In the News: DNA May Soon Be Used for Data Storage

All of the world's information, about 1.8 zettabytes, could be stored in about four grams of DNA

by Lucas Mearian

Researchers have created a way to store data in the form of DNA, which can last for tens of thousands of years.

The encoding method makes it possible to store at least 100 million hours of high-definition video in about a cup of DNA, the researchers said in a paper published in the journal Nature this week.

The researchers, from UK-based EMBL-European Bioinformatics Institute (EMBL-EBI), claimed to have stored encoded versions of an .mp3 of Martin Luther King's "I Have a Dream" speech, along with a .jpg photo of EMBL-EBI and several text files.

"We already know that DNA is a robust way to store information because we can extract it from wooly mammoth bones, which date back tens of thousands of years, and make sense of it," Nick Goldman, co-author of the study at EMBL-EBI, said in a statement. "It's also incredibly small, dense and does not need any power for storage, so shipping and keeping it is easy."

Reading DNA is fairly straightforward, but writing it has been a major hurdle. There are two challenges: First, using current methods, it is only possible to manufacture DNA in short strings. Secondly, both writing and reading DNA are prone to errors, particularly when the same DNA letter is repeated.

Nick and co-author Ewan Birney, associate director of EMBL-EBI, set out to create a code that overcomes both problems. The new method requires synthesizing DNA from the encoded information. EMBL-EBI worked with California-based Agilent Technologies, a maker of electronic and bio-analytical measurement instruments such as oscilloscopes and signal generators, to transmit the data and then encode it in DNA.

Agilent downloaded the files from the Web and then synthesized hundreds of thousands of pieces of DNA to represent the data. "The result looks like a tiny piece of dust," said Emily Leproust of Agilent.

Agilent then mailed the sample to EMBL-EBI, where the researchers were able to sequence the DNA and decode the files without errors.

This is not the first time DNA has been shown to be an effective method of storing data. Last fall, researchers at Harvard University demonstrated the ability to store 70 billion copies of a book in HTML form in DNA binary code.

The researchers created the binary code through DNA markers to preserve the text of the book, Regenesis: How Synthetic Biology Will Reinvent Nature and Ourselves in DNA.

The Harvard researchers stored 5.5 petabits, or 1 million gigabits, per cubic millimeter in the DNA storage medium. Because of the slow process for setting down the data, the researchers consider the DNA storage medium suitable only for data archive purposes -- for now.

"The total world's information, which is 1.8 zettabytes, [could be stored] in about four grams of DNA," Sriram Kosuri, a senior scientist at Harvard's Wyss Institute and senior author of the paper explaining the science, said at the time.

Researchers are pursuing methods of storing data in smaller and smaller packets because of the tremendous growth of data.

During the next eight years, the amount of digital data produced will exceed 40 zettabytes, which is the equivalent of 5,200GB of data for every man, woman and child on Earth, according to the latest Digital Universe study by research firm IDC.

The majority of data between now and 2020 will not be produced by humans but by machines as they talk to each other over data networks. That would include, for example, machine sensors and smart devices communicating with other devices.

"We've created a code that's error tolerant using a molecular form we know will last in the right conditions for 10,000 years, or possibly longer," Nick said. "As long as someone knows what the code is, you will be able to read it back if you have a machine that can read DNA."

The researchers said the next step in development is to perfect the coding scheme and explore practical aspects, paving the way for a commercially viable DNA storage model.

This graphic details the mind-boggling numbers.

From Wikipedia:

A zettabyte (symbol ZB, derived from the SI prefix zetta-) is a quantity of information or information storage capacity equal to 1021 bytes or 1,000 exabytes (or one sextillion (one long scale trilliard) bytes).

As of April 2012, no storage system has achieved one zettabyte of information. The combined space of all computer hard drives in the world was estimated at approximately 160 exabytes in 2006. This has increased rapidly however, as Seagate reported selling 330 exabytes worth of hard drives during the 2011 Fiscal Year. As of 2009, the entire World Wide Web was estimated to contain close to 500 exabytes. This is a half-zettabyte.

