Toward an evaluation of metabolite channeling in vivo
Graphical abstract
Introduction
Metabolic enzymes catalyzing sequential reactions of a metabolic pathway often form multi-enzyme complex, sometimes called a ‘metabolon’ [1], in which intermediate metabolites are directly passed from catalytic cores of the first to the second enzyme without diffusing into the bulk matrix. This inclusion of intermediate metabolites within a multi-enzyme complex or a multi-functional protein is metabolite channeling, also called substrate channeling or metabolic channeling. Various functions of metabolite channeling have been proposed (Figure 1). First, metabolite channeling increases intermediate concentration near the reaction centers of the second enzyme. This functions to enhance pathway reactions by 1) increasing reaction rates; 2) shortening transition time; and 3) overcoming thermodynamically infeasible equilibrium within a physiological metabolite concentration range (Figure 1a). Second, multi-enzyme complexes physically contain intermediates within the molecules and prevent the access by external molecules. This functions in 4) protecting unstable intermediates from degradation; 5) preventing cytotoxic reactions between intermediates and cellular components; 6) protecting reaction centers from inhibitors; 7) determining metabolic flux distribution through competing pathways by restricting the access of enzymes to the intermediates; and 8) limiting ionization of intermediates by excluding water molecules from the reaction (Figure 1b). The function in 9) shortening diffusion distance for intermediates to accelerate reactions (Figure 1c) is considered mostly unlikely due to much shorter time required for diffusion of small molecules than that for enzyme reactions [2,3]. Nevertheless, it may function in specific microenvironments, including highly condensed, limited water availability, or highly compartmented environments, which can significantly limit the diffusion of intermediates [4].
Metabolite channeling is considered as a central control mechanism of cellular metabolism. It also draws attention as a promising tool to enhance and regulate productions of desired molecules in chemical and biological engineering [5,6]. Especially in the last few years, various techniques have been developed to artificially organize multi-enzyme complexes in vitro and in vivo (reviewed in a recent book [7••]) and successfully applied to gain higher production of desired molecules [5,8]. Quantitative evaluation of the effects of metabolite channeling in metabolic flux modulation is desired to understand its functions and potentials. Whereas this is a technically very difficult task, recent advances in structural biology, computational modeling, and metabolic flux analysis bear potential for innovation in metabolite channeling studies. In this review, current approaches to demonstrate metabolite channeling are reviewed with the examples of recent studies. The strategies toward the quantitative understanding of metabolic and physiological functions of metabolite channeling will also be discussed.
Section snippets
Experimental approaches to demonstrate metabolite channeling
The experimental approaches to examine the occurrence of metabolite channeling are described as 1) enzyme kinetics analysis, 2) isotope dilution/ enrichment analysis, 3) enzyme competition assay, 4) inhibitor resistance assay, and 5) quantification of intermediate in the bulk phase (Figure 2) [9, 10, 11]. Since all the methodologies are indirect [9] and test only one function of channeling, combination of more than one proof is crucial. In addition, protein structure analyses often support
Capturing metabolite channeling using metabolic flux analysis
Metabolic flux analysis (MFA) analyzes isotope label (typically 13C) redistribution in metabolic network following feeding of isotopically labeled substrates. Since label redistribution is sensitive to channeling [26], MFA can be a tool to demonstrate metabolite channeling. Steady-state MFA is an approach to fit estimated metabolic fluxes in a metabolic network model to experimentally determined 13C re-distribution pattern of metabolites at an isotopic steady state. The effects of the
Metabolite channeling in flux balance analysis
Flux balance analysis (FBA) is another method to estimate metabolic flux distribution in a metabolic model in the constrained flux space defined by mass conservation and pre-specified reversibility of the reactions [33]. Thermodynamics of metabolic reactions is often used to add an additional layer of constraints in FBA [34]. However, channeling can overcome thermodynamic penalty and cause inconsistency between measured and estimated fluxes. For example, malate oxidation catalyzed by MDH in the
Toward a quantitative evaluation of metabolite channeling in vivo
One of the overarching goals of metabolite channeling study is an accurate evaluation of metabolic and physiological effects of metabolite channeling in vivo. Since measurement of metabolite contents and enzyme in subcellular compartments is technically difficult, application of in vitro kinetics results to living systems can have critical pitfalls. Assuming the transient nature of multi-enzyme complex mediating metabolite channeling [40], quantitative assessment of channeling effects is
Conclusions
Despite of remaining difficulties, combination of current analytical technologies will make the evaluation of metabolite channeling effects in metabolic network feasible. This will lead to more complete understanding of the mechanism of metabolic regulation, more precise evaluation of metabolic flux changes, and additional tools to design metabolic network for metabolic engineering. These will enable rational design of metabolite channeling and enhance its application in biotechnology.
Conflict of interest statement
Nothing declared.
References and recommended reading
Papers of particular interest, published within the period of review, have been highlighted as:
• of special interest
•• of outstanding interest
Acknowledgements
This work was supported by the National Science Foundation [grant number 1845451] and University of Nebraska-Lincoln Faculty Startup Grant.
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