American Institute of Mathematical Sciences

Advanced
2011, 8(4): 1135-1168. doi: 10.3934/mbe.2011.8.1135

Mathematical analysis of steady-state solutions in compartment and continuum models of cell polarization

Zhenzhen Zheng 1, , Ching-Shan Chou 2, , Tau-Mu Yi 3, and  Qing Nie 4,

1. 

Department of Mathematics, Center for Complex Biological Systems & Center for Mathematical and Computational Biology, University of California, Irvine, CA 92697, United States
2. 

Department of Mathematics, Mathematica Biosciences Institute, The Ohio State University, Columbus, OH 43221, United States
3. 

Developmental and Cell Biology, Center for Complex Biological Systems & Center for Mathematical and Computational Biology, University of California, Irvina, CA 92697, United States
4. 

Department of Mathematics, Center for Complex Biological Systems & Center for Mathematical and Computational Biology, University of California, Irvine, California, 92697-3875

Received  February 2011 Revised  May 2011 Published  August 2011

Cell polarization, in which substances previously uniformly distributed become asymmetric due to external or/and internal stimulation, is a fundamental process underlying cell mobility, cell division, and other polarized functions. The yeast cell S. cerevisiae has been a model system to study cell polarization. During mating, yeast cells sense shallow external spatial gradients and respond by creating steeper internal gradients of protein aligned with the external cue. The complex spatial dynamics during yeast mating polarization consists of positive feedback, degradation, global negative feedback control, and cooperative effects in protein synthesis. Understanding such complex regulations and interactions is critical to studying many important characteristics in cell polarization including signal amplification, tracking dynamic signals, and potential trade-off between achieving both objectives in a robust fashion. In this paper, we study some of these questions by analyzing several models with different spatial complexity: two compartments, three compartments, and continuum in space. The step-wise approach allows detailed characterization of properties of the steady state of the system, providing more insights for biological regulations during cell polarization. For cases without membrane diffusion, our study reveals that increasing the number of spatial compartments results in an increase in the number of steady-state solutions, in particular, the number of stable steady-state solutions, with the continuum models possessing infinitely many steady-state solutions. Through both analysis and simulations, we find that stronger positive feedback, reduced diffusion, and a shallower ligand gradient all result in more steady-state solutions, although most of these are not optimally aligned with the gradient. We explore in the different settings the relationship between the number of steady-state solutions and the extent and accuracy of the polarization. Taken together these results furnish a detailed description of the factors that influence the tradeoff between a single correctly aligned but poorly polarized stable steady-state solution versus multiple more highly polarized stable steady-state solutions that may be incorrectly aligned with the external gradient.
Keywords: modeling., yeast, pheromone gradient, Cell polarization, stability.
Mathematics Subject Classification: 92C15, 92C37, 34D2.
Citation: Zhenzhen Zheng, Ching-Shan Chou, Tau-Mu Yi, Qing Nie. Mathematical analysis of steady-state solutions in compartment and continuum models of cell polarization. Mathematical Biosciences & Engineering, 2011, 8 (4) : 1135-1168. doi: 10.3934/mbe.2011.8.1135
References:
[1]

G. L. Atkins, "Multicompartment Models for Biological Systems," Willmer Brothers Limited, Birkenhead, Great Britain, 1969.

[2]

D. M. Bryant and K. E. Mostov, From cells to organs: Building polarized tissue, Nature Rev. Mol. Cell Biol., 9 (2008), 887-901. doi: 10.1038/nrm2523.

[3]

C.-S. Chou, Q. Nie and T. M. Yi, Modeling robustness tradeoffs in yeast cell polarization induced by spatial gradients, PLoS One, 3 (2008), e3103. doi: 10.1371/journal.pone.0003103.

[4]

A. Dawes and L. Edelstein-Keshet, Phosphoinositides and Rho proteins spatially regulate actin polymerization to initiate and maintain directed movement in a 1D model of a motile cell, Biophys. J., 92 (2007), 1-25. doi: 10.1529/biophysj.106.090514.

