Balancing reaction-diffusion network for cell polarization pattern with stability and asymmetry

  1. Yixuan Chen
  2. Guoye Guan
  3. Lei-Han Tang  Is a corresponding author
  4. Chao Tang  Is a corresponding author
  1. South Bay Interdisciplinary Science Center, Songshan Lake Materials Laboratory, China
  2. Department of Physics, Sichuan University, China
  3. School of Physics, Peking University, China
  4. Center for Quantitative Biology, Peking University, China
  5. Department of Physics, Hong Kong Baptist University, China
  6. Peking-Tsinghua Center for Life Sciences, Peking University, China
12 figures, 4 tables and 3 additional files

Figures

Figure 1 with 6 supplements
The single modification on the antagonistic 2-node network causes the collapse of cell polarization pattern.

(a) Basic network with the transition plane (mid-plane) marked by gray dashed line. (b) Two subtypes of single-sided self-regulation. (c) Four subtypes of single-sided additional regulation. The corresponding spatial concentration distribution of [Lm] at t=0,100,200,300,400,and500, and the subtle difference between left and right panels are detailed in Figure 1—figure supplement 3. (d) Two subtypes of unequal system parameters, exemplified by unequal inhibition intensity and unequal cytoplasmic concentration. For each network, the corresponding spatial concentration distribution of [Am] and [Pm] at t=0,100,200,300,400,and500 are shown beneath with a color scheme listed in the bottom left corner. Note that within a network, normal arrows and blunt arrows symbolize activation and inhibition respectively.

Figure 1—figure supplement 1
The initial state at t=0 (shown on the left) and stable state at t=500 (shown in the middle) of the cell polarization pattern generated by the simple 2-node network and C. elegans 5-node network (shown on the right).

Note that the spatial concentration distribution on the cell membrane (Xmx,0) is averaged over all established viable parameter sets for each molecular species (i.e., 122 among 5,151 sets, ~2.37%, for the simple 2-node network; 602 among 262,701 sets, ~0.229%, for the C. elegans 5-node network). Note that within a network, normal arrows and blunt arrows symbolize activation and inhibition respectively.

Figure 1—figure supplement 2
The antagonistic 2-node network initiated with different initial spatial concentration distributions on the cell membrane.

(a) Uniform initial distribution with a higher global concentration in [A] than [P]. (b) Uniform initial distribution with a higher global concentration in [P] than [A]. (c) Polarized initial distribution with a posterior shift in the transition plane of [P]. (d) Polarized initial distribution with a posterior shift in the transition planes of [A] and [P]. (e) Polarized initial distribution with symmetric curve shapes for [A] and [P], where their concentrations in the anterior and posterior are slightly different. (f) Polarized initial distribution with asymmetric curve shapes for [A] and [P], where their concentrations in the anterior are almost the same. (g) Polarized initial distribution with asymmetric curve shapes for [A] and [P], where the widths of their transition regions are different. (h) Gaussian noise distribution for [A] and [P]. For each simulation, the corresponding spatial concentration distribution of [Am] and [Pm] at t=0,100,200,300,400,and500 are shown with a color scheme listed in the bottom right corner. Note that within a simulation, the mathematical expressions for the initial distributions are described on top (upper: [Am]; lower: [Pm]; N(μ,σ): Gaussian noise distribution with a mean of μ and a standard deviation of σ).

Figure 1—figure supplement 3
The antagonistic 2-node network added with four subtypes of single-sided additional regulation (corresponding to Figure 1c) causes the collapse of cell polarization pattern.

The node [L] is added anteriorly or posteriorly, mutually activating or inhibiting the existing anterior node [A] (1st row). For each network, the corresponding spatial concentration distribution of [Am] (2nd row), [Pm] (3rd row), and [Lm] (4th row) at t=0,100,200,300,400,and500 are shown beneath with a color scheme listed in the bottom right corner. Note that within a network, normal arrows and blunt arrows symbolize activation and inhibition respectively.

Figure 1—figure supplement 4
With different initial spatial concentration distributions on the cell membrane, the single modification on the antagonistic 2-node network causes the collapse of cell polarization pattern.

