Paushali senMCA 3nd yr 5th sem

Overview Introduction to DNA

What is DNA computing

Adleman’s Hamiltonian path problem.

Cutting Edge Technologies

Pros and Cons

DNA Vs Electronic Computers

Conclusion

What is DNA?

• DNA stands for Deoxyribonucleic Acid

• DNA represents the genetic blueprint of living

creatures

• DNA contains “instructions” for assembling

cells

• Every cell in human body has a complete set

of DNA

• DNA is unique for each individual

Double Helix

• “Sides”

Sugar-phosphate backbones

• “ladders”

complementary base pairs

Adenine & Thymine

Guanine & Cytosine

• Two strands are held together by

weak hydrogen bonds between the

complementary base pairs

• Thats the picture of human DNA

Uniqueness of DNA

Why is DNA a Unique Computational Element???

• Extremely dense information storage.

• Enormous parallelism.

• Extraordinary energy efficiency.

Dense Information Storage

This image shows 1 gram of DNA on a CD. The CD can hold 800 MB of data.

The 1 gram of DNA can hold about 1x1014 MB of data.

The number of CDs required to hold this amount of information, lined up edge to edge, would circle the Earth 375 times, and would take 163,000 centuries to listen to.

Storeing info inside DNA The following technique use for

copying,sorting,concating and spliting info into DNA module

• ligation,• hybridization,• polymerase chain reaction (PCR),• gel electrophoresis, and• enzyme reaction.

Steps of DNA computing Encodind schame

Ligation and hybridization

Polymerase Chain Reaction (PCR)

Affinity Separation

Gel Electrophoresis

Encoding schame Encode each object of interest into DNA sequence

A correct design is necessary

Incorrect design can make the system incorrect

Ligation and hybridization The sequence when DNA drop in a test tube using a

micro pipattor

DNA sequences recombine with each other by means of some enzymereaction, this process being referred to as ‘ligation’

. All DNA sequences to be used in the experiment are mixedtogether in a single test tube.

is heated to 95o centigrade (celsius) and cooled to 20oC at 1oC per minutefor hybridization

Picture of dropers and hybridization Droppers

hybridization

Polymerase chain reaction . Initialization: a mix solution of template, primer, dNTP and enzyme

isheated to 94 − 98◦C for 1 − 9 minutes to ensure that most of the DNAtemplate and primers are denatured.

. Denaturation: heat the solution to 94 − 98◦C for 20 − 30 seconds forseparation of DNA duplexes

Annealing: lower the temperature enough (usually between 50−64◦C) for20−40 seconds for primers to anneal specifically to the ssDNAtemplate.

Elongation/Extention: raise temperature to optimal elongation temperatureof Taq or similar DNA polymerase (70 − 74◦C) for the polymeraseadds dNTP’s from the direction of 5_ to 3_ that are complementary to thetemplate;

. Final Elongation/Extention: after the last cycle, a 5 − 15 minutes elongationmay be performed to ensure that any remaining ssDNA is fullyextended

Step 2 to 4 is repeated for 20−35 times called thermal cycler.

Affinity saparation Varify each of data include acertain sequinence or not

process a double stranded DNA is incubated with the

Watson-Crick complement of data that is conjugated to magnetic beads

. Abead is attached to a fragment complementary to a substring then a magneticfield is the used to pull out all of the DNA fragments containing suchsequence.

The process is then repeated

pictures

Gel electrophoresis charged molecules to move in an electric field

Basically, DNA molecules carry negative charge.Thus, when we place them in an electrical field, they tend to migrate towardsa positive pole.

Since DNA molecules have the same charge per unit length,they all migrate with the same force in an electrophoresis process. Smallermolecules therefore migrate faster through the gel, and can be sorted accordingto size (usually agarose gel is used as the medium here).

At the end of thisprocess the resultant DNA is photographed

How enormous is the parallelism?

• A test tube of DNA can contain trillions of strands. Each operation on a test tube of DNA is carried out on all strands in the tube in parallel !

• Check this out……. We Typically use

How extraordinary is the energy efficiency?

• Adleman figured his computer was running

2 x 1019 operations per joule.

Can DNA compute? DNA itself does not carry out any computation. It

rather acts as a massive memory.