[5]

P. Devreotes and C. Janetopoulos, Eukaryotic chemotaxis: Distinctions between directional sensing and polarization, J. Biol. Chem., 278 (2003), 20445-20448. doi: 10.1074/jbc.R300010200.

[6]

J. Dobbelaere and Y. Barral, Spatial coordination of cytokinetic events by compartmentalization of the cell cortex, Science, 305 (2004), 393-396. doi: 10.1126/science.1099892.

[7]

D. G. Drubin and W. J. Nelson, Origins of cell polarity, Cell, 84 (1996), 335-344. doi: 10.1016/S0092-8674(00)81278-7.

[8]

A. B. Goryachev and A. V. Pokhilko, Dynamics of cdc42 network embodies a turing-type mechanism of yeast cell polarity, FEBS Lett., 582 (2008), 1437-1443. doi: 10.1016/j.febslet.2008.03.029.

[9]

J. Haugh and I. Schneider, Spatial analysis of 3' phosphoinositide signaling in living fibroblasts: I. Uniform stimulation model and bounds on dimensionless groups, Biophys. J., 86 (2004), 589-598. doi: 10.1016/S0006-3495(04)74137-5.

[10]

P. A. Iglesias and A. Levchenko, Modeling the cell's guidance system, Sci STKE, 2002 (2002), re12. doi: 10.1126/stke.2002.148.re12.

[11]

A. Jilkine, A. F. M. Marée and L. Edelstein-Keshet, Mathematical model for spatial segregation of the Rho-family GTPases based on inhibitory crosstalk, Bull. Math. Biol., 69 (2007), 1943-1978. doi: 10.1007/s11538-007-9200-6.

[12]

J. Krishnan and P. A. Iglesias, Uncovering directional sensing: Where are we headed?, Syst. Biol. (Stevenage), 1 (2004), 54-61. doi: 10.1049/sb:20045001.

[13]

J. Krishnan and P. Iglesias, A modeling framework describing the enzyme regulation of membrane lipids underlying gradient perception in Dictyostelium cells, J. Theor. Biol., 229 (2004), 85-99. doi: 10.1016/j.jtbi.2004.03.005.

[14]

A. Levchenko and P. A. Iglesias, Models of eukaryotic gradient sensing: Application to chemotaxis of amoebae and neutrophils, Biophys. J., 82 (2002), 50-63. doi: 10.1016/S0006-3495(02)75373-3.

[15]

I. Maly, H. Wiley and D. Lauffenburger, Self-organization of polarized cell signaling via autocrine circuits: Computational model analysis, Biophys. J., 86 (2004), 10-22. doi: 10.1016/S0006-3495(04)74079-5.

[16]

A. Marée, A. Jilkine, A. Dawes, V. Grieneisen and L. Edelstein-Keshet, Polarization and movement of keratocytes: A multiscale modeling approach, Bull. Math. Biol., 68 (2006), 1169-1211.

[17]

F. R. Maxfield, Plasma membrane microdomains, Curr Opin Cell Biol, 14 (2002), 483-487. doi: 10.1016/S0955-0674(02)00351-4.

[18]

H. Meinhardt, "Models of Biological Pattern Formation," Academic Press, London, 1982.

[19]

H. Meinhardt, Orientation of chemotactic cells and growth cones: Models and mechanisms, J. Cell Sci., 112 (1999), 2867-2874.

[20]

I. Mellman and W. J. Nelson, Coordinated protein sorting, targeting and distribution in polarized cells, Nature Rev. Mol. Cell Biol., 9 (2008), 833-845. doi: 10.1038/nrm2525.

[21]

Y. Mori, A. Jilkine and L. Edelstein-Keshet, Wave-pinning and cell polarity from a bistable reaction-diffusion system, Biophys J., 94 (2008), 3684-3697. doi: 10.1529/biophysj.107.120824.

