One of the goals of bottom-up systems biology is to generate high-quality predictive models that enhance our understanding of cellular behaviour. For mathematical models of metabolism to accurately simulate experimental data, the conditions under which enzyme parameter values are obtained should closely resemble the actual in vivo environment. Traditionally, this alignment is often lacking, as many enzyme kinetic studies are conducted under optimal conditions for the enzyme, which may significantly differ from the enzyme’s native conditions. A frequently overlooked aspect of the intracellular environment is macromolecular crowding—the influence, through the excluded volume effect, of large quantities of different macromolecules occupying the cell.
To better understand how the complex heterogeneous environment of the cell influences enzyme kinetics, we exposed kinetic assays of various enzymes in the glycolytic pathway of Saccharomyces cerevisiae to inert synthetic polymers of different shapes and sizes at two concentrations, thus mimicking in vivo crowded conditions. Kinetic data were acquired from spectrophotometric assays with microtitre plates or from Nuclear Magnetic Resonance (NMR) spectroscopy time courses. Enzyme kinetic parameters were estimated by fitting initial rate kinetics and NMR time-course data to kinetic models based on rate equations for each enzyme.
The presence of synthetic polymers (Dextran70, Ficoll70, and PEG35) influenced the Vmax and KM-values for different enzymes to varying extents. In some cases, significant changes in kinetic parameters were observed in crowded solutions relative to baseline uncrowded solutions; for instance, high concentrations of crowding agents decreased the Vmax values of numerous enzymes. The changes in kinetic parameters depended on the size and shape of the crowding agent used. Current work focuses on determining the effect of these parameter changes on the kinetic behaviour of the entire pathway network, allowing us to assess the broader impact of macromolecular crowding on the network and its emergent properties under crowded versus dilute conditions.