Department Of Instrumentation

09

DNA Computing Seminar

Kunal Ray

7th Semester.

DNA Computing – Seminar

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Kunal Ray, CUSAT

Introduction: A DNA computer is basically a “nano-computer that uses DNA or

deoxyribonucleic acid to store information and perform calculations”.1 Basically

speaking, DNA computers are the next generation microprocessors which use

DNA, chemistry and molecular biology instead of the regular or traditional silicon

based computer technologies. DNA computing or more generally, molecular

computing, is a fast developing inter-disciplinary area. Millions of natural

supercomputers exist inside living organisms, include homo-sapiens. The DNA

molecules, which make up our genes, have the potential to perform calculations

millions of times faster than the world’s fastest man-made computers. It has been

forecasted that DNA might one day be integrated into a computer chip to create a

so-called biochip that will have the capability of pushing computers even faster.

DNA molecules have already been harnessed to perform complex mathematical

calculations. While still in their infancy, DNA computers shall be able to store

billions of times more data than the conventional computers.

History: DNA computing as a field was first developed by Leonard Adleman of

the University of Southern California, in 1994.2 Adleman demonstrated a proof of

concept use of DNA as a form of computation which solved the seven point

Hamiltonian path problem. Since the initial Adleman experiments, advances have

been made and various Turing machines have been constructed. “Turing machines

are basic abstract symbol manipulating devices which, despite their simplicity, can

be adapted to simulate the logic of any computer algorithm. They were described

in 1936 by Alan Turing”.3

1 DNA Computer – Definition, http://www.webopedia.com/TERM/D/DNA_computer.html Retrieved On July 5

th, 2009.

2 Adleman, Leonard M., 1994, Molecular Computation Of Solutions To Combinational Problems, Science Journal.

3 Turing Machine – Wikipedia, The Free Encyclopedia, http://en.wikipedia.org/wiki/Turing_machine

Retrieved On July 5th, 2009.

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“In 2002, researchers at the Weizmann Institute of Science in Rehovot,

Israel, unveiled a programmable molecular computing machine composed of

enzymes and DNA molecules instead of silicon microchips”.4 On April 28

th, 2004,

Ehud Shapiro, Yakov Benenson, Binyamin Gil, Uri Ben Dor and Rivka Adar at the

Weizmann Institute announced in the journal Nature that they had constructed a

DNA computer. “This was coupled with an input and output module and is capable

of diagnosing cancerous activity within a cell, and then releasing an anti-cancer

drug upon diagnosis”.5 A schematic for the above can be shown as below:

Fig: Disease diagnosis and drug administration using DNA computers.

A more detailed explanation shall be provided as we progress with the topic. The

design was one of its kinds and hailed as “the smallest bio-molecular computer

ever”, according to the Guinness Book of World Records.

4 Computer made from DNA and enzymes,

http://news.nationalgeographic.com/news/2003/02/0224_030224_DNAcomputer.html Retrieved On July 5

th, 2009.

5 Adar, Rivka et al, 2004, An autonomous molecular computer for logical control of gene expression, Nature Journal.

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Capability: The DNA computers shall come with a variety of definite advantages

over normal/conventional microprocessors using silicon chips. Some of them are

discussed below.

Parallel Computing: DNA computers by their inherent nature, work on the

principle of parallel computing. “Parallel computing is a principle according

to which, many calculations are carried out simultaneously”.6 This means

that a DNA computer breaks down a given large problem into several

smaller modules and these are then solved concurrently. This essentially

means that initially complex problems which a conventional computer

would take years to solve can be solved within hours using DNA computers.

In order to understand the ability of parallel computing in DNA consider the

fact that a test tube filled with DNA can contain trillions of strands. Each

operation on the test tube of DNA is carried out on all strands of the tube in

parallel. Hence typically we have-

Memory: A DNA computer a memory capacity much larger than any

conventional computer available at present. The picture below shows 1 gm

of DNA on a CD. The average CD has a storage space of 800 MB. But a

DNA computer can hold about 1× MB of data.

6 Almasi, G.S., Gottlieb, A., 1989, Highly Parallel Computing, Benjamin Cummings Publishers, Redwood City, CA.

300,000,000,000,000

molecules at a time

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Energy Consumption: The energy consumption for a DNA computer has

been reported to be very low when compared to conventional computers.