[22]

A. Narang, Spontaneous polarization in eukaryotic gradient sensing: A mathematical model based on mutual inhibition of frontness and backness pathways, J. Theor. Biol., 240 (2006), 538-553. doi: 10.1016/j.jtbi.2005.10.022.

[23]

M. Onsum and C. V. Rao, A mathematical model for neutrophil gradient sensing and polarization, PLoS Comput. Biol., 3 (2007), 436-450. doi: 10.1371/journal.pcbi.0030036.

[24]

M. Otsuji, S. Ishihara, C. Co, K. Kaibuchi, A. Mochizuki and S. Kuroda, A mass conserved reaction-diffusion system captures properties of cell polarity, PLoS Comput. Biol., 3 (2007), 1040-1054. doi: 10.1371/journal.pcbi.0030108.

[25]

D. Pruyne and A. Bretscher, Polarization of cell growth in yeast I. Establishment and maintenance of polarity states, J. Cell Sci., 113 (2000), 365-375.

[26]

Y. Sakumura, Y. Tsukada, N. Yamamoto and S. Ishii, A molecular model for axon guidance based on cross talk between Rho GTPases, Biophys. J., 89 (2005), 812-822. doi: 10.1529/biophysj.104.055624.

[27]

R. Skupsky, W. Losert and R. Nossal, Distinguishing modes of eukaryotic gradient sensing, Biophys. J., 89 (2005), 2806-2823. doi: 10.1529/biophysj.105.061564.

[28]

K. Subramanian and A. Narang, A mechanistic model for eukaryotic gradient sensing: Spontaneous and induced phosphoinositide polarization, J. Theor. Biol., 231 (2004), 49-67. doi: 10.1016/j.jtbi.2004.05.024.

[29]

D. W. Thompson, "On Growth and Form," Dover, New York, 1992.

[30]

M. Tomishige, Y. Sako and A. Kusumi, Regulation mechanism of the lateral diffusion of Band 3 in erythrocyte membranes by the membrane skeleton, J. Cell Biol., 142 (1998), 989-1000. doi: 10.1083/jcb.142.4.989.

[31]

A. M. Turing, The chemical basis of morphogenesis, Phil. Trans. Roy. Soc. Lond. B, 237 (1952), 37-72. doi: 10.1098/rstb.1952.0012.

[32]

M. Vicente-Manzanares and F. Sánchez-Madrid, Cell polarization: A comparative cell biology and immunological view, Clin. Dev. Immunol., 7 (2000), 51-65.

show all references

References:
[1]

G. L. Atkins, "Multicompartment Models for Biological Systems," Willmer Brothers Limited, Birkenhead, Great Britain, 1969.

[2]

D. M. Bryant and K. E. Mostov, From cells to organs: Building polarized tissue, Nature Rev. Mol. Cell Biol., 9 (2008), 887-901. doi: 10.1038/nrm2523.

[3]

C.-S. Chou, Q. Nie and T. M. Yi, Modeling robustness tradeoffs in yeast cell polarization induced by spatial gradients, PLoS One, 3 (2008), e3103. doi: 10.1371/journal.pone.0003103.

[4]

A. Dawes and L. Edelstein-Keshet, Phosphoinositides and Rho proteins spatially regulate actin polymerization to initiate and maintain directed movement in a 1D model of a motile cell, Biophys. J., 92 (2007), 1-25. doi: 10.1529/biophysj.106.090514.

[5]

P. Devreotes and C. Janetopoulos, Eukaryotic chemotaxis: Distinctions between directional sensing and polarization, J. Biol. Chem., 278 (2003), 20445-20448. doi: 10.1074/jbc.R300010200.

[6]

J. Dobbelaere and Y. Barral, Spatial coordination of cytokinetic events by compartmentalization of the cell cortex, Science, 305 (2004), 393-396. doi: 10.1126/science.1099892.

