280 likes | 395 Views
Module-Based Analysis of Robustness Tradeoffs in the Heat Shock Response System. Using module-based analysis coupled with rigorous mathematical comparisons,
E N D
Module-Based Analysis of Robustness Tradeoffs in the Heat Shock Response System 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.
What is protocol? How is a new module added to the existing system? Existing Module New module New Module TCP/IP USB
What is robustness? Biological systems maintain their homeostasis against environmental stress, genetic changes and noises. Perturbation Parameter Time
What is a tradeoff? A tradeoff usually refers to losing one quality or aspect of something in return for gaining another quality or aspect. It implies a decision to be made with full comprehension of both the upside and downside of a particular choice. (from WIKIPEDIA)
A universal principle? Robustness tradeoffs generate complexity. Heat shock response
Hierarchical modular structure 1 Molecular module 2 Functional module 3.Flux module
Modular Decomposition in the Heat Shock Response FF SENSOR 1. Molecular module RNAP, s32, DnaK FtsH, gene, mRNA,…. 2. Functional module PLANT FF SENSOR FB SENSOR COMPUTER ACTUATOR COMPUTER FB SENSOR PLANT ACTUATOR FF=feedfoward, FB=feedback
3. FLUX Module 1. FF:Temperature-induced translation of the rpoH mRNA 2. SEQ-FB: DnaK-mediated sequestering s32 3. DEG-FB:FtsH-mediated s32 degradation FF Feedforward flux module SEQ-FB SEQ-Feedback flux module DEG-FB DEG-Feedback flux module s32 amplification flux module
Four flux module s32 amplification FF SEQ-FB DEG-FB
Mathematical module decomposition A simple model for the heat shock response
Mathematical functional decomposition of the reduced order heat shock system
Mathematical flux decomposition of the reduced order heat shock system FF SEQ-FB DEG-FB
Mathematical system analysis The main objective of the heat shock response system is to refold denatured proteins upon exposure of higher temperatures by the heat shock proteins (hsps: e.g. chaperone, DnaK, FtsH,…).
Characterization criteria 1. Response speed 2. Yield for refolded proteins How much proteins are refolded? 3. Efficiency for chaperones How less chaperones are employed for refolding process? 4. Robustness (e.g. sensitivity analysis) Sensitivity of chaperone (DnaK) to parameter uncertainty Resistance of chaperone (DnaK) to noise
Virtual knockout mutant A flux module is removed while conserving the other modules in computers. A flux module is disabled to explore the function of it.
Mathematical comparison for robustness Some performances are compared while the others are set to the same. For example, a response speed is compared between wild type and a virtual knockout mutant while the yield and efficiency are set to the same. Wild: SEQ+DEG+FF Yield Efficiency Response speed Mutant: SEQ+FF Yield Efficiency Response speed = = >
SEQ-FB (DnaK-mediated sequestering s32) It seems sufficient for refolding proteins. Why other flux modules are added? At least two flux modules are added to the heat shock response. 1. (FF)Temperature-induced translation of the rpoH mRNA 2. (DEG-FB)FtsH-mediated s32 degradation
Time course of s32 and yield A response time is compared: FF slow SEQ slow SEQ+DEG middle SEQ+DEG+FF fast
FF SEQ+FF SEQ+DEG+FF Response time FFslow SEQ+DEG+FFvery fast SEQ+FFvery fast at a high concentration of s32
Sensitivity analysis Robustness of chaperone against parameter uncertainty SEQ +DEG SEQ +DEG +FF SEQ SEQ enhances the robustness (low sensitivity), while neither DEG addition norFF addition does it.
Robustness to noise SEQ SEQ+DEG Stochastic simulation Addition of DEG-FB provides the robustness to noise
Robustness and Tradeoff Robustness tradeoffs generate complex regulations.
Two cinarios for the heat shock response evolution SEQ Resistance to parameter uncertainty Resistance to noise +Fast response +High yield SEQ+DEG +Fast response +Resistance to noise SEQ+FF SEQ+DEG+FF +High yield Low s32 concentration in cytoplasm High s32concnetration in periplasm
Interconnected feedback loops Fragility is generated. s32 is very weak.
Protocol for new flux module addition Evolvable architecture of the interconnected feedback
Similarity between biology and engineering Hierarchical module architecture Robustness tradeoffs evolve complex systems
Strategy for exploring design principles Virtual biological systems In silico modeling Comparison Biological systems Engineering systems Design principle underlying molecular networks (bioalgorithm) In analogy to engineering systems Kurata, 2000