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The origin of phenotypic heterogeneity in a clonal cell population in vitro.

Stockholm D, Benchaouir R, Picot J, Rameau P, Neildez TM, Landini G, Laplace-Builhé C, Paldi A - PLoS ONE (2007)

Bottom Line: The key predictions of the two models were confronted with the results obtained experimentally using a myogenic cell line.The observations emphasize the importance of the "ecological" context and suggest that, consistently with the "extrinsic" model, local stochastic interactions between phenotypically identical cells play a key role in the initiation of phenotypic switch.Nevertheless, the "intrinsic" model also shows some other aspects of reality: The phenotypic switch is not triggered exclusively by the local environmental variations, but also depends to some extent on the phenotypic intrinsic robustness of the cells.

View Article: PubMed Central - PubMed

Affiliation: GENETHON-Centre National de la Recherche Scientifique (CNRS), UMR 8115, Evry, France.

ABSTRACT

Background: The spontaneous emergence of phenotypic heterogeneity in clonal populations of mammalian cells in vitro is a rule rather than an exception. We consider two simple, mutually non-exclusive models that explain the generation of diverse cell types in a homogeneous population. In the first model, the phenotypic switch is the consequence of extrinsic factors. Initially identical cells may become different because they encounter different local environments that induce adaptive responses. According to the second model, the phenotypic switch is intrinsic to the cells that may occur even in homogeneous environments.

Principal findings: We have investigated the "extrinsic" and the "intrinsic" mechanisms using computer simulations and experimentation. First, we simulated in silico the emergence of two cell types in a clonal cell population using a multiagent model. Both mechanisms produced stable phenotypic heterogeneity, but the distribution of the cell types was different. The "intrinsic" model predicted an even distribution of the rare phenotype cells, while in the "extrinsic" model these cells formed small clusters. The key predictions of the two models were confronted with the results obtained experimentally using a myogenic cell line.

Conclusions: The observations emphasize the importance of the "ecological" context and suggest that, consistently with the "extrinsic" model, local stochastic interactions between phenotypically identical cells play a key role in the initiation of phenotypic switch. Nevertheless, the "intrinsic" model also shows some other aspects of reality: The phenotypic switch is not triggered exclusively by the local environmental variations, but also depends to some extent on the phenotypic intrinsic robustness of the cells.

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The “intrinsic” model.A: Results of the “intrinsic” model simulations for large values for pBtoA. Note corresponding increase in proportion of type A cells (in red) and their random distribution. B: Analysis of type A (left panel) and type B (right panel) cell distributions in the “intrinsic” model as a function of average migration velocity using the standardized nearest neighbour distance (w). If w = 1, the cells are randomly distributed. Small standardized nearest neighbour distances (w<1) indicate clustering; this is only observed for B cells with very low average migration velocities (<0.2). In these examples pAtoB = 0.7 and pBtoA = 0.02, but similar results were obtained for other values of p.
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pone-0000394-g002: The “intrinsic” model.A: Results of the “intrinsic” model simulations for large values for pBtoA. Note corresponding increase in proportion of type A cells (in red) and their random distribution. B: Analysis of type A (left panel) and type B (right panel) cell distributions in the “intrinsic” model as a function of average migration velocity using the standardized nearest neighbour distance (w). If w = 1, the cells are randomly distributed. Small standardized nearest neighbour distances (w<1) indicate clustering; this is only observed for B cells with very low average migration velocities (<0.2). In these examples pAtoB = 0.7 and pBtoA = 0.02, but similar results were obtained for other values of p.

Mentions: In the “intrinsic” model we addressed the question of cell autonomy of the phenotypic switch. At each simulation step, type A cells have a fixed probability pAtoB to transform into B cells, and B cells have a probability pBtoA to become A cells (the environment plays no role in the switching). The simulations start with a single A cell which replicates to fill the available space, reaching a maximum size at an equilibrium between growth and death. B cells appear with a frequency determined by pAtoB. We explored the effects of varying the values of pAtoB and pBtoA between 0 and 0.5. If pBtoA = 0, B cells overgrow A cells and the whole population becomes B type. If B cells can switch to A (pBtoA≠0), the size of the two subpopulations, [A] and [B], reaches a steady state equilibrium with a ratio [A]/[B] that depends on pBtoA/pAtoB. (Fig. 2A). The spacial randomness of cell distribution was estimated by the calculation of the standardized nearest neighbour distance (w). The two cell types are distributed randomly in the population both during a) the growth phase and b) at the equilibrium when velocity values are higher than 0.2 (Fig. 2B). This suggests that the random element in cell type spatial distribution is a generic property of the “intrinsic” model.


