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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 “hybrid extrinsic-intrinsic” model.A. Cells migrate, divide and die under the same conditions as in the “extrinsic” and “intrinsic” models. The phenotypic switch of each cell is dependent on the local cell density as in the “extrinsic” model, but the cells encountering a favourable microenvironment undergo phenotypic change with probabilities pAtoB and pBtoA. B: Results of a typical simulation of the “hybrid” model during the growth phase and at equilibrium. Note the simultaneous presence of small clusters and dispersed single type A cells. pAtoB = 0.7 and pBtoA = 0.4. C: The distribution of the number of neighbours around the A and B cells (left and right respectively) in the hybrid model. The average number of neighbours and the standard deviation are indicated for each panel. Note the more dispersed distribution of type A cell neighbours. D: Analysis of the spatial distribution randomness of SP and MP cells using Ripley's L statistics. The upper panel shows the type A cell L-function (red line) with values larger than 0 and outside the range defined by the upper-and lower-envelope functions (black line) (this indicates significant clustering of type A cells at small R distances). The type B cells (green line) are randomly distributed, because the L(h) values are close to 0 at all scales (R).
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pone-0000394-g006: The “hybrid extrinsic-intrinsic” model.A. Cells migrate, divide and die under the same conditions as in the “extrinsic” and “intrinsic” models. The phenotypic switch of each cell is dependent on the local cell density as in the “extrinsic” model, but the cells encountering a favourable microenvironment undergo phenotypic change with probabilities pAtoB and pBtoA. B: Results of a typical simulation of the “hybrid” model during the growth phase and at equilibrium. Note the simultaneous presence of small clusters and dispersed single type A cells. pAtoB = 0.7 and pBtoA = 0.4. C: The distribution of the number of neighbours around the A and B cells (left and right respectively) in the hybrid model. The average number of neighbours and the standard deviation are indicated for each panel. Note the more dispersed distribution of type A cell neighbours. D: Analysis of the spatial distribution randomness of SP and MP cells using Ripley's L statistics. The upper panel shows the type A cell L-function (red line) with values larger than 0 and outside the range defined by the upper-and lower-envelope functions (black line) (this indicates significant clustering of type A cells at small R distances). The type B cells (green line) are randomly distributed, because the L(h) values are close to 0 at all scales (R).

Mentions: The dissimilarity in the distribution of the rare phenotype SP cells in culture and the type A cells in both the “extrinsic” and “intrinsic” models indicates that the phenotypic switch (at least in our system) may follow an intermediate scheme, where each model emulates reality only partially. One possibility is that low density per se is not sufficient to generate the SP phenotype in all cells because the MP and SP phenotypes are robust and are able to resist, to some extent, microenvironmental fluctuations. To test this assumption we designed a third “hybrid” model that combined the “extrinsic” and “intrinsic” assumptions. In the “hybrid” model the phenotypic switch is triggered by the microenvironment: type A cells can switch to the type B phenotype if they have more than Nex neighbours (again, within a circular region of radius R). Type B cells can switch back only if the local cell density becomes lower than the limit Nex. However, the cells encountering a favourable microenvironment undergo phenotypic change with an intrinsic probability pAtoB and pBtoA , so a fraction of cells keep their original phenotype even in a permissive microenvironment (Fig. 6A). If pAtoB and pBtoA = 1, the model is equivalent to the “extrisic” version. The results shown in Fig. 6B were obtained by using Nex = 30 values (the same as in Fig. 3A) and the p values were fixed at pAtoB = 0.7 and pBtoA = 0.4. Although the distribution of the number of neighbours is no longer bimodal, the simulations show a type A cell neighbour distribution (Fig. 6C) reminiscent of that observed for the SP cells. This could be interpreted as an indication that the “hybrid” model matches reality better.


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 “hybrid extrinsic-intrinsic” model.A. Cells migrate, divide and die under the same conditions as in the “extrinsic” and “intrinsic” models. The phenotypic switch of each cell is dependent on the local cell density as in the “extrinsic” model, but the cells encountering a favourable microenvironment undergo phenotypic change with probabilities pAtoB and pBtoA. B: Results of a typical simulation of the “hybrid” model during the growth phase and at equilibrium. Note the simultaneous presence of small clusters and dispersed single type A cells. pAtoB = 0.7 and pBtoA = 0.4. C: The distribution of the number of neighbours around the A and B cells (left and right respectively) in the hybrid model. The average number of neighbours and the standard deviation are indicated for each panel. Note the more dispersed distribution of type A cell neighbours. D: Analysis of the spatial distribution randomness of SP and MP cells using Ripley's L statistics. The upper panel shows the type A cell L-function (red line) with values larger than 0 and outside the range defined by the upper-and lower-envelope functions (black line) (this indicates significant clustering of type A cells at small R distances). The type B cells (green line) are randomly distributed, because the L(h) values are close to 0 at all scales (R).
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC1851097&req=5

pone-0000394-g006: The “hybrid extrinsic-intrinsic” model.A. Cells migrate, divide and die under the same conditions as in the “extrinsic” and “intrinsic” models. The phenotypic switch of each cell is dependent on the local cell density as in the “extrinsic” model, but the cells encountering a favourable microenvironment undergo phenotypic change with probabilities pAtoB and pBtoA. B: Results of a typical simulation of the “hybrid” model during the growth phase and at equilibrium. Note the simultaneous presence of small clusters and dispersed single type A cells. pAtoB = 0.7 and pBtoA = 0.4. C: The distribution of the number of neighbours around the A and B cells (left and right respectively) in the hybrid model. The average number of neighbours and the standard deviation are indicated for each panel. Note the more dispersed distribution of type A cell neighbours. D: Analysis of the spatial distribution randomness of SP and MP cells using Ripley's L statistics. The upper panel shows the type A cell L-function (red line) with values larger than 0 and outside the range defined by the upper-and lower-envelope functions (black line) (this indicates significant clustering of type A cells at small R distances). The type B cells (green line) are randomly distributed, because the L(h) values are close to 0 at all scales (R).
Mentions: The dissimilarity in the distribution of the rare phenotype SP cells in culture and the type A cells in both the “extrinsic” and “intrinsic” models indicates that the phenotypic switch (at least in our system) may follow an intermediate scheme, where each model emulates reality only partially. One possibility is that low density per se is not sufficient to generate the SP phenotype in all cells because the MP and SP phenotypes are robust and are able to resist, to some extent, microenvironmental fluctuations. To test this assumption we designed a third “hybrid” model that combined the “extrinsic” and “intrinsic” assumptions. In the “hybrid” model the phenotypic switch is triggered by the microenvironment: type A cells can switch to the type B phenotype if they have more than Nex neighbours (again, within a circular region of radius R). Type B cells can switch back only if the local cell density becomes lower than the limit Nex. However, the cells encountering a favourable microenvironment undergo phenotypic change with an intrinsic probability pAtoB and pBtoA , so a fraction of cells keep their original phenotype even in a permissive microenvironment (Fig. 6A). If pAtoB and pBtoA = 1, the model is equivalent to the “extrisic” version. The results shown in Fig. 6B were obtained by using Nex = 30 values (the same as in Fig. 3A) and the p values were fixed at pAtoB = 0.7 and pBtoA = 0.4. Although the distribution of the number of neighbours is no longer bimodal, the simulations show a type A cell neighbour distribution (Fig. 6C) reminiscent of that observed for the SP cells. This could be interpreted as an indication that the “hybrid” model matches reality better.

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.

Show MeSH
Related in: MedlinePlus