1,000,000,000,000,000,000,000 bytes = 10007 bytes = 1021 bytes
The term "zebibyte" (ZiB), using a binary prefix, is used for the corresponding power of 1024.
Comparisons for scale: A zettabyte is equal to 1 billion terabytes.

The world's technological capacity to receive information through one-way broadcast networks was 0.432 zettabytes of (optimally compressed) information in 1986, 0.715 in 1993, 1.2 in 2000, and 1.9 (optimally compressed) zettabytes in 2007 (this is the informational equivalent to every person on earth receiving 174 newspapers per day).

According to International Data Corporation, the total amount of global data is expected to grow to 2.7 zettabytes during 2012. This is 48% up from 2011.

Mark Liberman calculated the storage requirements for all human speech ever spoken at 42 zettabytes if digitized as 16 kHz 16-bit audio. This was done in response to a popular expression that states "all words ever spoken by human beings" could be stored in approximately 5 exabytes of data (see exabyte for details). Liberman did freely confess that "maybe the authors [of the exabyte estimate] were thinking about text".

Research from the University of Southern California reports that in 2007, humankind successfully sent 1.9 zettabytes of information through broadcast technology such as televisions and GPS.

Research from the University of California, San Diego reports that in 2008, Americans consumed 3.6 zettabytes of information.

The Epigenetics Revolution

This epigentics book looks interesting. I'll order a copy today.

The Epigenetics Revolution: How Modern Biology Is Rewriting Our Understanding of Genetics, Disease, and Inheritance by Nessa Carey

Epigenetics can potentially revolutionize our understanding of the structure and behavior of biological life on Earth. It explains why mapping an organism's genetic code is not enough to determine how it develops or acts and shows how nurture combines with nature to engineer biological diversity. Surveying the twenty-year history of the field while also highlighting its latest findings and innovations, this volume provides a readily understandable introduction to the foundations of epigenetics.

Nessa Carey, a leading epigenetics researcher, connects the field's arguments to such diverse phenomena as how ants and queen bees control their colonies; why tortoiseshell cats are always female; why some plants need cold weather before they can flower; and how our bodies age and develop disease. Reaching beyond biology, epigenetics now informs work on drug addiction, the long-term effects of famine, and the physical and psychological consequences of childhood trauma. Carey concludes with a discussion of the future directions for this research and its ability to improve human health and well-being.

 Biography
Here's the official version...
Nessa Carey has a virology PhD from the University of Edinburgh and is a former Senior Lecturer in Molecular Biology at Imperial College, London. She has worked in the biotech and pharmaceutical industry for ten years. She lives in Bedfordshire and this is her first book.
And what else?
After leaving school I went to the University of Edinburgh to become a vet. This didn't last because I was allergic to fur, unable to think in 3D (not good for anatomy), quite bored and really rubbish at the course. So I dropped out and at Catford Job Centre, in amongst the ads for short order chefs (I couldn't cook) and van drivers (I couldn't drive), was one for a forensic scientist. And oddly enough I had always wanted to work at this end of crime - I must have been the only kid in the UK who had read a biography of Bernard Spilsbury by the age of 11.
So for five years I worked at the Metropolitan Police Forensic Science Lab in London and studied part-time. I then realised that I loved academic science and went off to do a PhD. At the University of Edinburgh. In the veterinary faculty.
After that, it was the academic route of post-doc, Lecturer and Senior Lecturer. But I had a tendency to wander off on routes that intrigued me - degree in Immunology, PhD in Virology, post-doc in Human Genetics, academic position in Molecular Biology. Such wandering isn't necessarily the best idea in academia but the breadth of experience is really valued in industry. I've spent 10 years in biotech and have recently moved to the pharmaceutical sector.
And outside of work? I love birdwatching (no, I don't have a life-list), cycling, scavenging stuff from skips, and growing vegetables. I have a fantasy about one day having a smallholding (where I will starve to death if I really have to be self-sufficient) and I can't wait to write my next book. And I can now cook. And drive.

