modeling. Water Resour Res 2009, 45:02505.
  • [39]Simpson MJ, Landman KA, Hughes BD: Multi-species simple exclusion processes. Physica A 2009, 388:399-406.
  • [40]Morton KW, Mayers DF: Numerical Solution of Partial Differential Equations. Cambridge University Press, Cambridge; 2005.
  • [41]Zheng C, Bennett GD: Applied Contaminant Transport Modeling. John Wiley and Sons, New York; 2002.
  • [42]Coleman TF, Li Y: An interior trust region approach for nonlinear minimization subject to bounds. SIAM J Optim 1996, 6(2):418-45.
  • [43]Schultz G, Chegini N, Grant M, Khaw P, MacKay S: Effects of growth factors on corneal wound healing. Acta Ophthalmol 1992, 70(S202):60-6.
  • [44]Hammond JF, Bortz DM: Analytical solutions to Fisher’s equation with time-variable coefficients. Appl Math Comput 2011, 218:2497-508.
  • [45]Curtis CW, Bortz DM: Propagation of fronts in the Fisher-Kolmogorov equation with spatially varying diffusion. Phys Rev E 2012, 86:066108.
  • [46]Keller EF, Segel LA: Model for chemotaxis. J Theor Biol 1971, 30:225-234.
  • [47]Simpson MJ, Landman KA, Hughes BD, Newgreen DF: Looking inside an invasion wave of cells using continuum models: Proliferation is the key. J Theor Biol 2006, 243:343-360.
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