Modeling Epithelial Cell Behavior and Organization

Maheswaran, Satheesh; Speight, Paul M.; Hammond, Peter

doi:10.1109/tnb.2007.891907

Cited by 8 publications

(6 citation statements)

References 27 publications

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“…This aspect of our model is distinct from previously published mathematical models for normal human skin. [32][33][34][35][36][37][38][39] Here, we assume that the initial system state for the irradiation experiments occurs at 3 weeks after seeding, with the experimental observation window indicated in Fig. 1C and D (see vertical dashed lines).…”

Section: Resultsmentioning

confidence: 99%

“…We constructed a stochastic ABM for the epidermal layer of the skin equivalent that is based on several published models for normal human skin. [32][33][34][35][36][37][38][39] We used the simplest possible model formulation (parsimonious) necessary to analyze the data, and did not explicitly track the spatial positions of the nuclei. The base model for the tissue incorporates the normal epidermal processes that occur in the absence of radiation.…”

Section: Mathematical Model For Cell Proliferation and Differentiatio...mentioning

confidence: 99%

“…29 ABMs have been used in a cell culture context to understand keratinocyte colony formation, 30 and to analyze radiation effects on mammary epithelial cells. 31 Importantly, ABMs have been extensively applied to model cell behaviors within the stratified epidermal layer of human skin, including homeostatic mechanisms in normal skin, and their disruption in conditions such as psoriasis, [32][33][34][35][36][37][38][39] cell proliferation and migration during wound healing 40 and the promotion of a population of melanocytes in skin tissue. 38 These previous models replicated the steady-state homeostatic behavior of normal human skin with the aim of integrating experimental data.…”

Section: Introductionmentioning

confidence: 99%

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Integrated experimental and computational approach to understand the effects of heavy ion radiation on skin homeostasis

Neubeck

Shankaran

Geniza

et al. 2013

Integrative Biology

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The effects of low dose high linear energy transfer (LET) radiation on human health are of concern for space, occupational, and clinical exposures. As epidemiological data for such radiation exposures are scarce for making relevant predictions, we need to understand the mechanism of response especially in normal tissues. Our objective here is to understand the effects of heavy ion radiation on tissue homeostasis in a realistic model system. Towards this end, we exposed an in vitro three dimensional skin equivalent to low fluences of neon (Ne) ions (300 MeV u(-1)), and determined the differentiation profile as a function of time following exposure using immunohistochemistry. We found that Ne ion exposures resulted in transient increases in the tissue regions expressing the differentiation markers keratin 10, and filaggrin, and more subtle time-dependent effects on the number of basal cells in the epidermis. We analyzed the data using a mathematical model of the skin equivalent, to quantify the effect of radiation on cell proliferation and differentiation. The agent-based mathematical model for the epidermal layer treats the epidermis as a collection of heterogeneous cell types with different proliferation-differentiation properties. We obtained model parameters from the literature where available, and calibrated the unknown parameters to match the observed properties in unirradiated skin. We then used the model to rigorously examine alternate hypotheses regarding the effects of high LET radiation on the tissue. Our analysis indicates that Ne ion exposures induce rapid, but transient, changes in cell division, differentiation and proliferation. We have validated the modeling results by histology and quantitative reverse transcription polymerase chain reaction (qRT-PCR). The integrated approach presented here can be used as a general framework to understand the responses of multicellular systems, and can be adapted to other epithelial tissues.

