Bistability in fatty-acid oxidation resulting from substrate inhibition

In this study we demonstrated through analytic considerations and numerical studies that the mitochondrial fatty-acid β-oxidation can exhibit bistable-hysteresis behavior. In an experimentally validated computational model we identified a specific region in the parameter space in which two distinct stable and one unstable steady state could be attained with different fluxes. The two stable states were referred to as low-flux (disease) and high-flux (healthy) state. By a modular kinetic approach we traced the origin and causes of the bistability back to the distributive kinetics and the conservation of CoA, in particular in the last rounds of the β-oxidation. We then extended the model to investigate various interventions that may confer health benefits by activating the pathway, including (i) activation of the last enzyme MCKAT via its endogenous regulator p46-SHC protein, (ii) addition of a thioesterase (an acyl-CoA hydrolysing enzyme) as a safety valve, and (iii) concomitant activation of a number of upstream and downstream enzymes by short-chain fatty-acids (SCFA), metabolites that are produced from nutritional fibers in the gut. A high concentration of SCFAs, thioesterase activity, and inhibition of the p46Shc protein led to a disappearance of the bistability, leaving only the high-flux state. A better understanding of the switch behavior of the mitochondrial fatty-acid oxidation process between a low- and a high-flux state may lead to dietary and pharmacological intervention in the treatment or prevention of obesity and or non-alcoholic fatty-liver disease

The promiscuous enzyme medium-chain 3-keto-acyl-CoA thiolase triggers a vicious cycle in fatty-acid beta-oxidation

Mitochondrial fatty-acid beta-oxidation (mFAO) plays a central role in mammalian energy metabolism. Multiple severe diseases are associated with defects in this pathway. Its kinetic structure is characterized by a complex wiring of which the functional implications have hardly been explored. Repetitive cycles of reversible reactions, each cycle shortening the fatty acid by two carbon atoms, evoke competition between intermediates of different chain lengths for a common set of 'promiscuous' enzymes (enzymes with activity towards multiple substrates). In our validated kinetic model of the pathway, substrate overload causes a steep and detrimental flux decline. Here, we unravel the underlying mechanism and the role of enzyme promiscuity in it. Comparison of alternative model versions elucidated the role of promiscuity of individual enzymes. Promiscuity of the last enzyme of the pathway, medium-chain ketoacyl-CoA thiolase (MCKAT), was both necessary and sufficient to elicit the flux decline. Subsequently, Metabolic Control Analysis revealed that MCKAT had insufficient capacity to cope with high substrate influx. Next, we quantified the internal metabolic regulation, revealing a vicious cycle around MCKAT. Upon substrate overload, MCKAT's ketoacyl-CoA substrates started to accumulate. The unfavourable equilibrium constant of the preceding enzyme, medium/short-chain hydroxyacyl-CoA dehydrogenase, worked as an amplifier, leading to accumulation of upstream CoA esters, including acyl-CoA esters. These acyl-CoA esters are at the same time products of MCKAT and inhibited its already low activity further. Finally, the accumulation of CoA esters led to a sequestration of free CoA. CoA being a cofactor for MCKAT, its sequestration limited the MCKAT activity even further, thus completing the vicious cycle. Since CoA is also a substrate for distant enzymes, it efficiently communicated the 'traffic jam' at MCKAT to the entire pathway. This novel mechanism provides a basis to explore the role of mFAO in disease and elucidate similar principles in other pathways of lipid metabolism

Schematic representation of the modelled mFAO pathway in rat.

<p>Metabolites in blue are fixed parameters, while other metabolites are free variables. The sum of variable CoA esters and free CoA is a conserved moiety. Green: enzymes participating in the carnitine cycle; purple: enzymes participating in the short-chain branch; grey: enzymes participating in the medium-and long-chain branch. All processes are reversible and the size of the arrowheads indicates the net direction of the flux. This model is exactly the same as published before [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005461#pcbi.1005461.ref008" target="_blank">8</a>], without modifications.</p

Elucidating the mechanism of flux decline.

<p><b>1.</b> Upon substrate overload with cytosolic palmitoyl-CoA, MCKAT’s ketoacyl-CoA substrates start to accumulate. <b>2.</b> The unfavourable equilibrium constant of the preceding enzyme, medium/short-chain hydroxyacyl-CoA dehydrogenase, works as an amplifier, leading to the accumulation of upstream CoA esters, including acyl-CoA esters. <b>3.</b> These acyl-CoA esters are at the same time products of MCKAT and inhibit its already low activity further. <b>4.</b> Finally, the accumulation of CoA esters leads to a sequestration of free CoA. CoA being a cofactor for MCKAT, its sequestration limited the MCKAT activity even further, thus completing the vicious cycle. <b>5</b>. Since CoA is also a substrate for distant enzymes (such as MTP), it efficiently communicates the ‘traffic jam’ at MCKAT to the entire pathway.</p

The role of the short-chain branch.

