ArticleBMC systems biology2015
Estimating cell diffusivity and cell proliferation rate by interpreting IncuCyte ZOOM™ assay data using the Fisher-Kolmogorov model.
Article in BMC systems biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.
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Who cites it
45 citing papers in PubMed.
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- Decoding molecular programs in melanoma brain metastases.Nature communications · 2022Article
- Computationally efficient mechanism discovery for cell invasion with uncertainty quantification.PLoS computational biology · 2022Article
- Macrophages Protect Endometriotic Cells Against Oxidative Damage Through a Cross-Talk Mechanism.Reproductive sciences (Thousand Oaks, Calif.) · 2022Article
- Enhancing Mixing Performance in a Rotating Disk Mixing Chamber: A Quantitative Investigation of the Effect of Euler and Coriolis Forces.Micromachines · 2022Article
- Multi-parametric functional imaging of cell cultures and tissues with a CMOS microelectrode array.Lab on a chip · 2022Article
- Methodology for comprehensive cell-level analysis of wound healing experiments using deep learning in MATLAB.BMC molecular and cell biology · 2021Article
- Article
- KSR1- and ERK-dependent translational regulation of the epithelial-to-mesenchymal transition.eLife · 2021Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundStandard 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.
resultsThe 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.
conclusionsOur 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.
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