More on the "Project ENCODE" DNA Breakthrough Research

by Stephanie Pappas, LiveScience Senior Writer

September 05, 2012



UW genome scientist Dr. John A. Stamatoyannopolous led several major Project ENCODE related studies.


The ENCODE project has looked deeper into "junk DNA" than ever before. And junk it is not: According to more than 30 research papers published today (Sept. 5) in a number of journals including Science and Nature, at least 80 percent of the genome is biologically active, with much non-protein-coding DNA regulating nearby genes in a complex dance of influence. [Mysteries of Human Evolution]

The findings reveal that the genetic basis of many diseases may not be in protein-coding genes at all, but in their regulatory neighbors. For example, genetic variants related to metabolic diseases pop up in genetic regions that activated only in liver cells. Likewise, regions activated in immune cells hold variants that have been associated with autoimmune disorders such as lupus.

"These breakthrough studies provide the first extensive maps of the DNA switches that control human genes," study researcher John Stamatoyannopoulos, associate professor of genome sciences and medicine at the University of Washington, said in a statement. "This information is vital to understanding how the body makes different kinds of cells, and how normal gene circuitry gets rewired in disease. We are now able to read the living human genome at an unprecedented level of detail, and to begin to make sense of the complex instruction set that ultimately influences a wide range of human biology."

In the News: New DNA project shows us living beyond our genes

Well, once again, one man's junk is another man's treasure!

New DNA project shows us living beyond our genes

by Robert Bazell and Maggie Fox, NBC News
In what many scientists say is a revolution in biology, a giant new project is rewriting our understanding not only of what causes diseases or what makes our eyes a certain color, but what makes us human. And it turns out scientists have been looking in the wrong place for a very long time.

The bounty of new discoveries, released in a batch of 40 research papers on Wednesday, shows the stretches of DNA that we call genes are only a very small piece of what makes the body work. Much more important is the stuff in between the genes – stuff once dismissed as “junk DNA”. It turns out that junk DNA is what is in control, they report in the series of papers in the journals Nature, Science and elsewhere.

“This has opened up whole new galaxies.  It’s like having a bigger telescope,” says Dr. Bruce Stillman, president of Cold Spring Harbor Laboratory, which played a major role in the work.

Scientists already knew in 2003, as they finished the giant Human Genome Project, that they did not have the understanding they had hoped for.  It turned out that humans had just a measly 22,000 genes – fewer than some animals and far fewer even than a plant such as rice. How could something as complex and advanced as a human be boiled down into something so simple?

“We understood precious little about the processes that turns genes on and off. In short we had more questions than answers about how the human genome works,” said Dr. Eric Green, director of the National Human Genome Research Institute, which conducted the study.

The next phase of work, called ENCODE for Encyclopedia of DNA Elements, shows there’s nothing simple about it. As many as 40 million different switches are controlling these genes, turning them on and off in complex and subtle ways.

“The genome is loaded with gene controlling switches. There are literally millions of these,” Dr. John Stamatoyannopoulos of the University of Washington, who worked on the studies, told reporters in a telephone briefing.

Dr. Francis Collins, director of the National Institutes of Health, calls the findings “awesome and elegant.”

“This is the first truly comprehensive view, of how the three billion letter instruction book for human biology actually carries out its work, across many tissues and over the course of development,” he told NBC News in an interview.

Stanford University genomic expert Michael Snyder says it looks like gene mutations -- the changes in DNA sequences that we associate with causing diseases -- may only affect rare diseases. Common diseases, like heart disease, cancer, and allergy, are probably controlled elsewhere. “We think that most of the changes that affect disease don’t lie in the genes themselves, but the switches,” Snyder says.

So treating these common diseases may lie in trying to affect the switches. “The pharmaceutical industry has largely given up on genomics and the genome in favor of older approaches,” said Stamatoyannopoulos. These new findings may reinvigorate new drug research, he said. “Now we have a huge amount of genetic data about human disease that we can actually put to work to find the right kind of genes and proteins to target,” he said.