Structure of DNA: DNA (deoxyribonucleic acid) is the primary genetic material

in all living organisms - a molecule composed of two complementary strands that

are wound around each other in a double helix formation. The strands are

connected by base pairs that look like rungs in a ladder. Each base will pair with

only one other: adenine (A) pairs with thymine (T), guanine (G) pairs with

cytosine (C). The sequence of each single strand can therefore be deduced by the

identity of its partner. Genes are sections of DNA that code for a defined

biochemical function, usually the production of a protein. The DNA of an

organism may contain anywhere from a dozen genes, as in a virus, to tens of

thousands of genes in higher organisms like humans. The basic structure of a DNA

molecule can be illustrated below.

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Fig: Structure of DNA (deoxyribonucleic acid)

The structure of a protein determines its function. The sequence of bases in a given

gene determines the structure of a protein. Thus the genetic code determines what

proteins an organism can make and what those proteins can do. It is estimated that

only 1-3% of the DNA in our cells codes for genes; the rest may be used as a

decoy to absorb mutations that could otherwise damage vital genes.

Technology – DNA Separation: Working with individual DNA molecules is

tricky. Current technologies involve chemically binding each DNA molecule to a

plastic bead, then trapping and moving the bead by hitting it with an intense beam

of photons from a laser. A team of researchers from Japan has found a way to drag

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DNA molecules around without attaching them to a larger object. The researchers'

first approach was to sandwich the DNA between unconnected beads and move the

DNA indirectly by bombarding the beads with a laser. A schematic can be shown

below.

Fig: Laser Snatching Free Floating DNA.7

Although that method worked, it required a high degree of skill to carry out. The

researchers went on to find an easier way: they made the beads much smaller and

used many more of them. Key to the method is the size of the beads. The

7 The DNA Packaging Motor – Seeking The Mechanism,

http://www.ncbi.nlm.nih.gov/bookshelf/br.fcgi?book=eurekah&part=A40182 Retrieved On July 6th, 2009.

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researchers found that “a laser beam would trap, or aggregate a cluster of more

than 40 beads that were 200 nanometers in diameter, but would only trap a few

beads half that size. To demonstrate the technique, the researchers put the DNA in

a solution that contained 200-nanometer beads. When they focused a laser beam

into the solution, a group of beads aggregated at the point of focus. When they

focused the beam at the end of a single DNA molecule, a group of beads packed

tightly together around that point, and the researchers used the bead cluster to drag

the end of the molecule”.8 The molecule can be released and re-trapped by

switching the laser off and on, and a single DNA molecule can be manipulated at

any point along its length. Combined with florescent labeling, which tags a

molecule so that it can be seen through an optical florescent microscope, the

method allows for real-time handling of DNA molecules.

Salient Properties of DNA Molecules: The DNA molecules have some salient

properties which differentiate it from other silicon based microprocessors and add

to their usefulness. Some of the properties of DNA molecules used for the purpose

of DNA computing are as follows. It is important that one understands the

procedures mentioned below to have a complete insight regarding the

manufacturing of a DNA computer.

Replication: Replication is one of the most important properties used in

DNA computing. Replication is the method by which any molecule can form

an exact replica of itself and the DNA gets embedded in both these daughter

molecules. “For a cell to divide, it must first replicate its DNA. The process

is initiated at specific points within the DNA molecule, known as origins”.9

8 Laser Snatch Free Floating DNA, http://www.trnmag.com/Stories/2002/032002/Lasers_snatch_free-

floating_DNA_032002.html Retrieved On July 6

th, 2009.

9 Alberts B. et al, 2002, Molecular Biology Of The Cell, Garland Science, Chapter 5, DNA Replication Mechanisms.

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These origins are targeted by proteins that separate the two strands and

initiate DNA synthesis. A schematic showing DNA replication can be given

below.

Fig: DNA Replication – Schematic10

DNA Extraction: In this method, it is possible to separate and bring

together different strands of DNA that are of the same type. Suppose that

we have a test tube containing DNA in which some of the molecules contain

the strand “s”. Then it is possible to separate all the strands in the test tube

that contain “s” as a subsequence and separate from those strands that do not

contain these subsequences. A schematic for the above operation is shown

below and the operation of separation and effectively extraction of DNA

molecules illustrated.

