Behold the mutant ninja living cells!

"We're using very predictable and programmable RNA-RNA interactions to define what these circuits can do," says Green. "That means we can use computer software to design RNA sequences that behave the way we want them to in a cell. It makes the design process a lot faster." The study appears in the advance online edition of the journal Nature.

The approach described uses circuits composed of ribonucleic acid or RNA. These circuit designs, which resemble conventional electronic circuits, self-assemble in bacterial cells, allowing them to sense incoming messages and respond to them by producing a particular computational output, (in this case, a protein).

In the new study, specialised circuits known as logic gates were designed in the lab, then incorporated into living cells. The tiny circuit switches are tripped when messages (in the form of RNA fragments) attach themselves to their complementary RNA sequences in the cellular circuit, activating the logic gate and producing a desired output.

The RNA switches can be combined in various ways to produce more complex logic gates capable of evaluating and responding to multiple inputs, just as a simple computer may take several variables and perform sequential operations like addition and subtraction in order to reach a final result.

The new study dramatically improves the ease with which cellular computing may be carried out. The RNA-only approach to producing cellular nanodevices is a significant advance, as earlier efforts required the use of complex intermediaries, like proteins.

Now, the necessary ribocomputing parts can be readily designed on computer. The simple base-pairing properties of RNA's four nucleotide letters (A, C, G and U) ensure the predictable self-assembly and functioning of these parts within a living cell.

Green's work in this area began at the Wyss Institute at Harvard, where he helped develop the central component used in the cellular circuits, known as an RNA toehold switch. The work was carried out while Green was a post-doc working with nanotechnology expert Peng Yin, along with the synthetic biologists James Collins and Pamela Silver, who are all co-authors on the new paper. "The first experiments were in 2012," Green says. "Basically, the toehold switches performed so well that we wanted to find a way to best exploit them for cellular applications."

After arriving at ASU, Green's first grad student Duo Ma worked on experiments at the Biodesign Institute, while another postdoc, Jongmin Kim continued similar work at the Wyss Institute. Both are also co-authors of the new study.

In the new study, logic gates known as AND, OR and NOT were designed. An AND gate produces an output in the cell only when two RNA messages A AND B are present. An OR gate responds to either A OR B, while a NOT gate will block output if a given RNA input is present. Combining these gates can produce complex logic capable of responding to multiple inputs.

Using RNA toehold switches, the researchers produced the first ribocomputing devices capable of four-input AND, six-input OR and a 12-input device able to carry out a complex combination of AND, OR and NOT logic known as disjunctive normal form expression.

When the logic gate encounters the correct RNA binding sequences leading to activation, a toehold switch opens and the process of translation to protein takes place. All of these circuit-sensing and output functions can be integrated in the same molecule, making the systems compact and easier to implement in a cell.

The research represents the next phase of ongoing work using the highly versatile RNA toehold switches. In earlier work, Green and his colleagues demonstrated that an inexpensive, paper-based array of RNA toehold switches could act as a highly accurate platform for diagnosing the Zika virus. Detection of viral RNA by the array activated the toehold switches, triggering production of a protein, which registered as a color change on the array.

The basic principle of using RNA-based devices to regulate protein production can be applied to virtually any RNA input, ushering in a new generation of accurate, low-cost diagnostics for a broad range of diseases. The cell-free approach is particularly well suited for emerging threats and during disease outbreaks in the developing world, where medical resources and personnel may be limited.

According to Green, the next stage of research will focus on the use of the RNA toehold technology to produce so-called neural networks within living cells -- circuits capable of analysing a range of excitatory and inhibitory inputs, averaging them and producing an output once a particular threshold of activity is reached, much the way a neuron averages incoming signals from other neurons. Ultimately, researchers hope to induce cells to communicate with one another via programmable molecular signals, forming a truly interactive, brain-like network.