This new data will also help doctors diagnose disease in the first place, predict which treatments will work best for patients, and monitor their progress. It  points the way to studies to determine the causes of hundreds of diseases including  all kinds of cancer, Alzheimer’s disease, schizophrenia, heart disease, type 1 and type 2 diabetes, lupus, rheumatoid arthritis and asthma. 

It also may lead to a better understanding of how our genetics determine such non-disease factors as height, weight and expected life span.

Not only that – it can help explain why humans and chimpanzees share 98 percent or more of our genes, yet are so different.

"Genes occupy only a tiny fraction of the genome, and most efforts to map the genetic causes of disease were frustrated by signals that pointed away from genes. Now we know that these efforts were not in vain, and that the signals were in fact pointing to the genome's 'operating system' -- the instructions for which are hidden in millions of locations around the genome," said Stamatoyannopoulos. "The findings provide a new lens through which to view the role of genetics and genome function in disease."

Another surprising finding was that the regulatory circuitry blueprints could be used to pinpoint cell types that play a role in specific diseases -- without requiring any prior knowledge about how the disease worked. For example, DNA changes associated with Crohn's disease (a common type of inflammatory bowel disease) are concentrated in the switches controlling two types of immune cells.

Researchers can use this same method to identify cell types not previously known to play a role in a particular disease, expanding our understanding of the disease process and potentially leading to new therapies.

"We now have a parts list of what makes us human," says Mark Gerstein of Yale university, who worked on the project. "What we are doing is figuring out the wiring diagram of how it all works."

The findings rewrite biology 101 for most of us.  Each gene, we were taught, provided the code for a single protein. The proteins were the building blocks of cells, and the products made by the cells, from compounds called growth factors to signal-carrying chemicals. An intermediary genetic structure called RNA carried this information. ENCODE shows this is not quite so straightforward, that RNA generates the 40 million switches that can affect how and when many things happen within the cells.

“This is another grand chapter in the ongoing and historic research story that is unraveling the details about how life works, and how disease occurs,” Collins said.

From the "More Complexity, Please" Dept. :What is Gene Expression?

Gene expression is the process by which information from a gene is used in the synthesis of a functional gene product. These products are often proteins, but in non-protein coding genes such as rRNA genes or tRNA genes, the product is a functional RNA. The process of gene expression is used by all known life -- eukaryotes (including multicellular organisms), prokaryotes (bacteria and archaea) and viruses - to generate the macromolecular machinery for life.

Gene structure and gene expression in higher organisms

Several steps in the gene expression process may be modulated, including the transcription, RNA splicing, translation, and post-translational modification of a protein. Gene regulation gives the cell control over structure and function, and is the basis for cellular differentiation, morphogenesis and the versatility and adaptability of any organism. Gene regulation may also serve as a substrate for evolutionary change, since control of the timing, location, and amount of gene expression can have a profound effect on the functions (actions) of the gene in a cell or in a multicellular organism.

In genetics gene expression is the most fundamental level at which genotype gives rise to the phenotype. The genetic code is "interpreted" by gene expression, and the properties of the expression products give rise to the organism's phenotype.

Further Reading

• Gene Expression Mechanism
• Gene Expression Measurement
• Regulation of Gene Expression
• Gene Expression System
• Gene Expression Techniques

In the News: Genome Brings Ancient Girl to Life

This replica of a tiny finger bone from Denisova Cave yielded an entire genome. Photo: Max Planck Institute for Evolutionary Anthropology.

by Adrian Cho, ScienceNOW

In a stunning technical feat, an international team of scientists has sequenced the genome of an archaic Siberian girl 31 times over, using a new method that amplifies single strands of DNA. The sequencing is so complete that researchers have as sharp a picture of this ancient genome as they would of a living person’s, revealing, for example that the girl had brown eyes, hair, and skin. “No one thought we would have an archaic human genome of such quality,” says Matthias Meyer, a postdoc at the Max Planck Institute for Evolutionary Anthropology in Leipzig, Germany. “Everyone was shocked by the counts. That includes me.”


