The citrate carrier (CiC), a nuclear-encoded protein located in the mitochondrial inner membrane, is a member of the mitochondrial carrier family. CiC plays an important role in hepatic lipogenesis, which is responsible for the efflux of acetyl-CoA from the mitochondria to the cytosol in the form of citrate, the primer for fatty acid and cholesterol synthesis. In addition, CiC is a key component of the isocitrate-oxoglutarate and the citrate-malate shuttles. CiC has been purified from various species and its reconstituted function characterized as well as its cDNA isolated and sequenced. CiC mRNA and/or CiC protein levels are high in liver, pancreas, and kidney, but are low or absent in brain, heart, skeletal muscle, placenta, and lungs. A reduction of CiC activity was found in diabetic, hypothyroid, starved rats, and in rats fed on a polyunsaturated fatty acid (PUFA)-enriched diet. Molecular analysis suggested that the regulation of CiC activity occurs mainly through transcriptional and post-transcriptional mechanisms. This review begins with an assessment of the current understanding of CiC structural and biochemical characteristics, underlying the structure-function relationship. Emphasis will be placed on the molecular basis of the regulation of CiC activity in coordination with fatty acid synthesis.
"In addition to its wide array of industrial and medical uses, citrate is an important intermediate in TCA cycle and also an essential regulatory molecule in glycolysis and fatty acid synthesis , . Our newly developed cpFP-based citrate indicator can be effectively employed to follow the metabolic activities of cells in question to understand dynamic intracellular events in which citrate is involved in living cells and to explore the mechanism of citrate production. "
[Show abstract][Hide abstract] ABSTRACT: Indicators for citrate, particularly those applicable to its in vivo detection and quantitation, have attracted much interest in both biochemical studies and industrial applications since citrate is a key metabolic intermediate playing important roles in living cells. We generated novel fluorescence indicators for citrate by fusing the circularly permuted fluorescent protein (cpFP) and the periplasmic domain of the bacterial histidine kinase CitA, which can bind to citrate with high specificity. The ratiometric fluorescent signal change was observed with one of these cpFP-based indicators, named CF98: upon addition of citrate, the excitation peak at 504 nm increased proportionally to the decrease in the peak at 413 nm, suitable for build-in quantitative estimation of the binding compound. We confirmed that CF98 can be used for detecting citrate in vitro at millimolar levels in the range of 0.1 to 50 mM with high selectivity; even in the presence of other organic acids such as isocitrate and malate, the fluorescence intensity of CF98 remains unaffected. We finally demonstrated the in vivo applicability of CF98 to estimation of the intracellular citrate concentration in Escherichia coli co-expressing the genes encoding CF98 and the citrate carrier CitT. The novel indicator CF98 can be a specific and simple detection tool for citrate in vitro and a non-invasive tool for real-time estimation of intracellular concentrations of the compound in vivo.
PLoS ONE 11/2013; 8(5):e64597. DOI:10.1371/journal.pone.0064597 · 3.23 Impact Factor
"In rat, CIC activity was found to be decreased in diabetic and hypothyroid animals  . Later, it has been shown that CIC gene promoter contains an active FOXA site and that FOXA1 controls glucose-stimulated insulin secretion in INS-1 cells by transcriptional regulation of the CIC gene . "
[Show abstract][Hide abstract] ABSTRACT: The citrate carrier (CIC), a nuclear-encoded protein located in the mitochondrial inner membrane, plays an important metabolic role in the transport of acetyl-CoA from the mitochondrion to the cytosol in the form of citrate for fatty acid and cholesterol synthesis. Citrate has been reported to be essential for fibroblast differentiation into fat cells. Because peroxisome proliferator-activated receptor-gamma (PPARγ) is known to be one of the master regulators of adipogenesis, we aimed to study the regulation of CIC by the PPARγ ligand rosiglitazone (BRL) in 3T3-L1 fibroblasts and in adipocytes. We demonstrated that BRL up-regulated CIC mRNA and protein levels in fibroblasts, while it did not elicit any effects in mature adipocytes. The enhancement of CIC levels upon BRL treatment was reversed using the PPARγ antagonist GW9662, addressing how this effect was mediated by PPARγ. Functional experiments using a reporter gene containing rat CIC promoter showed that BRL enhanced CIC promoter activity. Mutagenesis studies, electrophoretic-mobility-shift assay and chromatin-immunoprecipitation analysis revealed that upon BRL treatment, PPARγ and Sp1 are recruited on the Sp1-containing region within the CIC promoter, leading to an increase in CIC expression. In addition, mithramycin, a specific inhibitor for Sp1-DNA binding activity, abolished the PPARγ-mediated up-regulation of CIC in fibroblasts. The stimulatory effects of BRL disappeared in mature adipocytes in which PPARγ/Sp1 complex recruited SMRT corepressor to the Sp1 site of the CIC promoter. Taken together, our results contribute to clarify the molecular mechanisms by which PPARγ regulates CIC expression during the differentiation stages of fibroblasts into mature adipocytes.
"The citrate carrier is the key component of citrate-malate-shuttle and it is located in the mitochondrial inner membrane. High levels of the citrate carrier can be found predominantly in liver, pancreas and kidney . A reduction of citrate carrier activity and protein levels, both affected by insulin and glucose levels at different regulatory steps, was found in diabetic mice . "
[Show abstract][Hide abstract] ABSTRACT: High blood glucose and diabetes are amongst the conditions causing the greatest losses in years of healthy life worldwide. Therefore, numerous studies aim to identify reliable risk markers for development of impaired glucose metabolism and type 2 diabetes. However, the molecular basis of impaired glucose metabolism is so far insufficiently understood. The development of so called 'omics' approaches in the recent years promises to identify molecular markers and to further understand the molecular basis of impaired glucose metabolism and type 2 diabetes. Although univariate statistical approaches are often applied, we demonstrate here that the application of multivariate statistical approaches is highly recommended to fully capture the complexity of data gained using high-throughput methods.
We took blood plasma samples from 172 subjects who participated in the prospective Metabolic Syndrome Berlin Potsdam follow-up study (MESY-BEPO Follow-up). We analysed these samples using Gas Chromatography coupled with Mass Spectrometry (GC-MS), and measured 286 metabolites. Furthermore, fasting glucose levels were measured using standard methods at baseline, and after an average of six years. We did correlation analysis and built linear regression models as well as Random Forest regression models to identify metabolites that predict the development of fasting glucose in our cohort.
We found a metabolic pattern consisting of nine metabolites that predicted fasting glucose development with an accuracy of 0.47 in tenfold cross-validation using Random Forest regression. We also showed that adding established risk markers did not improve the model accuracy. However, external validation is eventually desirable. Although not all metabolites belonging to the final pattern are identified yet, the pattern directs attention to amino acid metabolism, energy metabolism and redox homeostasis.
We demonstrate that metabolites identified using a high-throughput method (GC-MS) perform well in predicting the development of fasting plasma glucose over several years. Notably, not single, but a complex pattern of metabolites propels the prediction and therefore reflects the complexity of the underlying molecular mechanisms. This result could only be captured by application of multivariate statistical approaches. Therefore, we highly recommend the usage of statistical methods that seize the complexity of the information given by high-throughput methods.
Journal of Clinical Bioinformatics 02/2012; 2(1):3. DOI:10.1186/2043-9113-2-3
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