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Abstract (Expand)

Acyl-CoAs play a significant role in numerous physiological and metabolic processes making it important to assess their concentration levels for evaluating metabolic health. Considering the importanthe important role of acyl-CoAs, it is crucial to develop an analytical method that can analyze these compounds. Due to the structural variations of acyl-CoAs, multiple analytical methods are often required for comprehensive analysis of these compounds, which increases complexity and the analysis time. In this study, we have developed a method using a zwitterionic HILIC column that enables the coverage of free CoA and short- to long-chain acyl-CoA species in one analytical run. Initially, we developed the method on a QTOF instrument for the identification of acyl-CoA species, optimizing their chromatography and retention times. Later, a targeted HILIC-MS/MS method was created in scheduled multiple reaction monitoring mode on a QTRAP instrument. The performance of the method was evaluated based on various parameters such as linearity, precision, recovery and matrix effect. This method was applied to identify the difference in acyl-CoA profiles in HepG2 cells cultured in different conditions. Our findings revealed an increase in levels of acetyl-CoA, medium- and long-chain acyl-CoA while a decrease in the profiles of free CoA in the starved state, indicating a clear alteration in the fatty acid oxidation process.

Authors: Madhulika Singh, Ligia Akemi Kiyuna, Christoff Odendaal, Barbara M. Bakker, Amy C Harms, Thomas Hankemeier

Date Published: 11th Sep 2023

Publication Type: Journal

Abstract (Expand)

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.

Authors: C. Odendaal, E. A. Jager, A. M. F. Martines, M. A. Vieira-Lara, N. C. A. Huijkman, L. A. Kiyuna, A. Gerding, J. C. Wolters, R. Heiner-Fokkema, K. van Eunen, T. G. J. Derks, B. M. Bakker

Date Published: 4th Sep 2023

Publication Type: Journal

Abstract

Not specified

Authors: Theresa Kouril, Craig October, Stephanie Hollocks, Christoff Odendaal, David D. van Niekerk, Jacky L. Snoep

Date Published: 1st Sep 2023

Publication Type: Journal

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