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