On Apr. 22, 2026, the Korea Advanced Institute of Science and Technology (KAIST) announced that a research team led by Professor Yeongjae Choi from the Graduate School of Engineering Biology has developed a DNA-based bio-transistor, demonstrating a molecular circuit capable of performing both computation and information storage. The study was published in the international journal Science Advances on the 1st.

As semiconductor technology approaches the 2-nanometer scale, further miniaturization of silicon-based devices has become increasingly challenging. This has driven growing interest in alternative approaches that process information at the molecular level.

DNA presents a promising platform for such systems. Due to its ability to selectively pair with complementary bases, DNA can be precisely programmed to execute specific reactions. Moreover, with a base-pair spacing of only 0.34 nanometers, DNA enables information processing at a scale significantly smaller than conventional semiconductor devices.

However, conventional DNA circuits have been limited by their single-use nature. Once a DNA molecule undergoes a reaction, it is consumed, preventing continuous information processing or memory retention. As a result, previous DNA-based systems have been restricted to simple, one-time detection functions.

To overcome this limitation, the research team engineered DNA molecules that can reversibly assemble and disassemble in response to incoming signals, allowing their structural configurations to change and persist. These structural changes effectively encode information, enabling the system to store past inputs and use them as the basis for subsequent computations.

This approach mimics the function of a semiconductor transistor: just as electronic transistors process electrical signals, the DNA-based system processes chemical signals while simultaneously storing computational results—effectively functioning as a bio-transistor.

This breakthrough demonstrates the potential of DNA as a fundamental building block for intelligent molecular systems capable of both computation and memory. The technology could be further developed into molecular-scale diagnostic devices that detect disease signals and make autonomous decisions within biological environments.