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Theoretical basis of the community effect in development.

Saka Y, Lhoussaine C, Kuttler C, Ullner E, Thiel M - BMC Syst Biol (2011)

Bottom Line: We have derived the analytical formula for the threshold size of a cell population that is necessary for a community effect, which is in good agreement with stochastic simulation results.The mechanism of the community effect revealed by our theoretical analysis is analogous to that of quorum sensing in bacteria.The community effect may underlie the size control in animal development and also the genesis of autosomal dominant diseases including tumorigenesis.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institute of Medical Sciences, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD, UK. y.saka@abdn.ac.uk

ABSTRACT

Background: Genetically identical cells often show significant variation in gene expression profile and behaviour even in the same physiological condition. Notably, embryonic cells destined to the same tissue maintain a uniform transcriptional regulatory state and form a homogeneous cell group. One mechanism to keep the homogeneity within embryonic tissues is the so-called community effect in animal development. The community effect is an interaction among a group of many nearby precursor cells, and is necessary for them to maintain tissue-specific gene expression and differentiate in a coordinated manner. Although it has been shown that the cell-cell communication by a diffusible factor plays a crucial role, it is not immediately obvious why a community effect needs many cells.

Results: In this work, we propose a model of the community effect in development, which consists in a linear gene cascade and cell-cell communication. We examined the properties of the model theoretically using a combination of stochastic and deterministic modelling methods. We have derived the analytical formula for the threshold size of a cell population that is necessary for a community effect, which is in good agreement with stochastic simulation results.

Conclusions: Our theoretical analysis indicates that a simple model with a linear gene cascade and cell-cell communication is sufficient to reproduce the community effect in development. The model explains why a community needs many cells. It suggests that the community's long-term behaviour is independent of the initial induction level, although the initiation of a community effect requires a sufficient amount of inducing signal. The mechanism of the community effect revealed by our theoretical analysis is analogous to that of quorum sensing in bacteria. The community effect may underlie the size control in animal development and also the genesis of autosomal dominant diseases including tumorigenesis.

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Influence of gene copy number on gene expressions at steady state. (A) Probability distribution of [Ap] at the end of stochastic simulations for the community size n = 100 (t = 10000 min). Plots for different combinations of gene copy numbers are shown as indicated. (B) [Ap] at steady state ([Ap]*) is plotted as a function of community size for different gene copy numbers as indicated. [Ap]* is calculated according to Eqs.35 in additional file 1 with parameter values in Table 1, ε = 5.78 × 10 -7. Dotted lines are the theoretical maxima . (C) [Bpout] at steady state ([Bpout]*) is plotted as a function of community size for different gene copy numbers. Parameter values are the same as in (B). [Bpout]* also approaches to the theoretical upper limit  (not shown;  ≈ 358000 for a = 2, b = 2; 308000 for a = 1, b = 2; 172000 for a = 2, b = 1; 143000 for a = 1, b = 1).
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Figure 6: Influence of gene copy number on gene expressions at steady state. (A) Probability distribution of [Ap] at the end of stochastic simulations for the community size n = 100 (t = 10000 min). Plots for different combinations of gene copy numbers are shown as indicated. (B) [Ap] at steady state ([Ap]*) is plotted as a function of community size for different gene copy numbers as indicated. [Ap]* is calculated according to Eqs.35 in additional file 1 with parameter values in Table 1, ε = 5.78 × 10 -7. Dotted lines are the theoretical maxima . (C) [Bpout] at steady state ([Bpout]*) is plotted as a function of community size for different gene copy numbers. Parameter values are the same as in (B). [Bpout]* also approaches to the theoretical upper limit (not shown; ≈ 358000 for a = 2, b = 2; 308000 for a = 1, b = 2; 172000 for a = 2, b = 1; 143000 for a = 1, b = 1).

Mentions: Figure 6A shows that the heterozygous diploid cell community (a = 1, b = 2 or a = 2, b = 1) have a diminished expression of gene A (and gene B, data not shown) compared to the homozygous diploid cell community (a = 2, b = 2). Figure 6B shows [Ap] at steady state ([Ap]*) as a function of community size n with different gene copy numbers. The plot indicates that, even when cells in the community continue to proliferate, [Ap]* (and also [Bpin]*, data not shown) of the heterozygous diploid cells never reaches that of normal homozygous cells. The analysis revealed that [Ap]* has a theoretical upper limit (dotted lines in Figure 6B). Therefore, the compromised gene expression in the heterozygous diploid cell community cannot be compensated by increasing its population size.


Theoretical basis of the community effect in development.

