A systematic comparison of error correction enzymes by next-generation sequencing.

Area of Science:

• Molecular Biology
• Synthetic Biology
• Genomics

Background:

• Gene synthesis is crucial for molecular and synthetic biology.
• Errors in oligonucleotide synthesis and assembly limit gene synthesis quality and cost.
• Current error assessment methods (cloning, Sanger sequencing) lack quantitative precision.

Purpose of the Study:

• To develop a next-generation sequencing (NGS) based method for quantifying errors in synthetic DNA.
• To systematically compare the efficacy of six different enzymatic error correction enzymes.
• To profile the specificities and performance of error correction enzymes under various conditions.

Main Methods:

• Developed an NGS pipeline for quantitative error analysis in gene assemblies.
• Analyzed errors in model gene assemblies.
• Systematically evaluated six error correction enzymes across 11 conditions.

Main Results:

• ErrASE and T7 Endonuclease I demonstrated the highest reduction in average error rates (up to 5.8-fold).
• MutS significantly increased the proportion of perfect gene assemblies (up to 25.2-fold).
• Quantified enzyme specificities: ErrASE corrects C/G transversions, T7 Endonuclease I corrects A/T transversions.

Conclusions:

• The developed NGS pipeline offers a fast, scalable, and extensible method for analyzing gene assembly errors.
• This approach enables effective profiling of error correction methods and benchmarking of DNA synthesis technologies.
• Identified specific enzymes for targeted error reduction and improvement of synthetic DNA quality.