odendaal3

vacotciC10

C10AcylCoAMAT = ∅

vacotciC12

C12AcylCoAMAT = ∅

vacotciC14

C14AcylCoAMAT = ∅

vacotciC16

C16AcylCoAMAT = ∅

vacotcsC10

C10AcylCoAMAT = ∅

vacotcsC12

C12AcylCoAMAT = ∅

vacotcsC14

C14AcylCoAMAT = ∅

vacotcsC16

C16AcylCoAMAT = ∅

vacotcsC4

C4AcylCoAMAT = ∅

vacotcsC6

C6AcylCoAMAT = ∅

vacotcsC8

C8AcylCoAMAT = ∅

vcpt2C10

∅ = C10AcylCoAMAT

vcpt2C12

∅ = C12AcylCoAMAT

vcpt2C14

∅ = C14AcylCoAMAT

vcpt2C16

∅ = C16AcylCoAMAT

vcpt2C4

∅ = C4AcylCoAMAT

vcpt2C6

∅ = C6AcylCoAMAT

vcpt2C8

∅ = C8AcylCoAMAT

vcratC10

C10AcylCoAMAT = ∅

vcratC4

C4AcylCoAMAT = ∅

vcratC6

C6AcylCoAMAT = ∅

vcratC8

C8AcylCoAMAT = ∅

vcrotC10

C10EnoylCoAMAT = C10HydroxyacylCoAMAT

vcrotC12

C12EnoylCoAMAT = C12HydroxyacylCoAMAT

vcrotC14

C14EnoylCoAMAT = C14HydroxyacylCoAMAT

vcrotC16

C16EnoylCoAMAT = C16HydroxyacylCoAMAT

vcrotC4

C4EnoylCoAMAT = C4HydroxyacylCoAMAT

vcrotC6

C6EnoylCoAMAT = C6HydroxyacylCoAMAT

vcrotC8

C8EnoylCoAMAT = C8HydroxyacylCoAMAT

vmcadC10

PMSox + C10AcylCoAMAT = PMSred + C10EnoylCoAMAT

vmcadC12

PMSox + C12AcylCoAMAT = PMSred + C12EnoylCoAMAT

vmcadC14

PMSox + C14AcylCoAMAT = PMSred + C14EnoylCoAMAT

vmcadC16

PMSox + C16AcylCoAMAT = PMSred + C16EnoylCoAMAT

vmcadC4

PMSox + C4AcylCoAMAT = PMSred + C4EnoylCoAMAT

vmcadC6

PMSox + C6AcylCoAMAT = PMSred + C6EnoylCoAMAT

vmcadC8

PMSox + C8AcylCoAMAT = PMSred + C8EnoylCoAMAT

vmckatC10

C10KetoacylCoAMAT = C8AcylCoAMAT + C2AcylCoAMAT

vmckatC12

C12KetoacylCoAMAT = C2AcylCoAMAT + C10AcylCoAMAT

vmckatC14

C14KetoacylCoAMAT = C2AcylCoAMAT + C12AcylCoAMAT

vmckatC16

C16KetoacylCoAMAT = C2AcylCoAMAT + C14AcylCoAMAT

vmckatC4

C4KetoacylCoAMAT = C2AcylCoAMAT

vmckatC6

C6KetoacylCoAMAT = C4AcylCoAMAT + C2AcylCoAMAT

vmckatC8

C8KetoacylCoAMAT = C6AcylCoAMAT + C2AcylCoAMAT

vmschadC10

NAD + C10HydroxyacylCoAMAT = NADH + C10KetoacylCoAMAT

vmschadC12

NAD + C12HydroxyacylCoAMAT = NADH + C12KetoacylCoAMAT

vmschadC14

NAD + C14HydroxyacylCoAMAT = NADH + C14KetoacylCoAMAT

vmschadC16

NAD + C16HydroxyacylCoAMAT = NADH + C16KetoacylCoAMAT

vmschadC4

NAD + C4HydroxyacylCoAMAT = NADH + C4KetoacylCoAMAT

vmschadC6

NAD + C6HydroxyacylCoAMAT = NADH + C6KetoacylCoAMAT

vmschadC8

NAD + C8HydroxyacylCoAMAT = NADH + C8KetoacylCoAMAT

vmtpC10

NAD + C10EnoylCoAMAT = NADH + C8AcylCoAMAT + C2AcylCoAMAT

vmtpC12

NAD + C12EnoylCoAMAT = NADH + C2AcylCoAMAT + C10AcylCoAMAT

vmtpC14

NAD + C14EnoylCoAMAT = NADH + C2AcylCoAMAT + C12AcylCoAMAT

