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CSE 599 Lecture 4: DNA computing Cells process and store information DNA forms an instruction manual for the chemical processes in a cell DNA stores hereditary information passed from parents to offspring Information is encoded digitally as nucleotide sequences in the DNA Thanks to Chris Diorio and Doug Zonker for some of the slides Deoxyribonucleic acid (DNA) (a) inside, and (b) outside, the cell nucleus Used figures from “Understanding DNA” by Calladine and Drew R. Rao, Week 4: DNA computing 1 Digital Representation Rather than thinking “biology” or “molecule,” think in terms of digital information storage using the alphabet A, T, G, and C R. Rao, Week 4: DNA computing 2 Biomolecular computing: Basic Idea A DNA strand encodes a quaternary (2-bits/base) string Can use molecular techniques to manipulate strings Synthesize, cut, splice, copy, replicate and read DNA molecules Separate and classify strings according to their size or content These processes are slow but massively parallel DNA for general-purpose digital computation Encode: Map problem onto DNA strands Exhaustive Search: Generate all possible solutions by subjecting strands simultaneously to biochemical reactions Use molecular techniques to eliminate invalid solutions The result: Turing Universal DNA computing R. Rao, Week 4: DNA computing 3 DNA primer... DNA provides cells with long-term information storage Resides within cell nucleus Provides templates for protein manufacture mRNA is a temporary copy created from DNA Migrates out of nucleus into cytoplasm Ribosomes read mRNA to create proteins Assisted by tRNA Proteins perform cell functions R. Rao, Week 4: DNA computing 4 Components of DNA/RNA nitrogenous bases purines pyrimidines thymine in DNA uracil in RNA pentose sugar 2-deoxyribose in DNA ribose in RNA phosphate group R. Rao, Week 4: DNA computing 5 Nucleotides base + sugar = nucleoside nucleoside + phosphate = nucleotide bases are linked into a chain by alternating sugars and phosphates direction is significant read from 5’ end to 3’ end R. Rao, Week 4: DNA computing 6 DNA base pairing (Watson-Crick Complementarity) Antiparallel strands form hydrogen bonds between bases Pairing of bases cytosine guanine (C-G) thymine adenine (T-A) R. Rao, Week 4: DNA computing 7 DNA double helix Cells are filled with water Sugar–phosphate group is hydrophilic Bases are hydrophobic DNA double-strand twists to shield bases from water 10 – 12 bp/turn Forms a helix Human DNA strands can be 3cm long but only 20Å in diameter R. Rao, Week 4: DNA computing 8 DNA replication “…it has not escaped our notice that the specific pairing we have postulated immediately suggests a possible copying mechanism for the genetic material.” - Watson & Crick R. Rao, Week 4: DNA computing 9 mRNA production from DNA Producing mRNA 1. Unwind section of DNA 2. Catalyze mRNA using RNA polymerase Base pairing 40 bases/sec at 37° C 3. DNA reforms into double helix 4. mRNA leaves nucleus R. Rao, Week 4: DNA computing 10 Amino acids and Proteins 20 amino acids. Each is a carbon atom with: Amino (NH2) and carboxyl (COOH) groups A H+ atom (except proline) & something else Protein: A chain of amino acids Order of amino acids is primary structure Backbone folding gives secondary structure R. Rao, Week 4: DNA computing 11 mRNA allows protein synthesis Base triplets (codons) code for amino acids Ribosomes serve as decoding machines tRNA is the adapter molecule One end of tRNA carries an amino acid Other end carries an anticodon that matches codon on mRNA strand When a ribosome finds a tRNA with a matching anticodon, amino acid is broken off and attached to polypeptide chain R. Rao, Week 4: DNA computing 12 The genetic code Triplets code for amino acids AUG signals start of translation UAA, UAG, UGA signal end of translation Redundancy: Many triplets may code for 1 amino acid R. Rao, Week 4: DNA computing 13 A List of Molecular Techniques and Tools Separating and fusing DNA strands: Denaturation (melting) and Hybridization (also called annealing or renaturation) Amplifying DNA: PCR (polymerase chain reaction) Shortening and Cutting DNA (based on exonucleases and endonucleases) Determining the length of DNA (gel electrophoresis) Reading the contents of DNA (DNA sequencing) R. Rao, Week 4: DNA computing 14 Denaturation and Hybridization Double helix can be denatured by heating (85-95 degrees C) Denaturing is reversible by cooling (renaturing) Called hybridization when DNA is from different sources (e.g. DNA and RNA) The ability of two nucleic acid preparations to hybridize is a precise test for Watson-Crick complementarity of their base sequences R. Rao, Week 4: DNA computing DNA melting from heating 15 PCR amplifies DNA PCR: Polymerase chain reaction Polymerase: Enzyme that adds nucleotides to an existing DNA strand in the 5’-3’ direction Amplifies short segments of DNA Doubling in ~5 minutes Segment must be bracketed by known primer sequences ~20 bases R. Rao, Week 4: DNA computing 16 Enzymes that shorten or cut DNA Exonucleases shorten DNA Remove nucleotides one at a time from the ends of DNA molecules. E.g. ExonucleaseIII removes nucleotides from the two 3’ ends Endonucleases cut DNA E.g. Restriction enzymes such as EcoRI recognize a short sequence of DNA and cut the molecule at that site Recognition site typically 4-6 bases (e.g. GAATTC) Sticky ends – overhanging ends of DNA available for bonding R. Rao, Week 4: DNA computing 17 