Dataset Information

A metabolic model of the mitochondrion and its use in modelling diseases of the tricarboxylic acid cycle.

ABSTRACT: BACKGROUND:Mitochondria are a vital component of eukaryotic cells and their dysfunction is implicated in a large number of metabolic, degenerative and age-related human diseases. The mechanism or these disorders can be difficult to elucidate due to the inherent complexity of mitochondrial metabolism. To understand how mitochondrial metabolic dysfunction contributes to these diseases, a metabolic model of a human heart mitochondrion was created. RESULTS:A new model of mitochondrial metabolism was built on the principle of metabolite availability using MitoMiner, a mitochondrial proteomics database, to evaluate the subcellular localisation of reactions that have evidence for mitochondrial localisation. Extensive curation and manual refinement was used to create a model called iAS253, containing 253 reactions, 245 metabolites and 89 transport steps across the inner mitochondrial membrane. To demonstrate the predictive abilities of the model, flux balance analysis was used to calculate metabolite fluxes under normal conditions and to simulate three metabolic disorders that affect the TCA cycle: fumarase deficiency, succinate dehydrogenase deficiency and ?-ketoglutarate dehydrogenase deficiency. CONCLUSION:The results of simulations using the new model corresponded closely with phenotypic data under normal conditions and provided insight into the complicated and unintuitive phenotypes of the three disorders, including the effect of interventions that may be of therapeutic benefit, such as low glucose diets or amino acid supplements. The model offers the ability to investigate other mitochondrial disorders and can provide the framework for the integration of experimental data in future studies.

SUBMITTER: Smith AC

PROVIDER: S-EPMC3152903 | biostudies-literature | 2011 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A metabolic model of the mitochondrion and its use in modelling diseases of the tricarboxylic acid cycle.

Smith Anthony C AC Robinson Alan J AJ

BMC systems biology 20110629

<h4>Background</h4>Mitochondria are a vital component of eukaryotic cells and their dysfunction is implicated in a large number of metabolic, degenerative and age-related human diseases. The mechanism or these disorders can be difficult to elucidate due to the inherent complexity of mitochondrial metabolism. To understand how mitochondrial metabolic dysfunction contributes to these diseases, a metabolic model of a human heart mitochondrion was created.<h4>Results</h4>A new model of mitochondrial ...[more]

PMID: 21714867

Similar Datasets

Project description:Methylmalonic acidemia (MMA) is a propionate pathway disorder caused by dysfunction of the mitochondrial enzyme methylmalonyl-CoA mutase (MMUT). MMUT catalyzes the conversion of methylmalonyl-CoA to succinyl-CoA, an anaplerotic reaction which feeds into the tricarboxylic acid (TCA) cycle. As part of the pathological mechanisms of MMA, previous studies have suggested there is decreased TCA activity due to a "toxic inhibition" of TCA cycle enzymes by MMA related metabolites, in addition to reduced anaplerosis. Here, we have utilized mitochondria isolated from livers of a mouse model of MMA (Mut-ko/ki) and their littermate controls (Ki/wt) to examine the amounts and enzyme functions of most of the TCA cycle enzymes. We have performed mRNA quantification, protein semi-quantitation, and enzyme activity quantification for TCA cycle enzymes in these samples. Expression profiling showed increased mRNA levels of fumarate hydratase in the Mut-ko/ki samples, which by contrast had reduced protein levels as detected by immunoblot, while all other mRNA levels were unaltered. Immunoblotting also revealed decreased protein levels of 2-oxoglutarate dehydrogenase and malate dehydrogenase 2. Interesting, the decreased protein amount of 2-oxoglutarate dehydrogenase was reflected in decreased activity for this enzyme while there is a trend towards decreased activity of fumarate hydratase and malate dehydrogenase 2. Citrate synthase, isocitrate dehydrogenase 2/3, succinyl-CoA synthase, and succinate dehydrogenase are not statistically different in terms of quantity of enzyme or activity. Finally, we found decreased activity when examining the function of methylmalonyl-CoA mutase in series with succinate synthase and succinate dehydrogenase in the Mut-ko/ki mice compared to their littermate controls, as expected. This study demonstrates decreased activity of certain TCA cycle enzymes and by corollary decreased TCA cycle function, but it supports decreased protein quantity rather than "toxic inhibition" as the underlying mechanism of action. SUMMARY: Methylmalonic acidemia (MMA) is an inborn metabolic disorder of propionate catabolism. In this disorder, toxic metabolites are considered to be the major pathogenic mechanism for acute and long-term complications. However, despite optimized therapies aimed at reducing metabolite levels, patients continue to suffer from late complications, including metabolic stroke and renal insufficiency. Since the propionate pathway feeds into the tricarboxylic acid (TCA) cycle, we investigated TCA cycle function in a constitutive MMA mouse model. We demonstrated decreased amounts of the TCA enzymes, Mdh2 and Ogdh as semi-quantified by immunoblot. Enzymatic activity of Ogdh is also decreased in the MMA mouse model compared to controls. Thus, when the enzyme amounts are decreased, we see the enzymatic activity also decreased to a similar extent for Ogdh. Further studies to elucidate the structural and/or functional links between the TCA cycle and propionate pathways might lead to new treatment approaches for MMA patients.

