A hybrid stochastic model of the budding yeast cell cycle

The growth and division of eukaryotic cells are regulated by complex, multi-scale networks. In this process, the mechanism of controlling cell-cycle progression has to be robust against inherent noise in the system. In this paper, a hybrid stochastic model is developed to study the effects of noise on the control mechanism of the budding yeast cell cycle. The modeling approach leverages, in a single multi-scale model, the advantages of two regimes: (1) the computational efficiency of a deterministic approach, and (2) the accuracy of stochastic simulations. Our results show that this hybrid stochastic model achieves high computational efficiency while generating simulation results that match very well with published experimental measurements.

[1]  Michael A. Gibson,et al.  Efficient Exact Stochastic Simulation of Chemical Systems with Many Species and Many Channels , 2000 .

[2]  E. O’Shea,et al.  Global analysis of protein expression in yeast , 2003, Nature.

[3]  Yiannis Kaznessis,et al.  Accurate hybrid stochastic simulation of a system of coupled chemical or biochemical reactions. , 2005, The Journal of chemical physics.

[4]  Katherine C. Chen,et al.  A Model of Yeast Cell-Cycle Regulation Based on a Standard Component Modeling Strategy for Protein Regulatory Networks , 2016, PloS one.

[5]  Mudita Singhal,et al.  COPASI - a COmplex PAthway SImulator , 2006, Bioinform..

[6]  B. Futcher,et al.  Genetic analysis of the shared role of CLN3 and BCK2 at the G(1)-S transition in Saccharomyces cerevisiae. , 1999, Genetics.

[7]  Aidan P Thompson,et al.  A constant-time kinetic Monte Carlo algorithm for simulation of large biochemical reaction networks. , 2008, The Journal of chemical physics.

[8]  J. Tyson.  Modeling the cell division cycle: cdc2 and cyclin interactions. , 1991, Proceedings of the National Academy of Sciences of the United States of America.

[9]  Shuo Wang,et al.  Efficient implementation of the hybrid method for stochastic simulation of biochemical systems , 2012, BCB.

[10]  A. Murray,et al.  Recycling the Cell Cycle Cyclins Revisited , 2004, Cell.

[11]  F. Cross,et al.  Genes that can bypass the CLN requirement for Saccharomyces cerevisiae cell cycle START. , 1994, Molecular and cellular biology.

[12]  Katherine C. Chen,et al.  Integrative analysis of cell cycle control in budding yeast. , 2004, Molecular biology of the cell.

[13]  J. Rawlings,et al.  Approximate simulation of coupled fast and slow reactions for stochastic chemical kinetics , 2002 .

[14]  John J. Tyson,et al.  A Stochastic Model of Size Control in the Budding Yeast Cell Cycle , 2018, BCB.

[15]  Nagiza F. Samatova,et al.  The sorting direct method for stochastic simulation of biochemical systems with varying reaction execution behavior , 2006, Comput. Biol. Chem..

[16]  J. Paulsson,et al.  Effects of Molecular Memory and Bursting on Fluctuations in Gene Expression , 2008, Science.

[17]  Mike Tyers,et al.  How Cells Coordinate Growth and Division , 2004, Current Biology.

[18]  Frederick R. Cross,et al.  Mechanisms Controlling Subcellular Localization of the G1 Cyclins Cln2p and Cln3p in Budding Yeast , 2001, Molecular and Cellular Biology.

[19]  F. Cross,et al.  Two redundant oscillatory mechanisms in the yeast cell cycle. , 2003, Developmental cell.

[20]  F. Cross,et al.  Testing a mathematical model of the yeast cell cycle. , 2002, Molecular biology of the cell.

[21]  Fabian J Theis,et al.  Method of conditional moments (MCM) for the Chemical Master Equation , 2013, Journal of Mathematical Biology.

[22]  Andrea Ciliberto,et al.  Antagonism and bistability in protein interaction networks. , 2008, Journal of theoretical biology.

[23]  Stefan Bornholdt,et al.  Superstability of the yeast cell-cycle dynamics: ensuring causality in the presence of biochemical stochasticity. , 2006, Journal of theoretical biology.

[24]  Minping Qian,et al.  Stochastic model of yeast cell-cycle network , 2006, q-bio/0605011.

[25]  Shuo Wang,et al.  Accuracy Analysis of Hybrid Stochastic Simulation Algorithm on Linear Chain Reaction Systems , 2018, Bulletin of Mathematical Biology.

[26]  Linda R. Petzold,et al.  Improved leap-size selection for accelerated stochastic simulation , 2003 .

[27]  P. Swain,et al.  Intrinsic and extrinsic contributions to stochasticity in gene expression , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[28]  John J. Tyson,et al.  A Stochastic Model of the Yeast Cell Cycle Reveals Roles for Feedback Regulation in Limiting Cellular Variability , 2016, PLoS Comput. Biol..

[29]  Stefan Bornholdt,et al.  Boolean network models of cellular regulation: prospects and limitations , 2008, Journal of The Royal Society Interface.

[30]  John J. Tyson,et al.  Quantitative analysis of a molecular model of mitotic control in fission yeast , 1995 .

[31]  T M Murali,et al.  From START to FINISH: computational analysis of cell cycle control in budding yeast , 2015, npj Systems Biology and Applications.

