A compendium of inborn errors of metabolism mapped onto the human metabolic network

in Molecular Biosystems (2012), 8(10), 2545-2558

Inborn errors of metabolism (IEMs) are hereditary metabolic defects, which are encountered in almost all major metabolic pathways occurring in man. Many IEMs are screened for in neonates through ... [more ▼]

Inborn errors of metabolism (IEMs) are hereditary metabolic defects, which are encountered in almost all major metabolic pathways occurring in man. Many IEMs are screened for in neonates through metabolomic analysis of dried blood spot samples. To enable the mapping of these metabolomic data onto the published human metabolic reconstruction, we added missing reactions and pathways involved in acylcarnitine (AC) and fatty acid oxidation (FAO) metabolism. Using literary data, we reconstructed an AC/FAO module consisting of 352 reactions and 139 metabolites. When this module was combined with the human metabolic reconstruction, the synthesis of 39 acylcarnitines and 22 amino acids, which are routinely measured, was captured and 235 distinct IEMs could be mapped. We collected phenotypic and clinical features for each IEM enabling comprehensive classification. We found that carbohydrate, amino acid, and lipid metabolism were most affected by the IEMs, while the brain was the most commonly affected organ. Furthermore, we analyzed the IEMs in the context of metabolic network topology to gain insight into common features between metabolically connected IEMs. While many known examples were identified, we discovered some surprising IEM pairs that shared reactions as well as clinical features but not necessarily causal genes. Moreover, we could also re-confirm that acetyl-CoA acts as a central metabolite. This network based analysis leads to further insight of hot spots in human metabolism with respect to IEMs. The presented comprehensive knowledge base of IEMs will provide a valuable tool in studying metabolic changes involved in inherited metabolic diseases. [less ▲]

An integrative approach towards completing genome-scale metabolic networks.

in Molecular Biosystems (2009), 5(12), 1889-903

Genome-scale metabolic networks which have been automatically derived through sequence comparison techniques are necessarily incomplete. We propose a strategy that incorporates genomic sequence data and ... [more ▼]

Genome-scale metabolic networks which have been automatically derived through sequence comparison techniques are necessarily incomplete. We propose a strategy that incorporates genomic sequence data and metabolite profiles into modeling approaches to arrive at improved gene annotations and more complete genome-scale metabolic networks. The core of our strategy is an algorithm that computes minimal sets of reactions by which a draft network has to be extended in order to be consistent with experimental observations. A particular strength of our approach is that alternative possibilities are suggested and thus experimentally testable hypotheses are produced. We carefully evaluate our strategy on the well-studied metabolic network of Escherichia coli, demonstrating how the predictions can be improved by incorporating sequence data. Subsequently, we apply our method to the recently sequenced green alga Chlamydomonas reinhardtii. We suggest specific genes in the genome of Chlamydomonas which are the strongest candidates for coding the responsible enzymes. [less ▲]