Programmable Computational RNA Droplets Assembled via Kissing-Loop Interaction.

Area of Science:

• Biomolecular Engineering
• Synthetic Biology
• Nanotechnology

Background:

• DNA droplets, programmable liquid-like condensates, offer insights into biological phase separation.
• RNA-based counterparts are less explored despite diverse structures and functions.
• Developing RNA-based systems for logic operations and sensing is a key challenge.

Purpose of the Study:

• To design and demonstrate computational RNA droplets capable of two-input AND logic operations.
• To create a system with a macroscopic, naked-eye-distinguishable readout for molecular sensing.
• To explore the potential of RNA droplets in programmable biomolecular devices and artificial cells.

Main Methods:

• Utilized multibranched RNA nanostructures with kissing-loop (KL) interactions for self-assembly.
• Programmed nanostructures to disassemble into chain-like structures upon detection of target microRNAs.
• Optimized KL sequences using viral sequences through numerical and experimental studies.
• Observed phase-state changes from liquid to dispersed states as a readout.

Main Results:

• Successfully designed computational RNA droplets performing two-input AND logic.
• Demonstrated selective phase-state change (liquid to dispersed) upon detection of specific microRNAs.
• Showcased a macroscopic, naked-eye-distinguishable readout for molecular sensing.
• Validated the programmability of condensate phase behavior using multistranded motifs.

Conclusions:

• Multistranded RNA motifs offer a flexible approach for bottom-up programming of condensate phase behavior.
• Computational RNA droplets provide a robust platform for in situ programmable assembly of biomolecular devices.
• This technology has potential applications in creating artificial cells and advanced biosensors.