September  2009, 12(2): 439-453. doi: 10.3934/dcdsb.2009.12.439

Response of yeast mutants to extracellular calcium variations

1. 

Division of Mathematical and Natural Sciences, Arizona State University, Phoenix, AZ 85069-7100, United States, United States, United States

Received  October 2008 Revised  May 2009 Published  July 2009

We study, both experimentally and through mathematical modeling, the response of wild type and mutant yeast strains to systematic variations of extracellular calcium abundance. We extend a previously developed mathematical model (Cui and Kaandorp, Cell Calcium, 39, 337 (2006))[3], that explicitly considers the population and activity of proteins with key roles in calcium homeostasis. Modifications of the model can directly address the responses of mutants lacking these proteins. We present experimental results for the response of yeast cells to sharp, step-like variations in external $Ca^{++}$ concentrations. We analyze the properties of the model and use it to simulate the experimental conditions investigated. The model and experiments diverge more markedly in the case of mutants laking the Pmc1 protein. We discuss possible extensions of the model to address these findings.
Citation: Pamela A. Marshall, Eden E. Tanzosh, Francisco J. Solis, Haiyan Wang. Response of yeast mutants to extracellular calcium variations. Discrete & Continuous Dynamical Systems - B, 2009, 12 (2) : 439-453. doi: 10.3934/dcdsb.2009.12.439
[1]

Gianluca D'Antonio, Paul Macklin, Luigi Preziosi. An agent-based model for elasto-plastic mechanical interactions between cells, basement membrane and extracellular matrix. Mathematical Biosciences & Engineering, 2013, 10 (1) : 75-101. doi: 10.3934/mbe.2013.10.75

[2]

Jiying Ma, Dongmei Xiao. Nonlinear dynamics of a mathematical model on action potential duration and calcium transient in paced cardiac cells. Discrete & Continuous Dynamical Systems - B, 2013, 18 (9) : 2377-2396. doi: 10.3934/dcdsb.2013.18.2377

[3]

Shiqiu Liu, Frédérique Oggier. On applications of orbit codes to storage. Advances in Mathematics of Communications, 2016, 10 (1) : 113-130. doi: 10.3934/amc.2016.10.113

[4]

Houssein Ayoub, Bedreddine Ainseba, Michel Langlais, Rodolphe Thiébaut. Parameters identification for a model of T cell homeostasis. Mathematical Biosciences & Engineering, 2015, 12 (5) : 917-936. doi: 10.3934/mbe.2015.12.917

[5]

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

[6]

Yuchi Qiu, Weitao Chen, Qing Nie. Stochastic dynamics of cell lineage in tissue homeostasis. Discrete & Continuous Dynamical Systems - B, 2019, 24 (8) : 3971-3994. doi: 10.3934/dcdsb.2018339

[7]

Peter W. Bates, Yu Liang, Alexander W. Shingleton. Growth regulation and the insulin signaling pathway. Networks & Heterogeneous Media, 2013, 8 (1) : 65-78. doi: 10.3934/nhm.2013.8.65

[8]

H. G. E. Hentschel, Alan Fine, C. S. Pencea. Biological computing with diffusion and excitable calcium stores. Mathematical Biosciences & Engineering, 2004, 1 (1) : 147-159. doi: 10.3934/mbe.2004.1.147

[9]

Bogdan Kazmierczak, Zbigniew Peradzynski. Calcium waves with mechano-chemical couplings. Mathematical Biosciences & Engineering, 2013, 10 (3) : 743-759. doi: 10.3934/mbe.2013.10.743

[10]

Mohammad Asadzadeh, Anders Brahme, Jiping Xin. Galerkin methods for primary ion transport in inhomogeneous media. Kinetic & Related Models, 2010, 3 (3) : 373-394. doi: 10.3934/krm.2010.3.373

[11]

Sarthok Sircar, Anthony Roberts. Ion mediated crosslink driven mucous swelling kinetics. Discrete & Continuous Dynamical Systems - B, 2016, 21 (6) : 1937-1951. doi: 10.3934/dcdsb.2016030

[12]

David S. Ross, Christina Battista, Antonio Cabal, Khamir Mehta. Dynamics of bone cell signaling and PTH treatments of osteoporosis. Discrete & Continuous Dynamical Systems - B, 2012, 17 (6) : 2185-2200. doi: 10.3934/dcdsb.2012.17.2185

[13]

Mingxing Zhou, Jing Liu, Shuai Wang, Shan He. A comparative study of robustness measures for cancer signaling networks. Big Data & Information Analytics, 2017, 2 (1) : 87-96. doi: 10.3934/bdia.2017011

[14]

Jaroslaw Smieja, Malgorzata Kardynska, Arkadiusz Jamroz. The meaning of sensitivity functions in signaling pathways analysis. Discrete & Continuous Dynamical Systems - B, 2014, 19 (8) : 2697-2707. doi: 10.3934/dcdsb.2014.19.2697

[15]

Jinzhi Lei, Frederic Y. M. Wan, Arthur D. Lander, Qing Nie. Robustness of signaling gradient in drosophila wing imaginal disc. Discrete & Continuous Dynamical Systems - B, 2011, 16 (3) : 835-866. doi: 10.3934/dcdsb.2011.16.835

[16]

Tomáš Roubíček, Giuseppe Tomassetti. Thermomechanics of hydrogen storage in metallic hydrides: Modeling and analysis. Discrete & Continuous Dynamical Systems - B, 2014, 19 (7) : 2313-2333. doi: 10.3934/dcdsb.2014.19.2313

[17]

Phil Howlett, Julia Piantadosi, Paraskevi Thomas. Management of water storage in two connected dams. Journal of Industrial & Management Optimization, 2007, 3 (2) : 279-292. doi: 10.3934/jimo.2007.3.279

[18]

Ali Tebbi, Terence Chan, Chi Wan Sung. Linear programming bounds for distributed storage codes. Advances in Mathematics of Communications, 2019, 0 (0) : 0-0. doi: 10.3934/amc.2020024

[19]

Christos V. Nikolopoulos. Mathematical modelling of a mushy region formation during sulphation of calcium carbonate. Networks & Heterogeneous Media, 2014, 9 (4) : 635-654. doi: 10.3934/nhm.2014.9.635

[20]

Jaouad Danane, Karam Allali. Optimal control of an HIV model with CTL cells and latently infected cells. Numerical Algebra, Control & Optimization, 2019, 0 (0) : 0-0. doi: 10.3934/naco.2019048

2018 Impact Factor: 1.008

Metrics

  • PDF downloads (7)
  • HTML views (0)
  • Cited by (3)

[Back to Top]