Introduction to DNA Computing

Russell DeatonElectrical EngineeringThe University of MemphisMemphis, TN 38152rjdeaton@memphis.edu

Stephen A. KarlDepartment of BiologyUniversity of South FloridaTampa, FL 33620karl@chuma.cas.usf.edu

What is DNA Computing (DNAC) ?

The use of biological molecules, primarily DNA, DNA analogs, and RNA, for computational purposes.

Why Nucleic Acids?• Density (Adleman, Baum):

– DNA: 1 bit per nm3, 1020 molecules– Video: 1 bit per 1012 nm3

• Efficiency (Adleman)– DNA: 1019 ops / J– Supercomputer: 109 ops / J

• Speed (Adleman):– DNA: 1014 ops per s– Supercomputer: 1012 ops per s

What makes DNAC possible?• Great advances in molecular biology

– PCR (Polymerase Chain Reaction)– New enzymes and proteins– Better understanding of biological molecules

• Ability to produce massive numbers of DNA molecules with specified sequence and size

• DNA molecules interact through template matching reactions

What are the basics from molecular biology that I need to

know to understand DNA computing?

PHYSICAL STRUCTURE OF DNA

Nitrogenous Base

34 Å

MajorGroove

Minor Groove

Central Axis

Sugar-PhosphateBackbone

20 Å5’ C

3’ OH

3’ 0HC 5’

5’

3’

3’

5’

INTER-STRAND HYDROGEN BONDING

Adenine Thymine

to Sugar-PhosphateBackbone

to Sugar-PhosphateBackbone

(+) (-)

(+)(-)

Hydrogen Bond

Guanine Cytosine

to Sugar-PhosphateBackbone

to Sugar-PhosphateBackbone

(-) (+)

(+)(-)

(+)(-)

STRAND HYBRIDIZATION

A B

a b

A B

ab

b

B

a

A

HEAT

COOL

ba

A B

OR

100° C

DNA LIGATION

’ ’

’ ’

Ligase Joins 5' phosphateto 3' hydroxyl

’ ’

RESTRICTION ENDONUCLEASES

EcoRI

HindIII

AluI

HaeIII

- OH 3’

5’ P -

- P 5’

3’ OH -

GEL ELECTROPHORESIS - SIZE SORTING

BufferGel

Electrode

Electrode

Samples

Faster

Slower

ANTIBODY AFFINITY

CACCATGTGAC

GTGGTACACTG B

PMP

+

Anneal

CACCATGTGAC

GTGGTACACTG B+

CACCATGTGAC

GTGGTACACTG B PMP

Bind

Add oligo withBiotin label

Heat and cool

Add Paramagnetic-Streptavidin

Particles

Isolate with MagnetN

S

POLYMERASE CHAIN REACTION AMPLIFICATION

Cycle 1Cycle 2

Cycle 3 - 35...

3’

5’

3’

5’

3’

5’

3’

5’

3’

5’

5’5’3’

3’

Heat 95° C

Cool 55° C

Synthesize 72 ° C

What is a the typical methodology?

• Encoding: Map problem instance onto set of biological molecules and molecular biology protocols

• Molecular Operations: Let molecules react to form potential solutions

• Extraction/Detection: Use protocols to extract result in molecular form

What is an example?

• “Molecular Computation of Solutions to Combinatorial Problems”

• Adleman, Science, v. 266, p. 1021.

What are the success stories?

• Self-Assembling Computations Demonstrated (Winfree and Seeman)

• New Approaches and Protocols Developed – Surface-based (Wisconsin-Madison, Dimacs II)– PCR-based (Hagiya et al., Dimacs III)– Parallel Overlap Assembly (Kaplan et al.,

Dimacs II)– DNA Addition (Guarnieri and Bancroft,

Dimacs II)

Source: http://seemanlab4.chem.nyu.edu/

Source: Winfree, DIMACS IV

Source: http://corninfo.chem.wisc.edu/writings/dnatalk/dna01.html

Source: Hagiya, DIMACS III

What are the challenges?

• Error: Molecular operations are not perfect.

• Reversible and Irreversible Error

• Efficiency: How many molecules contribute?

• Encoding problem in molecules is difficult

• Scaling to larger problems

What are the challenges for Computer Science?

• Discover problems DNA Computers are good at– Messy reactions as positive– Evolvable, not programmable

• Characterize complexity for DNA computations with bounded resources

• New notions of what a “computation” is?

What are the challenges for molecular biology?

• Develop computation-specific protocols

• Better understanding of basic mechanisms and properties

• Better characterization of processes

• Measures of reliability and efficiency

• Advanced understanding of biomolecules other than DNA and RNA

How does DNAC relate to electronic computing?

• Solution versus solid state

• Individual molecules versus ensembles of charge carriers

• The importance of shape in biological molecules

• Programmability/Evolvability Trade-off (Conrad)

How does DNAC relate to evolutionary computing?

• DNA is at the core of biological evolution.

• Evolutionary Computing implementation in vitro with DNAC

• Enzymes changing the Sequence

• Use DNAC “errors” for similarity and fault-tolerance

• in vitro evolution and DNAC

How does DNAC relate to computational biology?

• Mirror images of each other

• Computational biology interested in applying CS to solve biological problems

• DNAC interested in applying biology to solve computational problems

• Use DNAC to solve computational biology problems

How does DNAC relate to living systems?

• Kari and Landweber (Dimacs IV)

• How do cells and nature compute?

• Thesis: Ciliates compute a difficult HP problem in gene unscrambling.

• Similarities to Adleman’s Path Finding Problem in the Cell

Source: http://www.princeton.edu/~lfl/washpost.html

What advances in molecular biology might benefit DNAC?

• Detergents

• Synthetic bases

• Error-prone PCR

• New enzymes

• Designer molecules

• Charge Transfer along DNA

• Improved separation techniques

What advances in DNAC might benefit molecular biology?

• Lipton and Landweber (Dimacs III)s

• DNA2DNA “killer app”

• Automation of protocols

• Better estimation of error rates

• 3-dimensional structure analysis

• Increased fidelity and efficiency of techniques

What developments can we expect in the near-term?

• Increased use of molecules other than DNA

• Evolutionary approaches

• Continued impact by advances in molecular biology

• Some impact on molecular biology by DNA computation

• Increased error avoidance and detection

What are the long-term prospects?

• Cross-fertilization among evolutionary computing, DNA computing, molecular biology, and computation biology

• Niche uses of DNA computers for problems that are difficult for electronic computers

• Increased movement into exploring the connection between life and computation?

Where can I learn more?

• Web Sites:• http://www.wi.leidenuniv.nl/~jdassen/dna.html• http://dope.caltech.edu/winfree/DNA.html• http://www.msci.memphis.edu/~garzonm/bmc.html• (Conrad) http://www.cs.wayne.edu/biolab/index.html

• DIMACS Proceedings: DNA Based Computers I (#27), II (#44), III (#48), IV (Special Issue of Biosystems), V (MIT, June 1999)• Other: Genetic Programming 1 (Stanford, 1997), Genetic Programming 2 (Wisconsin-Madison, 1998), IEEE International Conference on Evolutionary Computation (Indianapolis, 1997)• G. Paun (ed.), Computing with Biomolecules: Theory and Experiment, Springer-Verlag, Singapore 1998.• “DNA Computing: A Review,” Fundamenta Informaticae, 35, 231-245.