10

DNA Replication And Synthesis, http://library.thinkquest.org/C006188/basics/replication.htm Retrieved On July 6th, 2009.

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Fig: Separation & Extraction, DNA Strands.11

DNA Annealing: This is the method by which two DNA strands can be

brought together and then paired together or melted to form one single

entity. A highly simplistic model can be shown below.

Fig: Two strands bearing s-subsequence coming closer.

11

DNA Separation, http://chemistry2.csudh.edu/rpendarvis/NuclAcids.html Retrieved On July 6th, 2009.

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Fig: Annealed Pair resulting in Single Entity.

The concept behind this is that “the hydrogen bonding between two

complementary sequences is weaker than the one that links nucleotides of

the same sequence. It is therefore possible to pair (anneal) or separate (melt)

to anti parallel and complementary single strands”.

Understanding DNA Computing – Hamiltonian Problem: There exists a

classical problem, known as the Hamiltonian problem or the “Travelling Salesman

Problem”, which can be used to explain the usefulness of DNA computing and its

definite edge over conventional silicon based microprocessors.

Problem Statement: Consider a salesman who has to travel to a number of cities

on a daily basis. Now the problem is to find for him the fastest route, without

taking him through the same city twice. A schematic for the problem can be shown

below. Now the problem seems to be simple enough if the number of cities is 5.

But what if the number of cities is 25 or for that matter 500 or even more. In such

cases, the conventional computer shall invariably take years to find out the

accurate answer. The reason for this is that it must generate a list of all the possible

paths and then search out the shortest path, an extremely time consuming task. But

using the DNA computing mechanism, the answer can be found accurately within

hours.

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Solution: The solution to the above problem can be found out using the

property of replication of DNA and by using the fact that we can use fluorescent

labeling to tag individual molecules in DNA. A single strand of DNA cannot yield

much power. But since DNAs can replicate themselves, so one can have as much

DNA as required to perform complex tasks like the one explained above. And

since DNA works on the principle of parallel processing, a number of options can

be checked simultaneously and the right answer can be arrived at instantly. So far,

this method has been successfully applied up to 15 cities. With advances taking

place almost daily, the number of cities shall shoot up, provided we have enough

DNA to go around with!! So let us see Adleman’s algorithm used to solve the

problem at hand.

o Generate all possible routes.

o Select itineraries that start with the proper city and end with the final city.

Delhi

(Source)

Mumbai

Kolkata

Bangalore

Kochi

(Destination)

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o Select itineraries with the correct number of cities.

o Select itineraries which contain each city only once.

Let us explain all the above steps one by one.

Generating all possible routes: For this purpose, we encode all the cities

one by one as shown below.

Delhi GCTACG

Mumbai CTAGTA

Kolkata TCGTAC

Bangalore CTACGG

Kochi ATGCCG

The short single DNA is synthesized by a technology called DNA synthesizer. In

the next step, we encode all the itineraries by connecting the city sequences for

which routes exist. This can be shown below.

(CTACGG)

CGG ATG GCCTAG

(ATGCCG)

GCCTAG

(After Hybridization)

Bangalore

Kochi

Bangalore Kochi Bangalore to

Kochi

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Select the desired itineraries: The next step is to select the itineraries that

start and end with the correct route. The strategy is to selectively cope and

amplify only that DNA which starts with Delhi and end with Kochi. This

can be shown below.

G C T A C G A T G C C G

The technique used for the above operation is Polymerase Chain Reaction

(PCR). This technique allows the production of many copies of a specific

sequence of DNA.

Select itineraries with correct no. of cities: Sort the DNA by length and

select the DNA whose length equals to 5 cities. The process can be shown

below. Generally, the DNA is a negatively charged molecule, having a

constant charge density. The GEL slows down the passing of DNA

depending on the lengths therefore, producing bands. “The technique used is

GEL Electrophoresis. It is used to differentiate between DNA molecules

having different lengths”.12

12 Gene Almanac, GEL Electrophoresis, http://www.dnalc.org/ddnalc/resources/electrophoresis.html

CGATGC (Start Primer)

Delhi

(source)

TACGGC (End Primer)

Kochi

(destination)

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Fig: GEL Electrophoresis.

