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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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Localization of the SP cells in the growing population of C2C12 cells.A: The SP cells were identified on the basis of their capacity to exclude the fluorescent dye Hoechst 33342. Four representative images (a, b, c and d) are shown from regions with different cell densities. The nuclei are shown in false color (red for SP cells and green for MP cells). B: The frequency distribution of the number of neighbours is significantly different for SP and MP cells (upper and lower panel). The average number of neighbours is shown on the left side of each panel. Note the bimodal distribution for SP cells. The number of neighbours for each cell in a circle of R = 15 µm was calculated on the basis of the digitalized images. The two distributions were found to be significantly different (p<0.001) as analysed by the non-parametric Wilcoxon-Rank-Sum test. C: Analysis of the spatial randomness of SP cell distribution using Ripley's L statistics of the four images shown in Fig. 5A. The red lines indicate the L-functions for the SP cells over a range of r = 100. The black lines show the upper and lower limits of the envelope functions for the images analysed. The c and d patterns are significantly different from a random pattern, because the values of the observed L-function are larger than the upper envelope function while the two other L-functions (panels a and b) indicate homogeneously distributed SP cells on the corresponding images.
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pone-0000394-g005: Localization of the SP cells in the growing population of C2C12 cells.A: The SP cells were identified on the basis of their capacity to exclude the fluorescent dye Hoechst 33342. Four representative images (a, b, c and d) are shown from regions with different cell densities. The nuclei are shown in false color (red for SP cells and green for MP cells). B: The frequency distribution of the number of neighbours is significantly different for SP and MP cells (upper and lower panel). The average number of neighbours is shown on the left side of each panel. Note the bimodal distribution for SP cells. The number of neighbours for each cell in a circle of R = 15 µm was calculated on the basis of the digitalized images. The two distributions were found to be significantly different (p<0.001) as analysed by the non-parametric Wilcoxon-Rank-Sum test. C: Analysis of the spatial randomness of SP cell distribution using Ripley's L statistics of the four images shown in Fig. 5A. The red lines indicate the L-functions for the SP cells over a range of r = 100. The black lines show the upper and lower limits of the envelope functions for the images analysed. The c and d patterns are significantly different from a random pattern, because the values of the observed L-function are larger than the upper envelope function while the two other L-functions (panels a and b) indicate homogeneously distributed SP cells on the corresponding images.

Mentions: The computer simulations show that both the “intrinsic” and “extrinsic” mechanisms are able to generate heterogeneous populations of cells with a stable proportion of the two cell types. The comparison of the “intrinsic” and “extrinsic” models provided testable predictions. Type A cells in the “extrinsic” model had on average fewer neighbours than B cells (Fig. 3B). Since the A to B switch was defined as a function of the local cell density, this was expected. An unforeseen consequence, however, was that the rare phenotype A tended to form clusters while the B cells are distributed randomly. The “intrinsic” model instead produced A cells distributed randomly and which had on average the same number of neighbours as B cells. These distinctive features in the two models was investigated experimentally using the C2C12 myogenic cell line. There are two subpopulations in the cultures of these cells: the rare stem-like SP (A cells in the model) and the myoblast-like MP cells (B cells in the model). The SP cells can differentiate into MP cells and vice versa. Analysis of the spatial distribution of the SP cells provides an experimental test for the model prediction, because clustering of the A cells in the “extrinsic” model was more apparent when the frequency of these cells was low. We then examined the distribution of the SP cells in cultures of C2C12 cells. To do this, cells were grown in vitro and stained using Hoechst 33342 dye in the culture dish. Instead of analysing the fluorescence intensity of the nuclei by cytometry, we acquired nuclear images by two photon microscopy. Since the size of the cell population was considerably large, images from separate fields were acquired and analysed as statistical samples of the whole population. The analysis was performed using image segmentation software (developed in our laboratory) which makes possible the automatic measurement of the fluorescence intensity of the nuclei while also recording the position within the culture. Since SP cells represent only a small fraction of the population, it is necessary to analyse large numbers of cells to find enough SP cells for statistical analysis. The blue and red Hoechst 33342 fluorescence intensity of 5900 cells was analysed. Only 71 (1.2%) were identified as SP cells within the limits defined by the usual criteria. The results are shown in Fig. 5A. Many SP cells formed small groups in the regions with relatively low cell density on the periphery of the growing cell population. However, numerous MP cells were also found in these low dense regions, indicating that low density per se may not be sufficient to generate the SP phenotype. On the other hand, many SP cells were found in the regions of high cell density. These cells did not form groups; they were dispersed in a high density MP environment (Fig. 3A). The number of neighbours around the SP cells had a bimodal frequency distribution (Fig. 5B), suggesting the existence of two distinct subpopulations. The frequency distribution of the neighbours (a measure of the local cell density) for SP and MP cells is significantly different (Wilcoxon-Rank-Sum test, p<0.001). In order to determine whether the spatial distribution of SP cells shows significant clustering, we used Ripley's L-statistics. Since the whole cell population in the culture-dish can not be analysed on a single image due to its large size, the analysis was done on separate sample images. Significant clustering was found only for SP cells in low density regions, while the distribution in the high density regions it did not significantly differ from the uniform pattern. On Fig. 5C we show two examples of statistics for clustering and two for homogeneous distributions of SP cells. Interestingly, the MP cells also show clustering over a wide scale of distances, suggesting that the randomization of the pattern by cell migration and death was incomplete in the analysed growing population.


