Undergraduates Learning Genomics Through Research A. Malcolm Campbell University of Wisconsin - Madison May 15, 2008 Seven Year Collaboration; Three Countries www.bio.davidson.edu/GCAT GCAT Makes DNA Chips Affordable Steady Growth Over Time 10,000+ Undergraduates and Counting Distribution of GCAT Members GCAT Publication of Outcomes Basic Research Publications 2008: 4 peer-reviewed publications 2007: 2 peer-reviewed publications 2006: 1 peer-reviewed publication Student Learning Outcomes Question 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. Topic Microarray experimental error–dye bias Microarray experimental error–gradient Microarray negative controls Microarray experimental design Gene expression ratios using a graph Gene expression–probability Gene expression–gene clusters Gene expression–regulatory cascade Gene expression–gene circuit graphs Interpreting microarray results Diagnosis with microarrays * indicates p < 0.05; N = 409 Increase (%) + 36.2* + 10.5* + 10.3* + 38.2* + 5.8* + 0.2 + 22.3* + 14.9* + 11.8* + 19.0* + 12.5* Increased Student Interest in Research . Area Genomics Biology Research 1 = decreased a lot 7 = increased a lot N = 409 Mean 5.5 5.5 5.4 SD . 1.1 1.1 1.2 Student Satisfaction with Methods Activity Practicing data analysis before my own data Isolating RNA or genomic DNA to produce probe Producing the fluorescently labeled probe Hybridizing the probe with the spotted DNA Designing my own experiment Analyzing data from public domain source Reading papers that used DNA microarrays 1 = not effective at all 7 = highly effective Mean 5.25 5.32 % >4 93.6 94.1 % >5 67.1 70.0 N 313 323 5.22 5.20 5.13 5.22 5.06 94.4 92.8 87.3 94.7 88.9 68.9 70.1 64.3 65.8 62.4 306 334 244 325 343 Course Grade Assessment Assessment method % Using method Test 42.2 Term paper/lab report 51.1 Poster presentation 33.3 Oral presentation 26.6 Manuscript for publication 8.8 Course evaluation 33.3 Informal feedback 62.2 Other 24.4 Faculty Appreciate GCAT Resources Mean Access to microarray technology without GCAT1.5 0.75 Online GCAT protocols useful 4.4 The GCAT -Listserv helpful 4.2 SD GCAT network significant factor 4.2 0.79 Positive experience using GCAT I would use GCAT again in the future 4.6 4.7 0.60 0.63 1 = strongly disagree 5 = strongly agree 0.69 1.0 Faculty Development “You have awakened parts of my brain that have been dormant since my last stats course. The only reason I have gone over the manual so carefully is that this is my first time teaching microarrays, or even using them, for that matter. GCAT has been remarkably helpful to me. In fact I don’t think I would have undertaken this new module in my lab course without the tools GCAT makes available.” Introduced Microarrays Early Ben Kittinger ‘05 Wet-lab microarray simulation kit - fast, cheap, works every time. GCAT Develops Commercial Product Enable Students to Practice www.bio.davidson.edu/projects/GCAT/Spot_synthesizer/Spot_synthesizer.html Open Source and Free Software www.bio.davidson.edu/MAGIC What Else Can Chips Do? Jackie Ryan ‘05 Comparative Genome Hybridizations Synthetic Biology What is Synthetic Biology? BioBrick Registry of Standard Parts http://parts.mit.edu/registry/index.php/Main_Page What is iGEM? Peking University Imperial College iGEM Team Mosaic of Institutions SYNTHETIC BIOLOGY iGEM 2006 Davidson College Malcolm Campbell (bio.) Laurie Heyer (math) Karmella Haynes (HHMI) Lance Harden Sabriya Rosemond (HU) Samantha Simpson Erin Zwack Missouri Western State