Systems Biology and Metabolic Modeling

Abstract

This chapter deals with the subject of systems biology, specifically the kinetic modeling of metabolic pathways, as a tool for better understanding the control and regulation of a cellular system and for developing strategies to manipulate it. The concept of network stoichiometry is introduced as a component of all metabolic models; without any additional information, such models are referred to as structural. When, additionally, kinetic information is available for the pathway enzymes, this enables further analyses, i.e., time-course simulation, steady-state analysis, and metabolic control analysis. Strategies for model parameterization and software for modeling are discussed. The approach is illustrated with three models from the general plant physiology literature, before providing an historical overview of the kinetic modeling of sugarcane physiology. A steady-state sugarcane growth model is introduced where the culm is modeled in segments, each internode separately. This model is extended to a continuous growth model that explicitly includes phloem flow linking the internodes and is simulated within an advection-diffusion-reaction framework. Such models allow control points within the network to be identified and may pinpoint potential targets for biotechnological intervention. Future challenges include the integration of kinetic models on the different levels of the cellular and organizational hierarchy.

Diel oscillations in cell wall components and soluble sugars as a response to short-day in sugarcane (Saccharum sp.)

“…It has been shown sugar transporters play role on phloem loading of sucrose [53] and collaborate to control source-sink mechanism [47] in Arabidopsis [54] and sugarcane [49, 53]. The power of combined large-scale transcriptomics, protein measurements and kinetic modelling could collaborate to build more realistic models that addresses perturbations [55] in a diurnal fashion, such as different photoperiods. Little is known on the regulation of sugar transporters during stress because most of the studies are conducted at a physiological levels [47], therefore understanding that mechanism may led to higher yields in response to diverse environmental conditions.…”