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)

Localization of the SP cells in the growing population of C2C12 cells.A: The SP cells were identified on the basis of their capacity to exclude the fluorescent dye Hoechst 33342. Four representative images (a, b, c and d) are shown from regions with different cell densities. The nuclei are shown in false color (red for SP cells and green for MP cells). B: The frequency distribution of the number of neighbours is significantly different for SP and MP cells (upper and lower panel). The average number of neighbours is shown on the left side of each panel. Note the bimodal distribution for SP cells. The number of neighbours for each cell in a circle of R = 15 µm was calculated on the basis of the digitalized images. The two distributions were found to be significantly different (p<0.001) as analysed by the non-parametric Wilcoxon-Rank-Sum test. C: Analysis of the spatial randomness of SP cell distribution using Ripley's L statistics of the four images shown in Fig. 5A. The red lines indicate the L-functions for the SP cells over a range of r = 100. The black lines show the upper and lower limits of the envelope functions for the images analysed. The c and d patterns are significantly different from a random pattern, because the values of the observed L-function are larger than the upper envelope function while the two other L-functions (panels a and b) indicate homogeneously distributed SP cells on the corresponding images.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC1851097&req=5

pone-0000394-g005: Localization of the SP cells in the growing population of C2C12 cells.A: The SP cells were identified on the basis of their capacity to exclude the fluorescent dye Hoechst 33342. Four representative images (a, b, c and d) are shown from regions with different cell densities. The nuclei are shown in false color (red for SP cells and green for MP cells). B: The frequency distribution of the number of neighbours is significantly different for SP and MP cells (upper and lower panel). The average number of neighbours is shown on the left side of each panel. Note the bimodal distribution for SP cells. The number of neighbours for each cell in a circle of R = 15 µm was calculated on the basis of the digitalized images. The two distributions were found to be significantly different (p<0.001) as analysed by the non-parametric Wilcoxon-Rank-Sum test. C: Analysis of the spatial randomness of SP cell distribution using Ripley's L statistics of the four images shown in Fig. 5A. The red lines indicate the L-functions for the SP cells over a range of r = 100. The black lines show the upper and lower limits of the envelope functions for the images analysed. The c and d patterns are significantly different from a random pattern, because the values of the observed L-function are larger than the upper envelope function while the two other L-functions (panels a and b) indicate homogeneously distributed SP cells on the corresponding images.
Mentions: The computer simulations show that both the “intrinsic” and “extrinsic” mechanisms are able to generate heterogeneous populations of cells with a stable proportion of the two cell types. The comparison of the “intrinsic” and “extrinsic” models provided testable predictions. Type A cells in the “extrinsic” model had on average fewer neighbours than B cells (Fig. 3B). Since the A to B switch was defined as a function of the local cell density, this was expected. An unforeseen consequence, however, was that the rare phenotype A tended to form clusters while the B cells are distributed randomly. The “intrinsic” model instead produced A cells distributed randomly and which had on average the same number of neighbours as B cells. These distinctive features in the two models was investigated experimentally using the C2C12 myogenic cell line. There are two subpopulations in the cultures of these cells: the rare stem-like SP (A cells in the model) and the myoblast-like MP cells (B cells in the model). The SP cells can differentiate into MP cells and vice versa. Analysis of the spatial distribution of the SP cells provides an experimental test for the model prediction, because clustering of the A cells in the “extrinsic” model was more apparent when the frequency of these cells was low. We then examined the distribution of the SP cells in cultures of C2C12 cells. To do this, cells were grown in vitro and stained using Hoechst 33342 dye in the culture dish. Instead of analysing the fluorescence intensity of the nuclei by cytometry, we acquired nuclear images by two photon microscopy. Since the size of the cell population was considerably large, images from separate fields were acquired and analysed as statistical samples of the whole population. The analysis was performed using image segmentation software (developed in our laboratory) which makes possible the automatic measurement of the fluorescence intensity of the nuclei while also recording the position within the culture. Since SP cells represent only a small fraction of the population, it is necessary to analyse large numbers of cells to find enough SP cells for statistical analysis. The blue and red Hoechst 33342 fluorescence intensity of 5900 cells was analysed. Only 71 (1.2%) were identified as SP cells within the limits defined by the usual criteria. The results are shown in Fig. 5A. Many SP cells formed small groups in the regions with relatively low cell density on the periphery of the growing cell population. However, numerous MP cells were also found in these low dense regions, indicating that low density per se may not be sufficient to generate the SP phenotype. On the other hand, many SP cells were found in the regions of high cell density. These cells did not form groups; they were dispersed in a high density MP environment (Fig. 3A). The number of neighbours around the SP cells had a bimodal frequency distribution (Fig. 5B), suggesting the existence of two distinct subpopulations. The frequency distribution of the neighbours (a measure of the local cell density) for SP and MP cells is significantly different (Wilcoxon-Rank-Sum test, p<0.001). In order to determine whether the spatial distribution of SP cells shows significant clustering, we used Ripley's L-statistics. Since the whole cell population in the culture-dish can not be analysed on a single image due to its large size, the analysis was done on separate sample images. Significant clustering was found only for SP cells in low density regions, while the distribution in the high density regions it did not significantly differ from the uniform pattern. On Fig. 5C we show two examples of statistics for clustering and two for homogeneous distributions of SP cells. Interestingly, the MP cells also show clustering over a wide scale of distances, suggesting that the randomization of the pattern by cell migration and death was incomplete in the analysed growing population.

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