[32]  R. Bundschuh,et al.  Fluctuations and slow variables in genetic networks. , 2003, Biophysical Journal.

[33]  Katherine C. Chen,et al.  Kinetic analysis of a molecular model of the budding yeast cell cycle. , 2000, Molecular biology of the cell.

[34]  M. B,et al.  Bifurcation Analysis of a Model of Mitotic Control in Frog Eggs , 1998 .

[35]  Linda Petzold,et al.  Logarithmic Direct Method for Discrete Stochastic Simulation of Chemically Reacting Systems ∗ , 2006 .

[36]  Jean Peccoud,et al.  Measurement and modeling of transcriptional noise in the cell cycle regulatory network , 2013, Cell cycle.

[37]  J. Tyson,et al.  A stochastic, molecular model of the fission yeast cell cycle: role of the nucleocytoplasmic ratio in cycle time regulation. , 2001, Biophysical chemistry.

[38]  John J. Tyson,et al.  Hybrid ODE/SSA Model of the Budding Yeast Cell Cycle Control Mechanism with Mutant Case Study , 2017, BCB.

[39]  Frederick R. Cross,et al.  The effects of molecular noise and size control on variability in the budding yeast cell cycle , 2007, Nature.

[40]  John J Tyson,et al.  Exploring the roles of noise in the eukaryotic cell cycle , 2009, Proceedings of the National Academy of Sciences.

[41]  Masaki Sasai,et al.  Stable stochastic dynamics in yeast cell cycle. , 2007, Biophysical journal.

[42]  Adam P. Rosebrock,et al.  Daughter-Specific Transcription Factors Regulate Cell Size Control in Budding Yeast , 2009, PLoS biology.

[43]  Achim Tresch,et al.  Dynamic transcriptome analysis measures rates of mRNA synthesis and decay in yeast , 2011, Molecular systems biology.

[44]  Hong Qian,et al.  Synchronized dynamics and non-equilibrium steady states in a stochastic yeast cell-cycle network. , 2009, Mathematical biosciences.

[45]  Q. Ouyang,et al.  The yeast cell-cycle network is robustly designed. , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[46]  Attila Csikász-Nagy,et al.  Stochastic Petri Net extension of a yeast cell cycle model. , 2008, Journal of theoretical biology.

[47]  D. Thieffry,et al.  Modular logical modelling of the budding yeast cell cycle. , 2009, Molecular bioSystems.

[48]  Zhen Liu,et al.  Hybrid modeling and simulation of stochastic effects on progression through the eukaryotic cell cycle. , 2012, The Journal of chemical physics.

[49]  D. Stavenga,et al.  Gyroid cuticular structures in butterfly wing scales: biological photonic crystals , 2007, Journal of The Royal Society Interface.

[50]  Hong Li,et al.  Efficient formulation of the stochastic simulation algorithm for chemically reacting systems. , 2004, The Journal of chemical physics.

[51]  John J. Tyson,et al.  Modeling the Cell Division Cycle: M-phase Trigger, Oscillations, and Size Control , 1993 .

[52]  S. Bornholdt,et al.  Boolean Network Model Predicts Cell Cycle Sequence of Fission Yeast , 2007, PloS one.

[53]  Thomas T. Ballmer,et al.  Prospects and Limitations , 1981 .

[54]  C. Rao,et al.  Stochastic chemical kinetics and the quasi-steady-state assumption: Application to the Gillespie algorithm , 2003 .

[55]  Alan J Tackett,et al.  Genetic and biochemical evaluation of the importance of Cdc6 in regulating mitotic exit. , 2003, Molecular biology of the cell.

[56]  D. Gillespie.  A General Method for Numerically Simulating the Stochastic Time Evolution of Coupled Chemical Reactions , 1976 .

[57]  Luca Cardelli,et al.  A Stochastic Hybrid Approximation for Chemical Kinetics Based on the Linear Noise Approximation , 2016, CMSB.

[58]  D. Gillespie.  Approximate accelerated stochastic simulation of chemically reacting systems , 2001 .

[59]  John J Tyson,et al.  A model of yeast cell-cycle regulation based on multisite phosphorylation , 2010, Molecular systems biology.

[60]  Rajat Singhania,et al.  A Hybrid Model of Mammalian Cell Cycle Regulation , 2011, PLoS Comput. Biol..

[61]  M. Thattai,et al.  Intrinsic noise in gene regulatory networks , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[62]  John J. Tyson,et al.  Stochastic exit from mitosis in budding yeast , 2011, Cell cycle.

[63]  J. Tyson,et al.  Regulation of the eukaryotic cell cycle: molecular antagonism, hysteresis, and irreversible transitions. , 2001, Journal of theoretical biology.

[64]  R. Steuer.  Effects of stochasticity in models of the cell cycle: from quantized cycle times to noise-induced oscillations. , 2004, Journal of theoretical biology.

[65]  John J. Tyson,et al.  Temporal Organization of the Cell Cycle , 2008, Current Biology.

[66]  Laura L. Newcomb,et al.  ACE2 is required for daughter cell-specific G1 delay in Saccharomyces cerevisiae , 2003, Proceedings of the National Academy of Sciences of the United States of America.