http www cds caltech edudoyleshortcourse htm Systems Biology

http: //www. cds. caltech. edu/~doyle/shortcourse. htm Systems Biology Shortcourse May 21 -24 Winnett Lounge, Caltech Speakers: Adam Arkin (UC Berkeley), Frank Doyle (UCSB), Drew Endy (MIT), Dan Gillespie (Caltech), Michael Savageau (UC Davis) Organized by John Doyle (Caltech). There is no registration or fees. Note: Friday 4 pm talk by Adam Arkin in Beckman Institute Auditorium.

Collaborators and contributors (partial list) Theory: Parrilo, Carlson, Paganini, Papachristodoulo, Prajna, Goncalves, Fazel, Lall, D’Andrea, Jadbabaie, many current and former students, … Web/Internet: Low, Willinger, Vinnicombe, Kelly, Zhu, Yu, Wang, Chandy, Effros, … Biology: Csete, Yi, Tanaka, Arkin, Savageau, Simon, Af. CS, Kurata, Khammash, El-Samad, Gross, Bolouri, Kitano, Hucka, Sauro, Finney, … Turbulence: Bamieh, Dahleh, Bobba, Gharib, Marsden, … Physics: Mabuchi, Doherty, Barahona, Reynolds, Asimakapoulos, … Engineering CAD: Ortiz, Murray, Schroder, Burdick, … Disturbance ecology: Moritz, Carlson, Robert, … Caltech faculty Finance: Martinez, Primbs, Yamada, Giannelli, … Other Caltech Other

Whole cell metabolism Core metabolism Polymerization and assembly Transport Autocatalytic and regulatory feedback

Metabolite Enzyme Autocatalysis +Regulation

Enzyme - ++ Metabolite

Stoichiometry or mass and energy balance Interna l Nutrients Products

Core metabolism

Whole cell metabolism Core metabolism Polymerization and assembly Transport Autocatalytic and regulatory feedback

Nested “bowties” Core metabolism Polymerization and assembly transport Autocatalytic and regulatory feedback

Nested “bowties” Core metabolism transport Our first universal architecture Polymerization and assembly

The core metabolism “bowtie” Nutrients Products

Nucleotides Catabolism Carriers and Sugars Precursor Metabolites Amino Acids Fatty acids Energy and reducing Cartoon metabolism Biosynthesis

Catabolism Carriers and Precursor Metabolites Nucleotides Sugars Amino Acids Fatty acids Energy and reducing The metabolism “bowtie” protocol Catabolism Nutrients Synthesis Products

Core: special purpose enzymes controlled by competitive inhibition and allostery Un in rta ce Edges: general purpose polymerases and machines controlled by regulated recruitment e c Un n i a rt

Core: Highly efficient Un n i a rt in rta ce e c Un Edges: Robustness and flexibility

Almost everything complex is made this way: Cars, planes, buildings, power, fuel, laptops, … This “cartoon” is pure protocol.

Collect and import raw materials Common currencies and building blocks Complex assembly Manufacturing and metabolism Polymerization and assembly Taxis and transport Core metabolism Autocatalytic and regulatory feedback

Electric power Variety of producers

Electric power Variety of consumers

Variety of producers • • • Energy carriers Variety of consumers 110 V, 60 Hz AC (230 V, 50 Hz AC) Gasoline ATP, glucose, etc Proton motive force

Complex assembly Raw materials Building blocks Complex assembly

Collect and import raw materials Common currencies and building blocks Complex assembly Steel manufacturing

transport metabolism assembly Core: special purpose machines controlled by allostery Variety of producers Energy carriers Variety of consumers

transport metabolism assembly Edges: general purpose machines controlled by regulated recruitment Variety of producers Energy carriers Variety of consumers

metabolism transport assembly Robust and evolvable Variety of producers Energy carriers Variety of consumers

transport metabolism assembly Fragile and hard to change Variety of producers Energy carriers Variety of consumers

transport metabolism assembly Preserved by selection on three levels: 1. Fragile to change (short term) 2. Facilitates robustness elsewhere (short term) 3. Facilitates evolution (long term) Variety of producers Energy carriers Variety of consumers

