Module-Based Analysis of Robustness Tradeoffs in the Heat Shock Response System

Biological systems have evolved complex regulatory mechanisms, even in situations where much simpler designs seem to be sufficient for generating nominal functionality. Using module-based analysis coupled with rigorous mathematical comparisons, we propose that in analogy to control engineering architectures, the complexity of cellular systems and the presence of hierarchical modular structures can be attributed to the necessity of achieving robustness. We employ the Escherichia coli heat shock response system, a strongly conserved cellular mechanism, as an example to explore the design principles of such modular architectures. In the heat shock response system, the sigma-factor σ32 is a central regulator that integrates multiple feedforward and feedback modules. Each of these modules provides a different type of robustness with its inherent tradeoffs in terms of transient response and efficiency. We demonstrate how the overall architecture of the system balances such tradeoffs. An extensive mathematical exploration nevertheless points to the existence of an array of alternative strategies for the existing heat shock response that could exhibit similar behavior. We therefore deduce that the evolutionary constraints facing the system might have steered its architecture toward one of many robustly functional solutions.

[1]  Sarah E. Ades,et al.  Regulation of the Alternative Sigma Factor σE during Initiation, Adaptation, and Shutoff of the Extracytoplasmic Heat Shock Response in Escherichia coli , 2003, Journal of bacteriology.

[2]  H. McAdams,et al.  Gene regulation: Towards a circuit engineering discipline , 2000, Current Biology.

[3]  H. Yanagi,et al.  Synergistic roles of HslVU and other ATP-dependent proteases in controlling in vivo turnover of sigma32 and abnormal proteins in Escherichia coli , 1997, Journal of bacteriology.

[4]  W. Donachie,et al.  CHAPTER 3 – Temporal Control of Gene Expression in Bacteria , 1969 .

[5]  M Ptashne,et al.  Transcription initiation: imposing specificity by localization. , 2001, Essays in biochemistry.

[6]  John Doyle,et al.  Supplementary Notes: Elementary Feedback Concepts , 2005 .

[7]  John C. Doyle,et al.  Surviving heat shock: control strategies for robustness and performance. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[8]  A. Arkin,et al.  Stochastic kinetic analysis of developmental pathway bifurcation in phage lambda-infected Escherichia coli cells. , 1998, Genetics.

[9]  J. Keasling,et al.  Mathematical Model of the lac Operon: Inducer Exclusion, Catabolite Repression, and Diauxic Growth on Glucose and Lactose , 1997, Biotechnology progress.

[10]  Vivek K. Mutalik,et al.  Insights into transcriptional regulation and sigma competition from an equilibrium model of RNA polymerase binding to DNA. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[11]  K. Nakahigashi,et al.  Regulation of the heat-shock response. , 1999, Current opinion in microbiology.

[12]  Y. Kyōgoku,et al.  Translational induction of heat shock transcription factor sigma32: evidence for a built-in RNA thermosensor. , 1999, Genes & development.

[13]  Katherine C. Chen,et al.  Sniffers, buzzers, toggles and blinkers: dynamics of regulatory and signaling pathways in the cell. , 2003, Current opinion in cell biology.

[14]  Takashi Yura,et al.  Regulatory Conservation and Divergence of ς32 Homologs from Gram-Negative Bacteria: Serratia marcescens, Proteus mirabilis, Pseudomonas aeruginosa, and Agrobacterium tumefaciens , 1998, Journal of bacteriology.

[15]  H H McAdams,et al.  Towards a circuit engineering discipline. , 2000, Current biology : CB.

[16]  Hirotada Mori,et al.  Heat shock regulation in the ftsH null mutant of Escherichia coli: dissection of stability and activity control mechanisms of σ32in vivo , 1998, Molecular microbiology.

[17]  H. Bujard,et al.  A cycle of binding and release of the DnaK, DnaJ and GrpE chaperones regulates activity of the Escherichia coli heat shock transcription factor sigma32. , 1996, The EMBO journal.

[18]  H. Bremer Modulation of Chemical Composition and Other Parameters of the Cell by Growth Rate , 1999 .

[19]  Carol A. Gross,et al.  The heat shock response of E. coli is regulated by changes in the concentration of σ32 , 1987, Nature.

[20]  P. Christen,et al.  Kinetics of molecular chaperone action. , 1994, Science.

[21]  石浜 明,et al.  Control of cell growth and division , 1991 .

[22]  U. Alon,et al.  Robustness in bacterial chemotaxis , 2022 .

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

[24]  H. Kurata,et al.  CADLIVE dynamic simulator: direct link of biochemical networks to dynamic models. , 2005, Genome research.

[25]  A. Ishihama,et al.  Regulation of RNA polymerase sigma subunit synthesis in Escherichia coli: intracellular levels of sigma 70 and sigma 38 , 1995, Journal of bacteriology.

[26]  M. Ptashne,et al.  Imposing specificity by localization: mechanism and evolvability , 1998, Current Biology.

[27]  A. Barabasi,et al.  Hierarchical Organization of Modularity in Metabolic Networks , 2002, Science.

[28]  A. Goldbeter Computational approaches to cellular rhythms , 2002, Nature.

[29]  Carol A Gross,et al.  A chaperone network controls the heat shock response in E. coli. , 2004, Genes & development.

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

[31]  K. Kohn Molecular interaction map of the mammalian cell cycle control and DNA repair systems. , 1999, Molecular biology of the cell.

[32]  J. Hopfield,et al.  From molecular to modular cell biology , 1999, Nature.

[33]  Arthur R. Schulz Enzyme Kinetics: Biochemical systems theory , 1994 .

[34]  W. McClure,et al.  Mechanism and control of transcription initiation in prokaryotes. , 1985, Annual review of biochemistry.

[35]  J. Stelling,et al.  Robustness properties of circadian clock architectures. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[36]  L. Hood,et al.  Reverse Engineering of Biological Complexity , 2007 .

[37]  C. Rao,et al.  Control motifs for intracellular regulatory networks. , 2001, Annual review of biomedical engineering.

[38]  R. Burgess,et al.  Nonspecific interactions of Escherichia coli RNA polymerase with native and denatured DNA: differences in the binding behavior of core and holoenzyme. , 1978, Biochemistry.

[39]  Hana El-Samad,et al.  Regulated degradation is a mechanism for suppressing stochastic fluctuations in gene regulatory networks. , 2006, Biophysical journal.

[40]  H. Kurata,et al.  CADLIVE for constructing a large-scale biochemical network based on a simulation-directed notation and its application to yeast cell cycle. , 2003, Nucleic acids research.