GUINNESS WORLD RECORD .....here is a real life story of a computer
100,000 times faster than the current fasted PC....and is a DNA molecule made by
Fifty years on from the discovery of DNA, scientists unveil a
molecular-level computing device that’s so tiny, you
could fit 60 TRILLION of them into a teardrop
No, it’s not science fiction – Israeli scientists have announced the
creation of the world’s smallest biological computing device. Ehud Shapiro and
colleagues from the Weizmann Institute of Science in Israel have adapted DNA
molecules to act as computing devices, and just a 1000th of a milliliter could
contain 3 trillion of these DNA devices, performing 66 billion operations a
To validate this achievement, Guinness World Records science editor David
Hawksett spoke to Prof Shapiro and colleague Yaakov Benenson:
DH: How does the smallest computing device work?
ES: It has three components: an input molecule, software molecules, and a
hardware molecule. The input molecule is a double-stranded DNA molecule, and the
hardware is a naturally occurring enzyme called FokI. Each molecular computer
performs an operation every 20 seconds. But our "computer soup" contains 15,000
trillion computers performing 330 trillion operations per second, which is more
than 100,000 times faster than the fastest PC.
Also, this spoonful releases less than one 25 millionth of a watt, so it’s a
million times time more efficient than a PC.
DH: What will the impact of this research be?
ES: It’s probably too early to predict its impact, but we envision
bio-molecular computing devices operating as "smart components" in biochemical
reactions, which may have pharmaceutical applications in the future.
Want to know more? Read the full interview transcript by clicking on the next
The following is a transcript of
an interview between
Guinness World Record science editor David Hawksett
Ehud Shapiro and Yaakob Benenson,
two of the creators of the world's smallest biological computing device.
DH: How does the smallest computing device work?
ES: All electronic computers work according to a mathematical model – developed
by John von Neumann in the 1940s – called the "stored program computer". In it,
both the program and data are stored as words in the computer memory. Each
memory word can be accessed by its address. The electronic computer fetches
program instructions one by one from its memory and executes them. Typically,
the instructions are to load data from a certain memory location into a
register, or to store the content of a register into a memory location, or to
perform an operation on registers, such as adding the content of two registers
and store the result in a third register.
The stored program computer model is ideal for realization using electronic
circuits, and hence it has been the basis of all electronic computers for more
than 50 years.
Our molecular computer is based on a very different model, called a "finite
automaton", which is a simplified version of the Turing machine, a mathematical
model of computation developed by the British mathematician Alan Turing in the
The Turing machine has data stored as a string of symbols. (Turing envisioned a
paper tape divided into squares, each holding one symbol.) A control unit, which
holds the program rules, is in a particular location on the string, and can be
in one of a finite number of states. The Turing machine starts the computation
in an initiate state and on the leftmost symbol in the string. In each cycle, a
Turing machine reads a symbol and executes a program rule that specifies what
action to take according to the symbol read and the internal state. The actions
can be to replaces the symbol with a new symbol, move one symbol to the left or
to the right, and/or change internal state.
A "finite automaton" is a Turing machine that cannot change the string of
symbols, and in each step moves one symbol to the right. Hence the result of the
computation of the finite automaton is the final state reached upon reaching the
last input symbol.
Both the stored program computer and the Turing machine are so-called "universal
computers" and as such have equivalent computing power. A finite automaton is
Our "molecular finite automaton" has three components. An input molecule, which
stores the data to be processed (as well as the fuel needed for the
computation), software molecules, which encode program rules, and a hardware
molecule, which performs the computation, as directed by the software and the
input. The molecules float in a watery solution containing some salts needed for
the operation of the hardware molecule.
The input molecule is a double-stranded DNA molecule. A mathematical trick is
used to store the current state and current symbol to be processed in a
"sticky-end" of the DNA molecule, a single-stranded protrusion obtained by
having one strand longer than the other. The software molecules also have
"sticky-ends", each matching a different state-and-symbol input combination.
Through a spontaneous chemical process called DNA hybridization, the input
molecule and a matching software molecule temporarily connect to each other.
The hardware is a naturally occurring molecule, an enzyme called FokI that
attaches to DNA in a specifically coded location and cuts both strands at a
fixed distance from that location, creating a sticky end. Using additional
chemical and mathematical tricks, the software molecules are designed so that
the hardware enzyme attaches to them and, once a software molecule hybridizes
with an input molecule, the hardware molecule cuts the input molecule in a
programmed location, exposing a new sticky end that encodes the next state and
the next symbol to be processed. The final sticky end, obtained at the end of
the computation, encodes the computation result.