Modules and protocols • Much confusion surrounds these terms • Biologists already understand the important distinction • Most of basic sciences doesn’t

Modules and protocols in experiments • Modules: components of experiments • Protocols: rules or recipes by which the modules interact • This generalizes to most important situations • Important distinction in experiments • Even more important in understanding the complexity of biological networks

Modules and protocols example • Suppose some specific experimental protocol has a step that requires the use of a PCR machine module. • The PCR machine in turn implements a complex protocol with its own modules. • Thus protocols and modules are hierarchically nested. • A nested collection of protocols/modules is called an architecture or protocol suite.

Modules and protocols example • Consider this laptop/projector combination. • The modules include software, hardware, and connectors. • The protocols are the rules by which these modules must interact. • Hardware modules change between talks • Within talks slides change, not hardware • Robust and “evolvable” yet fragile

Varied systems Robust Mesoscale Varied components The LEGO connector protocol

Early computing Various functionality Software Digital Hardware Analog substrate

Applications Software Hardware Modern Computing Operating System Hardware

Applications Software Modern Computing Operating System Hardware

Modules and protocols • Protocols and modules are complementary (dual) notions • Primitive technologies = modules are more important than protocols • Advanced technologies = protocols are at least as important • Even bacteria are “advanced technology”

Reductionism and protocols • Reductionism = modules are more important than protocols • Usually: “Huh? What’s a protocol? ” • Systems approach: Protocols are as important as modules

Necessity or “frozen accident”? • Laws are absolute necessity. • Conjecture: Protocols in biology are largely necessary. (More so than in engineering!) • Modules? ? ? Appear to be more of a mix of necessity and accident.

Necessity or “frozen accident”? • Conservation laws are necessary. • Bowtie protocols are essentially necessary if robustness and efficiency are required. • Conjecture: It is necessary that there is an energy carrier, it may not be necessary that it be ATP.

Conjectures on laws and protocols • The important laws governing biological complexity have yet to be fully articulated • Biology has highly organized dynamics using protocol suites • Both are true for advanced technologies

Nested bowtie and hourglass Core metabolism Conservation of energy and moiety is a law. Polymerization and assembly Taxis Enzymes are and modules. transport “Bowtie architectures” is a protocol. Autocatalytic and regulatory feedback

essential: nonessential: unknown: total: 230 2373 1804 4407 http: //www. shigen. nig. ac. jp/ecoli/pec

transport metabolism Autocatalytic feedback Regulatory feedback assembly

transport metabolism assembly Kn ock Autocatalytic feedbackouts of ten Knockouts often lose robustness, not minimal functionality Regulatory feedback let hal

Steering Brakes Anti-skid Cruise control Traction control Shifting Electronic ignition Wipers Mirrors GPS Temperature control Electronic fuel injection Seatbelts Bumpers Fenders Suspension (control) Airbags Radio Headlights Seats

Knoc kouts Steering Brakes often letha l Anti-skid Wipers Mirrors Cruise control GPS Radio Knockouts often lose robustness, Traction control Shifting not minimal functionality Headlights Electronic ignition Temperature control Seats Electronic fuel injection Seatbelts Bumpers Fenders Suspension (control) Airbags

transport metabolism assembly Supplies Materials & Energy Autocatalytic feedback Robustness Complexity Supplies Robustness Regulatory feedback

transport metabolism assembly Autocatalytic feedback If feedback regulation is the dominant protocol, what are the laws constraining what’s possible? Regulatory feedback

transport metabolism assembly A historical aside: • These systems are not at the edge-of-chaos, self-organized critical, scale-free, at an orderdisorder transition, etc Autocatalytic feedback • • • Not only are they as opposite from this as can possibly be (an observational fact)… But also, it is provably impossible for robust systems to have it otherwise (a theoretical assertion) Regulatory The facts are easily checked, what is the feedback theoretical foundation?

