Validation of a model of the GAL regulatory system via robustness analysis of its bistability characteristics

BackgroundIn Saccharomyces cerevisiæ, structural bistability generates a bimodal expression of the galactose uptake genes (GAL) when exposed to low and high glucose concentrations. This indicates that yeast cells can decide between using either the limited amount of glucose or growing on galactose under changing environmental conditions. A crucial requirement for any plausible mechanistic model of this system is that it reproduces the robustness of the bistable response observed in vivo against inter-individual parametric variability and fluctuating environmental conditions.ResultsWe show how a control-theoretic analysis of the robustness of a model of the GAL regulatory network may be used to establish the model’s plausibility in characterizing the persistent memory of different carbon sources, without the need for extensive simulations. Chemical Reaction Network Theory is used to establish that the proposed network model is compatible with structural bistability. The robustness of each of the two operative conditions against fluctuations of the species concentrations is demonstrated by studying the Domains of Attraction of the corresponding equilibrium points. Finally, we use a global robustness analysis method based on Semi-Definite Programming to evaluate the modification of the bistable steady states induced by multiple parametric variations throughout bounded regions of the parameter space.ConclusionsOur analysis provides convincing evidence for the robustness, and hence plausibility, of the GAL regulatory network model. The proposed workflow also demonstrates the power of analytical methods from control theory to provide a direct quantitative characterization of the dynamics of multistable biomolecular regulatory systems without recourse to extensive computer simulations.

[1]  Ufuk Topcu,et al.  Robust Region-of-Attraction Estimation , 2010, IEEE Transactions on Automatic Control.

[2]  Frank Allgöwer,et al.  Guaranteed steady state bounds for uncertain (bio-)chemical processes using infeasibility certificates , 2010 .

[3]  Eduardo Sontag,et al.  Untangling the wires: A strategy to trace functional interactions in signaling and gene networks , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[4]  A. Vicino,et al.  On the estimation of asymptotic stability regions: State of the art and new proposals , 1985 .

[5]  Y. Kuznetsov Elements of Applied Bifurcation Theory , 2023, Applied Mathematical Sciences.

[6]  Francesco Amato,et al.  Structural Bistability of the GAL Regulatory Network and Characterization of its Domains of Attraction , 2012, J. Comput. Biol..

[7]  J. Doyle,et al.  Robustness as a measure of plausibility in models of biochemical networks. , 2002, Journal of theoretical biology.

[8]  Frank Allgöwer,et al.  Steady state and (bi-) stability evaluation of simple protease signalling networks , 2007, Biosyst..

[9]  Mathukumalli Vidyasagar,et al.  Maximal lyapunov functions and domains of attraction for autonomous nonlinear systems , 1981, Autom..

[10]  Michael G. Safonov,et al.  Stability analysis of the GAL regulatory network in Saccharomyces cerevisiae and Kluyveromyces lactis , 2010, BMC Bioinformatics.

[11]  Sharad Bhartiya,et al.  Autoregulation of regulatory proteins is key for dynamic operation of GAL switch in Saccharomyces cerevisiae , 2004, FEBS letters.

[12]  Paike Jayadeva Bhat Galactose Regulon of Yeast: From Genetics to Systems Biology , 2008 .

[13]  Anton van den Hengel,et al.  Semidefinite Programming , 2014, Computer Vision, A Reference Guide.

[14]  Carlo Cosentino,et al.  On the region of attraction of nonlinear quadratic systems , 2007, Autom..

[15]  Antonis Papachristodoulou,et al.  On validation and invalidation of biological models , 2009, BMC Bioinformatics.

[16]  P de Atauri,et al.  Evolution of 'design' principles in biochemical networks. , 2004, Systems biology.

[17]  J. Stelling,et al.  Robustness of Cellular Functions , 2004, Cell.

[18]  Stephen P. Boyd,et al.  Linear Matrix Inequalities in Systems and Control Theory , 1994 .

[19]  D G Bates,et al.  Validation and invalidation of systems biology models using robustness analysis. , 2011, IET systems biology.

[20]  John P. Wikswo,et al.  External Control of the GAL Network in S. cerevisiae: A View from Control Theory , 2011, PloS one.

[21]  W. Stout,et al.  Domain of Attraction , 2006 .

[22]  A. Oudenaarden,et al.  Enhancement of cellular memory by reducing stochastic transitions , 2005, Nature.

[23]  Graziano Chesi Estimating the domain of attraction for uncertain polynomial systems , 2004, Autom..

[24]  Willy Govaerts,et al.  MATCONT: A MATLAB package for numerical bifurcation analysis of ODEs , 2003, TOMS.

[25]  F. Allgöwer,et al.  Robustness properties of apoptosis models with respect to parameter variations and intrinsic noise. , 2005, Systems biology.

[26]  Herbert M Sauro,et al.  Sensitivity analysis of stoichiometric networks: an extension of metabolic control analysis to non-steady state trajectories. , 2003, Journal of theoretical biology.

[27]  M. Feinberg Chemical reaction network structure and the stability of complex isothermal reactors—I. The deficiency zero and deficiency one theorems , 1987 .

[28]  Antonis Papachristodoulou,et al.  A New Computational Tool for Establishing Model Parameter Identifiability , 2009, J. Comput. Biol..

[29]  E. Yaz Linear Matrix Inequalities In System And Control Theory , 1998, Proceedings of the IEEE.

[30]  Antonis Papachristodoulou,et al.  Discriminating between rival biochemical network models: three approaches to optimal experiment design , 2010, BMC Systems Biology.

[31]  G. Chesi Domain of Attraction: Analysis and Control via SOS Programming , 2011 .

[32]  Declan G. Bates,et al.  Feedback Control in Systems Biology , 2011 .

[33]  Antonis Papachristodoulou,et al.  Advanced Methods and Algorithms for Biological Networks Analysis , 2006, Proceedings of the IEEE.

[34]  Ufuk Topcu,et al.  Local Stability Analysis for Uncertain Nonlinear Systems , 2009, IEEE Transactions on Automatic Control.

[35]  E. Ostertag Linear Matrix Inequalities , 2011 .

[36]  Nils Blüthgen,et al.  How robust are switches in intracellular signaling cascades? , 2003, Journal of theoretical biology.

[37]  M. Feinberg Chemical reaction network structure and the stability of complex isothermal reactors—II. Multiple steady states for networks of deficiency one , 1988 .

[38]  A. Wagner Robustness and Evolvability in Living Systems , 2005 .

[39]  I Postlethwaite,et al.  Robustness analysis of biochemical network models. , 2006, Systems biology.

[40]  Vincent Schächter,et al.  The adaptive filter of the yeast galactose pathway. , 2006, Journal of theoretical biology.

[41]  Francesco Amato,et al.  Stability analysis of nonlinear quadratic systems via polyhedral Lyapunov functions , 2008, 2008 American Control Conference.

[42]  P. J. Bhat,et al.  Growth-related model of the GAL system in Saccharomyces cerevisiae predicts behaviour of several mutant strains. , 2012, IET systems biology.