Implementing complex nucleic acid circuits in living cells.

Area of Science:

• Synthetic biology
• Molecular computing
• Biotechnology

Background:

• Synthetic nucleic acid computing shows promise in vitro but faces challenges in cellular environments due to instability and interference.
• Existing methods struggle with reliable and programmable execution of complex computations within living cells.

Purpose of the Study:

• To introduce a novel allosteric strand exchange (ASE) strategy for robust and programmable intracellular computing.
• To engineer scalable genetic circuits for detecting specific molecular inputs and controlling cellular functions.

Main Methods:

• Developed an allosteric strand exchange (ASE) mechanism leveraging conformational cooperativity for strand exchange regulation.
• Engineered a modular circuit architecture capable of AND/OR logic operations, scaling to eight inputs.
• Demonstrated messenger RNA detection in mammalian cells using ASE-based AND logic circuits.

Main Results:

• Successfully implemented scalable intracellular circuits with flexible programmability using the ASE strategy.
• Achieved high specificity in detecting messenger RNAs in mammalian cells via AND logic computation.
• Demonstrated a multi-input molecular classifier for monitoring cell reprogramming events and programmable control of CRISPR-Cas9 for gene editing.

Conclusions:

• The ASE strategy provides a powerful and modular platform for intracellular computing, overcoming previous limitations.
• ASE-based circuits enable sophisticated information processing and programmable control of cellular functions, including gene editing.
• This approach holds significant potential for advancing intracellular biocomputation and synthetic biology applications.