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

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.

Biosynthesis and tissue-specific partitioning of camphor and eugenol in Ocimum kilimandscharicum

In Ocimum kilimandscharicum, the relative volatile composition of camphor in leaves was as high as 55%, while that of eugenol in roots was 57%. These metabolites were differentially partitioned between the aerial and root tissues. Global metabolomics revealed tissue-specific biochemical specialization, evident by the differential distribution of 2588 putative metabolites across nine tissues. Next-generation sequencing analysis indicated differential expression of 51 phenylpropanoid and 55 terpenoid pathway genes in aerial and root tissues. By integrating metabolomics with transcriptomics, the camphor biosynthesis pathway in O. kilimandscharicum was elucidated. In planta bioassays revealed the role of geranyl diphosphate synthase (gpps) and borneol dehydrogenase (bdh) in camphor biosynthesis. Further, the partitioning of camphor was attributed to tissue-specific gene expression of both the pathway entry point (gpps) and terminal (bdh) enzyme. Unlike camphor, eugenol accumulated more in roots; however, absence of the eugenol synthase gene in roots indicated long distance transport from aerial tissues. In silico co-expression analysis indicated the potential involvement of ATP-binding cassette, multidrug and toxic compound extrusion, and sugar transporters in eugenol transport. Similar partitioning was evident across five other Ocimum species. Overall, our work indicates that metabolite partitioning maybe a finely regulated process, which may have implications on plant growth, development, and defense.