U. Todd Eckdahl (bio.) Jeff Poet (math) Marian Broderick Adam Brown Trevor Butner Lane Heard (HS student) Eric Jessen Kelley Malloy Brad Ogden Advantages of Bacterial Computation Software Hardware Computation Computation Computation Advantages of Bacterial Computation Software Hardware Computation $ Computation ¢ Computation Burnt Pancake Problem 1 2 3 4 Burnt Pancake Problem Look familiar? Advantages of Bacterial Computation • Non-Polynomial (NP) # of Processors • No Efficient Algorithms Cell Division Flipping DNA with Hin/hixC Flipping DNA with Hin/hixC Flipping DNA with Hin/hixC How to Make Flippable DNA Pancakes All on 1 Plasmid: Two pancakes (Amp vector) + Hin RBS pLac Hin LVA T T RBS hixC Tet pBad hixC pancake 1 hixC pancake 2 Hin Flips DNA of Different Sizes Hin Flips Individual Segments -2 1 No Equilibrium 11 hrs Post-transformation Hin Flips Paired Segments mRFP off 1 -2 double-pancake flip mRFP on -1 white light 2 u.v. Modeling to Understand Flipping (-2,-1) (-2,1) (1,2) (-1,2) (1,-2) (-1,-2) (2,-1) (2,1) ( 1, 2) (-2, -1) ( 1, -2) (-1, 2) (-2, 1) ( 2, -1) (-1, -2) ( 2, 1) Modeling to Understand Flipping (-2,-1) (-2,1) (1,2) (-1,2) (1,-2) (-1,-2) (2,-1) (2,1) 1 flip: 0% solved ( 1, 2) (-2, -1) ( 1, -2) (-1, 2) (-2, 1) ( 2, -1) (-1, -2) ( 2, 1) Modeling to Understand Flipping (-2,-1) (-2,1) (1,2) (-1,2) (1,-2) (-1,-2) (2,-1) (2,1) 2 flips: 2/9 (22.2%) solved ( 1, 2) (-2, -1) ( 1, -2) (-1, 2) (-2, 1) ( 2, -1) (-1, -2) ( 2, 1) 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 gene Evolutionary insights Success at iGEM 2006 Living Hardware to Solve the Hamiltonian Path Problem, 2007 Students: Oyinade Adefuye, Will DeLoache, Jim Dickson, Andrew Martens, Amber Shoecraft, and Mike Waters; Jordan Baumgardner, Tom Crowley, Lane Heard, Nick Morton, Michelle Ritter, Jessica Treece, Matt Unzicker, Amanda Valencia Faculty: Malcolm Campbell, Todd Eckdahl, Karmella Haynes, Laurie Heyer, Jeff Poet The Hamiltonian Path Problem 1 4 3 2 5 The Hamiltonian Path Problem 1 4 3 2 5 Hin/hixC to to Solve the HPP Using Using Hin/hixC Solve the HPP 1 4 3 2 5 1 3 4 5 4 3 3 2 1 4 2 4 3 5 4 1 Hin/hixC to to Solve the HPP Using Using Hin/hixC Solve the HPP 1 4 3 2 5 1 3 4 5 4 3 3 2 1 4 2 4 hixC Sites 3 5 4 1 Hin/hixC to to Solve the HPP Using Using Hin/hixC Solve the HPP 1 4 3 2 5 Hin/hixC to to Solve the HPP Using Using Hin/hixC Solve the HPP 1 4 3 2 5 Using Hin/hixC Solvethe the HPP Using Hin/hixC to to Solve HPP 1 4 3 2 5 Using Hin/hixC to Solve the HPP 1 4 3 2 5 Solved Hamiltonian Path How to Split a Gene RBS Detectable Phenotype Reporter Promoter RBS Promoter Repo- rter hixC ? Detectable Phenotype Gene Splitter Website http://gcat.davidson.edu/iGEM07/genesplitter.html Input Output 1. Gene Sequence (cut and paste) 1. Generates 4 Primers (optimized for Tm). 2. Where do you want your hixC site? 2. Biobrick ends are added to primers. 3. Pick an extra base to avoid a frameshift. 3. Frameshift is eliminated. Gene-Splitter Output Note: Oligos are optimized for Tm. Predicting Outcomes of Bacterial Computation Probability of HPP Solution Starting Arrangements 4 Nodes & 3 Edges Number of Flips How Many Plasmids Do We Need? Probability of at least k solutions on m plasmids for a 14-edge graph k=1 5 10 20 m = 10,000,000 .0697 0 0 0 50,000,000 .3032 .00004 0 0 100,000,000 .5145 .0009 0 0 200,000,000 .7643 .0161 .000003 0 500,000,000 .973 .2961 .0041 0 1,000,000,000 .9992 .8466 .1932 .00007 k = actual number of occurrences λ = expected number of occurrences λ = m plasmids * # solved permutations of edges ÷ # permutations of edges Cumulative Poisson Distribution: e x P(# of solutions ≥ k) = 1 x! x0 k1 False Positives Extra Edge 1 4 3 2 5 False Positives PCR Fragment Length 1 4 3 2 5 PCR Fragment Length Detection of True Positives 100000000.00 Total Total##ofofPositives Positives 10000000.00 1000000.00 100000.00 10000.00 1000.00 100.00 1 Total # of Positives # of True Positives ÷ 10.00 1.00 4/6 6/9 7/12 7/14 of Nodes / # of Edges ## of Nodes / # of Edges 0.75 0.5 0.25 0 4/6 6/9 7/12 # of Nodes / # of Edges 7/14 How to Build a Bacterial Computer Choosing Graphs C A A B B Graph 1 Graph 2 D Splitting Reporter Genes Green Fluorescent Protein Red Fluorescent Protein Splitting Reporter Genes GFP Split by hixC RFP Split by hixC HPP Constructs Graph 0 Construct: A AB B Graph 1 Constructs: Graph 0 ABC C ACB A B Graph 1 BAC Graph 2 Construct: DBA A B Graph 2 D Coupled Hin & HPP Graph Hin + Unflipped HPP Transformation PCR to Remove Hin Ligate & Transform Flipping Detected by Phenotype ABC (Yellow) ACB (Red) BAC (None) Flipping Detected by Phenotype ABC (Yellow) ACB (Red) BAC (None) Hin-Mediated Flipping ABC Flipping Yellow Hin Yellow, Green, Red, None ACB Flipping Red Hin Yellow, Green, Red, None BAC Flipping None Hin Yellow, Green, Red, None Flipping Detected by PCR ABC ACB BAC BAC ABC ACB Unflipped Flipped Flipping Detected by PCR ABC ACB BAC BAC ABC ACB Unflipped Flipped Flipping Detected by Sequencing BAC RFP1 hixC GFP2 Flipping Detected by Sequencing BAC RFP1 Flipped-BAC RFP1 hixC GFP2 Hin hixC RFP2 Conclusions • Modeling revealed feasibility of our approach • GFP and RFP successfully split using hixC • Added 69 parts to the Registry • HPP problems given to bacteria • Flipping shown by fluorescence, PCR, and sequence • Bacterial computers are working on the HPP and may have solved it Living Hardware to Solve the Hamiltonian Path Problem Acknowledgements: Thanks to The Duke Endowment, HHMI, NSF DMS 0733955, Genome Consortium for Active Teaching, Davidson College James G. Martin Genomics Program, Missouri Western SGA, Foundation, and Summer Research Institute, and Karen Acker (DC ’07). Oyinade Adefuye is from North Carolina Central University and Amber Shoecraft is from Johnson C. Smith University. What is the Focus? Thanks to my life-long collaborators Extra Slides Enter: Flapjack & The Hotcakes Erin Zwack (Jr. Bio); Lance Harden (Soph. Math); Sabriya Rosemond (Jr. Bio) Enter: Flapjack & The Hotcakes Erin Zwack (Jr. Bio); Lance Harden (Soph. Math); Sabriya Rosemond (Jr. Bio) Wooly Mammoths of Missouri Western Genome Sequencing Sarah Elgin at Washington University Genome Education Partnership Students finish and annotate genome sequences Support staff online Free workshops in St. Louis Growing number of schools participating Tuajuanda Jordan at HHMI Phage Genome Initiative Science Education Alliance Students isolate phage Students purify phage DNA; Sequenced at JGI Students annotate and compare geneomes National experiment to examine phage variation Free workshop and reagents Cheryl Kerfeld at Joint Genome Institute Undergraduate Genomics Research Initiative > 1000 prokaryote genomes sequenced Students annotate genome Data posted online Workshop for training of faculty Wide range of species Burnt Pancake Problem Design of controlled flipping RBS-mRFP hix pLac hix (reverse) RBS-tetA(C) hix Can we build a biological computer? The burnt pancake problem can be modeled as DNA (-2, 4, -1, 3) (1, 2, 3, 4) DNA Computer Movie >>