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Montek Singh COMP790-084 Nov 15, 2011.  Two different technologies ◦ TODAY: DNA as biochemical computer  DNA molecules encode data  enzymes, probes.

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Presentation on theme: "Montek Singh COMP790-084 Nov 15, 2011.  Two different technologies ◦ TODAY: DNA as biochemical computer  DNA molecules encode data  enzymes, probes."— Presentation transcript:

1 Montek Singh COMP790-084 Nov 15, 2011

2  Two different technologies ◦ TODAY: DNA as biochemical computer  DNA molecules encode data  enzymes, probes etc. manipulate data ◦ Thurs: DNA used to assemble electronic computer  DNA molecules used as scaffolding  nanoscale electronic components piggyback  DNA assembles the computer

3 “I was fascinated. With my own hands, I was creating DNA that did not exist in nature.” Leonard M. Adleman Scientific American, August 1998

4  What is a DNA computer? ◦ A system that manipulates DNA to solve mathematical problems ◦ How is information represented?  In DNA molecules ◦ How is information manipulated?  Using enzymes and ligases ◦ How do you obtain gain/amplification?  DNA replication ◦ How do you read output?  mechanical isolation, separation, probes

5  4 types of molecular building blocks ◦ Adenine, Thymine, Guanine, Cytosine ◦ Shortened to 4 symbols: A, T, G, C  Double-helix structure ◦ complementary strands ◦ A and T bond with each other ◦ G and C bond with each other

6  Watson-Crick pairing ◦ each strand has its complement ◦ the two will “anneal” (twist around each other)  weak hydrogen bonds  break easily with heat ◦ non-complementary strands will not anneal

7  Polymerases ◦ copy information ◦ from a strand template, make its complement ◦ need a “start signal”  a short DNA fragment, or primer  starts adding symbols to the primer  zips it up!

8  Ligases ◦ covalently bonds DNA molecules together ◦ joins two pieces into single strand ◦ nature’s repair mechanism!

9  Nucleases ◦ scissors to cut DNA strands ◦ some nucleases will search for, and cut at, only specific sequences ◦ e.g.: EcoRI (from E. coli) cuts after the G in GAATTC

10  Technique to separate molecules in a slab of gel ◦ current applied to gel ◦ DNA is –vely charged ◦ shorter strands move faster than longer ones ◦ one can also weigh down specific strands by attaching metal balls to them

11  Mail order! ◦ Write down the sequence on a piece of paper ◦ Send to a synthesis facility ◦ Wait 10 days ◦ Receive 10 18 molecules in a test tube  Today’s price [from www.genscript.com]

12  To build a computer, only two things are really needed ◦ a method of storing information ◦ a few simple operations for acting on that information  Turing machine  Is DNA good enough? ◦ great way to store the “blueprint of life” ◦ enzymes (polymerases and ligases) can operate ◦ Is this enough? YES!

13  Hamiltonian Path Problem ◦ given: a directed graph, G ◦ given: specified start and end nodes, s and t ◦ definition: Hamiltonian path is one that goes from start node to end node, passing through each remaining node exactly once ◦ decide: whether a Hamiltonian path exists for  Like all good problems, this one is NP-complete

14 Given graph with n vertices, 1. Generate a set of random paths through th graph 2. For each path: a.check if path has correct start and end nodes b.check if path passes through exactly n nodes c.check if each vertex is visited Remove path if it fails any of these checks 3. If set is not empty, report that a Hamiltonian path exists.

15  Hamiltonian Path Problem ◦ 7 cities, 14 nonstop flights ◦ takes about a min for most of us  Smaller problem ◦ 4 cities ◦ for illustration

16  Use DNA fragments to code cities and flights ◦ each city X has two parts to its name  (X 1 X 2 )  and complement (X’ 1 X’ 2 ) ◦ a flight also has 2 parts  flight from X 1 X 2 to Y 1 Y 2 has sequence: (X 2 Y 1 )

17  Synthesize: ◦ complements of city names (X’ 1 X’ 2 ) ◦ flights (X 2 Y 1 )  A pinch of each has 10 14 molecules ◦ throw them all into a test tube ◦ add water, ligase, salt ◦ one drop, one second!

18  Each flight bonds only with complements of its start and end cities: ◦ flights (X 2 Y 1 ) ◦ bonds with (X’ 1 X’ 2 ) and (Y’ 1 Y’ 2 ) ◦ ligase seals fragments  Sequences grow: ◦ Atlanta-Boston ◦ Atlanta-Boston-Chicago ◦ …

19  10 14 or so parallel computations!  All paths created at once

20  How to weed out the paths that were not Hamiltonian?  Answer: ◦ clever use of probes, polymerization, gel electrophoresis, etc.

21  Gain: ◦ Want to weed out the incorrect paths ◦ Want to amplify correct paths  Strategy: ◦ Add 2 primers 1.add last name of start city  alerts polymerase to copy the right city strings  complements of sequences with the right start city 2.add complement of the first name of the end city  alerts polymerase to copy the right flight sequences  with the right end city ◦ Exponential growth!

22  Use gel electrophoresis ◦ short solutions do not go through all cities  move faster ◦ keep long ones (length 24)

23  Use metal probes ◦ e.g., specific probe for Boston ◦ sticks to only those paths that contain Boston ◦ electrophoresis to weed out others ◦ heat and repeat

24  If there is any DNA left, there is a Hamiltonian Path!  Also possible to “read out” the path [see refs.]

25  highly parallel ◦ 10 14 solutions simultaneously explored in about 1 second  highly energy efficient ◦ 2 10 19 ligation operations per joule ◦ theoretical max is 34 10 19 joule ◦ today’s computers? ~ 10 9 – 10 10 ops/joule


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