<p><b>(A)</b> Steady-state flux versus [palmitoyl-CoA]_CYT in the published model (black line), a model without any enzymatic promiscuity (black dashed line, reproducing results from [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005461#pcbi.1005461.ref008" target="_blank">8</a>] as a reference), a model without promiscuity of MCKAT (green line), and finally a model with only promiscuity of MCKAT, but not of any of the other enzymes (purple line). <b>(B)</b> The flux control coefficients in the original model as a function of [palmitoyl-CoA]_CYT. Only enzymes with a substantial contribution are included; for a complete set of flux control coefficients, see figure A in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005461#pcbi.1005461.s002" target="_blank">S2 Fig</a>. <b>(C-D)</b> Top 15 flux response coefficients with the highest absolute values at 25 μM (C) and 60 μM (D) of [palmitoyl-CoA]_CYT. The parameters <i>p</i> for which the flux response coefficient was calculated is indicated on the Y-axis. Dark grey bars represent CPT1-related parameters, pink bars represent M/SCHAD-related parameters, purple bars represent MCKAT-related parameters and the light blue bar represents a crotonase-related parameter. <b>(E)</b> Flux response coefficient of [NAD⁺]/[NADH] () partitioned in contributions of individual NAD⁺-dependent reactions at 5 palmitoyl-CoA concentrations according to . (cf. <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005461#pcbi.1005461.e009" target="_blank">Eq 4</a>). The contributions of M/SCHAD reactions C8-C16 to were negligible and therefore not shown in the legend.</p

Simulated steady-state fluxes and concentrations in the mFAO model.

<p><b>(A)</b> The effect of cytosolic palmitoyl-CoA concentration ([palmitoyl-CoA]_CYT) on the steady-state flux. The steady-state uptake flux of palmitoyl-CoA (J_uptake) is plotted (calculated as the steady-state flux of palmitoyl-carnitine through CACT, i.e. the uptake of palmitoyl-carnitine into the mitochondria), in contrast to van Eunen <i>et al</i>. 2013 [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005461#pcbi.1005461.ref008" target="_blank">8</a>] in which the NADH flux was plotted. The two are uniquely linked with the latter being 7-fold higher. <b>(B)</b> The steady-state concentrations of free CoA (identical to data from [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005461#pcbi.1005461.ref008" target="_blank">8</a>]), the sum of all intermediate CoA esters, the sum of all C4- and C6 CoA esters and the subset of C4- and C6 CoA esters (new results). <b>(C-D)</b> Distribution of steady-state fluxes (J) of different chain-length substrates through MTP and MCKAT, respectively. Only the chain lengths which are converted by these enzymes (cf. <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005461#pcbi.1005461.g001" target="_blank">Fig 1</a>) are included.</p

Time course of key short-chain reaction rates and regulation of the MCKAT-C4 reaction.

<p><b>(A)</b> Time course of the reaction rates of MCKAT for its C6 and C4 substrates (vMCKATC6 and vMCKATC4, respectively) and of the summed activities of SCAD and MCAD on their C4 substrate (vMCADC4 + vSCADC4) after a sudden upshift of [palmitoyl-CoA]_CYT from 0.1 to 60 μM. <b>(B)</b> Time course of regulatory metabolite contributions to vMCKATC4 after a sudden [palmitoyl-CoA]_CYT increase from 0.1 to 60 μM.</p

Regulation of key reactions by their substrates and products.

<p><b>(A-F)</b> Relative average absolute contribution, i.e. , of metabolites to the transition from the steady state at 0.1 μM to the indicated concentration of palmitoyl-CoA, calculated for vMCKATC6 (panel A), vMCKATC4 (panel B), vMCADC6 (panel C), vSCADC4 (panel D), vMPTC8 (panel E), vCPT2C16 (panel F).</p

Personalised modelling of clinical heterogeneity between medium-chain acyl-CoA dehydrogenase patients

Abstract Background Monogenetic inborn errors of metabolism cause a wide phenotypic heterogeneity that may even differ between family members carrying the same genetic variant. Computational modelling of metabolic networks may identify putative sources of this inter-patient heterogeneity. Here, we mainly focus on medium-chain acyl-CoA dehydrogenase deficiency (MCADD), the most common inborn error of the mitochondrial fatty acid oxidation (mFAO). It is an enigma why some MCADD patients—if untreated—are at risk to develop severe metabolic decompensations, whereas others remain asymptomatic throughout life. We hypothesised that an ability to maintain an increased free mitochondrial CoA (CoASH) and pathway flux might distinguish asymptomatic from symptomatic patients. Results We built and experimentally validated, for the first time, a kinetic model of the human liver mFAO. Metabolites were partitioned according to their water solubility between the bulk aqueous matrix and the inner membrane. Enzymes are also either membrane-bound or in the matrix. This metabolite partitioning is a novel model attribute and improved predictions. MCADD substantially reduced pathway flux and CoASH, the latter due to the sequestration of CoA as medium-chain acyl-CoA esters. Analysis of urine from MCADD patients obtained during a metabolic decompensation showed an accumulation of medium- and short-chain acylcarnitines, just like the acyl-CoA pool in the MCADD model. The model suggested some rescues that increased flux and CoASH, notably increasing short-chain acyl-CoA dehydrogenase (SCAD) levels. Proteome analysis of MCADD patient-derived fibroblasts indeed revealed elevated levels of SCAD in a patient with a clinically asymptomatic state. This is a rescue for MCADD that has not been explored before. Personalised models based on these proteomics data confirmed an increased pathway flux and CoASH in the model of an asymptomatic patient compared to those of symptomatic MCADD patients. Conclusions We present a detailed, validated kinetic model of mFAO in human liver, with solubility-dependent metabolite partitioning. Personalised modelling of individual patients provides a novel explanation for phenotypic heterogeneity among MCADD patients. Further development of personalised metabolic models is a promising direction to improve individualised risk assessment, management and monitoring for inborn errors of metabolism