Initial distributions are shown in the 1st column, which are the same as those shown in Figure 1—figure supplement 2d (2nd row), Figure 1—figure supplement 2e (3rd row), and Figure 1—figure supplement 2g (4th row), alongside the basic network (2nd column) and the ones added with single-sided self-regulation (exemplified by self-activation on [A], where qA1A=1 and qA2A=0.012, 3rd column), single-sided additional regulation (exemplified by [A]~[L] mutual inhibition with [L] in the posterior, where γL=αL=0.05, kL1A=kA1L=0.05, and kL2A=kA2L=0.025, 4th column), and unequal system parameters (exemplified by unequal inhibition intensity, where kP2A is increased from 1 to 1.6, 5th column; exemplified by unequal cytoplasmic concentration, where [Ac] is increased from 1 to 1.25, 6th column) shown on top. For each network, the corresponding spatial concentration distribution of [Am], [Pm], and [Lm] at t=0,100,200,300,400,and500 are shown beneath with a color scheme listed in the bottom right corner. Note that within a network, normal arrows and blunt arrows symbolize activation and inhibition respectively. Note that within a simulation, the mathematical expressions for the initial distributions are described on the left (upper: [Am]; lower: [Pm]).

Figure 1—figure supplement 5
With parameters (i.e., γ, α, k1, k2, q1, q2, and [Xc]) assigned with various values concerning all nodes and regulations (detailed in Appendix 1—table 2, Appendix 1—table 3), the single modification on the simple 2-node network (top panel) and C. elegans 5-node network (bottom panel) causes the collapse of cell polarization pattern.

(a) Basic network with the transition plane marked by gray dashed line. (b) Two subtypes of single-sided regulation. For a 2-node network, a self-activation (qA1A=1 and qA2A=0.025, 2nd column) or anteroposterior mutual inhibition (γL=αL=0.02, kL1A=kA1L=1, kL2A=kA2L=2, and [Lc]=1, 3rd column) is added on the node [A]. For a 5-node network, anteroposterior mutual inhibition between [A] and [L] (2nd column) or anterior mutual activation between [A] and [C] (3rd column) is eliminated. (c) Two subtypes of unequal system parameters, exemplified by unequal inhibition intensity and unequal cytoplasmic concentration. For a 2-node network, the inhibition intensity kP2A is increased from 3.8471 to 5 (4th column); the cytoplasmic concentration [Ac] is increased from 1.5361 to 2 (5th column). For a 5-node network, the inhibition intensity kL2A is increased from 3.7357 to 15 (4th column); the cytoplasmic concentration [Lc] is increased from 2.3793 to 5 (5th column). For each network, the corresponding spatial concentration distribution of [Am], [Cm], [Pm], [Lm], and [Hm] at t=0,100,200,300,400,and500 are shown beneath with a color scheme listed in the bottom right corner. Note that within a network, normal arrows and blunt arrows symbolize activation and inhibition respectively.

Figure 1—video 1
The spatial concentration distribution of each molecular species on the cell membrane over time generated by the antagonistic 2-node network and the ones with a single modification added, corresponding to Figure 1.
Figure 2 with 1 supplement
The combination of two opposite modifications recovers the cell polarization pattern stability.

The basic network and the ones added with a single modification are shown in the 1st and 2nd columns, respectively; the three combinatorial networks composed of any two of the three single modifications are shown in the 3rd column. For each network, the corresponding spatial concentration distribution of [Am] and [Pm] at t=0,100,200,300,400,and500 are shown beneath with a color scheme listed on the right. Here, the value assignments on the modifications in the 3rd column are as follows: qA2A=0.012 and kL2A&kA2L=0.01 for 1st row, qA2A=0.012 and kP2A=1.24 for 2nd row, and qA2A=0.012 and kA2P&kA2L=2 for 3rd row. Note that within a network, normal arrows and blunt arrows symbolize activation and inhibition respectively.

Figure 2—video 1
The spatial concentration distribution of each molecular species on the cell membrane over time generated by the antagonistic 2-node network and the ones with a single modification or two combinatorial modifications added, corresponding to Figure 2.
The balance between system parameters is needed for maintaining pattern stability.

