Sparse Epistatic Patterns in the Evolution of Terpene Synthases

Area of Science:

• Biochemistry and Molecular Biology
• Enzyme kinetics and evolution
• Natural product biosynthesis

Background:

• Terpene synthases are crucial enzymes producing diverse cyclic hydrocarbons used in biological processes.
• Understanding enzyme evolution, particularly the emergence of cyclization, is key to deciphering complex biochemical pathways.
• The (E)-β-farnesene synthase from Artemisia annua serves as a model for studying the transition from linear to cyclic terpene production.

Purpose of the Study:

• To investigate the sequence determinants governing enzyme activity and specificity within the terpene synthase family.
• To elucidate the molecular mechanisms underlying the evolution of terpene cyclization.
• To develop and apply computational models for predicting enzyme kinetics and fitness landscapes.

Main Methods:

• Systematic mutagenesis of (E)-β-farnesene synthase to create synthetic enzyme libraries.
• Biochemical characterization of mutant enzymes to determine reaction rates.
• Application of the Michaelis-Menten model with amino acid contributions and couplings to predict enzyme kinetics.
• Development of biophysical fitness models to analyze evolutionary landscapes and epistasis.

Main Results:

• The Michaelis-Menten model accurately predicted measured reaction rates, revealing simple, interpretable free energy landscapes with minimal epistasis.
• Biophysical fitness models demonstrated that maximizing correct product output while minimizing byproducts leads to more complex, epistatic fitness landscapes.
• The study successfully characterized the evolutionary emergence of novel enzymatic functions through microevolutionary exploration of sequence space.

Conclusions:

• Enzyme activity and specificity are primarily dictated by sequence, with simple energetic landscapes facilitating evolutionary adaptation.
• The interplay between enzyme function, fitness, and evolutionary constraints shapes the emergence of novel catalytic activities.
• This framework provides a powerful approach for understanding enzyme evolution and engineering new biocatalysts.