[7]

D. G. Drubin and W. J. Nelson, Origins of cell polarity, Cell, 84 (1996), 335-344. doi: 10.1016/S0092-8674(00)81278-7.

[8]

A. B. Goryachev and A. V. Pokhilko, Dynamics of cdc42 network embodies a turing-type mechanism of yeast cell polarity, FEBS Lett., 582 (2008), 1437-1443. doi: 10.1016/j.febslet.2008.03.029.

[9]

J. Haugh and I. Schneider, Spatial analysis of 3' phosphoinositide signaling in living fibroblasts: I. Uniform stimulation model and bounds on dimensionless groups, Biophys. J., 86 (2004), 589-598. doi: 10.1016/S0006-3495(04)74137-5.

[10]

P. A. Iglesias and A. Levchenko, Modeling the cell's guidance system, Sci STKE, 2002 (2002), re12. doi: 10.1126/stke.2002.148.re12.

[11]

A. Jilkine, A. F. M. Marée and L. Edelstein-Keshet, Mathematical model for spatial segregation of the Rho-family GTPases based on inhibitory crosstalk, Bull. Math. Biol., 69 (2007), 1943-1978. doi: 10.1007/s11538-007-9200-6.

[12]

J. Krishnan and P. A. Iglesias, Uncovering directional sensing: Where are we headed?, Syst. Biol. (Stevenage), 1 (2004), 54-61. doi: 10.1049/sb:20045001.

[13]

J. Krishnan and P. Iglesias, A modeling framework describing the enzyme regulation of membrane lipids underlying gradient perception in Dictyostelium cells, J. Theor. Biol., 229 (2004), 85-99. doi: 10.1016/j.jtbi.2004.03.005.

[14]

A. Levchenko and P. A. Iglesias, Models of eukaryotic gradient sensing: Application to chemotaxis of amoebae and neutrophils, Biophys. J., 82 (2002), 50-63. doi: 10.1016/S0006-3495(02)75373-3.

[15]

I. Maly, H. Wiley and D. Lauffenburger, Self-organization of polarized cell signaling via autocrine circuits: Computational model analysis, Biophys. J., 86 (2004), 10-22. doi: 10.1016/S0006-3495(04)74079-5.

[16]

A. Marée, A. Jilkine, A. Dawes, V. Grieneisen and L. Edelstein-Keshet, Polarization and movement of keratocytes: A multiscale modeling approach, Bull. Math. Biol., 68 (2006), 1169-1211.

[17]

F. R. Maxfield, Plasma membrane microdomains, Curr Opin Cell Biol, 14 (2002), 483-487. doi: 10.1016/S0955-0674(02)00351-4.

[18]

H. Meinhardt, "Models of Biological Pattern Formation," Academic Press, London, 1982.

[19]

H. Meinhardt, Orientation of chemotactic cells and growth cones: Models and mechanisms, J. Cell Sci., 112 (1999), 2867-2874.

[20]

I. Mellman and W. J. Nelson, Coordinated protein sorting, targeting and distribution in polarized cells, Nature Rev. Mol. Cell Biol., 9 (2008), 833-845. doi: 10.1038/nrm2525.

[21]

Y. Mori, A. Jilkine and L. Edelstein-Keshet, Wave-pinning and cell polarity from a bistable reaction-diffusion system, Biophys J., 94 (2008), 3684-3697. doi: 10.1529/biophysj.107.120824.

[22]

A. Narang, Spontaneous polarization in eukaryotic gradient sensing: A mathematical model based on mutual inhibition of frontness and backness pathways, J. Theor. Biol., 240 (2006), 538-553. doi: 10.1016/j.jtbi.2005.10.022.

[23]

M. Onsum and C. V. Rao, A mathematical model for neutrophil gradient sensing and polarization, PLoS Comput. Biol., 3 (2007), 436-450. doi: 10.1371/journal.pcbi.0030036.

