Exploring metabolism flexibility in complex organisms through quantitative study of precursor sets for system outputs

From the biochemical pieces to the nutritional puzzle: using meta-reactions in teaching and research

We now live in an era where metabolic data are increasingly accessible and available. Analysis of this data can be done using novel techniques (e.g., machine learning and artificial intelligence) but this does not alleviate scientists to use "human intelligence". The objective of this paper is to combine the information of a large database of biochemical reactions with a method and tool to make nutritional biochemistry more accessible to nutritionists. A script was developed to extract information from a database with more than 16 000 biochemical reactions so that it can be used for "biochemical bookkeeping". A system of more than 300 meta-reactions (i.e., the outcome reaction of a series of connected individual reactions) was constructed covering a wide range of metabolic pathways for macro- and micronutrients. Meta-reactions were constructed by identifying metabolic nodes, which are inputs or outputs of a metabolic system or that serve as connection points between meta-reactions. Complete metabolic pathways can be constructed by combining and balancing the meta-reactions using a simple Excel tool. To illustrate the use of meta-reactions and the tool in the teaching of nutritional biochemistry, examples are given to illustrate how much ATP can be synthesized from glucose, either directly or indirectly (i.e., via storage and mobilization or via transfer of intermediate metabolites between tissues and generations). To illustrate how meta-reactions and the tool can be used in research, nutrient balance data of the mammary gland of a dairy cow were used to construct a plausible pathway of nutrient metabolism of the whole mammary gland. The balance data included 34 metabolites taken up or exported by the mammary gland and 39 meta-reactions were used to construct a metabolic pathway that accounted for the uptake and output of metabolites. The results highlighted the importance of the synthesis of proline from arginine and the concomitant synthesis of urea by the mammary gland. It also raised the question of whether the availability of metabolic pathways or glucose uptake would be the more limiting factor for the synthesis of NADPH required for fatty acid synthesis. The availability of an open database with biochemical reactions, the concept of meta-reactions, and the provision of a tool allow users to construct metabolic pathways, which helps acquiring a more comprehensive and integrated view of metabolism and may raise issues that may be difficult to identify otherwise.

A systemic approach to explore the flexibility of energy stores at the cellular scale: Examples from muscle cells

Variations in energy storage and expenditure are key elements for animals adaptation to rapidly changing environments. Because of the multiplicity of metabolic pathways, metabolic crossroads and interactions between anabolic and catabolic processes within and between different cells, the flexibility of energy stores in animal cells is difficult to describe by simple verbal, textual or graphic terms. We propose a mathematical model to study the influence of internal and external challenges on the dynamic behavior of energy stores and its consequence on cell energy status. The role of the flexibility of energy stores on the energy equilibrium at the cellular level is illustrated through three case studies: variation in eating frequency (i.e., glucose input), level of physical activity (i.e., ATP requirement), and changes in cell characteristics (i.e., maximum capacity of glycogen storage). Sensitivity analysis has been performed to highlight the most relevant parameters of the model; model simulations have then been performed to illustrate how variation in these key parameters affects cellular energy balance. According to this analysis, glycogen maximum accumulation capacity and homeostatic energy demand are among the most important parameters regulating muscle cell metabolism to ensure its energy equilibrium.