That precision allows the team to compare the nuclear genome of this girl, who lived in Siberia’s Denisova Cave more than 50,000 years ago, directly to the genomes of living people, producing a “near-complete” catalog of the small number of genetic changes that make us different from the Denisovans, who were close relatives of Neandertals. “This is the genetic recipe for being a modern human,” says team leader Svante Pääbo, a paleogeneticist at the institute.

Ironically, this high-resolution genome means that the Denisovans, who are represented in the fossil record by only one tiny finger bone and two teeth, are much better known genetically than any other ancient human—including Neandertals, of which there are hundreds of specimens. The team confirms that the Denisovans interbred with the ancestors of some living humans and found that Denisovans had little genetic diversity, suggesting that their small population waned further as populations of modern humans expanded. “Meyer and the consortium have set up the field of ancient DNA to be revolutionized—again,” says Beth Shapiro, an evolutionary biologist at the University of California, Santa Cruz, who was not part of the team. Evolutionary geneticist Sarah Tishkoff of the University of Pennsylvania agrees: “It’s really going to move the field forward.”


Pääbo’s group first gave the field a jolt in May 2010 by reporting a low-coverage sequence (1.3 copies on average) of the composite nuclear genome from three Neandertals. They found that 1% to 4% of the DNA of Europeans and Asians, but not of Africans, was shared with Neandertals and concluded that modern humans interbred with Neandertals at low levels.

Just 7 months later, the same group published 1.9 copies on average of a nuclear genome from a girl’s pinky finger bone from Denisova Cave. They found she was neither a Neandertal nor a modern human—although bones of both species had been found in the cave—but a new lineage that they called Denisovan. The team found “Denisovan DNA” in some island Southeast Asians and concluded that their ancestors also interbred with the ancestors of Denisovans, probably in Asia.

But these genomes were too low quality to produce a reliable catalog of differences. Part of the problem was that ancient DNA is fragmentary, and most of it breaks down into single strands after it is extracted from bone.

Meyer’s breakthrough came in developing a method to start the sequencing process with single strands of DNA instead of double strands, as is usually done. By binding special molecules to the ends of a single strand, the ancient DNA was held in place while enzymes copied its sequence. The result was a sixfold to 22-fold increase in the amount of Denisovan DNA sequenced from a meager 10-milligram sample from the girl’s finger. The team was able to cover 99.9% of the mappable nucleotide positions in the genome at least once, and more than 92% of the sites at least 20 times, which is considered a benchmark for identifying sites reliably. About half of the 31 copies came from the girl’s mother and half from her father, producing a genome “of equivalent quality to a recent human genome,” says paleoanthropologist John Hawks of the University of Wisconsin, Madison, who was not part of the team.

Now, the view of the ancient genome is so clear that Meyer and his colleagues were able to detect for the first time that Denisovans, like modern humans, had 23 pairs of chromosomes, rather than 24 pairs, as in chimpanzees. By aligning the Denisovan genome with that of the reference human genome and counting mutations, the team calculated that the Denisovan and modern human populations finally split between 170,000 and 700,000 years ago.

The researchers also estimated ancient Denisovan population sizes by using methods to estimate the age of various gene lineages and the amount of difference between the chromosomes the girl inherited from her mother and father. They found that Denisovan genetic diversity, already low, shrank even more 400,000 years ago, reflecting small populations at that time. By contrast, our ancestors’ population apparently doubled before their exodus from Africa.
The team also counted the differences between Denisovans and chimps, and found that they have fewer differences than do modern people and chimps. The girl’s lineage had less time to accumulate mutations, and the “missing evolution” suggests she died about 80,000 years ago, although the date is tentative, says co-author David Reich, a population geneticist at Harvard University. If this date—the first proof that a fossil can be directly dated from its genome—holds up, it is considerably older than the very rough dates of 30,000 to more than 50,000 years for the layer of sediment where the fossils of Denisovans, Neandertals, and modern humans all were found.

