Sequence-controlled RNA self-processing: computational design, biochemical analysis, and visualization by AFM.

Area of Science:

• Molecular Biology
• Biochemistry
• Synthetic Biology

Background:

• Reversible chemistry is crucial for biological self-organization and the evolution of RNA.
• Ribozymes capable of both cleaving and forming phosphodiester bonds may have driven early RNA complexity.

Purpose of the Study:

• To computationally optimize a hairpin ribozyme variant for efficient circularization and concatemer formation.
• To investigate the behavior of engineered RNA sequences using biochemical and physical analyses.

Main Methods:

• Computational optimization using the Vienna RNA package.
• In vitro selection and characterization of engineered ribozymes.
• Two-dimensional polyacrylamide gel electrophoresis (PAGE) for activity and product analysis.
• Atomic Force Microscopy (AFM) imaging for structural analysis and distribution calculations.

Main Results:

• Four optimized hairpin ribozyme variants were selected and confirmed to be catalytically active.
• High yields of cyclic RNA species were obtained from the engineered ribozymes.
• AFM imaging revealed the formation of trimers, a significant advancement over the original system.

Conclusions:

• Computational design and experimental validation provide a powerful approach for predicting and controlling ribozyme function.
• Engineered ribozymes can efficiently produce cyclic RNA and concatemers, with potential applications in synthetic biology.
• This study demonstrates a promising strategy for designing ribozymes with specific, predefined functions.