Scientists Demonstrate Basics of Nucleic Acid Computing Inside Cells

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DETAILS: Using strands of nucleic acid, scientists have demonstrated basic computing operations inside a living mammalian cell. Shown examining a cellular “AND” gate are associate professor Philip Santangelo and research scientist Chiara Zurla. (Credit: Rob Felt, Georgia Tech)

Using strands of nucleic acid, scientists have demonstrated basic computing operations inside a living mammalian cell. The research could lead to an artificial sensing system that could control a cell’s behavior in response to such stimuli as the presence of toxins or the development of cancer.

The research uses DNA strand displacement, a technology that has been widely used outside of cells for the design of molecular circuits, motors and sensors. Researchers modified the process to provide both “AND” and “OR” logic gates able to operate inside the living cells and interact with native messenger RNA (mRNA).

The tools they developed could provide a foundation for bio-computers able to sense, analyze and modulate molecular information at the cellular level. Supported by the Defense Advanced Research Projects Agency (DARPA) and the National Science Foundation (NSF), the research was reported December 21 in the journal Nature Nanotechnology.

“The whole idea is to be able to take the logic that is used in computers and port that logic into cells themselves,” said .Philip Santangelo, an associate professor in the .Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech and Emory University. “These devices could sense an aberrant RNA, for instance, and then shut down cellular translation or induce cell death.”

Strand displacement reactions are the biological equivalent of the switches or gates that form the foundation for silicon-based computing. They can be programmed to turn on or off in response to an external stimuli such as a molecule. An “AND” gate, for example, would switch when both conditions were met, while an “OR” gate would switch when either condition was met.

In the switches the researchers used, a fluorophore reporter molecule and its complementary quenching molecule were placed side-by-side to create an “off” mode. Binding of RNA in one of the strands then displaced a portion of nucleic acid, separating the molecules and allowing generation of a signal that created an “on” mode. Two “on” modes on adjacent nucleic acid strands created an “AND” gate.

“Demonstrating individual logic gates is only a first step,” said Georg Seelig, assistant professor of computer science and engineering and electrical engineering at the University of Washington. “In the longer term, we want to expand this technology to create circuits with many inputs, such as those we have constructed in cell-free settings.”

The researchers used ligands designed to bind to specific portions of the nucleic acid strands, which can be created as desired and produced by commercial suppliers.

“We sensed molecules and showed that we could respond to them,” said Santangelo. “We showed that we could utilize native molecules in the cell as part of the circuit, though we haven’t been able to control a cell yet.”

Getting basic computing operations to function inside cells was no easy task, and the research required a number of years to accomplish. Among the challenges were getting the devices into the cells without triggering the switches, providing operation rapid enough to be useful, and not killing the human cell lines that researchers used in the lab.

“We had to chemically change the probes to get them to work inside the cell and to make them stable enough inside the cells,” said Santangelo. “We found that these strand displacement reactions can be slow within the cytosol, so to get them to work faster, we built scaffolding onto the messenger RNA that allowed us to amplify the effects.”

The nucleic acid computers ultimately operated as desired, and the next step is to use their switching to trigger the production of signaling chemicals that would prompt the desired reaction from the cells. Cellular activity is normally controlled by the production of proteins, so the nucleic acid switches will have to be given the ability to produce enough signaling molecules to induce a change.

“We need to generate enough of whatever final signal is needed to get the cell to react,” Santangelo explained. “There are amplification methods used in strand displacement technology, but none of them have been used so far in living cells.”

Even without that final step, the researchers feel they’ve built a foundation that can be used to attain the goal.

“We were able to design some of the basic logical constructs that could be used as building blocks for future work,” Santangelo said. “We know the concentrations of chemicals and the design requirements for individual components, so we can now start putting together a more complicated set of circuits and components.”

Cells, of course, already know how to sense toxic molecules and the development malignant tendencies, and to then take action. But those safeguards can be turned off by viruses or cancer cells that know how to circumvent natural cellular processes.

“Our mechanism would just give cells a hand at doing this,” Santangelo said. “The idea is to add to the existing machinery to give the cells enhanced capabilities.”

Applying an engineering approach to the biological world sets this example apart from other efforts to control cellular machinery.

“What makes DNA strand displacement circuits unique is that all components are fully rationally designed at the level of the DNA sequence,” said Seelig. “This really makes this technology ideal for an engineering approach. In contrast, many other approaches to controlling the cellular machinery rely on components that are borrowed from biology and are not fully understood.”

Beyond those already mentioned, the research team included Benjamin Groves, Yuan-Jyue Chen and Sergii Pochekailov from the University of Washington and Chiara Zurla and Jonathan Kirschman from Georgia Tech and Emory University.

This material is based on work supported by the Defense Advanced Research Projects Agency (DARPA) under contract W911NF-11-2-0068 and by National Science Foundation CAREER award 1253691. The content is solely the responsibility of the authors and does not necessarily represent the official views of DARPA or the NSF.

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Image shows activation of “AND” gates in cells as observed by fluorescence microscopy.
(Credit: Chiara Zurla, Georgia Tech)

CITATION: Benjamin Groves, et al., “Computing in mammalian cells with nucleic acid strand exchange,” (Nature Nanotechnology, 2015)..http://dx.doi.org/10.1038/nnano.2015.278

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ORIGINAL: .Geogia Tech
January 19, 2016

Can We Identify Every Kind of Cell in the Body?

