UMI-linked consensus sequencing enables phylogenetic analysis of directed evolution.

Area of Science:

• Protein engineering and molecular evolution.
• Biocatalysis and enzyme engineering.
• Genomics and sequencing technologies.

Background:

• Protein evolution success depends on mutation context, influenced by intra-gene epistasis (non-additive amino acid interactions).
• Limited understanding of epistasis impedes prediction of mutation effects and adaptive potential.
• Accurate mapping of evolutionary trajectories requires robust sequencing of full gene variants.

Purpose of the Study:

• To present a novel workflow, UMIC-seq, for simplified mapping of protein evolutionary trajectories.
• To enable accurate consensus generation of closely related gene variants using nanopore sequencing.
• To identify lineages, founding variants, and epistasis in directed evolution experiments.

Main Methods:

• Development of a unique molecular identifier (UMI)-linked consensus sequencing workflow (UMIC-seq).
• Application of UMIC-seq to nanopore sequencing for accurate full-length gene variant analysis.
• Reconstruction of an artificial phylogeny from three rounds of directed evolution of an amine dehydrogenase biocatalyst using ultrahigh throughput droplet screening.

Main Results:

• UMIC-seq successfully mapped evolutionary trajectories of an amine dehydrogenase biocatalyst.
• The workflow identified distinct lineages and their founding variants.
• Non-additive interactions (sign epistasis) between mutations within the full gene were identified.

Conclusions:

• UMIC-seq provides a straightforward method for mapping evolutionary trajectories using full-length sequences.
• Accurate long-read sequencing facilitates the prediction of beneficial mutations and adaptive potential.
• This approach enhances in silico analysis of large sequence datasets for protein engineering.