DNA Computing Computation with the Code of Life

1. DNA ComputingComputation with the Code of Life Michael Ang <m@michaelang.com> Interactive Telecommunications Program New York University February 16, 2007

2. What is it? • Invented by Len Adleman (1994) • Realized combinatorial properties of DNA could be used to solve problems encoded as strings of DNA

3. Why is it interesting? • Cross-discipline (CS meets Molecular Biology) • High data density • Data and computation happens at molecular level • Each base of DNA is 0.35nm • Massively parallel • 1012 or more copies of DNA in a test tube • Use biological enzymes to make these copies • Energy efficient • Potential to perform computation inside the body • Though big challenges before a reality

4. What is DNA? • Source code to life • Instructions for building and regulating cells • Data store for genetic inheritance • Cellular machinery (enzymes) translates DNA into proteins, duplicates, repairs, etc. • Think of enzymes as hardware, DNA as software

5. What is DNA made of? • Composed of four nucleotides (+ sugar-phosphate backbone) • A – Adenine • T –Thymine • C – Cytosine • G – Guanine • Bond in pairs • A – T • C – G

6. How does it work? • Use specially coded DNA as initial conditions for biological reaction • Natural enzymes duplicate DNA • Matching DNA base pairs attach to each other • Find answer in resulting soup of DNA strands

7. Travelling Salesman • Simple problem (at small scale) • Complexity scales exponentially

8. Algorithm • Generate all possible routes • Select routes that start with the initial city and end with the destination city • Select itineraries with the correct number of cities • Select itineraries that contain each city once

9. Algorithm • Generate all possible routes • Select routes that start with the initial city and end with the destination city • Select itineraries with the correct number of cities • Select itineraries that contain each city once

10. City Encoding

11. Annealing • Use “a lot” (1013) copies of each city and path

12. We’ve made all the routes

13. Algorithm • Generate all possible routes • Select routes that start with the initial city and end with the destination city • Select itineraries with the correct number of cities • Select itineraries that contain each city once

14. Polymerase Chain Reaction

15. And repeat…

16. Algorithm • Generate all possible routes • Select routes that start with the initial city and end with the destination city • Select itineraries with the correct number of cities • Select itineraries that contain each city once

17. Gel electrophoresis • “Race” the DNA through a gel • Shorter lengths go faster

18. Algorithm • Generate all possible routes • Select routes that start with the initial city and end with the destination city • Select itineraries with the correct number of cities • Select itineraries that contain each city once

19. Affinity purify • Pull out strands matching one city at a time

20. We have our answer • Sequence result or perform more PCR reactions to determine combinatorically • Took Adleman 7 days to run through the steps • Actual “computation” took minutes

21. Problems/Challenges • Relatively high error rate in DNA • Sometimes bases don’t align properly • Problem complexity still scales exponentially • 200 city problem might take DNA weighing more than Earth • Many people doubtful…

22. Can I do it? • If you have access to a lab, yes • DIY seems possible (<$500) Personal Biocomputing – Eugene Thacker

23. Further Research • Use to break DES (1995) • Turing Machine (at least… “similar to”) (2001) • Play tic-tac-toe (2003) • DNA computer to detect and treat cancer (2004) • Use enzymes and DNA to create state machine using mRNA as input • Output DNA sequence to suppress disease causing gene • In vitro (petri dish) so far • Much harder in vivo (living cell)

24. Maya II – Tic Tac Toe

25. Maya II – Logic Gates

26. Maya II – Fluorescent Output

27. DNA Automata

28. A nanoscale programmable computing machine with input, output, software and hardware made of biomolecules Nature 414, 430-434 (2001) • 1012 automata run independently and in parallel • on potentially distinct inputs • in 120 ml • at room temperature • at combined rate of 109 transitions per second • with accuracy greater than 99.8% per transition, • consuming less than 10-10 Watt.

29. (Video from Weizmann Institute)

30. So what? • Computation at molecular level • Computation (potentially) within cells • Operate with cellular messages as input and output • Operate near theoretical power limits • Computer Science implemented in Biology • Practical applications still a dream…

31. To correctly gauge the practicality of molecular computing will require inputs from experts in a wide variety of fields including: biology, chemistry, computer science, engineering, mathematics and physics. - Len Adleman (1995)

32. References • “What is DNA” - Genetics Home Reference • “DNA Computer Could Target Cancer” – Nanotech Web • “DNA Computing: A Primer” – Arstechnica • “On Constructing a Molecular Computer” – Len Adleman • “Breaking DES using a molecular computer” - D. Boneh, C. Dunworth, and R. Lipton • “Injectable Medibots: Programmable DNA could diagnose and treat cancer” - Alexandra Goho • “First game-playing DNA computer revealed” – New Scientist • “Programmable and autonomous computing machine made of biomolecules” - Benenson, Paz-Elizur, Adar, Keinan, Livneh & Shapiro • “Personal Biocomputing” – Eugene Thacker • “Biological Nanocomputer” – Weizman Institute • “Computer Made from DNA and Enzymes” – National Geographic News

33. Thanks Michael Ang <m@michaelang.com> Interactive Telecommunications Program New York University February 16, 2007