The team says the new genome confirms their previous findings, showing that about 3% of the genomes of living people in Papua New Guinea come from Denisovans, while the Han and Dai on mainland China have only a trace of Denisovan DNA. Furthermore, the team determined that Papuans have more Denisovan DNA on their autosomes, inherited equally often from both parents, than on their X chromosomes, inherited twice as often from the mother. This curious pattern suggests several possible scenarios, including that male Denisovans interbred with female modern humans, or that these unions were genetically incompatible, with natural selection weeding out some of the X chromosomes, Reich says.

The new genome also suggests one odd result. By using the detailed Denisovan genome to sharpen the view of their close cousins the Neandertals, the team concludes that living East Asians have more Neandertal DNA than Europeans have. But most Neandertal fossils are from Europe; paleoanthropologist Richard Klein of Stanford University in Palo Alto, California, calls the result “peculiar.”

Most exciting to Pääbo is the “nearly complete catalog” of differences in genes between the groups. This includes 111,812 single nucleotides that changed in modern humans in the past 100,000 years or so. Of those, eight were in genes associated with the wiring of the nervous system, including those involved in the growth of axons and dendrites and a gene implicated in autism. Pääbo is intrigued in particular by a change in a gene that is regulated by the so-called FOXP2 gene, implicated in speech disorders. It is “tempting to speculate that crucial aspects of synaptic transmission may have changed in modern humans,” the team wrote. Thirty-four genes are associated with disease in humans. The list suggests some obvious candidates for gene-expression studies. “The cool thing is that it isn’t an astronomically large list,” Pääbo says. “Our group and others will probably be able to analyze most of them in the next decade or two.”

Back in Leipzig, the mood is upbeat, as researchers pull fossil samples off the shelf to test anew with “Matthias’s method.” First on Pääbo’s list: Neandertal bone samples, to try to produce a Neandertal genome to rival that of the little Denisovan girl.

This story provided by ScienceNow, the daily online news service of the journal Science.

More Complexity, Please: Health -- Not Just Genes -- Epigenetics

From yee Wiki:

 In biology, and specifically genetics, epigenetics is the study of heritable changes in gene expression or cellular phenotype caused by mechanisms other than changes in the underlying DNA sequence – hence the name epi- (Greek: επί- over, above, outer) - genetics. It refers to functionally relevant modifications to the genome that do not involve a change in the nucleotide sequence. Examples of such changes are DNA methylation and histone modification, both of which serve to regulate gene expression without altering the underlying DNA sequence.

Conclusive evidence supporting epigenetics show that these mechanisms can enable the effects of parents' experiences to be passed down to subsequent generations.

These changes may remain through cell divisions for the remainder of the cell's life and may also last for multiple generations. However, there is no change in the underlying DNA sequence of the organism; instead, non-genetic factors cause the organism's genes to behave (or "express themselves") differently.

One example of epigenetic changes in eukaryotic biology is the process of cellular differentiation. During morphogenesis, totipotent stem cells become the various pluripotent cell lines of the embryo, which in turn become fully differentiated cells. In other words, a single fertilized egg cell – the zygote – changes into the many cell types including neurons, muscle cells, epithelium, endothelium of blood vessels, etc. as it continues to divide. It does so by activating some genes while inhibiting others.

In 2011, it was demonstrated that the methylation of mRNA has a critical role in human energy homeostasis. Obesity associated FTO gene is shown to be able to demethylate N6-methyladenosine in RNA. This opened the related field of RNA epigenetics.

For more on Wiki:


http://en.wikipedia.org/wiki/Epigenetics

Computing With Soup

From the Economist:

Technology Quarterly: Q1 2012

Molecular computing: DNA is sometimes called the software of life. Now it is being used to build computers that can run inside cells

Ever since the advent of the integrated circuit in the 1960s, computing has been synonymous with chips of solid silicon. But some researchers have been taking an alternative approach: building liquid computers using DNA and its cousin RNA, the naturally occurring nucleic-acid molecules that encode genetic information inside cells. Rather than encoding ones and zeroes into high and low voltages that switch transistors on and off, the idea is to use high and low concentrations of these molecules to propagate signals through a kind of computational soup.