vmtpC16

NAD + C16EnoylCoAMAT = NADH + C2AcylCoAMAT + C14AcylCoAMAT

vmtpC6

NAD + C6EnoylCoAMAT = NADH + C2AcylCoAMAT

vmtpC8

NAD + C8EnoylCoAMAT = NADH + C6AcylCoAMAT + C2AcylCoAMAT

vscadC4

PMSox + C4AcylCoAMAT = PMSred + C4EnoylCoAMAT

vscadC6

PMSox + C6AcylCoAMAT = PMSred + C6EnoylCoAMAT

vvlcadC10

PMSox + C10AcylCoAMAT = PMSred + C10EnoylCoAMAT

vvlcadC12

PMSox + C12AcylCoAMAT = PMSred + C12EnoylCoAMAT

vvlcadC14

PMSox + C14AcylCoAMAT = PMSred + C14EnoylCoAMAT

vvlcadC16

PMSox + C16AcylCoAMAT = PMSred + C16EnoylCoAMAT

vvlcadC8

PMSox + C8AcylCoAMAT = PMSred + C8EnoylCoAMAT

Global parameters

Assignment rules

CarMAT = -C2AcylCarMAT + CarMATt - C10AcylCarMAT - C12AcylCarMAT - C14AcylCarMAT - C16AcylCarMAT - C4AcylCarMAT - C6AcylCarMAT - C8AcylCarMAT

CoAMAT = CoAMATt - CoASHseq - C10AcylCoAMAT - C10EnoylCoAMAT - C10HydroxyacylCoAMAT - C10KetoacylCoAMAT - C12AcylCoAMAT - C12EnoylCoAMAT - C12HydroxyacylCoAMAT - C12KetoacylCoAMAT - C14AcylCoAMAT - C14EnoylCoAMAT - C14HydroxyacylCoAMAT - C14KetoacylCoAMAT - C16AcylCoAMAT - C16EnoylCoAMAT - C16HydroxyacylCoAMAT - C16KetoacylCoAMAT - C2AcylCoAMAT - C4AcylCoAMAT - C4EnoylCoAMAT - C4HydroxyacylCoAMAT - C4KetoacylCoAMAT - C6AcylCoAMAT - C6EnoylCoAMAT - C6HydroxyacylCoAMAT - C6KetoacylCoAMAT - C8AcylCoAMAT - C8EnoylCoAMAT - C8HydroxyacylCoAMAT - C8KetoacylCoAMAT

Vmcad = 0.038 * mcad

Vvlcad = 0.076 * vlcad

Function definitions

Note that constraints are not enforced in simulations. It remains the responsibility of the user to verify that simulation results satisfy these constraints.


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

  • Christoff Odendaal
  • Emmalie A Jager
  • Anne-Claire M F Martines
  • Marcel A Vieira-Lara
  • Nicolette C A Huijkman
  • Ligia A Kiyuna
  • Albert Gerding
  • Justina C Wolters
  • Rebecca Heiner-Fokkema
  • Karen van Eunen
  • Terry G J Derks
  • Barbara M Bakker
BMC Biol 2023; 21 (1): 184
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.
Model adapted from odendaal1 to simulate an in vitro experiment using cell lysate. Cytosolic compartment removed, partitioning factors set to 1, and volume and substrate concentration adjusted to the assay volume. Two Vmaxes, Vmcad and Vvlcad, contain terms allowing the user to easily set them to zero, to emulate the immunoprecipitation of those enzymes in the experiments and are therefore assignment rules and not parameters.