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## E.HOP: A Bacterial Computer to Solve the Pancake Problem

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**E.HOP: A Bacterial Computer to Solve the Pancake Problem**Davidson College iGEM TeamLance Harden, Sabriya Rosemond, Samantha Simpson, Erin Zwack Faculty advisors: Malcolm Campbell, Karmella Haynes, Laurie Heyer**Basic Pancake Parts**Hin Davidson Missouri Western HinLVA RBS Kan Kan Chl Chl Tet Tet**Basic Pancake Parts**Hin Davidson Missouri Western HinLVA RBS Kan Kan Chl Chl Tet Tet**T**T T T Define a Biological Pancake Tet Nonfunctional RBS RE hixC pBad hixC hixC pancake 1 pancake 2 Tet Functional RBS RE hixC pBad hixC hixC pancake 1 pancake 2**Modeling Pancake Flipping**-2 4 -1 3 5C2 = 10 ways to choose two spatula positions Assume all 10 ways are equally likely Simulate random flipping process with MATLAB**Modeling 8 Stacks of 2 Pancakes***Solution is (1, 2) or (-2, -1) ( 1 2) (-1 2) ( 1 -2) (-1 -2) ( 2 1) (-2 1) ( 2 -1) (-2 -1)**Modeling 8 Stacks of 2 Pancakes***Solution is (1, 2) or (-2, -1) ( 1, 2) (-2, -1) ( 1, -2) (-1, 2) (-2, 1) ( 2, -1) (-1, -2) ( 2, 1)**Modeling 8 Stacks of 2 Pancakes***Solution is (1, 2) or (-2, -1) ( 1, 2) (-2, -1) ( 1, -2) (-1, 2) (-2, 1) ( 2, -1) (-1, -2) ( 2, 1)**Observed Tet Resistance**+ Tet RBS + Tet RBS + Tet RBS Tet RBS T T T T T T T T + Four One-Pancake Constructs PredictedTet Resistance (1) 2 + (-1) 2 - 1 (2) + 1 (-2) -**Tet**RBS Tet RBS Tet RBS Tet RBS T T T T T T T T How to Detect Flipping via Restriction Digest NheI NheI ExpectedFragment Size (1) 2 200 bp (-1) 2 300 bp 1 (2) 200 bp 1 (-2) 1100 bp**Hin-mediated Flipping**Tet Pancake Flipping pBad Pancake Flipping 1 (2) + Hin (1) 2 + Hin 1 (-2) (-1) 2 1 (2) (1) 2**device**EX SP T T pSB1A7 rep(pMB1) ampR T T T T Read-Through Transcription Blocked by pSB1A7 • Observed Tet Resistancein pSB1A3 • + (1) 2 • + (-1) 2 • + 1 (2) • + 1(-2)**device**EX SP T T pSB1A7 rep(pMB1) ampR T T T T Read-Through Transcription Blocked by pSB1A7 • Observed Tet Resistancein pSB1A3 • + (1) 2 • + (-1) 2 • + 1 (2) • + 1(-2) • Observed Tet Resistancein pSB1A7 • + (1) 2 • - (-1) 2 • + 1 (2) • - 1(-2)**Hin LVA**Tet AraC PC RBS RBS pLac hixC pBad hixC hixC RE T T T T Original Design Problems**Unclonable**Unclonable pSB1A7 Hin LVA Tet AraC PC RBS RBS pLac hixC pBad hixC hixC RE T T T T Original Design Problems**Hin LVA**Tet AraC PC RBS RBS pLac hixC pBad hixC hixC RE Flips too fast T T T T Original Design Problems**T**T T T Two-Plasmid Solution #1: Two pancakes (Amp vector) #2: AraC/Hin generator (Kan vector) Tet RBS pSB1A7 hixC pBad hixC hixC AraC PC Hin LVA RBS pSB1K3 pLac**Tet**RBS Tet RBS Biological Equivalence Problem (1,2) LB Amp + Kan+ Tet (-2,-1)**Tet**RBS RBS RFP RFP Tet RBS RBS Biological Equivalence Solution (1,2) (1,2) LB Amp + Kan+ Tet (-2,-1) (-2,-1)**(-2,1)**(-1,2) (-1,-2) (2,1) Eight Two-Pancake Stacks (1,2) (-2,-1) (2,-1) (1,-2)**Intermediate Results**Repress pBad-Tet Activate pLac-Hin Screen forOrientation**gene**regulator CONCLUSIONS:Consequences of DNA Flipping Devices -1,2 -2,-1 in 2 flips! PRACTICAL Proof-of-concept for bacterial computers Data storage n units gives 2n(n!) combinations BASIC BIOLOGY RESEARCH Improved transgenes in vivo Evolutionary insights**Number of flips vs.Time?**Number of flips Time Next Steps Better control of kinetics Slow down Hin activity Determine x flips second-1 Size bias?**Modeling Plasmid Copy Number**P(cell survives) = n = plasmid copy number p = probability of a pancake stack being sorted x = number of sorted stacks sufficient for cell survival**Next Steps**Improved insulating vector Accepts B0015 double terminator Bigger pancake stacks**Summary: What We Learned**Multiple campuses increase capacity with parallel processing Collective Troubleshooting Primarily Undergraduate Institutions can iGEM collaboratively**Summary: What We Learned**Math and Biology mesh really well Math modelingWe proved a new theorem! Challenges of biological components**But above all…**We had a flippin’ good time!!!**E.HOP: A Bacterial Computer to Solve the Pancake Problem**Collaborators at MWSU: Marian Broderick, Adam Brown, Trevor Butner, Lane Heard, Eric Jessen, Kelly Malloy, Brad Ogden Support: Davidson College HHMI NSF Genome Consortium for Active Teaching James G. Martin Genomics Program**Modeling 384 Stacks of 4 Pancakes**2n(n!) = X Combinations 24 (4!) = 384 Combinations**Modeling 384 Stacks of 4 Pancakes*** * Build one representative of each family * * * ***Modeling Random Flipping**for trial = 1 to n trials stack = input_stack flips = 0 while stack ~= 1:k flips = flips + 1 int = choose_random_interval stack = [stack(1:(int(1)-1)) -1 * fliplr(stack(int(1):int(2))) stack(int(2)+1:k)] end end**-2 1**-2 -1 -1 2 1 2 1 -2 -1 -2 2 1 2 -1 P2: 2 Burnt Pancakes 8 vertices, each with degree 3 Flip length 1 Flip length 2**-2 1**-2 -1 -1 2 1 2 1 -2 -1 -2 2 1 2 -1 P2: 2 Burnt Pancakes 8 vertices, each with degree 3**-2 1**-2 -1 -1 2 1 2 1 -2 -1 -2 2 1 2 -1 B2: 2 Burnt Pancakes 8 vertices, each with degree 3