 

Computing with nucleic acids is much slower than using transistors. Unlike silicon chips, however, DNA-based computers could be made small enough to operate inside cells and control their activity. “If you can programme events at a molecular level in cells, you can cure or kill cells which are sick or in trouble and leave the other ones intact. You cannot do this with electronics,” says Luca Cardelli of Microsoft's research centre in Cambridge, England, where the software giant is developing tools for designing molecular circuits.

At the heart of such circuits is Watson-Crick base pairing, the chemical Velcro that binds together the two strands of DNA's double helix. The four chemical “bases” (the letters of the genetic alphabet) that form the rungs of the helix stick together in complementary pairs: A (adenine) with T (thymine), and C (cytosine) with G (guanine). By making single strands of DNA or RNA with specific A, T, C and G sequences, researchers can precisely define and predict which part of a strand will bind to another. These synthesised strands typically consist of fewer than 100 bases (a gene, by contrast, has thousands of bases).

Leonard Adleman, an American computer scientist, first demonstrated the use of nucleic-acid strand interactions for computing in 1994. He solved a version of the travelling-salesman problem—given a network of linked cities, what is the shortest route that visits each city exactly once?—in a test tube using specially sequenced DNA molecules and standard molecular-biology procedures (see box). Solving such a specific task is a far cry from building a general-purpose computer. But it showed that information could indeed be processed using interactions between strands of synthetic DNA.

Dr Adleman's work prompted other researchers to develop DNA-based logic circuits, the fundamental building blocks of computing, using a variety of approaches. The resulting circuits can perform simple mathematical and logical operations, recognise patterns based on incomplete data and play simple games. Molecular circuits can even detect and respond to a disease signature inside a living cell, opening up the possibility of medical treatments based on man-made molecular software.

Liquid logic

Erik Winfree's group at the California Institute of Technology (Caltech) is one of the best-known in this emerging field. In recent years it has made many nucleic acid-based digital logic circuits in test tubes, linking up logic gates capable of simple operations (such as AND, OR and NOT) using a trick called strand displacement, pioneered by three Caltech researchers, Georg Seelig, David Soloveichik and Dave Zhang.
In a strand-displacement logic circuit, inputs take the form of free-floating single DNA or RNA strands, and logic gates are complexes of two or more such strands, one of which is the potential output signal. “Sticky” tabs on the gates allow passing signals to latch on. If an input signal has a base-pair sequence complementary to the sequence on a gate, it binds to it, displacing the output strand and causing it to detach. The free-floating output strand can then, in turn, trigger another logic gate, causing a signal to travel through the circuit in a cascade. Billions of copies of the input, gate and output molecules are intermixed in a molecular soup. Programming such a system involves choosing specific base sequences to make up the different gates and the signal paths that connect them.

 

In a paper published last year in the journal Science, Dr Winfree and his colleague Lulu Qian described the use of strand-displacement cascades to build circuits of increasing complexity, culminating in a circuit made of 74 different DNA strands (pictured) that was capable of calculating the square roots of four-digit binary numbers. Together with their colleague Jehoshua Bruck, they then built a tiny neural network, made up of four interconnected artificial neurons, using a soup of 112 different interacting DNA strands. Each neuron was designed to fire when the sum of its input signals exceeded a certain threshold, and could be configured to assign different weights to different inputs. Such neural networks can recognise simple patterns, even when presented with incomplete data.

To test their neural network's pattern-recognition powers, Dr Qian made up a game to identify one out of four scientists. Each scientist was represented by a different set of answers to four yes-or-no questions. A human player would add to the test tube some (but not all) of the DNA strands corresponding to one set of answers. The circuit then guessed which scientist was the closest match, showing its answer using different-coloured fluorescent signals. The circuit took eight hours to give its answer, but got it right every time. And this circuit should work in a volume of a cubic micron (one-millionth of a metre), says Dr Winfree, which is small enough to fit into many sorts of cell.