Select the paths having complete set of cities: In this section, the DNA

molecules are successively filtered city by city, one city at a time. The

technique used for the above process is Affinity Purification. It is done by

attaching the compliment of the sequence in question to a substrate like

magnetic bead. The DNA which is contained in the sequence hybridizes

with the complement sequence on the beads. Graduated PCRs can be used if

we already have the city encodings. The procedure can be shown below.

Retrieved On July 7th, 2009.

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Hence, as shown above, through DNA computing, the shortest path from one city

to another can be calculated and the Hamiltonian problem be solved.

Biological Implementation of Computer Logic: The question which arises after

all this explanation is that how is it possible to implement the various computer

operations with the help of DNA strands. As an answer to this query, scientists

have successfully developed mechanisms, which can replicate the logical and

computational operations of a conventional computer. "The recent discovery of

DNA Logic Gates is the first step towards creating a DNA computer which has a

structure similar to an electronic PC”.13

Given below is a comparison of the various

operations in a conventional computer and their biological implementation.

13

DNA Computing Technology, How Stuff Works?, http://computer.howstuffworks.com/dna-computer1.htm Retrieved On July 7th, 2009.

CGATGC GATCAT AGCATG GATGCC TACGGC

GCTACG CTAGTA TCGTAC CTACGG ATGCCG

Delhi to

Mumbai

Mumbai to

Kolkata

Kolkata to

Bangalore

Bangalore to

Kochi

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Conventional Logic Biological Implementation

Sum: This adds a value x to all the

numbers inside a set S.

Sum: In this a number is added to all the

strands using the RST method.

Subtraction: This operation subtracts a

value x from all numbers in a set S.

Subtraction: In this, the same number is

removed from all the strands using RST.

Division: This step will separate the set

S into two different sets based on the

criteria C. If no criterion is given, then

components in these two sets are

randomly picked from set S and S will

be evenly distributed into two sets S1

and S2.

Division: The necessary operation for

this step of DNA computing is to

separate one tube of strands into two

tubes. Each resultant tube will have

approximately half of the strands of the

original tube. The criteria C can be

containing or not containing a certain

segment, e.g. ATTCG, and we may use

the metal bead method to extract them.

Union: The operation combines, in

parallel, all the components of sets S1

and S2 into set S.

Union: This operation will simply pour

two tubes of strands into one.

Copy: This will produce a copy of S:

S1.

Copy: We need to make copies of DNA

strands of the original tube and double

the number of strands we have for this

copy operation. Best and easiest method

is PCR (explained above).

Select: This operation will select an

element of S following criteria C. If no

C is given, then an element is selected

randomly.

Select: This procedure will actually

extract out the strand we are looking for.

So, it will extract strands from tube S

following certain criteria C.

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A schematic of the different logic cells can be given below as per their biological

implementation.

Fig: The Genetic NOT Gate.

Fig: The Genetic AND Gate.

As shown above, similar genetic analogy exists for other logic gates as well.

Finally, we can give a comparison of the conventional and DNA computers.

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DNA Based Computers Classical Computers

Slow at individual operations. Fast at individual operations.

Can do billions of operations

simultaneously.

Can do substantially fewer operations

simultaneously.

Can provide huge memory in small

space. One cubic centimeter of DNA

soup could store as much as 10^21bits

of information.

Smaller memory. At most 10^14 bits.

Setting up a problem may require

considerable preparations.

Setting up only requires keyboard input.

DNA is sensitive to chemical

deterioration.

Electronic data is vulnerable but can be

backed up easily.

Conclusion: DNA, the genetic code of life itself has been the molecule of this

century and certainly for the next one. The future of DNA manipulation is speed,

automation and miniaturization. Perhaps it will not be good enough to play games

or surf the web, things traditional computers are good at, but it certainly might be

used in the study of logic, encryption, genetic programming and algorithms,

automata and lots of other things that haven’t even been invented yet!!

Therefore, it won’t be an exaggeration to state that DNA computing is

definitely the technology to watch out for in the coming years is certainly here to

stay.