Saka Y, Lhoussaine C, Kuttler C, Ullner E, Thiel M - BMC Syst Biol (2011)

Influence of gene copy number on gene expressions at steady state. (A) Probability distribution of [Ap] at the end of stochastic simulations for the community size n = 100 (t = 10000 min). Plots for different combinations of gene copy numbers are shown as indicated. (B) [Ap] at steady state ([Ap]*) is plotted as a function of community size for different gene copy numbers as indicated. [Ap]* is calculated according to Eqs.35 in additional file 1 with parameter values in Table 1, ε = 5.78 × 10 -7. Dotted lines are the theoretical maxima . (C) [Bpout] at steady state ([Bpout]*) is plotted as a function of community size for different gene copy numbers. Parameter values are the same as in (B). [Bpout]* also approaches to the theoretical upper limit  (not shown;  ≈ 358000 for a = 2, b = 2; 308000 for a = 1, b = 2; 172000 for a = 2, b = 1; 143000 for a = 1, b = 1).
© Copyright Policy - open-access
Related In: Results  -  Collection

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Show All Figures
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Figure 6: Influence of gene copy number on gene expressions at steady state. (A) Probability distribution of [Ap] at the end of stochastic simulations for the community size n = 100 (t = 10000 min). Plots for different combinations of gene copy numbers are shown as indicated. (B) [Ap] at steady state ([Ap]*) is plotted as a function of community size for different gene copy numbers as indicated. [Ap]* is calculated according to Eqs.35 in additional file 1 with parameter values in Table 1, ε = 5.78 × 10 -7. Dotted lines are the theoretical maxima . (C) [Bpout] at steady state ([Bpout]*) is plotted as a function of community size for different gene copy numbers. Parameter values are the same as in (B). [Bpout]* also approaches to the theoretical upper limit (not shown; ≈ 358000 for a = 2, b = 2; 308000 for a = 1, b = 2; 172000 for a = 2, b = 1; 143000 for a = 1, b = 1).
Mentions: Figure 6A shows that the heterozygous diploid cell community (a = 1, b = 2 or a = 2, b = 1) have a diminished expression of gene A (and gene B, data not shown) compared to the homozygous diploid cell community (a = 2, b = 2). Figure 6B shows [Ap] at steady state ([Ap]*) as a function of community size n with different gene copy numbers. The plot indicates that, even when cells in the community continue to proliferate, [Ap]* (and also [Bpin]*, data not shown) of the heterozygous diploid cells never reaches that of normal homozygous cells. The analysis revealed that [Ap]* has a theoretical upper limit (dotted lines in Figure 6B). Therefore, the compromised gene expression in the heterozygous diploid cell community cannot be compensated by increasing its population size.

Bottom Line: We have derived the analytical formula for the threshold size of a cell population that is necessary for a community effect, which is in good agreement with stochastic simulation results.The mechanism of the community effect revealed by our theoretical analysis is analogous to that of quorum sensing in bacteria.The community effect may underlie the size control in animal development and also the genesis of autosomal dominant diseases including tumorigenesis.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institute of Medical Sciences, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD, UK. y.saka@abdn.ac.uk

ABSTRACT

Background: Genetically identical cells often show significant variation in gene expression profile and behaviour even in the same physiological condition. Notably, embryonic cells destined to the same tissue maintain a uniform transcriptional regulatory state and form a homogeneous cell group. One mechanism to keep the homogeneity within embryonic tissues is the so-called community effect in animal development. The community effect is an interaction among a group of many nearby precursor cells, and is necessary for them to maintain tissue-specific gene expression and differentiate in a coordinated manner. Although it has been shown that the cell-cell communication by a diffusible factor plays a crucial role, it is not immediately obvious why a community effect needs many cells.

Results: In this work, we propose a model of the community effect in development, which consists in a linear gene cascade and cell-cell communication. We examined the properties of the model theoretically using a combination of stochastic and deterministic modelling methods. We have derived the analytical formula for the threshold size of a cell population that is necessary for a community effect, which is in good agreement with stochastic simulation results.

Conclusions: Our theoretical analysis indicates that a simple model with a linear gene cascade and cell-cell communication is sufficient to reproduce the community effect in development. The model explains why a community needs many cells. It suggests that the community's long-term behaviour is independent of the initial induction level, although the initiation of a community effect requires a sufficient amount of inducing signal. The mechanism of the community effect revealed by our theoretical analysis is analogous to that of quorum sensing in bacteria. The community effect may underlie the size control in animal development and also the genesis of autosomal dominant diseases including tumorigenesis.

Show MeSH
Related in: MedlinePlus