(a) The phase diagram between qA2A and kL2A & kA2L in the network modified by self-activation (quantified by qA2A) and additional inhibition (quantified by kL2A & kA2L) on [A]. The representative parameter assignment for each phase is marked with ① (i.e., qA2A=0.015 and kL2A & kA2L=0 with a homogeneous state dominated by [A]), ② (i.e., qA2A=0.015 and kL2A & kA2L=0.0135 with a stable polarized state), and ③ (i.e., qA2A=0.02 and kL2A & kA2L=0 with a homogeneous state dominated by [P]). The corresponding spatial concentration distribution of [Am] and [Pm] at t=0,100,200,300,400,and500 are shown around the phase diagram with a color scheme listed on top. (b) The phase diagram between responsive concentration k1, basal on-rate γ, basal off-rate α, cytoplasmic concentration [Xc], and inhibition intensity k2. For each phase diagram in (a) (b), the final state dominated by [A] or [P] or stably polarized is colored in orange, green, and gray, respectively. Note that within a network, normal arrows and blunt arrows symbolize activation and inhibition respectively.

Figure 4 with 1 supplement
Adopting parameter sets corresponding to opposite interface velocities on two sides of the interface, the zero-velocity interface position of the polarity pattern is shiftable and regulatable.

(a) Spatially inhomogeneous parameters (2nd column) of a symmetric 2-node network generate a symmetric pattern (1st column), from the same simulation in Figure 1a. (b) Using the parameter combination with the posterior-shifting interface on the left and anterior-shifting interface on the right, a stable polarity pattern (1st column) can be remained by increasing  kA2P to 1.5 at x<0 and decreasing γA to 0.01 at (2nd column). (c–d) The stable interface position can be optionally adjusted by setting the change position of the step-up function (2nd column). (c) As in (b), but changing the step position to x=-0.1, the interface stabilizes around x=-0.1 (1st column). (d) As in (b), but changing the step position to x=0.1, the interface stabilizes around x=0.1 (1st column). For each parameter set, the corresponding spatial concentration distribution of [Am] and [Pm] at t=0,100,200,300,400,and500 are shown beneath with a color scheme listed in the bottom right corner. Note that all the interface positions in (a–d) (1st column) are marked by gray dashed lines. Note that all the spatially homogeneous parameter distributions in (a) (2nd column) are marked by gray dashed lines in (b–d) (2nd column).

Figure 4—video 1
The spatial concentration distribution of each molecular species on the cell membrane over time generated by the antagonistic 2-node network with spatially inhomogeneous parameters, corresponding to Figure 4.
Figure 5 with 6 supplements
The molecular interaction network in C. elegans zygote and its natural advantages in terms of pattern stability, balanced network configuration, viable parameter sets, and parameter robustness.

(a) The schematic diagram of the network composed of five molecular species, each of which has a polarized spatial concentration distribution on the cell membrane shown beneath. The left nodes PAR-3/PAR-6/PKC-3 (i.e., [A]) and CDC-42 (i.e., [C]) exhibit high concentration in the anterior pole and low concentration in the posterior pole, schemed by the purple line beneath; the right nodes PAR-1/PAR-2 (i.e., [P]), LGL-1 (i.e., [L]), and CHIN-1 (i.e., [H]) exhibit low concentration in the anterior pole and high concentration in the posterior pole, schemed by the cyan line beneath. Note that within the network, normal arrows and blunt arrows symbolize activation and inhibition respectively. (b–d) The structure of 4-Node, LGL-1-, and WT networks (1st row). The final spatial concentration distribution (t=500) averaged over all established viable parameter sets for each molecular species (i.e., 62 among 262,701 sets,~0.024%, for the 4-Node network; 62 among 5,151 sets,~1.2%, for the LGL-1- network; 602 among 262,701 sets,~0.229%, for the WT network), shown by a solid line (2nd row). For each position, MEAN ±STD (i.e., standard deviation) calculated with all viable parameter sets is shown by shadow. The pattern movement velocity (vM) over evolution time (t) (3rd row). For each subfigure in the 3rd row, each line with a unique color represents the simulation of a unique viable parameter set, and vM=10-4 is marked by a gray dashed line. For (a–d), the legend for the relationship between molecular species and corresponding color is placed in the bottom right corner. (e) The viable parameter sets of WT (blue points; 602 among 262,701 sets, ~0.229%) and 4-Node networks (red points; 62 among 5,151 sets, ~1.2%). (f) The interplay between [A]~[C] mutual activation and [A]~[L] mutual inhibition on the interface velocity. The contour map of the interface velocity vI with different parameter combinations of qC2A & qA2C and kL2A & kA2L represents its moving trend. The darker the red is, the faster the interface is moving toward the posterior pole; the darker the blue is, the faster the interface is moving toward the anterior pole; the closer the color is to white, the stabler the interface is. (g) The averaged pattern error in a perturbed condition compared to the original 4-Node, LGL-1-, and WT networks. The Gaussian noise is simultaneously exerted on all the parameters γ, α, k1, k2, q1 and q2 , where standard deviation σ denotes the noise amplification. For a specific noise level, the pattern error is averaged over 1,000 independent simulations.

