(516b) Unveiling Metabolic Requirements for Gluconeogenesis through Kinetic Modeling and Optimization

Gluconeogenesis, the synthesis of glucose from various carbon sources, is a primary function of the liver and plays a critical role in maintaining the blood glucose level in human bodies. The gluconeogenic pathway shares most of the enzymes in glycolysis, with additional gluconeogenic enzymes which bypass the irreversible reactions in glycolysis. The largely overlapping glycolysis ad gluconeogenesis pathways run in forward or reverse direction through hormone regulation under different physiological conditions [1]. Dysregulation of gluconeogenesis is associated with several human diseases, such as non-alcoholic fatty liver disease and diabetes. Several attempts targeting metabolism have been made and shown early success in clinical trials [2]. Therefore, understanding the mechanism of gluconeogenesis can provide valuable insights for the treatment of such diseases.

Both stoichiometric and kinetic metabolic models are powerful tools to study metabolism [3, 4]. Kinetic models have the capability to capture the effect of enzyme expression and complex allosteric, signaling and hormonal regulation. However, the identification and estimation of kinetic parameters and enzyme activities pose challenges in constructing a kinetic model. Moreover, due to the strong nonlinearity of enzyme kinetics, kinetic metabolic models are computationally complex and have hence rarely been used for metabolic optimization, which can help redesign the metabolic network with respect to specific objectives.

In this work, we adapt a kinetic model of central metabolism and propose an optimization approach to study the metabolic requirements which enable the glycolytic pathway to become gluconeogenic. The adapted kinetic model considers different isozymes, hormonal regulation and the gluconeogenic enzymes. The optimization framework developed in our previous work was extended to identify the subset of enzymes whose expression level change enables glucose synthesis from several carbon sources [5], including lactate, amino acids, and glycerol. A two-stage algorithm is proposed to identify the smallest set of enzymes whose expression level change allow a given level of glucose production. Our results recapitulate the intricacy of gluconeogenesis. Aside from expressing gluconeogenic enzymes, changes in isozyme ratios and hormone regulation are required for gluconeogenesis. We also analyzed enzyme group effects on gluconeogenesis from different carbon sources, which provides nontrivial enzyme targets for future treatment of diseases related to dysregulated glucose metabolism.

References:

[1] Liangyou Rui. Energy metabolism in the liver. Comprehensive Physiology, 4(1):177–197, 2014.

[2] Bedair Dewidar, Sabine Kahl, Kalliopi Pafili, and Michael Roden. Metabolic liver disease in diabetes – From mechanisms to clinical trials. Metabolism: Clinical and Experimental, 111, 2020.

[3] Jeffrey D. Orth, Ines Thiele, and Bernhard O. Palsson. What is flux balance analysis? Nature Biotechnology, 28(3):245–248, 2010.

[4] Charles J. Foster, Lin Wang, Hoang V. Dinh, Patrick F. Suthers, and Costas D. Maranas. Building kinetic models for metabolic engineering. Current Opinion in Biotechnology, 67:35-41, 2021.

[5] Conor O’Brien, Andrew Allman, Prodromos Daoutidis, and Wei Shou Hu. Kinetic model optimization and its application to mitigating the Warburg effect through multiple enzyme alterations. Metabolic Engineering, 56:154–164, 2019.