A kinetic-based approach to understanding heterologous mevalonate pathway function in E. coli

Area of Science:

• Metabolic Engineering
• Systems Biology
• Computational Biology

Background:

• Engineered metabolic pathways require optimization for yield and productivity.
• Computational models are essential tools for predicting pathway flux changes based on experimental variables.

Purpose of the Study:

• Develop a kinetic model for a heterologous mevalonate pathway in E. coli.
• Identify key parameters limiting amorphadiene production through sensitivity analysis.
• Test model predictions experimentally to validate engineering strategies.

Main Methods:

• Ordinary differential equation (ODE) model development.
• Kinetic parameterization using literature data and Selective Reaction Monitoring Mass Spectrometry (SRM-MS) for enzyme concentrations.
• Global sensitivity analysis to identify rate-limiting steps.
• Experimental validation through strain construction and productivity measurements.

Main Results:

• Amorphadiene synthase activity identified as the primary limitation for amorphadiene production.
• Model predicted and experimental results confirmed pathway flux insensitivity to farnesyl pyrophosphate (FPP)-mediated inhibition of mevalonate kinase.
• Experimental validation closely matched model predictions, especially with in vivo-derived kinetic constants.

Conclusions:

• Kinetic modeling of engineered pathways, parameterized with experimental data, is a powerful approach for predicting productivity.
• This strategy effectively tests hypotheses and guides experimental efforts in metabolic engineering.
• The study highlights the utility of integrating computational and experimental approaches for optimizing biological systems.