BUT, the way complementary bases react with each other can be used to compute things.

Proposed by Adelman in 1994

DNA COMPUTING

A computer that uses DNA (deoxyribonucleic acids) to store information and perform complex calculations.

The main benefit of using DNA computers to solve complex problems is that different possible solutions are created all at once. This is known as parallel processing.

Adleman’s Experiment• Hamilton Path Problem

(also known as the travelling salesperson problem)

Perth

Darwin

Brisbane

Sydney

Melbourne

Alice Spring

Is there any Hamiltonian path from Darwin to Alice Spring?

Adleman’s Experiment • Solution by inspection is:

Darwin Brisbane Sydney Melbourne Perth

Alice Spring

• BUT, there is no deterministic solution to this

problem, i.e. we must check all possible

combinations.

Perth

Darwin

Brisbane

Sydney

Melbourne

Alice Spring

Adleman’s Experiment

1. Encode each city with complementary base -

vertex moleculesSydney - TTAAGG

Perth - AAAGGG

Melbourne - GATACT

Brisbane - CGGTGC

Alice Spring – CGTCCA

Darwin - CCGATG

Adleman’s Experiment (Cont’d)

2. Encode all possible paths using the

complementary base – edge moleculesSydney Melbourne – AGGGAT

Melbourne Sydney – ACTTTA

Melbourne Perth – ACTGGG

etc…

Adleman’s Experiment (Cont’d)

3. Merge vertex molecules and edge molecules.All complementary base will adhere to each other to

form a long chains of DNA molecules

Solution with

vertex DNA

molecules

Solution with

edge DNA

molecules

Merge

&

Anneal

Long chains of DNA molecules (All

possible paths exist in the graph)

Adleman’s Experiment (Cont’d)

• The solution is a double helix molecule:

CCGATG – CGGTGC – TTAAGG – GATACT – AAAGGG – CGTCCA

TACGCC – ACGAAT – TCCCTA – TGATTT – CCCGCA

Darwin Brisbane Sydney Melbourne Perth Alice Spring

DarwinBrisbane

BrisbaneSydney

SydneyMelbourne

MelbournePerth

PerthAlice Spring

Operations (Cont’d)

• Mergingmixing two test tubes with many DNA molecules

• AmplificationDNA replication to make many copies of the original

DNA molecules

• Selectionelimination of errors (e.g. mutations) and selection of

correct DNA molecules

THE FUTURE!

Algorithm used by Adleman for the traveling salesman problem was simple. As technology becomes more refined, more efficient algorithms may be discovered.

DNA Manipulation technology has rapidly improved in recent years, and future advances may make DNA computers more efficient.

The University of Wisconsin is experimenting with chip-based DNA computers.

DNA computers are unlikely to feature word processing, emailing and solitaire programs.

Instead, their powerful computing power will be used for areas of encryption, genetic programming, language systems, and algorithms or by airlines wanting to map more efficient routes. Hence better applicable in only some promising areas.

DNA Chip

Chemical IC

The Smallest Computer

• The smallest programmable DNA computer was developed at Weizmann Institute in Israel by Prof. Ehud Shapiro last year

• It uses enzymes as a program that processes on 0n the input data (DNA molecules).

Pros and Cons

+ Massively parallel processor

DNA computers are very good to solve Non-

deterministic Polynomial problems such as

DNA analysis and code cracking.

+ Small in size and power consumption

Pros and Cons (Cont’d)

- Requires constant supply of proteins and

enzymes which are expensive

- Errors occur frequently

a complex selection mechanism is required and

errors increase the amount of DNA solutions

needed to compute

- Application specific

- Manual intervention by human is required

DNA Vs Electronic computers

At Present, NOT competitive with the state-of-the-art algorithms on electronic computers

Only small instances of HDPP can be solved. Reason?..for n vertices, we require 2^n molecules.

Time consuming laboratory procedures.

Good computer programs that can solve HSP for 100 vertices in a matter of minutes.

No universal method of data representation.

Conclusion

• Many issues to be overcome to produce a

useful DNA computer.

• It will not replace the current computers

because it is application specific, but has a

potential to replace the high-end research

oriented computers in future.

• Recently its use in elevator system.

Thank you