[24]

M. Otsuji, S. Ishihara, C. Co, K. Kaibuchi, A. Mochizuki and S. Kuroda, A mass conserved reaction-diffusion system captures properties of cell polarity, PLoS Comput. Biol., 3 (2007), 1040-1054. doi: 10.1371/journal.pcbi.0030108.

[25]

D. Pruyne and A. Bretscher, Polarization of cell growth in yeast I. Establishment and maintenance of polarity states, J. Cell Sci., 113 (2000), 365-375.

[26]

Y. Sakumura, Y. Tsukada, N. Yamamoto and S. Ishii, A molecular model for axon guidance based on cross talk between Rho GTPases, Biophys. J., 89 (2005), 812-822. doi: 10.1529/biophysj.104.055624.

[27]

R. Skupsky, W. Losert and R. Nossal, Distinguishing modes of eukaryotic gradient sensing, Biophys. J., 89 (2005), 2806-2823. doi: 10.1529/biophysj.105.061564.

[28]

K. Subramanian and A. Narang, A mechanistic model for eukaryotic gradient sensing: Spontaneous and induced phosphoinositide polarization, J. Theor. Biol., 231 (2004), 49-67. doi: 10.1016/j.jtbi.2004.05.024.

[29]

D. W. Thompson, "On Growth and Form," Dover, New York, 1992.

[30]

M. Tomishige, Y. Sako and A. Kusumi, Regulation mechanism of the lateral diffusion of Band 3 in erythrocyte membranes by the membrane skeleton, J. Cell Biol., 142 (1998), 989-1000. doi: 10.1083/jcb.142.4.989.

[31]

A. M. Turing, The chemical basis of morphogenesis, Phil. Trans. Roy. Soc. Lond. B, 237 (1952), 37-72. doi: 10.1098/rstb.1952.0012.

[32]

M. Vicente-Manzanares and F. Sánchez-Madrid, Cell polarization: A comparative cell biology and immunological view, Clin. Dev. Immunol., 7 (2000), 51-65.

[1]

Tatsuki Mori, Kousuke Kuto, Tohru Tsujikawa, Shoji Yotsutani. Exact multiplicity of stationary limiting problems of a cell polarization model. Discrete and Continuous Dynamical Systems, 2016, 36 (10) : 5627-5655. doi: 10.3934/dcds.2016047
[2]

Alessandro Cucchi, Antoine Mellet, Nicolas Meunier. Self polarization and traveling wave in a model for cell crawling migration. Discrete and Continuous Dynamical Systems, 2022, 42 (5) : 2381-2407. doi: 10.3934/dcds.2021194
[3]

Mostafa Adimy, Fabien Crauste. Modeling and asymptotic stability of a growth factor-dependent stem cell dynamics model with distributed delay. Discrete and Continuous Dynamical Systems - B, 2007, 8 (1) : 19-38. doi: 10.3934/dcdsb.2007.8.19
[4]

Tatsuki Mori, Kousuke Kuto, Masaharu Nagayama, Tohru Tsujikawa, Shoji Yotsutani. Global bifurcation sheet and diagrams of wave-pinning in a reaction-diffusion model for cell polarization. Conference Publications, 2015, 2015 (special) : 861-877. doi: 10.3934/proc.2015.0861
[5]

Lisette dePillis, Trevor Caldwell, Elizabeth Sarapata, Heather Williams. Mathematical modeling of regulatory T cell effects on renal cell carcinoma treatment. Discrete and Continuous Dynamical Systems - B, 2013, 18 (4) : 915-943. doi: 10.3934/dcdsb.2013.18.915
[6]

Michael Leguèbe. Cell scale modeling of electropermeabilization by periodic pulses. Mathematical Biosciences & Engineering, 2015, 12 (3) : 537-554. doi: 10.3934/mbe.2015.12.537
[7]

A. Chauviere, T. Hillen, L. Preziosi. Modeling cell movement in anisotropic and heterogeneous network tissues. Networks and Heterogeneous Media, 2007, 2 (2) : 333-357. doi: 10.3934/nhm.2007.2.333
[8]