Project description:ObjectiveIt is well known that paclitaxel (PTX)-induced neurotoxicity seriously affects the quality of life of patients and is the main reason for reducing the dose of chemotherapy or even stopping chemotherapy. The current data are limited, and further information is required for practice and verification. The aims of this study were to clarify the molecular mechanism underlying PTX-induced neurotoxicity by combining in vivo and in vitro metabolomics studies and provide new targets for the prevention and treatment of PTX-induced neurotoxicity.MethodsIn the in vivo study, a PTX-induced neurotoxicity mouse model was established by intraperitoneal injection of PTX (6 mg/kg every three days) for two consecutive weeks. After verification by water maze tests and HE staining of pathological sections, hippocampal metabolites were measured and the differential metabolites and related metabolic pathways were identified by multivariate statistical analysis. In the in vitro study, we investigated the effects of PTX on mouse hippocampal neuron cells, assessing the concentration and time of administration by MTT assays. After modeling, the relevant metabolites in the TCA cycle were quantified by targeted metabolomics using stable isotope labeling. Finally, the key enzymes of the TCA cycle in tissues and cells were verified by RT-PCR.ResultsAdministration of PTX to model mice resulted in neurological damage, shown by both water-maze tests and hippocampal tissue sections. Twenty-four metabolites and five associated metabolic pathways were found to differ significantly between the hippocampal tissues of the model and control groups. These included metabolites and pathways related to the TCA cycle and pyruvate metabolism. Metabolomics analysis using stable isotope labeling showed significant changes in metabolites associated with the TCA cycle compared with the control group (P < 0.05). Finally, RT-PCR verified that the expression of key enzymes in the TCA cycle was changed to different degrees in both hippocampal tissues and cells.ConclusionOur results showed that PTX neurotoxicity in hippocampal tissue and neuron cells was associated with inhibition of the TCA cycle. This inhibition leads to brain insufficiency and impaired metabolism, resulting in various neurotoxic symptoms.

Project description:Introduction: Cervical cancer (CC) is the fourth most common malignant tumor in term of in incidence and mortality among women worldwide. The tricarboxylic acid (TCA) cycle is an important hub of energy metabolism, networking one-carbon metabolism, fatty acyl metabolism and glycolysis. It can be seen that the reprogramming of cell metabolism including TCA cycle plays an indispensable role in tumorigenesis and development. We aimed to identify genes related to the TCA cycle as prognostic markers in CC. Methods: Firstly, we performed the differential expressed analysis the gene expression profiles associated with TCA cycle obtained from The Cancer Genome Atlas (TCGA) database. Differential gene list was generated and cluster analysis was performed using genes with detected fold changes >1.5. Based on the subclusters of CC, we analysed the relationship between different clusters and clinical information. Next, Cox univariate and multivariate regression analysis were used to screen genes with prognostic characteristics, and risk scores were calculated according to the genes with prognostic characteristics. Additionally, we analyzed the correlation between the predictive signature and the treatment response of CC patients. Finally, we detected the expression of ench prognostic gene in clinical CC samples by quantitative polymerase chain reaction (RT-qPCR). Results: We constructed a prognostic model consist of seven TCA cycle associated gene (ACSL1, ALDOA, FOXK2, GPI, MDH1B, MDH2, and MTHFD1). Patients with CC were separated into two groups according to median risk score, and high-risk group had a worse prognosis compared to the low-risk group. High risk group had lower level of sensitivity to the conventional chemotherapy drugs including cisplatin, paclitaxel, sunitinib and docetaxel. The expression of ench prognostic signature in clinical CC samples was verified by qRT-PCR. Conclusion: There are several differentially expressed genes (DEGs) related to TCA cycle in CC. The risk score model based on these genes can effectively predict the prognosis of patients and provide tumor markers for predicting the prognosis of CC.

Dataset Information

A metabolic model of the mitochondrion and its use in modelling diseases of the tricarboxylic acid cycle.

Publications

A metabolic model of the mitochondrion and its use in modelling diseases of the tricarboxylic acid cycle.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets