“What I cannot create I do not understand”: The parallel synergistic pathways of design and discovery

1. “What I cannot create I do not understand”:The parallel synergistic pathways of design and discovery Michael L. SimpsonCenter for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, TN 37831Materials Science and Engineering Department, The University of Tennessee, Knoxville, TN 37996NSF Workshop on Molecular Communication: Biological Communications Technology February 20-21, 2008

2. Grand Challenges DOE – BES recently released list of ‘grand challenges”

3. Biological systems 4B years of harsh peer review Scale (density), Complexity (connectivity) Components Complexity in function usually entails complexity in in the wiring….

4. Understand Design Questions for S2 • How do biological entities communicate? • How is biological information encoded onto and decoded from molecules? • What are the recurring architectures of biological communications? • What are the robustness-fragility trade-offs in biological communications systems? • How can different biological systems be interfaced to enhance communication? • How may communication mechanisms employed by biological entities be applied to create an artificial communication system using biological materials?

5. Understand Design This talk • What is the system environment? • Beyond 1st approximations • Information landscape (noise is everywhere) • Communicating in a crowd • Architectures that have evolved in this environment • Bow ties, robustness, and fragility • Poster child for biological communications, quorum sensing • With incomplete knowledge, how do we design in this environment? • Top-down • Bottom-up

6. Transmitter Receiver Channel gene1 gene2 From a systems view communication has three main players • First order approximations – system-wide high fidelity • Transmitter encodes with high fidelity (receiver decodes) information in size or state of a molecular population/ concentration • There is no ‘uncertainty’ in the information • Free diffusion of information through a noiseless channel • Activity of gene2 directly proportional to activity of gene1 (e.g. Hill expression)

7. TatA Rev t1/2 = 40 hrs Tat Vpu Nef 5’LTR Gag Pol Env 3’LTR Vif Vpr Information Processing by Cells:Beyond First Approximations Transient driven function • “rates” and “concentrations”. • reactions diffusion-limitedin a well-mixed cell. • Our aim: To quantify cellular information processing at the level of individual events in space and time. Gene activity (RNA/Protein) 40 hrs Lysis ON +FB Latency Time Ido Golding, Dept. of Physics, UIUC Leor Weinberger, UCSD

8. Gene P mRNA decay noise kR Transcription noise * mRNA kP Translation noise Protein decay noise * Protein Noise is everywhere • Poisson processes • σ2= <M> • Gene expression is bursty • σ2~ b<M> • Transcriptional control is much noisier than Hill kinetics shows • Extrinsic noise • Correlated noise that couples into all gene circuits • Is noise always ‘bad’? • May convey the real uncertainty in information • Exists in the context of a highly networked complex system • what are the ‘systems’ properties of noise?

9. System-wide look at noise Noise in yeast proteins Noise structure is more complex Noise is 2-d: magnitude (size of fluctuations); and correlation (duration of fluctuations) High population & high noise? Why? Simpson, et al., Proc. Nat. Acad. Sci.100, 4551-4556 (2003). Austin, et al. Nature, 439, 608-611 (2006). Bar-Even, et al., Nat Genet, 38, 636-643 (2006). Newman, et al. Nature, 441, 840-846 (2006).

10. Conservation and distribution of stochasticity • Fundamental question: How should stochasticity be distributed and regulated • Uniformly distributed? • Distributed by function type? • Is stochasticity always minimized? BUT Is bounded ~50M molecules, few thousand different proteins Total stochasticity is conserved, but it can be unequally distributed across the components

11. Sender Receiver Channel gene1 gene1 gene2 gene2 gene1 gene2 gene3 gene3 The information landscape is crowded and noisy…..so is the physical landscape Marsh,et al. PNAS, 98, 2399-2406, 2001

12. Bow ties, robustness, and fragility Csete and Doyle, Trends in Biotechnology, 2004

13. The p53 Network – Bow-Tie Signaling ArchitectureEric Bachelor, Harvard DNA damage repair Apoptosis Cell cycle arrest Senescence g radiation Stalled replication forks UV radiation Ribosomal Stress Oncogenes p53