Gel electrophoresis determines length DNA molecules are negatively charged Place DNA on gel in electric field DNA molecules drift through gel toward positive electrode Small molecules move faster through gel than large ones Deactivate field when first molecules reach positive electrode Determine lengths by comparing distance of a sample with distance traveled by control fragments with known lengths R. Rao, Week 4: DNA computing 18 Sequencing DNA Break DNA at some instance of known site E.g. break DNA strands at G Determine length of broken strands Do this also for A, T, and C. Electrophorese the results on one gel Read out sequence from right to left R. Rao, Week 4: DNA computing 19 DNA computing Field started by Leonard M. Adleman (USC) Used DNA strands and molecular techniques to solve a simple Hamiltonian path problem: Find a path that visits all vertices once and only once Nov. '94 issue of Science magazine Molecular Computations of Solutions to Combinatorial Problems Laboratory experiment Constructed DNA molecules representing the possible solutions to a 7-city travelling salesperson problem Details: see copy of paper that was handed out in class R. Rao, Week 4: DNA computing 20 The computational premise Construct a DNA molecule for each potential solution Generate candidate solutions in parallel Use molecular operations to eliminate invalid solutions Five basic operations Extract: Separates 1 DNA tube into: One tube with all molecules containing a particular substring Another with the remaining molecules Merge: Mixes two tubes Detect: Checks if there are any DNA strands in a tube Copy: Amplifies the strands in a tube Append: Attaches a string to the end of every molecule in a tube R. Rao, Week 4: DNA computing 21 Adleman’s DNA-based encoding of graphs Input graph: Encoding: R. Rao, Week 4: DNA computing 22 Basic Steps in Adleman’s Algorithm Input: A directed graph G with n vertices, a start vertex vin and a stop vertex vout Step 1: Generate paths in G randomly in large quantities Step 2: Reject all paths that do not begin with vin and end in vout Step 3: Reject all paths that do not involve exactly n vertices Step 4: For each vertex v, reject all paths that do not involve v Output: “Yes” if any path remains, “No” otherwise R. Rao, Week 4: DNA computing 23 Adleman’s experiment Took 7 days to solve 7-city problem, mainly due to laboratory-related set-up time; Robotic manipulators could speed things up All steps are amenable to molecular implementation Related Problems: SAT: Solution proposed by Lipton Created a directed graph whose paths correspond to all possible Boolean assignments of variables Search paths for a satisfiable assignment according to the structure of input formula Cracking the DES (data encryption standard) Search for correct 56-bit key given (plaintext, cryptotext) pairs Not done yet: at 1 operation/hour, requires 9 months R. Rao, Week 4: DNA computing 24 Reasons to be optimistic... DNA computing is orders of magnitude more energy and density efficient than digital computers Employs massive parallelism Field is only 7 years old, so many untried paths Example: Use the structure of DNA and proteins to compute? Living cells hold many secrets Copy their information-processing approaches Possibly use living cells in computing systems DNA can form self-assembling structures Analogous to cellular automata R. Rao, Week 4: DNA computing 25 Reasons to be pessimistic... Generate-and-test approach requires one strand of DNA for each candidate solution 270 DNA strands of length 1000 is 8 kilograms DNA processing is slow and error prone 1 hour per reaction Approximate matches and mutations may give incorrect results Need to learn to build reliable computers from noisy components No communication between strands No easy way to determine if a tube contains two identical strands No killer app has been identified yet R. Rao, Week 4: DNA computing 26 Homework Assignment (due in two weeks) Solve the SUBSET SUM problem using DNA computing SUBSET SUM: Given a set of N positive integers S0, S1, … , SN and a positive integer T (the "target"), is there some subset of these integers Si (with possible repetitions) that sums exactly to T? Examples: Input: S = { 2, 4, 6, 8, 10 }, T = 12; Answer: Yes Input: S = { 2, 4, 6, 8, 10 }, T = 13; Answer: No Input: S = { 1, 5, 4, 2, 7, 2, 12, 19, 17}, T = 42; Answer: Yes (T = 1 + 5 + 5 + 2 + 12 + 17 or 1 + 1 + … + 1) R. Rao, Week 4: DNA computing 27 Homework Assignment (cont.) Three parts: Encode a given problem instance using DNA strands List the steps that will allow you to extract an answer Implement your idea using the Strand software package for high level simulation of DNA computing Strand C++ Class Library: Simulates the creation of DNA strands Basic representation: short strand of DNA = an “Element” Does not use individual bases or base sequences High level simulation of typical operations performed in DNA computing: melt, anneal, cut, detect, extract, remove, pour, append, read, and length. Documentation: http://www.lut.fi/~kyrki/dna/doku.html R. Rao, Week 4: DNA computing 28 Next Week: Fundamentals of Neurobiology No homework due next week. Read the on-line articles for additional information on DNA computing Download and test the simulator using sample programs for the Hamiltonian path and SAT problems Contact TA or instructor if you have any questions or problems regarding the DNA computing assignment Have a great weekend! R. Rao, Week 4: DNA computing 29