The human body contains about 37 trillion cells, which run like a sophisticated and efficient microcomputer that automatically receives, transduces and processes information from the body all the time.

How to make powerful cells follow instructions from humans and perform complex information processing and computing functions in response to various biomedical scenarios is a hot topic in the field of modern synthetic biology, and it is also the research interest of WANG Hui at the Research Center for Life Sciences Computing of Zhejiang Lab (ZJ Lab).

On July 31, 2024 (Beijing Time), a joint research team composed of WANG Hui, the co-corresponding author of the paper, and other fellows from Zhejiang University, National University of Defense Technology, and Westlake University, published their research result entitled Multi-layered Computational Gene Networks by Engineered Tristate Logics in Cell. The joint research team proposed the TriLoS design principle for the first time. They designed "tri-state gates" to replace traditional "logic gates" as basic computing elements in a multi-layered gene regulatory network (GRN), and engineered single human cells to produce a complex logic computing network and code these cells, so as to facilitate customized and precision therapies.

Paper Link: https://www.cell.com/cell/fulltext/S0092-8674(24)00716-5

WANG Hui, a Research Expert at ZJ Lab's Research Center for Life Sciences Computing

"A cell can be understood as a digital circuit composed of combinatorial and sequential logic, and designing and modifying this circuit is based on a 'transistor' tailored to this cell." WANG Hui said that at the beginning of this century, experts in synthetic biology made a bold attempt to mimic "0/1" Boolean logic in electronic engineering with artificial gene circuits, enabling biological computing. However, complexities of gene regulation in mammalian cells, as well as a shortage of gene building blocks and theoretical guidance systems, result in a long cycle, high costs and slow progress in terms of GRN R&D.

After joining ZJ Lab, and with the help of the Lab's powerful intelligent computing platform, WANG Hui has explored and optimized underlying designs for cell-based computing to increase efficiency in experimentation, and successfully solved bottlenecks in research on full adder and full subtracter in mammalian single cells by abstracting intracellular hierarchical cascade regulatory circuits into a "tri-state gate" architecture. That is, with a "tri-state gate" as the basic logic element, cells are "reprogrammed" through engineering approaches such as modularization, Boolean algebra operation, and logic simplification (with Karnaugh maps) to realize specific functions.

"Specifically, intracellular hierarchical cascade regulatory circuits are abstracted into a 'tri-state gate' architecture. For example, transcriptional control (Input B) serves as an upstream control pathway for translational control (Input A), and the translation system generates the final output of 0, 1, or Z (means a high-impedance state for the translation pathway if genes are not transcribed) as transcription regulators switch genes on or off," WANG Hui explained. "By modularizing different 'tri-state gates' and connecting them in parallel or in series using Boolean expressions, more complex gene regulatory networks can be engineered."

With "tri-state gates", more intelligent cell design schemes can be derived theoretically, and the treatment of complex diseases can be simplified into mathematical formulas. For example, a cell-based computing system for diabetes was built on the "tri-state gate" theory. It can respond to three types of input by diabetes type, and regulate outputs from GLP-1 or insulin to realize phased, automated precision therapies for the treatment of diabetes.

Supported by intelligent computing, the potential of synthetic biological gene circuits goes far beyond that. "If the pathogenesis of a disease is mimicked with gene circuits, high-throughput screening can be performed using intelligent cells, and this technique can accelerate drug discovery when combined with virtual drug screening tools like AI."

WANG Hui believes that synthetic biology techniques driven by AI + large-scale computing can close the loop of "design, construction and testing" of artificial gene circuits in a high-throughput, low-cost and multi-cycle way. "On the one hand, AI-based simulation and emulation can deepen our understanding of how an organism works. On the other hand, synthetic biology techniques can inspire and validate computing models, and the two together can address more complex life science problems."

Creating new functions for cells is an expedition to the unknown world. After graduation from Tsinghua University, WANG Hui went to ETH Zurich and studied under Academician Martin Fussenegger well known for mammalian synthetic biology. She has also published several papers in top journals such as Cell, Science, and Nature series. It is fair to say that she has worked hard and learned a lot all the way in the field of synthetic biology. "In the future, I remain focused on computing and biology integrated innovation, and study and design a variety of gene regulatory circuits, hoping to have my research results applied to precision therapy and drug screening," said WANG Hui.