transport metabolism assembly Supplies Materials & Energy Autocatalytic feedback What are the laws of robustness? Supplies Robustness Regulatory feedback

Whole cell metabolism Transport Core metabolism Polymerization and assembly Autocatalytic and regulatory feedback

Metabolite Enzyme Autocatalysis +Regulation

Enzyme - ++ Metabolite

Yi, Ingalls, Goncalves, Sauro perturbation Product inhibition

Step increase in demand for “ATP. ” [ATP] 1. 05 1 h=3 0. 95 h=2 h=1 0. 9 0. 85 0. 8 h=0 0 5 10 Time (minutes) 15 h = [0 1 2 3] 20

h=3 h=2 h=1 Transients, Oscillations Tighter steady-state regulation h=0 0 5 10 15 Higher feedback “gain” Time 20

[ATP] 1. 05 1 h=3 0. 95 Time response 0. 9 Yet fragile 0. 85 0. 8 h=0 0 5 10 Time (minutes) 15 20 0. 8 h=3 Robust Log(Sn/S 0) 0. 6 Spectrum 0. 4 0. 2 h=0 0 -0. 2 -0. 4 -0. 6 -0. 8 0 2 4 Frequency 6 8 10

Yet fragile 0. 8 h=3 Robust Log(Sn/S 0) 0. 6 0. 4 0. 2 h=0 0 -0. 2 -0. 4 -0. 6 -0. 8 0 2 4 Frequency 6 8 10

Yet fragile 0. 8 Robust Log(Sn/S 0) 0. 6 0. 4 0. 2 h=0 0 -0. 2 -0. 4 -0. 6 -0. 8 0 2 4 Frequency 6 8 10

Theorem Transients, Oscillations 0. 8 Log(Sn/S 0) Tighter steady-state regulation h=3 0. 6 0. 4 h=2 0. 2 h=0 0 h=1 -0. 2 -0. 4 -0. 6 -0. 8 0 2 4 Frequency 6 8 10

This tradeoff is a law. log|S | Transients, Oscillations Tighter regulation Biological complexity is dominated by the evolution of mechanisms to more finely tune this robustness/fragility tradeoff.

This tradeoff is a law. log|S | Product inhibition is a protocol.

This tradeoff is a law. log|S | PFK and ATP are modules. Product inhibition is a protocol.

log|S | Conservation of “fragility”

Diseases of complexity Fragile Complex development Regeneration/renewal Complex societies Immune response Parasites Cancer Epidemics Auto-immune disease Uncertainty Robust

log|S | We have a proof of this. X 0 X 1 … Xi … Xn Error X

This is a cartoon. We have no proof of this. Yet. Complex development Regeneration/renewal Complex societies Immune response Fragile Parasites Cancer Epidemics Auto-immune disease Uncertainty Robust

Immune response Parasites Development Cancer Regeneration Epidemics renewal Auto-immune Societies disease Robust Uncertainty Fragile Why should any biologists care about this? How does it effect what can be done to understand complex biological networks?

h=3 h=2 h=1 Transients, Oscillations h=0 0 5 10 Time 15 20 0. 8 Log(Sn/S 0) Tighter steady-state regulation h=3 0. 6 0. 4 h=2 0. 2 h=0 0 h=1 -0. 2 -0. 4 -0. 6 -0. 8 0 2 4 Frequency 6 8 10

Autocatalysis Enzyme Metabolite Energy and materials +Regulation

transport metabolism assembly Autocatalytic feedback Even though autocatalytic feedback contributes relatively modestly to complexity, it has a huge indirect Regulatory impact on regulatory complexity. feedback

transport metabolism assembly Autocatalytic feedback • • • Autocatalysis is everywhere in human and natural systems as well as biology Make energy, materials, and machines to make … Consumers are investors are labor… Regulatory feedback

