Biocomputation using tristate buffers

Access through your institution Buy or subscribe Boolean logic gates are often considered the basic elements to construct more complex computational systems. When applying this approach to

biocomputation in mammalian cells, a number of biological challenges, limit the level of achievable complexities when building multilayered networks. “We were always keeping an eye on the

capability to overcome this long-lasting hurdle of expanding the computational capacity of mammalian cells,” says Mingqi Xie at Westlake University. Xie and colleagues Jiawei Shao, Lingyun

Zhu, Hui Wang and others have developed a new strategy of biocomputation using tristate buffers. A tristate buffer in electronics uses an upstream switch to control a downstream switch, with

the downstream input determining the circuit output only when it is in the state in which it is plugged by the upstream switch. Following a similar idea, in mammalian cells, the researchers

used two small molecules acting as the external input signals that control a gene circuit that consists of an upstream transcription-based switch and a downstream translation-based gene

switch mediated by synthetic translation initiation factors. Connecting and expanding such core elements, gene networks that facilitate various multichannel input–output calculations can be

constructed by a modular engineering rationale. This so called TriLoS (tristate-based logic synthesis) framework takes advantage of the similarity between its hierarchical structure and what

is often observed in biological regulatory networks. It also benefits from the fact that, while tristate buffers in electronics typically have three types of output signal (0, 1 and

unplugged Z), biological systems need only distinguish two output states (ON and OFF), notes Xie. “In fact, this approximation was probably a key factor for robust, resource-efficient and

interference-free biocomputation.” This is a preview of subscription content, access via your institution ACCESS OPTIONS Access through your institution Access Nature and 54 other Nature

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AFFILIATIONS * Nature Methods http://www.nature.com/nmeth Lin Tang Authors * Lin Tang View author publications You can also search for this author inPubMed Google Scholar CORRESPONDING

AUTHOR Correspondence to Lin Tang. RIGHTS AND PERMISSIONS Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Tang, L. Biocomputation using tristate buffers. _Nat Methods_ 21, 1580

(2024). https://doi.org/10.1038/s41592-024-02423-2 Download citation * Published: 10 September 2024 * Issue Date: September 2024 * DOI: https://doi.org/10.1038/s41592-024-02423-2 SHARE THIS

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