Figure 5—figure supplement 1
The transformation from the simple 2-node network to the C. elegans 5-node network.

The reconstructed C. elegans 5-node network (4th row) appears to be an integration of an antagonistic 2-node network (1st row) doubled into an antagonistic 4-node network (2nd row) with full connections, and then augmented by the [A]~[C] mutual activation (3rd row, left) and [A]~[L] mutual inhibition (3rd row, right).

Figure 5—figure supplement 2
The in silico perturbation experiments on [L] based on the C. elegans modeling framework.

(a) The experimental condition (1st row) and final spatial concentration distribution (t=500) averaged over all established viable parameter sets (602 among 262,701 sets, ~0.229%) for [A] and [C] (2nd row) (Hoege et al., 2010). The perturbed conditions with depletion on [P] (solid line in 2nd column), [L] (solid line in 3rd column), or both (solid line in 4th column) are compared with the wild-type one (solid line in 1st column and dashed line in 2nd, 3rd, and 4th columns). (b) The pattern error in C. elegans mutant networks with depletion on [P], [L], or both (shown from left to right), compared to the pattern in C. elegans wild-type network. (c) The perturbed conditions (1st row) and final spatial concentration distribution (t=500) averaged over all established viable parameter sets (602 among 262,701 sets,~0.229%) for [A] and [C] (2nd row; Beatty et al., 2010; Beatty et al., 2013). The perturbed conditions with depletion on [P] (solid line in 2nd column), depletion on [P] but overexpression of [L] ([Lc] increased from 1 to 1.5) (solid line in 3rd column), and depletion on both [P] and [H] but overexpression of [L] ([Lc] increased from 1 to 1.5) (solid line in 4th column) are compared with the wild-type one (solid line in 1st column and dashed line in 2nd, 3rd, and 4th columns). (d) The pattern error in C. elegans mutant networks with depletion on [P] or both [P] and [H] but overexpression of [L] ([Lc] increased from 1 to 1.5), compared to the pattern in C. elegans wild-type network. For (a) (c), within a network, normal arrows and blunt arrows symbolize activation and inhibition respectively. For (b) (d), the pattern error is shown by a bar chart with the average of all viable parameter sets (602 among 262,701 sets, ~0.229%), while the values from each viable parameter set are plotted with gray dots, and the ones from the same viable parameter set but in different networks are connected with gray lines.

Figure 5—figure supplement 3
The in silico perturbation experiments on [C] based on the C. elegans modeling framework.

The experimental condition (1st row) and final spatial concentration distribution (t=500) averaged over all established viable parameter sets (602 among 262,701 sets,~0.229%) (2nd row) (Gotta et al., 2001; Aceto et al., 2006). The perturbed conditions with depletion on [C] (2nd column, (b)), overexpression of [C] ([Cc] increased from 1 to 1.5, 3rd column, (c)), and removal of [A]~[C] mutual activation (4th column, (d)) are compared with the wild-type one (1st column, (a)). Note that within a network, normal arrows and blunt arrows symbolize activation and inhibition respectively.

Figure 5—figure supplement 4
With different initial spatial concentration distributions on the cell membrane, the single modification on the C. elegans 5-node network causes the collapse of cell polarization pattern.

