Architecture, networks, and complexity

1. John Doyle Architecture, networks, and complexity John G Braun Professor Control and dynamical systems BioEngineering, Electrical Engineering Caltech

2. NRC theory report: Bad news and good news Bad: Attempts to connect with theory • Topology, modularity, information,… Good: Biology motivation • Diversity • Metabolism • Cell interior • Architecture (is not topology) • Robustness • Decision • Behavior

3. Alternative: Essential ideas • Listening to physicians, biologists, and engineers • Robust yet fragile (RYF) • “Constraints that deconstrain” (G&K) • Unity creating diversity • Network architecture • Layering • Control and dynamics (C&D) • Hourglasses and Bowties

4. Collaborators and contributors(partial list) Biology:Csete,Yi, El-Samad, Khammash, Tanaka, Arkin, Savageau, Simon, AfCS, Kurata, Smolke, Gross, Kitano, Hucka, Sauro, Finney,Bolouri, Gillespie, Petzold, F Doyle, Stelling, Caporale,… Theory:Parrilo, Carlson, Murray,Vinnicombe, Paganini, Mitra Papachristodoulou, Prajna, Goncalves, Fazel, Liu,Lall, D’Andrea, Jadbabaie,Dahleh, Martins, Recht,many more current and former students, … Web/Internet: Li, Alderson, Chen, Low, Willinger,Kelly, Zhu,Yu, Wang, Chandy, … Turbulence: Bamieh, Bobba, McKeown,Gharib,Marsden, … Physics:Sandberg,Mabuchi, Doherty, Barahona, Reynolds, Disturbance ecology: Moritz, Carlson,… Finance:Martinez, Primbs, Yamada, Giannelli,… Current Caltech Former Caltech Longterm Visitor Other

5. Thanks to you for inviting me, and • NSF ITR • AFOSR • NIH/NIGMS • ARO/ICB • DARPA • Lee Center for Advanced Networking (Caltech) • Boeing • Pfizer • Hiroaki Kitano (ERATO) • Braun family

6. My interests Multiscale Physics Core theory challenges Network Centric, Pervasive, Embedded, Ubiquitous Systems Biology & Medicine Sustainability?

7. Bacterial networks • Necessity in chemotaxis • Design principles in heat shock response • Architecture of metabolism • Origin of high variability and power laws • Architecture of the cell • Control of core metabolism and glycolytic oscillations • SBML/SBW • SOSTOOLS • Wildfire ecology • Physiology and medicine (new) Systems Biology & Medicine Publications: Science, Nature, Cell, PNAS, PLOS, Bioinfo., Trends, IEEE Proc., IET SysBio, FEBS, PRL,…

8. Wilbur Wright on Control, 1901 • “We know how to construct airplanes.” (lift and drag) • “Men also know how to build engines.” (propulsion) • “Inability to balance and steer still confronts students of the flying problem.” (control) • “When this one feature has been worked out, the age of flying will have arrived, for all other difficulties are of minor importance.”

9. Feathers and flapping? Or lift, drag, propulsion, and control?

10. Recommendations • (Obviously…) More and better theory • Need an “architecture” for research that is as networked as biology and our best technologies • Create the right “waist” of the research hourglass • E.g. find the constraints that deconstrain

11. Human complexity Robust Yet Fragile • Efficient, flexible metabolism • Complex development and • Immune systems • Regeneration & renewal • Complex societies • Advanced technologies • Obesity and diabetes • Rich microbe ecosystem • Inflammation, Auto-Im. • Cancer • Epidemics, war, … • Catastrophic failures • Evolved mechanisms for robustness allow for, even facilitate, novel, severe fragilities elsewhere • often involving hijacking/exploiting the same mechanism • There are hard constraints (i.e. theorems with proofs)

12. Peter Sterling and Allostasis Blood food intake Glucose Oxygen Amino acids Fatty acids Organs Tissues Cells Molecules Universal metabolic system

13. Universal reward systems sports music dance crafts art toolmaking sex food Prefrontal cortex Accumbens dopamine VTA Dopamine, Ghrelin, Leptin,…