14. Varied p53 Dynamic Responses to DNA Damage g radiation UV radiation DNA Double Strand Breaks Single Strand DNA ATM ATR Chk1 Chk2 Series of Undamped p53 Pulses Graded p53 Pulses p53 Mdm2 Wip1

15. LuxR O O O N H O Pheromone-mediated control of bioluminescence in Vibrio fischeri is a simple “quorum sensing” regulatory circuit… “lux box” luxR luxI luxC luxD luxA luxB luxE luxG FMNH2 + O2 + RCHO RCOOH + FMN + H2O + light LuxI 3-oxo-C6-HSL 3-oxo-C6-HSL Eric Stabb, University of Georgia

16. …or is it? 3OC6 3OC6 3OC6 3OC6 C8 C8 C8 C8 AI-2 AI-2 AI-2 AI-2 AI-2 OM AI-2 LuxP C8 acnB phoQ ainS hns lon guaB pstA/pstC tfoX topA tRNA LuxQ IM AinR 54 Hfq C8- LuxR P-LuxO sRNA’s (C8 and AI-2 lead to less LuxO-P) 3OC6- LuxR LuxO LuxU litR LuxR LitR luxR luxI luxC luxD luxA luxB luxE luxG “lux box” LuxS ArcA/ArcB LuxI bioluminescence OH HO O O AinS B- O O O N HO H O O O HO O N (3OC6) H O (AI-2) (C8) C8 3OC6 AI-2 Eric Stabb, University of Georgia

17. Biological systems Scale (density), Complexity (connectivity) • Top-down • Understanding system environment & • rewiring complexity Components • Bottom-up • Construction of complexity The confluence of design and discovery:System design methodology? “….often more is learned about existing system architecture through an attempted redesign than through analysis alone….”

18. Design space Design space Design space: Around the edges rigidity plasticity plasticity Kobayashi, H. et al. (2004) Programmable cells: Interfacing natural and engineered gene networks. Proc. Natl. Acad. Sci. U. S. A. 101, 8414–8419 Whole-Cell Synthetic Biology (Jeff Hasty in S2)

19. Replacing the core rigidity rigidity plasticity plasticity Yin et al., Nature, Jan. 2008

20. PORE DNA Transcription SENSOR Protein Translation PORE Images from www.nsf.gov A little of both: cell mimics Material Synthesis, Information Processing, Energy ConversionM. J. Doktycz, ORNL - Replace with synthetic micro- and nano-fabricated structures - Define cell size - Predictably control material flux - Defines volume (concentration) - Controls presentation and release of materials Membrane - Gather input - Signal amplification - Logic - Generate output - Metabolize energy Molecular Networks - DNA based instructions - Modulate gene copy number, control codon usage, cross reactivity… - Cell free transcription/translation A potentially universal platform for sensing, actuating, generating energy, computing and interfacing to natural systems A starting point for understanding integrated systems,the effect of scale on network function, and the creation of practical devices

21. Sealed Container 120 ng/µl DNA 60 ng/µl DNA Control 25 min 35 min 45 min Nano-enabled synthetic biology • Macromolecular crowding and organization • 10–40%/V of cell volume is crowded with macromolecules • Reaction rates are accelerated, effective concentrations are changed, and activity coefficients are altered • understand transport in crowded environments • reveal diffusional flux at the nanoscale • Transport rates can depend on time/distance in crowded environments • Assembly and testing of genetic networks and cell-cell communication • DNA construct containing a gene for GFP and a T7 promoter are placed in the cell mimic • E. coli S30 cell free extract and small metabolites are are added Fowlkes et al., Nanotechnology 17 (22): 5659-5668 (2006)

22. Speakers for S2 • Eric Stabb – Quorum sensing • Eric Bachelor – P53 bow tie signaling architecture • John Doyle – Robustness and fragility • Leor Weinberger – Decision making in individual cells/transient driven function • Ido Golding – Information processing in cells • Jeff Hasty – Synthetic biology system design • Sasitharan Balasubramaniam – biological communication in Nano/MEMS devices