Regulatory feedback only h=3 Transients, Oscillations h=0 h=2 h=1 0 5 10 Time 15 20 0. 8 Log(Sn/S 0) Tighter steady-state regulation h=3 0. 6 0. 4 h=2 0. 2 h=0 0 h=1 -0. 2 -0. 4 -0. 6 -0. 8 0 2 4 Frequency 6 8 10

Add more autocatalytic feedback

Add autocatalytic feedback Transients, Oscillations

Add more regulator feedback

More “instability” aggravates

Control demo

transport Conservation of energy, moiety, and fragility are laws. metabolism Autocatalytic feedback “Bowtie architectures” with product inhibition is a protocol suite. Regulatory feedback assembly Enzymes are modules.

Nested bowtie and hourglass Core metabolism Conservation of energy and moiety is a law. Polymerization and assembly Taxis Enzymes are and modules. transport “Bowtie architectures” is a protocol. Autocatalytic and regulatory feedback

Key themes 1. Multiscale and large-scale stochastic simulation is an essential technology for systems biology. 2. Simulation alone is not scalable to larger network problems because complex, uncertain systems need an exponentially large number of simulations to answer biologically meaningful questions. 3. There are fundamental laws governing the organization of biological networks.

Hypotheses 1. Multiscale and large-scale stochastic simulation. Gillespie + Petzold for stiff stochastic systems. 2. Simulation alone is not scalable. Automated scalable inference using SOSTOOLS. 3. There are fundamental laws governing the organization of biological networks. Without exploiting these, the complexity is overwhelming.

Recently, there has been a remarkable convergences. A coherent foundation for a general understanding of highly evolved complexity

Biology Molecular biology has catalogued cellular components, and network structure is becoming more apparent.

Biology Advanced Technology Advanced technologies are producing networks approaching biological levels of complexity (which is hidden to the user).

Biology Math Advanced Technology New mathematics provides for the first time a coherent theoretical framework for complex networks (but not yet an accessible one).

Biology Math Advanced Technology A coherent foundation for a general understanding of highly evolved complexity After many false starts.

Biology Math Advanced Technology Complementary ways to tell this story: 1. Give lots of examples from biology and technology 2. Prove relevant theorems 3. Deliver useful software tools

Biology Math Advanced Technology • Today: an attempt to distill an accessible message from enormous amount of detail • Focus on universal laws that transcend details • Minimize math, maximize examples • Provide broader context for the rest of the shortcourse

Biology Math Advanced Technology This week: • Case studies in microbial signaling and regulation networks • Will attempt to put details into broader context • Saturday will consider computational challenges

Hard Problems co. NP NP P “easy”

co. NP Hard Problems Economics Algorithms Controls NP Communications Dynamical Systems Physics P

• Domain-specific assumptions • Enormously successful • Handcrafted theories • Incompatible assumptions • Tower of Babel where even experts cannot communicate • “Unified theories” failed • New challenges unmet Economics Algorithms Controls Communications Dynamical Systems Physics P

Hard Problems Internet co. NP Economics Algorithms Controls NP Communications Dynamical Systems Physics P

Hard Problems Biology co. NP Economics Algorithms Controls NP Internet Communications Dynamical Systems Physics P

Biology and advanced technology • Biology – Integrates control, communications, computing – Into distributed control systems – Built at the molecular level • Advanced technologies will increasingly do the same • We need new theory and math, plus unprecedented connection between systems and devices • Two challenges for greater integration: – Unified theory of systems – Multiscale: from devices to systems

co. NP Hard Unified Problems Goal Theory Economics Algorithms Biology NP Go al Controls Internet Communications Dynamical Systems Physics P

Hard Problems Biology co. NP Economics Algorithms Controls NP Internet Communications Dynamical Systems Physics P