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Section: Resultsmentioning

confidence: 99%

Section: Mathematical Model For Cell Proliferation and Differentiatio...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Integrated experimental and computational approach to understand the effects of heavy ion radiation on skin homeostasis

Neubeck

Shankaran

Geniza

et al. 2013

Integrative Biology

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“…Bindschadler and McGrath92 used an agent‐based model of a cell with crawling and growth dynamics to study scratch‐wound healing. Maheswaran et al 93 have used an individual‐based model to study epithelial development.…”

Section: Models Of Epithelial Tissuementioning

confidence: 99%

Computational modeling of epithelial tissues

Smallwood

2009

WIREs Mechanisms of Disease

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There is an extensive literature on the computational modeling of epithelial tissues at all levels from subcellular to whole tissue. This review concentrates on behavior at the individual cell to whole tissue level, and particularly on organizational aspects, and provides an indication of where information from other areas, such as the modeling of angiogenesis, is relevant. The skin, and the lining of all of the body cavities (lung, gut, cervix, bladder etc) are epithelial tissues, which in a topological sense are the boundary between inside and outside the body. They are thin sheets of cells (usually of the order of 0.5 mm thick) without extracellular matrix, have a relatively simple structure, and contain few types of cells. They have important barrier, secretory and transport functions, which are essential for the maintenance of life, so homeostasis and wound healing are important aspects of the behavior of epithelial tissues. Carcinomas originate in epithelial tissues.There are essentially two approaches to modeling tissues--to start at the level of the tissue (i.e., a length scale of the order of 1 mm) and develop generalized equations for behavior (a continuum approach); or to start at the level of the cell (i.e., a length scale of the order of 10 µm) and develop tissue behavior as an emergent property of cellular behavior (an individual-based approach). As will be seen, these are not mutually exclusive approaches, and they come in a variety of flavors.

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“…During the last two decades, much work has been devoted to studying different aspects of epithelial patterns due to their importance for a variety of biological functions (14,(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29). Epithelia are layers of cells that line the surfaces of organs and cover the exterior of the animal body.…”

Section: Introductionmentioning

confidence: 99%

Structural Characterization and Statistical-Mechanical Model of Epidermal Patterns

Chen

Devenport

et al. 2016

Biophysical Journal

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In proliferating epithelia of mammalian skin, cells of irregular polygon-like shapes pack into complex, nearly flat two-dimensional structures that are pliable to deformations. In this work, we employ various sensitive correlation functions to quantitatively characterize structural features of evolving packings of epithelial cells across length scales in mouse skin. We find that the pair statistics in direct space (correlation function) and Fourier space (structure factor) of the cell centroids in the early stages of embryonic development show structural directional dependence (statistical anisotropy), which is a reflection of the fact that cells are stretched, which promotes uniaxial growth along the epithelial plane. In the late stages, the patterns tend toward statistically isotropic states, as cells attain global polarization and epidermal growth shifts to produce the skin's outer stratified layers. We construct a minimalist four-component statistical-mechanical model involving effective isotropic pair interactions consisting of hard-core repulsion and extra short-range soft-core repulsion beyond the hard core, whose length scale is roughly the same as the hard core. The model parameters are optimized to match the sample pair statistics in both direct and Fourier spaces. By doing this, the parameters are biologically constrained. In contrast with many vertex-based models, our statistical-mechanical model does not explicitly incorporate information about the cell shapes and interfacial energy between cells; nonetheless, our model predicts essentially the same polygonal shape distribution and size disparity of cells found in experiments, as measured by Voronoi statistics. Moreover, our simulated equilibrium liquid-like configurations are able to match other nontrivial unconstrained statistics, which is a testament to the power and novelty of the model. The array of structural descriptors that we deploy enable us to distinguish between normal, mechanically deformed, and pathological skin tissues. Our statistical-mechanical model enables one to generate tissue microstructure at will for further analysis. We also discuss ways in which our model might be extended to better understand morphogenesis (in particular the emergence of planar cell polarity), wound healing, and disease-progression processes in skin, and how it could be applied to the design of synthetic tissues.

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Modeling Epithelial Cell Behavior and Organization

Cited by 8 publications

References 27 publications

Integrated experimental and computational approach to understand the effects of heavy ion radiation on skin homeostasis

Integrated experimental and computational approach to understand the effects of heavy ion radiation on skin homeostasis

Computational modeling of epithelial tissues

Structural Characterization and Statistical-Mechanical Model of Epidermal Patterns

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