Initial distributions are shown in the 1st column, which are the same as those shown in Figure 1—figure supplement 2d (2nd row), Figure 1—figure supplement 2e (3rd row), and Figure 1—figure supplement 2g (4th row), alongside the basic network (2nd column) and the ones with removal of single-sided self-regulation (exemplified by [A]~[C] mutual activation, 3rd column) and single-sided additional regulation (exemplified by [A]~[L] mutual inhibition, 4th column), and added with unequal system parameters (exemplified by unequal inhibition intensity, where kL2A is increased from 1 to 1.6, 5th column; exemplified by unequal cytoplasmic concentration, where [Lc] is increased from 1 to 1.25, 6th column) shown on top. For each simulation, the corresponding spatial concentration distribution of [Am], [Cm], [Pm], [Lm], and [Hm] at are shown beneath with a color scheme listed in the bottom right corner. Note that within a network, normal arrows and blunt arrows symbolize activation and inhibition respectively. Note that within a simulation, the mathematical expressions for the initial distributions are described on the right (upper: [Am] and [Cm]; lower: [Pm], [Lm], and [Hm]).

Figure 5—figure supplement 5
The 32 possible additional feedback loops between LGL-1 (abbr. , [L]) and PAR-3/PAR-6/PKC-3 (abbr., [A]) or PAR-1/PAR-2 (abbr., [P]).

The position of nodes on the left and right represents that the corresponding molecular species is initially set with a high concentration on the anterior and posterior cell membrane respectively. Note that within a network, normal arrows and blunt arrows symbolize activation and inhibition respectively, while dashed lines mean no regulation.

Figure 5—video 1
The spatial concentration distribution of each molecular species on the cell membrane over time generated by the 4-Node, LGL-1-, and WT networks, corresponding to Figure 5b–d.
Figure 6 with 1 supplement
The control of the interface velocity and position by adjusting parameters in a multi-dimensional system.

(a) The parameter space (1st row) and the linear relationship (2nd row) between interface velocity and parameters. The discrete viable parameter space of the WT network is fitted by a blue curved surface to represent its null surface with little or no pattern interface moving (1st row). The benchmark point Ω(γ=0.039, k1=1.55, q2=0.05) and its neighborhood are marked by an orange cube. Centering on the benchmark point Ω*, the relationship between the velocity interface and parameters in the region marked by the orange cube is shown by slice planes orthogonal to the γ-axis at the values 0.034, 0.036, 0.038, 0.04, 0.042, and 0.044 (2nd row). The darker the red is, the faster the interface is moving toward the posterior pole; the darker the blue is, the faster the interface is moving toward the anterior pole; the closer the color is to white, the stabler the interface is. (b–e) As in Figure 4, the control of the zero-velocity interface position of the polarity pattern by spatially inhomogeneous parameters corresponding to opposite interface velocities on two sides of the interface can be applied to the C. elegans 5-node network. (b) Using Ω* as a representative, spatially homogeneous parameters (2nd column) generate a stable polarity pattern (1st column). (c) On top of (b), a stable polarity pattern (1st column) with its interface around x=0 can be obtained by increasing qC2A & qA2C to 0.12 at x<0 and increasing γP,γL,andγH to 0.06 at x>0 (2nd column). (d) As in (c) but changing the step position to x=-0.1 (2nd column), the interface stabilizes around x=-0.1 (1st column). (e) As in (c), but changing the step position to x=0.1 (2nd column), the interface stabilizes around x=0.1 (1st column). For each parameter set, the corresponding spatial concentration distribution of [Am], [Cm], [Pm], [Lm], and [Hm] at t=0,100,200,300,400,and500 are shown beneath with a color scheme listed on the right. Note that all the interface positions in (b–e) (1st column) are marked by gray dashed lines. Note that all the spatially homogeneous parameter distributions in (b) (2nd column) are marked by gray dashed lines in (c–e) (2nd column).

Figure 6—video 1
The spatial concentration distribution of each molecular species on the cell membrane over time generated by the C. elegans 5-node network with spatially inhomogeneous parameters, corresponding to Figure 6b–e.
Appendix 2—figure 1
The instructions to open the PolarSim GUI.

① The files in the folder ‘PolarSim’. ② Open Matlab under the path of the folder ‘PolarSim’ and double-click to open ‘GUI.m’. ③ Click ‘Run’ to open the PolarSim GUI shown by ④.

Appendix 2—figure 2
The examples of network parameters.