The origin of phenotypic heterogeneity in a clonal cell population in vitro.

Stockholm D, Benchaouir R, Picot J, Rameau P, Neildez TM, Landini G, Laplace-Builhé C, Paldi A - PLoS ONE (2007)

The “intrinsic” model.A: Results of the “intrinsic” model simulations for large values for pBtoA. Note corresponding increase in proportion of type A cells (in red) and their random distribution. B: Analysis of type A (left panel) and type B (right panel) cell distributions in the “intrinsic” model as a function of average migration velocity using the standardized nearest neighbour distance (w). If w = 1, the cells are randomly distributed. Small standardized nearest neighbour distances (w<1) indicate clustering; this is only observed for B cells with very low average migration velocities (<0.2). In these examples pAtoB = 0.7 and pBtoA = 0.02, but similar results were obtained for other values of p.
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC1851097&req=5

pone-0000394-g002: The “intrinsic” model.A: Results of the “intrinsic” model simulations for large values for pBtoA. Note corresponding increase in proportion of type A cells (in red) and their random distribution. B: Analysis of type A (left panel) and type B (right panel) cell distributions in the “intrinsic” model as a function of average migration velocity using the standardized nearest neighbour distance (w). If w = 1, the cells are randomly distributed. Small standardized nearest neighbour distances (w<1) indicate clustering; this is only observed for B cells with very low average migration velocities (<0.2). In these examples pAtoB = 0.7 and pBtoA = 0.02, but similar results were obtained for other values of p.
Mentions: In the “intrinsic” model we addressed the question of cell autonomy of the phenotypic switch. At each simulation step, type A cells have a fixed probability pAtoB to transform into B cells, and B cells have a probability pBtoA to become A cells (the environment plays no role in the switching). The simulations start with a single A cell which replicates to fill the available space, reaching a maximum size at an equilibrium between growth and death. B cells appear with a frequency determined by pAtoB. We explored the effects of varying the values of pAtoB and pBtoA between 0 and 0.5. If pBtoA = 0, B cells overgrow A cells and the whole population becomes B type. If B cells can switch to A (pBtoA≠0), the size of the two subpopulations, [A] and [B], reaches a steady state equilibrium with a ratio [A]/[B] that depends on pBtoA/pAtoB. (Fig. 2A). The spacial randomness of cell distribution was estimated by the calculation of the standardized nearest neighbour distance (w). The two cell types are distributed randomly in the population both during a) the growth phase and b) at the equilibrium when velocity values are higher than 0.2 (Fig. 2B). This suggests that the random element in cell type spatial distribution is a generic property of the “intrinsic” model.

Bottom Line: The key predictions of the two models were confronted with the results obtained experimentally using a myogenic cell line.The observations emphasize the importance of the "ecological" context and suggest that, consistently with the "extrinsic" model, local stochastic interactions between phenotypically identical cells play a key role in the initiation of phenotypic switch.Nevertheless, the "intrinsic" model also shows some other aspects of reality: The phenotypic switch is not triggered exclusively by the local environmental variations, but also depends to some extent on the phenotypic intrinsic robustness of the cells.

View Article: PubMed Central - PubMed

Affiliation: GENETHON-Centre National de la Recherche Scientifique (CNRS), UMR 8115, Evry, France.

ABSTRACT

Background: The spontaneous emergence of phenotypic heterogeneity in clonal populations of mammalian cells in vitro is a rule rather than an exception. We consider two simple, mutually non-exclusive models that explain the generation of diverse cell types in a homogeneous population. In the first model, the phenotypic switch is the consequence of extrinsic factors. Initially identical cells may become different because they encounter different local environments that induce adaptive responses. According to the second model, the phenotypic switch is intrinsic to the cells that may occur even in homogeneous environments.

Principal findings: We have investigated the "extrinsic" and the "intrinsic" mechanisms using computer simulations and experimentation. First, we simulated in silico the emergence of two cell types in a clonal cell population using a multiagent model. Both mechanisms produced stable phenotypic heterogeneity, but the distribution of the cell types was different. The "intrinsic" model predicted an even distribution of the rare phenotype cells, while in the "extrinsic" model these cells formed small clusters. The key predictions of the two models were confronted with the results obtained experimentally using a myogenic cell line.

Conclusions: The observations emphasize the importance of the "ecological" context and suggest that, consistently with the "extrinsic" model, local stochastic interactions between phenotypically identical cells play a key role in the initiation of phenotypic switch. Nevertheless, the "intrinsic" model also shows some other aspects of reality: The phenotypic switch is not triggered exclusively by the local environmental variations, but also depends to some extent on the phenotypic intrinsic robustness of the cells.

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