A Physics-Inspired Approach to Improve Oligonucleotide Design and Gene Synthesis

Area of Science:

• Synthetic Biology
• Molecular Biology
• Bioinformatics

Background:

• Polymerase cycling assembly (PCA) is crucial for gene synthesis using overlapping oligonucleotides.
• Achieving optimal PCA yield requires uniform hybridization temperatures and minimal spurious dimer formation, which is challenging for certain DNA sequences.

Purpose of the Study:

• To develop a novel algorithm for designing overlapping oligonucleotides for PCA.
• To address limitations of heuristic methods in designing oligonucleotides for challenging sequences.

Main Methods:

• The algorithm models oligonucleotide design using a statistical physics approach.
• It employs a transfer-matrix formalism for exact solutions and incorporates simulated annealing for repair and optional codon redesign.
• The method generates thermodynamically consistent oligonucleotide sets.

Main Results:

• The algorithm successfully redesigned over 80% of previously unsuitable sequences for PCA.
• With codon redesign, the success rate increased to over 91%.
• Experimental validation confirmed the absence of dimer formation and successful gene assembly with clean results.

Conclusions:

• This new algorithm provides a robust solution for oligonucleotide design in PCA, especially for difficult sequences.
• It is a valuable tool for synthetic biology and automated gene assembly workflows.
• The method enhances the reliability and efficiency of gene synthesis.