Systems Biology Shortcourse May 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 4pm talk by Adam Arkin in Beckman Institute Auditorium.

Collaborators and contributors (partial list) Theory: Parrilo, Carlson, Paganini, Papachristodoulo, Prajna, Goncalves, Fazel, Lall, DAndrea, Jadbabaie, many current and former students, … Web/Internet: Low, Willinger, Vinnicombe, Kelly, Zhu,Yu, Wang, Chandy, Effros, … Biology: Csete,Yi, Tanaka, Arkin, Savageau, Simon, AfCS, 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, … Finance: Martinez, Primbs, Yamada, Giannelli,… Caltech faculty Other Caltech Other

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

Metabolite Enzyme +Regulation Autocatalysis

Metabolite Enzyme +Regulation Autocatalysis

Metabolite Enzyme + - +

Stoichiometry or mass and energy balance Nutrients Products Interna l

Core metabolism

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

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

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

The core metabolism bowtie Nutrients Products

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

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

Core: special purpose enzymes controlled by competitive inhibition and allostery Edges: general purpose polymerases and machines controlled by regulated recruitment Uncertain

Core: Highly efficient Edges: Robustness and flexibility Uncertain

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

Variety of producers Electric power

Variety of consumers Electric power

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

Complex assembly Raw materials Complex assembly Raw materials Building blocks

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

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

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

Variety of consumers Variety of producers Energy carriers transport assemblymetabolism Robust and evolvable

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

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

Modules and protocols Much confusion surrounds these terms Biologists already understand the important distinction Most of basic sciences doesnt

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

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 components Varied systems Robust Mesoscale The LEGO connector protocol

Software Hardware Early computing Analog substrate Various functionality Digital

Software Hardware Applications Operating System Modern Computing

Software Hardware Applications Operating System Modern Computing

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? Whats 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

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

essential : 230 nonessential:2373 unknown:1804 total:4407

Autocatalytic feedback Regulatory feedback transport assemblymetabolism

Autocatalytic feedback Regulatory feedback transport assemblymetabolism Knockouts often lose robustness, not minimal functionality Knockouts often lose robustness, not minimal functionality Knockouts often lethal

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

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

Autocatalytic feedback Regulatory feedback transport assemblymetabolism Supplies Materials & Energy Supplies Materials & Energy Supplies Robustness Supplies Robustness Complexity Robustness Complexity

Autocatalytic feedback Regulatory feedback transport assemblymetabolism If feedback regulation is the dominant protocol, what are the laws constraining whats possible?

Autocatalytic feedback Regulatory feedback transport assemblymetabolism A historical aside: These systems are not at the edge-of-chaos, self-organized critical, scale-free, at an order- disorder transition, etc 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) The facts are easily checked, what is the theoretical foundation? A historical aside: These systems are not at the edge-of-chaos, self-organized critical, scale-free, at an order- disorder transition, etc 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) The facts are easily checked, what is the theoretical foundation?

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

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

Metabolite Enzyme +Regulation Autocatalysis

Metabolite Enzyme +Regulation Autocatalysis

Metabolite Enzyme + - +

perturbation Product inhibition Yi, Ingalls, Goncalves, Sauro

h = [ ] Time (minutes) [ATP] h = 2 h = 1 h = 0 Step increase in demand for ATP. h = 3

Time h = 3 h = 2 h = 1 h = 0 Tighter steady-state regulation Transients, Oscillations Higher feedback gain

Time (minutes) [ATP] h = 3 h = Frequency Log(Sn/S0) h = 3 h = 0 Spectrum Time response Robust Yet fragile

Frequency Log(Sn/S0) h = 3 h = 0 Robust Yet fragile

Frequency Log(Sn/S0) h = 0 Robust Yet fragile

Frequency Log(Sn/S0) h = 3 h = 2 h = 1 h = 0 Tighter steady-state regulation Transients, Oscillations Theorem

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

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

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

log|S | Conservation of fragility

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

X n+1 X0X0 X1X1 XiXi XnXn ……Error log|S | We have a proof of this.

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

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

Robust Fragile Uncertainty Modeling robust yet fragile systems Required model complexity May need great detail here And much less detail here.

Robust Fragile Uncertainty Required model complexity More detail. Less detail. Robust (fragile) to perturbations in components and environment Robust (fragile) to errors and simplifications in modeling

Time h = 3 h = 2 h = 1 h = Frequency Log(Sn/S0) h = 3 h = 2 h = 1 h = 0 Tighter steady-state regulation Transients, Oscillations

Metabolite Enzyme +Regulation Autocatalysis Energy and materials

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

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

Time h = 3 h = 2 h = 1 h = Frequency Log(Sn/S0) h = 3 h = 2 h = 1 h = 0 Tighter steady-state regulation Transients, Oscillations Regulatory feedback only

Add autocatalytic feedback more

Add autocatalytic feedback Transients, Oscillations

Add more regulator feedback

More instability aggravates

Control demo

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

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

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.

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

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

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

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

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

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 Advanced Technology Math

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 Advanced Technology Math

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

NP coNP P easy Hard Problems

NP coNP P Controls Communications Economics Dynamical Systems Physics Algorithms Hard Problems

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

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

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

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

NP coNP P Hard Problems Controls Communications Economics Dynamical Systems Physics Algorithms Goal Internet Biology Unified Theory

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