A microscopic quest to find out what we’re really made of.

WHY IT MATTERS

There is still no accurate atlas of human cell types.

A microfluidic device (at center) can carry out experiments on individual cells.

How many types of cells are there in the human body? Textbooks say a couple of hundred. But the true number is undoubtedly far larger.

Aviv Regev. Regev received her M.Sc. from Tel Aviv University, studying biology, computer science, and mathematics in the Interdisciplinary Program for the Fostering of Excellence. She received her Ph.D. in computational biology from Tel Aviv University. Photo: Broad Institute

Piece by piece, a new, more detailed catalogue of cell types is emerging from labs like that of Aviv Regev at the Broad Institute, in Cambridge, Massachusetts, which are applying recent advances in single-cell genomics to study individual cells at a speed and scale previously unthinkable.

The technology applied at the Broad uses fluidic systems to separate cells on microscopic conveyor belts and then submits them to detailed genetic analysis, at the rate of thousands per day. Scientists expect such technologies to find use in medical applications where small differences between cells have big consequences, including cell-based drug screens, stem-cell research, cancer treatment, and basic studies of how tissues develop.

Regev says she has been working with the new methods to classify cells in mouse retinas and human brain tumors, and she is finding cell types never seen before. “We don’t really know what we’re made of,” she says.

Other labs are racing to produce their own surveys and improve the underlying technology. Today a team led by Stephen Quake of Stanford University published its own survey of 466 individual brain cells, calling it “a first step” toward a comprehensive cellular atlas of the human brain.

Such surveys have only recently become possible, scientists say. “A couple of years ago, the challenge was to get any useful data from single cells,” says Sten Linnarsson, a single-cell biologist at the Karolinska Institute in Stockholm, Sweden. In March, Linnarsson’s group used the new techniques to map several thousand cells from a mouse’s brain, identifying 47 kinds, including some subtypes never seen before.

Historically, the best way to study a single cell was to look at it through a microscope. In cancer hospitals, that’s how pathologists decide if cells are cancerous or not: they stain them with dyes, some first introduced in the early 1900s, and consider their location and appearance. Current methods distinguish about 300 different types, says Richard Conroy, a research official at the National Institutes of Health.

Individual cells are captured and separated in bubbles of liquid, readying them for analysis.

The new technology works instead by cataloguing messenger RNA molecules inside a cell. These messages are the genetic material the nucleus sends out to make proteins. Linnarsson’s method attaches a unique molecular bar code to every RNA molecule in each cell. The result is a gene expression profile, amounting to a fingerprint of a cell that reflects its molecular activity rather than what it looks like.

“Previously, cells were defined by one or two markers,” says Linnarsson. “Now we can say what is the full complement of genes expressed in those cells.”

Although researchers determined how to accurately sequence RNA from a single cell a few years ago, it’s only more recently that clever innovations in chemistry and microfluidics have led to an explosion of data. A California company, Cellular Research, showed this year that it could sort cells into micro-wells and then measure the RNA of 3,000 separate cells at once, at the cost of few pennies a cell.

Scientists think the new single-cell methods could overturn previous research findings. That is because previous gene expression studies were based on tissue samples or blood specimens containing thousands, even millions, of cells. Studying such blended mixtures meant researchers were seeing averages, says Eric Lander, head of the Broad Institute.

“Single-cell genomics has come of age in an unbelievable way in just the last 18 months,” Lander told an audience at the National Institutes of Health this year. “And once you realize we are at the point of doing individual cells, how could you ever put up with a fruit smoothie? It is just nuts to be doing genomics on smoothies.”

Lander, one of the leaders of the Human Genome Project, says it may be time to turn pilot projects like those Regev is leading into a wider effort to create a definitive atlas—one cataloguing all human cell types by gene activity and tracking them from the embryo all the way to adulthood.

“It’s a little premature to declare a national or international project until there’s been more piloting, but I think it’s an idea that’s very much in the air,” Lander said in a phone interview. “I think [in two years] we’re going to be in the position where it would be crazy not to have this information. If we had a periodic table of the cells, we would be able to figure out, so to speak, the atomic composition of any given sample.”

Gene profiles might eventually be combined with other efforts to study single cells. Paul Allen, Microsoft’s cofounder, said last December he would be spending $100 million to create a new scientific institute, the Allen Institute for Cell Science It will study stem cells and video their behavior under microscopes as they develop into various cell types, with the ultimate goal of creating a massive animated model. Rick Horwitz, who leads that effort, says that it will serve as a kind of Google Earth for exploring a cell’s life cycle.

The eventual payoff of collecting all this data, says Garry Nolan, an immunologist at Stanford University, won’t be just a catalogue of cell types, but a deeper understanding of how cells work together. “The single-cell approach is a way station that needs to be understood on the way to understanding the greater system,” he says. “In 50 years, we’ll probably be measuring every molecule in the cell dynamically.”

ORIGINAL: MIT Tech Review

By Courtney Humphries

May 18, 2015