Shinji Nakaoka, Hisashi Inaba. Demographic modeling of transient amplifying cell population growth. Mathematical Biosciences & Engineering, 2014, 11 (2) : 363-384. doi: 10.3934/mbe.2014.11.363
[9]

A. Chauviere, L. Preziosi, T. Hillen. Modeling the motion of a cell population in the extracellular matrix. Conference Publications, 2007, 2007 (Special) : 250-259. doi: 10.3934/proc.2007.2007.250
[10]

Christina Surulescu, Nicolae Surulescu. Modeling and simulation of some cell dispersion problems by a nonparametric method. Mathematical Biosciences & Engineering, 2011, 8 (2) : 263-277. doi: 10.3934/mbe.2011.8.263
[11]

Katarzyna A. Rejniak. A Single-Cell Approach in Modeling the Dynamics of Tumor Microregions. Mathematical Biosciences & Engineering, 2005, 2 (3) : 643-655. doi: 10.3934/mbe.2005.2.643
[12]

Pamela A. Marshall, Eden E. Tanzosh, Francisco J. Solis, Haiyan Wang. Response of yeast mutants to extracellular calcium variations. Discrete and Continuous Dynamical Systems - B, 2009, 12 (2) : 439-453. doi: 10.3934/dcdsb.2009.12.439
[13]

El Miloud Zaoui, Marc Laforest. Stability and modeling error for the Boltzmann equation. Kinetic and Related Models, 2014, 7 (2) : 401-414. doi: 10.3934/krm.2014.7.401
[14]

Hongjing Shi, Wanbiao Ma. An improved model of t cell development in the thymus and its stability analysis. Mathematical Biosciences & Engineering, 2006, 3 (1) : 237-248. doi: 10.3934/mbe.2006.3.237
[15]

Fabien Crauste. Global Asymptotic Stability and Hopf Bifurcation for a Blood Cell Production Model. Mathematical Biosciences & Engineering, 2006, 3 (2) : 325-346. doi: 10.3934/mbe.2006.3.325
[16]

Adélia Sequeira, Rafael F. Santos, Tomáš Bodnár. Blood coagulation dynamics: mathematical modeling and stability results. Mathematical Biosciences & Engineering, 2011, 8 (2) : 425-443. doi: 10.3934/mbe.2011.8.425
[17]

Qiang Du, Chun Liu, R. Ryham, X. Wang. Modeling the spontaneous curvature effects in static cell membrane deformations by a phase field formulation. Communications on Pure and Applied Analysis, 2005, 4 (3) : 537-548. doi: 10.3934/cpaa.2005.4.537
[18]

Julia M. Kroos, Christian Stinner, Christina Surulescu, Nico Surulescu. SDE-driven modeling of phenotypically heterogeneous tumors: The influence of cancer cell stemness. Discrete and Continuous Dynamical Systems - B, 2019, 24 (8) : 4629-4663. doi: 10.3934/dcdsb.2019157
[19]

Ming-Chia Li. Stability of parameterized Morse-Smale gradient-like flows. Discrete and Continuous Dynamical Systems, 2003, 9 (4) : 1073-1077. doi: 10.3934/dcds.2003.9.1073
[20]

Patrick Nelson, Noah Smith, Stanca Ciupe, Weiping Zou, Gilbert S. Omenn, Massimo Pietropaolo. Modeling dynamic changes in type 1 diabetes progression: Quantifying $\beta$-cell variation after the appearance of islet-specific autoimmune responses. Mathematical Biosciences & Engineering, 2009, 6 (4) : 753-778. doi: 10.3934/mbe.2009.6.753

2018 Impact Factor: 1.313

Tools

Metrics

  • PDF downloads (36)
  • HTML views (0)
  • Cited by (5)

Other articles
by authors

[Back to Top]

Copyright © 2022 American Institute of Mathematical Sciences | Privacy Policy