14. Universal reward systems sports music dance crafts art toolmaking sex food Prefrontal cortex Accumbens dopamine VTA food Blood Organs Tissues Cells Molecules Glucose Oxygen Universal metabolic system

15. Universal reward systems work family community nature Prefrontal cortex Accumbens dopamine VTA food sex toolmaking sports music dance crafts art Robust and adaptive, yet …

16. work family community nature Prefrontal cortex Accumbens dopamine VTA sex food toolmaking sports music dance crafts art

17. work family community nature market/ consumer culture money salt sugar/fat nicotine alcohol Prefrontal cortex Accumbens dopamine VTA Vicarious sex food toolmaking sports music dance crafts art industrial agriculture

18. work family community nature money salt sugar/fat nicotine alcohol Prefrontal cortex Accumbens dopamine VTA Vicarious sex toolmaking sports music dance crafts art cocaine amphetamine

19. coronary, cerebro- vascular, reno- vascular hyper- tension athero- sclerosis diabetes cancer inflammation cirrhosis immune suppression accidents/ homicide/ suicide high sodium money obesity salt sugar/fat nicotine alcohol overwork smoking Vicarious alcoholism drug abuse

20. coronary, cerebro- vascular, reno- vascular hyper- tension athero- sclerosis diabetes cancer inflammation cirrhosis immune suppression accidents/ homicide/ suicide high sodium money dopamine VTA obesity salt sugar/fat nicotine alcohol overwork smoking Vicarious alcoholism Glucose Oxygen drug abuse

21. Human complexity Robust Yet Fragile • Efficient, flexible metabolism • Complex development and • Immune systems • Regeneration & renewal • Complex societies • Advanced technologies • Obesity and diabetes • Rich microbe ecosystem • Inflammation, Auto-Im. • Cancer • Epidemics, war, … • Catastrophic failures • Evolved mechanisms for robustness allow for, even facilitate, novel, severe fragilities elsewhere • often involving hijacking/exploiting the same mechanism • There are hard constraints (i.e. theorems with proofs)

22. Robust yet fragile Systems can have robustness of • Some properties to • Some perturbations in • Some components and/or environment Yet fragile to other properties or perturbations. Many issues are special cases, e.g.: • Efficiency: robustness to resource scarcity • Scalability: robustness to changes in scale • Evolvability: robustness of lineages on long times to possibly large perturbations

23. Today (primary): Cell biology Today (secondary): Internet Toy example: Lego Wildfire ecology Physiology Power grid Manufacturing Transportation Other possibilities: Turbulence Statistical mechanics Physiology (e.g. HR variability, exercise and fatigue, trauma and intensive care) RYF physio (e.g. diabetes, obesity, addiction, …) Disasters statistics (earthquakes) Case studies

24. Bio and hi-tech nets • Exhibit extremes of • Robust Yet Fragile • Simplicity and complexity • Unity and diversity • Evolvable and frozen • Constrained and deconstrained What makes this possible and/ or inevitable? Architecture

25. We use this word all the time. • What do we really mean by it? • What would a theory look like? Architecture

26. Human complexity Robust Yet Fragile • Obesity and diabetes • Rich microbe ecosystem • Inflammation, Auto-Im. • Cancer • Epidemics, war, … • Catastrophic failures • Efficient, flexible metabolism • Complex development and • Immune systems • Regeneration & renewal • Complex societies • Advanced technologies • It is much easier to create the robust features than to prevent the fragilities. • There are poorly understood “conservation laws” at work

27. Robust yet fragile Most essential challenge in technology, society, politics, ecosystems, medicine, etc: • Managing spiraling complexity/fragility • Not predicting what is likely or typical • But understanding what is catastrophic (though perhaps rare) What community will step up and be central in this challenge?