DNA-based computers could be made small enough to operate inside cells and control their activity.

Milan Stojanovic at Columbia University is building circuits using a different form of strand displacement based on catalytic DNA strands, also known as deoxyribozymes or DNAzymes. These are synthetic single-stranded DNA sequences that are, among other things, capable of cutting nearby DNA strands in specific places.

Dr Stojanovic makes a DNAzyme into a logic gate by attaching a loop of DNA at one end that prevents the DNAzyme from working. When one or more input strands bind to complementary sequences on the loop, the loop breaks, activating the DNAzyme and switching the gate on. It can then interact with other strands, chopping them to trigger other gates or activate fluorescent tags that display the circuit's final output. Dr Stojanovic and his colleague Joanna Macdonald have used this approach to build simple DNA-based circuits capable of playing tic-tac-toe (though they take about half an hour to make each move).

Yannick Rondelez, a researcher in molecular programming at the University of Tokyo, is creating circuits in test tubes in a way that more closely resembles the operation of natural cells. He is using enzymes such as polymerases, nucleases and exonucleases that can also copy, cut and destroy nucleic-acid strands. In cells, enzymes are the basis of the natural circuits that switch genes on and off, maintain biological rhythms and produce molecular answers in response to environmental stimuli. Dr Rondelez has used his enzyme-based approach to build a molecular oscillator, which should be a useful addition to the molecular-computing toolbox.

A group at the Swiss Federal Institute of Technology (ETH Zurich) led by Yaakov Benenson, in collaboration with Ron Weiss of the Massachusetts Institute of Technology, is also creating circuits using enzymes. But unlike Dr Rondelez's circuits, which work in test tubes, these operate inside cells, piggybacking on the existing cellular machinery found within them. Last year Dr Benenson's team developed one of the most complex cell-based molecular circuits created so far, though it is still much simpler than systems built in test tubes. It is capable of recognising the signature of cervical cancer and destroying the host cell when it is found.

The circuit works by looking out for short strands called microRNAs, which regulate some processes within cells. They do this by interfering with the activity of the messenger RNA strands that transfer genetic information from the cell's nucleus to its protein-making machinery. Dr Benenson and his team chose five microRNAs associated with cervical cancer and designed a “classifier” circuit able to detect them. Only if all five are found at the right levels does the circuit activate, producing a protein that causes the cell to destroy itself.

Computer-aided DNA

Rather than injecting the necessary components, the researchers tricked the cell into producing them itself by adding instructions for them, in the form of synthetic genes, to the genetic instructions in the cell's nucleus. “We build the template in the form of synthetic genes and the cell turns them into components,” says Dr Benenson. “So we are hijacking the pathway that already exists.” But this trick is currently possible only for simple circuits.

With molecular circuits becoming steadily more complex, new software tools are being developed to design, model and debug them. Microsoft's researchers in Cambridge are working with experimentalists at Caltech, the University of Washington and the University of Oxford on a programming language and simulator for strand-displacement circuits, called the DNA Strand Displacement (DSD) tool. Users specify a description of a DNA-based circuit, including how individual DNA strands are joined together, and the software then simulates its behaviour, explains Andrew Phillips, the head of Microsoft's biological-computation group.

Dr Phillips's group is also developing tools to model the machinery within cells, including a language called Genetic Engineering of Cells (GEC). Work is under way with synthetic-biology researchers at the University of Cambridge to hook up these different biological modelling environments. “You could have a model of a DNA circuit written in DSD, which interfaces with a model of the cell machinery written in GEC,” he says. It would then be possible to simulate the operation of a DNA circuit that runs inside a cell and outputs drug molecules when certain conditions are met, for example.

Treatments based on molecular computers are still some way off. Today's most elaborate DNA circuits operate on work benches, not inside cells. But the border between computing and biology is vanishing fast, and the process of hijacking the information-processing potential of DNA to build logic circuits has only just begun.