(a) ‘Simple Antagonistic 2-Node Network.xlsx lists the parameters’ in Figure 1a. (b) ‘C. elegans Wild-Type 5-Node Network.xlsx’ lists the parameters for the benchmark point Ω(γ=0.039,k1=1.55, q2=0.05) in Figure 6b. (c) ‘LGL-1 Mutant 4-Node Network.xlsx’ lists the parameters as in (b) but with the Node [L] knocked out.

Appendix 2—figure 3
The progress bar, files, and subfolders of PolarSim.

(a) The progress bar showing the running progress. (b) All files and output subfolders in the folder ‘PolarSim’.

Appendix 2—figure 4
The results of Example 1 (‘Simple Antagonistic 2-Node Network.xlsx’) and Example 2 (‘C. elegans Wild-Type 5-Node Network.xlsx’) of PolarSim.

(a) The flow chart for computing Example 1: ① input parameters; ② click ‘Run’; ③ the simulation is completed with a progress bar shown and files saved in the folder ‘Output 2-Node’; the file ‘Pattern_500.mat’ is used to show the data format on the right, where the first part stores the molecular species or nodes’ names and locations while the second part stores their spatial concentration distributions on the cell membrane; ④ input the pathway of the outputted pattern file; ⑤ click ‘Plot’; ⑥ the simulation is completed with a figure shown and the position of the transition plane given in the box ‘Output: Transition Plane’; ⑦ input the pathway of the two outputted files ‘Pattern_*.mat’ at different time points into ‘Import: Start Time’ and ‘Import: End Time’, where ‘*’ denotes the start time and end time respectively; ⑧ click ‘Run’; ⑨ the simulation is completed with the interface velocity given in the box ‘Output: Interface Velocity’. (b) The same as a but for the ‘C. elegans Wild-Type 5-Node Network.xlsx’.

Appendix 2—figure 5
The results of Example 3 (‘LGL-1 Mutant 4-Node Network.xlsx’) of PolarSim.

(a) The transition plane is shown at t=500, with the value xT=0.207071. The interface velocity is calculated between t=300 and t=500, with the value vI=0.000429293 representing an unstable pattern (top). The figure is plotted at t=500 (bottom). (b) The transition plane and the figure are shown at t=1000 and the interface velocity is calculated between t=800 and t=1000. The pattern collapses to a homogeneous state with [A] and [C] invading the posterior domain at t=1000, and thereby the transition plane doesn’t exist and the interface can’t be calculated.

Appendix 2—figure 6
The effects of cell size (length) on the cell polarization pattern.

(a–e) The pattern of ‘Simple Antagonistic 2-Node Network.xlsx’ at t=500. From left to right, the cell lengths are 0.1, 0.2, 0.3, 0.4 and 0.5, respectively. (f–j) The same as (a–e) but for the ‘C. elegans Wild-Type 5-Node Network.xlsx’.

Tables

Appendix 1—table 1
The parameter description of the reaction-diffusion model for simulating a cell polarization network.
ParameterBiological implicationDefaulted nondimensionalvalue in simulation
xPosition along the anterior-posterior axis[–0.25,0.25] in steps 0.005
tTime[0,500] in steps 1
(corresponding to
2 sec per step) (
Blanchoud et al., 2015; Seirin-Lee et al., 2020b)
[X]Molecular species/
[Xm]Spatial concentration distribution on the cell membrane/
[Xc]Spatial concentration distribution in the cell cytosol1
DmXDiffusion coefficient across the cell membrane2.748×10–5 for anteriorly-located molecular species and 1.472×10–5 for posteriorly-located molecular species
(Goehring et al., 2011a; Goehring et al., 2011b; Geßele et al., 2020; Seirin-Lee et al., 2020b)
γXBasal on-rate (cell membrane association)[0,0.05] in steps 0.001
αXBasal off-rate (cell membrane dissociation)[0,0.05] in steps 0.001
qY1XResponsive concentration in the activation pathway from [Y] to [X][0,5] in steps 0.05
kY1XResponsive concentration in the inhibition pathway from [Y] to [X][0,5] in steps 0.05
qY2XActivation intensity from [Y] to [X][0,0.05] in steps 0.001
kY2XInhibition intensity from [Y] to [X]1
ΩA three-dimensional (3D) grid representing nondimensionalized parameter set(γ,k1,q2)
nHill coefficient2
(Seirin-Lee and Shibata, 2015; Seirin-Lee, 2021)
LCell/embryo length0.5
vMPattern movement velocity/
xTPattern transition plane or interface/
vIInterface velocity/
NNumber of molecular species types/
MNumber of viable parameter sets/
QNumber of independent simulations/
Appendix 1—table 2
Viable parameter set searched by Monte Carlo method for the simple 2-node network.