28. Systems requirements: functional, efficient, robust, evolvable, scalable Perturbations Robust yet fragile System and architecture Components and materials Perturbations

29. System-level Architecture= Constraints Aim: a universal taxonomy of complex systems and theories Emergent Protocols Contraints that deconstrain Component • Describe systems/components in terms of constraints on what is possible • Decompose constraints into component, system-level, protocols, and emergent • Not necessarily unique, but hopefully illuminating nonetheless

30. universal carriers fan-out of diverse outputs fan-in of diverse inputs Diverse function Universal Control Diverse components Universal architectures • Hourglasses for layering of control • Bowties for flows within layers

31. Evolution of theory • Verbal arguments (stories, cartoons, diagrams) • Data and statistics (plots, tables) • Modeling and simulation (dynamics, numerics) • Analysis (theorems, proofs) • Synthesis (hard limits on the achievable, reverse engineering good designs, forward engineering new designs) All levels interact and iterate

32. Example: Theory of planetary motion • Verbal (Ptolemy, Copernicus) • Data & stats (Brahe, Galileo, Kepler) • Model & sim (Newton, Einstein) • Analysis (Lagrange, Hamilton, Poincare) • Synthesis (NASA/JPL) All levels interact and iterate

33. Describe theory Show some math Just to give a flavor You can ignore details Always return to verbal descriptions and hand-waving summaries Drill down

34. Synthesis theories: Limits and tradeoffs On systems and their components • Thermodynamics (Carnot) • Communications (Shannon) • Control (Bode) • Computation (Turing/Gödel) Assume different architectures a priori. No networks

35. Hard limits and tradeoffs On systems and their components • Thermodynamics (Carnot) • Communications (Shannon) • Control (Bode) • Computation (Turing/Gödel) • Fragmented and incompatible • Cannot be used as a basis for comparing architectures • New unifications are encouraging No dynamics or feedback

36. Hard limits and tradeoffs Robust/ fragile is unifying concept On systems and their components • Thermodynamics (Carnot) • Communications (Shannon) • Control (Bode) • Computation (Turing/Gödel) • Include dynamics and feedback • Extend to networks • New unifications are encouraging

37. Why glycolytic oscillations? • Various answers depend on meaning of “why” • Will go deeper into “why” using stages… • Start with simplest possible models • Motivate generalizable and scalable methods • Extremely familiar and “done” problem in biology and dynamics at the small circuit level • Convenient to introduce new theory and thinking using the most familiar possible examples

38. Basics of glyc-oscillations • Verbal arguments (stories, cartoons, diagrams) • Data and statistics (plots, tables) Result: Cells and extracts show oscillatory behavior. Why?

39. Why? Modeling and simulation • Verbal arguments (stories, cartoons, diagrams) • Data and statistics (plots, tables) • Modeling and simulation (dynamics, numerics) • Why = propose mechanism, model, simulate, compare with data • Has been done extensively for this problem • What’s new? Simplicity and robustness

40. x y consumption Autocatalytic Control reaction metabolite reaction

41. Catabolism Precursors Carriers Core metabolism Sugars Amino Acids Nucleotides Fatty acids Co-factors

42. Catabolism Precursors Carriers

43. Gly G1P G6P F6P F1-6BP Gly3p ATP 13BPG 3PG TCA Oxa ACA 2PG PEP Pyr NADH Cit Catabolism

44. Gly G1P G6P F6P F1-6BP Gly3p 13BPG 3PG TCA Oxa ACA 2PG PEP Pyr Cit Precursors

45. Gly G1P G6P Precursors F6P Autocatalytic F1-6BP Gly3p Carriers ATP 13BPG 3PG TCA Oxa ACA 2PG PEP Pyr NADH Cit

46. Gly G1P G6P Regulatory F6P F1-6BP Gly3p ATP 13BPG 3PG TCA Oxa ACA 2PG PEP Pyr NADH Cit

47. Gly G1P G6P F6P F1-6BP Gly3p 13BPG 3PG TCA Oxa ACA 2PG PEP Pyr Cit

48. If we drew the feedback loops the diagram would be unreadable. Gly G1P G6P F6P F1-6BP Gly3p ATP 13BPG 3PG TCA Oxa ACA 2PG PEP Pyr NADH Cit

49. Internal Products Nutrients Stoichiometry or mass and energy balance Biology is not a graph.

50. Stoichiometry plus regulation  Matrix of integers  “Simple,” can be known exactly  Amenable to high throughput assays and manipulation  Bowtie architecture  Vector of (complex?) functions  Difficult to determine and manipulate  Effected by stochastics and spatial/mechanical structure  Hourglass architecture  Can be modeled by optimal controller (?!?)