Limits...
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.

Show MeSH

Related in: MedlinePlus

Influence of the cell-cell communication rate ε and the decay rate of extracellular factor δd on gene expressions. Protein number of Ap and Bpout at steady state for different communitysizes are plotted as a function of ε (A, B) and δd (C, D). These plots are with gene copy numbers a = 1, b = 1, but qualitatively similar plots can be obtained with different gene copy numbers.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC3105943&req=5

Figure 7: Influence of the cell-cell communication rate ε and the decay rate of extracellular factor δd on gene expressions. Protein number of Ap and Bpout at steady state for different communitysizes are plotted as a function of ε (A, B) and δd (C, D). These plots are with gene copy numbers a = 1, b = 1, but qualitatively similar plots can be obtained with different gene copy numbers.

Mentions: Figure 7 shows steady-state activity [Ap]* and [Bpout]* as a function of ε (Figure 7A, B) and δd (Figure 7C, D). In Figure 7A and 7B, the intersection of each line for constant cell number with the axis of ε corresponds to the value of ε for which that cell number is nc. Similar argument can be applied in Figure 7C and 7D to the value of δd with regard to nc. Figure 7A indicates that for the large population n ≫ nc, [Ap]* is independent of ε. Therefore, a small fluctuation of has little influence on the expression of Ap at steady state. In contrast, [Bpout]* can change dramatically in response to a slight change in ε if n ≈ nc. For example, for ε = 1.12 × 10 -6 and n = 50 (≈ nc), [Bpout]* is ≈ 23 but increases to ≈ 3200 when ε changes upward by half (ε ≈ 1.68 10 -6) while it becomes 0 when ε changes downward by the same amount (ε ≈ 0.56 × 10 -6). On the other hand, when n ≫ nc, [Bpout]* is relatively insensitive to small changes in ε. Similarly, [Ap]* and [Bpout]* is independent of δd when n ≫ nc. For n ≫ nc, a small perturbation of δd barely influences [Bpout]* or [Ap]*. In contrast, [Bpout]* could change drastically when n ≈ nc (Figure 7C, D).


Theoretical basis of the community effect in development.

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

Influence of the cell-cell communication rate ε and the decay rate of extracellular factor δd on gene expressions. Protein number of Ap and Bpout at steady state for different communitysizes are plotted as a function of ε (A, B) and δd (C, D). These plots are with gene copy numbers a = 1, b = 1, but qualitatively similar plots can be obtained with different gene copy numbers.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3105943&req=5

Figure 7: Influence of the cell-cell communication rate ε and the decay rate of extracellular factor δd on gene expressions. Protein number of Ap and Bpout at steady state for different communitysizes are plotted as a function of ε (A, B) and δd (C, D). These plots are with gene copy numbers a = 1, b = 1, but qualitatively similar plots can be obtained with different gene copy numbers.
Mentions: Figure 7 shows steady-state activity [Ap]* and [Bpout]* as a function of ε (Figure 7A, B) and δd (Figure 7C, D). In Figure 7A and 7B, the intersection of each line for constant cell number with the axis of ε corresponds to the value of ε for which that cell number is nc. Similar argument can be applied in Figure 7C and 7D to the value of δd with regard to nc. Figure 7A indicates that for the large population n ≫ nc, [Ap]* is independent of ε. Therefore, a small fluctuation of has little influence on the expression of Ap at steady state. In contrast, [Bpout]* can change dramatically in response to a slight change in ε if n ≈ nc. For example, for ε = 1.12 × 10 -6 and n = 50 (≈ nc), [Bpout]* is ≈ 23 but increases to ≈ 3200 when ε changes upward by half (ε ≈ 1.68 10 -6) while it becomes 0 when ε changes downward by the same amount (ε ≈ 0.56 × 10 -6). On the other hand, when n ≫ nc, [Bpout]* is relatively insensitive to small changes in ε. Similarly, [Ap]* and [Bpout]* is independent of δd when n ≫ nc. For n ≫ nc, a small perturbation of δd barely influences [Bpout]* or [Ap]*. In contrast, [Bpout]* could change drastically when n ≈ nc (Figure 7C, D).

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