DH: What exactly can your "computer" do?
ES: Our molecular computing device is a so-called "two-state two-symbol finite
automaton", which can do a rather limited set of computations, depending on
which program molecules are used (i.e., mixed in the watery solution). For
example, it can detect if a list of 0's and 1's has an even number of 1's; if it
has at least one 0; if it has no two consecutive 1's; if it has no 0's after a
1; or if it starts with 1 and ends in 0.
DH: How do performances compare with a traditional computer – a PC for example?
ES: Each molecular computer is rather slow… on the average it performs one
operation per 20 seconds. Also, a PC is a "universal computer" whereas out
molecular finite automaton is very limited in its computing capabilities.
Nevertheless, if we consider the size and energy consumption, then a spoonful (5
milliliters) of our "computer soup" contains 15,000 trillion computers that
together perform 330 trillion operations per second, which is more than 100,000
times faster than the fastest PC. This spoonful releases less than 25 millionth
of a watt, hence its energy-efficiency is more than a million times that of a
DH: What will the impact of this research be?
ES: This is basic research at an early stage, it may be too early to predict its
impact. However, we envision bio-molecular computing devices operating as "smart
components" in biochemical reactions - which may have pharmaceutical and
biomedical applications in the future.
DH: What is new about this latest work, compared with previous research into
ES: The key conceptual advance, compared with our earlier molecular automaton
published more than a year ago, is that the new automaton uses its DNA input as
its source of fuel, hence it does not need an external fuel supply. In addition,
in our previous molecular automaton, each computational step consumed one
software molecule, and hence the computation needed an ongoing supply of
software molecules. The new automaton does not, so the net result is that a
fixed set of software and hardware molecules can process any input molecule, of
any length, without an external supply of energy.
YB: As we mentioned, DNA would break into pieces unless high energetic barriers
prevent it from doing it. Nuclease enzymes lower these barriers and allow DNA to
decompose. Some of the nucleases cleave very precisely at certain locations,
determined by the exact sequence of the nucleotides at or near their cleavage
sites. Yet, even such specific cleavage would only generate useless heat. In our
molecular computer, we use this energy to drive a useful process, namely
It should be understood that on the physico-chemical level we have a sequence of
chemical reactions, resulting in a certain chemical product. This chemical
process would not happen if energy were not released at each step. The energy is
indeed released because we break DNA into smaller pieces with the help of FokI
At a conceptual level, the sequence of chemical reactions is the steps of
computation, and the final product is a computational output. The whole
computation process and output formation depend on the energy stored in the
starting material, a molecule encoding an input data. Therefore, the computation
(an abstract notion) is made possible thanks to the (physical) energy stored in
the (physical implementation of its) input relative to the energy stored in its
output. There are no other sources of energy; the computation is fueled solely
by its input.
So, there are five main differences between what we've done now and what we
achieved in the past:
The new computer does not use ATP [Adenosine triphosphate, an organism's natural
source of energy] and is fueled by its input; the old one relied on ATP as its
The new computer recycles its software and hardware; the old one consumed one
software molecule per transition.
The new computer is 50 times faster and performs 8000 times more operations in
parallel than the old one.
The new computer can process much longer input strings. We could routinely
compute on inputs 12 symbols long but also got results with 20-symbols long
strings. The yield of a single step rose above 98%. The old one could only
process 6-symbol inputs on a good day, with about 50% single step yield.
The new computer has a completely redesigned structure, making possible all the
improvements summarized above.
DH: What other work has been done in this field?
ES: The field started in 1994 with the publication of a paper by Len Adleman. It
described how DNA can be used to solve combinatorial problems, such as the
so-called "traveling salesman" problem, in which the aim is to find an optimal
route through several cities, given the distances between them. The hope was
that the parallel nature of DNA manipulation could be used to outperform
electronic computers in solving such problems.
YB: Another line of research is "semi-autonomous molecular computation", which
is pursued by Hagiya and Sakamoto in Tokyo University, and by Winfree, Reif and
Seeman in the USA. This approach aims at creating systems that evolve in a
programmed fashion to perform a computation, while minimizing the external
intervention. These researches were successful in performing very simple
computations without much interference except regulating the temperature during
the process. Still, experimentally demonstrated computation capabilities of
these systems are substantially lower than that of our devices, and they're not