For the 10 parameters in the simple 2-node network, the corresponding scanned ranges are γ[0,0.05],α[0,0.05],k1[0.05,5],k2[0.05,5], and . Among 100,000 independent simulations, only 20 viable parameter sets pass the computational pipeline. One representative viable parameter set used to reproduce the conclusions in Figure 1; Figure 1—figure supplement 5 -1st row is listed below.

ParameterNondimensionalValue in SimulationParameterNondimensionalValue in Simulation
Ac1.5361Pc0.6662
γA0.0251αA0.0437
γP0.0312αP0.0245
kP1A0.1995kP2A3.8471
kA1P1.3638kA2P2.2571
Appendix 1—table 3
Viable parameter set searched by Monte Carlo method for the C. elegans 5-node network.

For the 39 parameters in the C. elegans 5-node network, the corresponding scanned ranges are γ[0,0.05],α[0,0.05],k1[0.05,5],k2[0.05,5],q1[0.05,5],q2[0,0.05], and [Xc][0.05,5]. Among 100,000 independent simulations, only 6 viable parameter sets pass the computational pipeline. One representative viable parameter set used to reproduce the conclusions in Figure 1; Figure 1—figure supplement 5 -2nd row is listed below.

ParameterNondimensionalValue in SimulationParameterNondimensionalValue in Simulation
Ac2.4420Pc3.6739
Cc1.8330Lc2.3793
Hc3.4683
γA0.0448αA0.0310
γP0.0164αP0.0334
γC0.0158αC0.0071
γL0.0146αL0.0221
γH0.0197αH0.0410
qA1C4.1521qA2C0.0495
qC1A1.3029qC2A0.0201
kP1A3.7955kP2A0.2009
kL1A2.3597kL2A3.7357
kH1A1.9557kH2A2.2441
kA1P3.7180kA2P3.7342
kC1P4.5544kC2P1.5792
kP1C0.5495kP2C2.8838
kH1C2.6518kH2C1.2697
kA1L2.4436kA2L4.8334
kA1H4.4505kA2H0.3688
kC1H3.3712kC2H2.0272
Appendix 2—table 1
The instructions for the format of Network Parameter in an Excel table.

In the 1st row and 1st column, ‘Node N’ represents the name of the node. The 2nd row explains the characteristic parameters of each node (i.e., location, cytoplasmic concentration, basal on-rate, and basal off-rate as listed from left to right). The interaction parameters start from the 3rd row and 2nd column, where the ith row and jth column describe the activation/inhibition effect from Node j to Node i. Note that qY2X and kY2X should be set to 0 when no activation or inhibition is exerted on X from Y respectively. ‘Location’ should be assigned with the string ‘a’ or ‘p’ while the description of the other parameters is detailed in Appendix 1—table 1.

Node ANode BNode N
Location (a or p)/
[Ac]/γA/αA
Location (a or p)/
[Bc]/γB/αB
Location (a or p)/
[Nc]/γN/αN
Node AqA1A/qA2A/nAqA/kA1A/kA2A/nAkAqB1A/qB2A/nBqA/kB1A/kB2A/nBkAqN1A/qN2A/nNqA/kN1A/kN2A/nNkA
Node BqA1B/qA2B/nAqB/kA1B/kA2B/nAkBqB1B/qB2B/nBqB/kB1B/kB2B/nBkBqN1B/qN2B/nNqB/kN1B/kN2B/nNkB
Node NqA1N/qA2N/nAqN/kA1N/kA2N/nAkNqB1N/qB2N/nBqN/kB1N/kB2N/nBkNqN1N/qN2N/nNqN/kN1N/kN2N/nNkN

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  1. Yixuan Chen
  2. Guoye Guan
  3. Lei-Han Tang
  4. Chao Tang
(2025)
Balancing reaction-diffusion network for cell polarization pattern with stability and asymmetry
eLife 13:RP96421.
https://doi.org/10.7554/eLife.96421.3