1. Bio-Design Automation EE5393 – University of Minnesota Brian’s Automated Modular Biochemical Instantiator

2. What, How, Why, …ECE Expense Reports Investigating design strategies for generating “netlists” of protein-protein biochemical reactions. Applying circuit CAD methodologies: modularity / abstractions / hierarchical designs. What are we doing? How are we going about it? Such tools and methods will revolutionize the way synthetic biology is done. Why are we bothering?

3. Playing by the Rules

4. waveforms circuit netlist SPICE Rules for integrated circuits: amplifier v1 1 0 rin1 1 0 9e12 rjump 1 4 1e-12 rin2 4 0 9e12 e1 3 0 1 2 999k e2 6 0 4 5 999k e3 9 0 8 7 999k rload 9 0 10k r1 2 3 10k rgain 2 5 10k r2 5 6 10k r3 3 7 10k r4 7 9 10k r5 6 8 10k r6 8 0 10k.dc v1 0 10 1.print dc v(9).end amplifier v1 1 0 rin1 1 0 9e12 rjump 1 4 1e-12 rin2 4 0 9e12 e1 3 0 1 2 999k e2 6 0 4 5 999k e3 9 0 8 7 999k rload 9 0 10k r1 2 3 10k rgain 2 5 10k r2 5 6 10k r3 3 7 10k r4 7 9 10k r5 6 8 10k r6 8 0 10k.dc v1 0 10 1.print dc v(9).end

5. Playing by the Rules histogram: resulting quantities of proteins biochemical reactions Rules for biochemistry: SPICE X=100, Y = 30 X a = X b = X n = 0 Y = 0 and initial quantities of proteins Gillespie’s SSA

6. Playing by the Rules SPICE Gillespie’s SSA data structures (Gibson & Bruck, Fett & Riedel); approximation methods (Petzold); hybrid discrete/continuous methods (Kaznessis); … algorithms widely studied Rules for biochemistry:

7. SPICE X=100, Y = 30 X a = X b = X n = 0 Y = 0 Gillespie’s SSA dynamics well studied mathematics (Tyson, Khammash, Doyle, …); biology (Arkin, Endy, Brent); … computation (Winfree, Shapiro); …

8. X=100, Y = 30 X a = X b = X n = 0 Y = 0 Where does the netlist come from? Biochemical Netlists Elucidated by biologists. Designed by skilled experimentalists (by tinkering with existing mechanisms). Netlists found in nature: New Netlists:

9. Synthetic Biology Positioned as an engineering discipline. –“Novel functionality through design”. – Repositories of standardized parts. Driven by experimental expertise in particular domains of biology. – Modify gene regulation, signaling pathways, metabolic pathways…

10. Building Bridges "Think of how engineers build bridges. They design quantitative models to help them understand what sorts of pressure and weight the bridge can withstand, and then use these equations to improve the actual physical model. [In our work on memory in yeast cells] we really did the same thing.” – Pam Silver, Harvard 2007 Quantitative modeling. Mathematical analysis. Incremental and iterative design changes. Engineering Design

11. Synthetic Biology Cellulosic ethanol (Nancy Ho, Purdue, ’04) Anti-malarial drugs (Jay Keasling, UC Berkeley, ‘06) Tumor detection (Chris Voigt, UCSF ‘06) Feats of synthetic bio-engineering: Strategy: apply experimental expertise; formulate ad-hoc designs; perform extensive simulations.

12. inputsoutputs Design is driven by the input/output specification. CAD tools are not part of the design process; they are the design process. Building Digital Circuits digital circuit... ),,( 11m xxf  ),,( 12m xxf  ),,( 1mn xxf ...

13. [computational] Synthetic Biology [computational] Analysis “There are known ‘knowns’; and there are unknown ‘unknowns’; but today I’ll speak of the known ‘unknowns’.” – Donald Rumsfeld, 2004 Biological Process Molecular Inputs Molecular Products Known Unknown Known / Unknown Unknown Given

14. Gene Regulation Hard to tinker with this; but it’s the way computation is done…

15. Biochemistry in a Nutshell DNA: string of n nucleotides ( n ≈ 10 9 )... ACCGTTGAATGACG... Nucleotides: Amino acid: coded by a sequence of 3 nucleotides. Proteins: produced from a sequence of m amino acids (m ≈ 10 3 ) called a “gene”.

16. Custom Gene Synthesis US Patent 20070122826 (pending): “The present invention relates to a minimal set of protein-coding genes which provides the information required for replication of a free-living organism in a rich bacterial culture medium.” – J. Craig Venter Institute Going from reading genetic codes to writing them.

17. Moderator: “Some people have accused you of playing God.” J. Craig Venter: “Oh no, we’re not playing.” Custom Gene Synthesis

18. X=100, Y = 30 X a = X b = X n = 0 Y = 0 Biochemical Netlists Figuring out how to design netlists in terms of abstract protein types so that we meet desired specs. Implement computation & signal processing on protein quantities. What are we doing? Why? Ok, but how?

19. Biochemical Reactions: how types of molecules combine. Playing by the Rules + + 2a2a b c

20. Biochemical Reactions 9 6 7 cell speciescount + 8 5 9 Discrete chemical kinetics; spatial homogeneity.

21. Biochemical Reactions + + + slow medium fast Relative rates or (reaction propensities): Discrete chemical kinetics; spatial homogeneity.

22. R1R1 R2R2 R3R3 See D. Gillespie, “Stochastic Chemical Kinetics”, 2006. The probability that a given reaction is the next to fire is proportional to: Its rate. The number of ways that the reactants can combine. Stochastic Kinetics

23. Choose the next reaction according to: RiRi let For each reaction Stochastic Kinetics

24. Logic Synthesis SPICE Register Level Design Behavioral Specification (e.g., DSP function) Structural Description (e.g., memory and functional units) Circuit-Level Description (e.g., NAND2 and D flip-flops) waveforms Integrated Circuits Design Automation for

25. Biochemistry Logic Synthesis SPICE Register Level Design Behavioral Specification (e.g., DSP function) Structural Description (e.g., memory and functional units) Biochemical Netlist (e.g., Proteins, Enzymes) Integrated Circuits Design Automation for waveforms Biochemical Synthesis STA Engine PSB 2009: “Stochastic Transient Analysis Biochemical Systems”

26. Biochemistry Logic Synthesis SPICE Register Level Design Behavioral Specification (e.g., DSP function) Structural Description (e.g., memory and functional units) Biochemical Netlist (e.g., Proteins, Enzymes) Integrated Circuits Design Automation for waveforms Biochemical Synthesis STA Engine DAC 07, SB 3.0: “The Synthesis of Stochastic Biochemical Systems”

27. Biochemical Synthesis Biochemistry SPICE Register Level Design Behavioral Specification (e.g., DSP function) Structural Description (e.g., memory and functional units) Biochemical Netlist (e.g., Proteins, Enzymes) Integrated Circuits Design Automation for waveforms STA Engine Joint work with Keshab Parhi’s group. Brian’s Automated Modular Biochemical Instantiator