A new research on synthetic biology from the Arizona State University has demonstrated how living cells can be induced to carry out computations in the manner of tiny robots or computers.

The results of the study, according to researchers, have significant implications for intelligent drug design and smart drug delivery, green energy production, low-cost diagnostic technologies and even the development of futuristic nanomachines capable of hunting down cancer cells or switching off aberrant genes.

The approach, described in the journal Nature, 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 the 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, according to the researchers.

Alex Green, an assistant professor at ASU’s Biodesign Institute, said the new study 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 a 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.

“We’re using very predictable and programmable RNA-RNA interactions to define what these circuits can do,” Green said. “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 possibility of using DNA and RNA, the molecules of life, to perform computer-like computations was first demonstrated in 1994 by Leonard Adleman of the University of Southern California. Since then, rapid progress has advanced the field considerably, and recently, such molecular computing has been accomplished within living cells.

The technique described in the new paper takes advantage of the fact that RNA, unlike DNA, is single-stranded when it is produced in cells. This allows researchers to design RNA circuits that can be activated when a complementary RNA strand binds with an exposed RNA sequence in the designed circuit. This binding of complementary strands is regular and predictable, with A nucleotides always pairing with U and C always pairing with G.

20170731_EDNA_ASU-RNA-nanodevice-01 (cr) Figure 1: In new research, Alex Green, an assistant professor at ASU’s Biodesign Institute and School of Molecular Sciences, demonstrates how living cells can be induced to carry out computations in the manner of tiny robots or computers. (Source: ASU)

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 into the same molecule, making the systems compact and easier to implement in a cell.

Green said 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.