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1.
Biochim Biophys Acta Mol Cell Biol Lipids ; 1863(6): 614-624, 2018 Jun.
Article in English | MEDLINE | ID: mdl-29526665

ABSTRACT

ACSL3 is the only long chain fatty acyl-CoA synthetase consistently found on growing and mature lipid droplets (LDs), suggesting that this specific localization has biological relevance. Current models for LD growth propose that triglycerides are synthesized by enzymes at the LD surface, with activated fatty acids provided by LD localized ACSL3, thus allowing growth independent of the ER. Here, we tested this hypothesis by quantifying ACSL3 on LDs from human A431 cells. RNAi of ACSL3 reduced the oleoyl-CoA synthetase activity by 83%, suggesting that ACSL3 is by far the dominant enzyme of A431 cells. Molar quantification revealed that there are 1.4 million ACSL3 molecules within a single cell. Metabolic labeling indicated that each ACSL3 molecule contributed a net gain of 3.1 oleoyl-CoA/s. 3D reconstruction of confocal images demonstrated that 530 individual lipid droplets were present in an average oleate fed A431 cell. A representative single lipid droplet with a diameter of 0.66 µm contained 680 ACSL3 molecules on the surface. Subcellular fractionation showed that at least 68% of ACSL3 remain at the ER even during extensive fatty acid supplementation. High resolution single molecule microscopy confirmed the abundance of cytoplasmic ACSL3 outside of LDs. Model calculations for triglyceride synthesis using only LD localized ACSL3 gave significant slower growth of LDs as observed experimentally. In conclusion, although ACSL3 is an abundant enzyme on A431 LDs, the metabolic capacity is not sufficient to account for LD growth solely by the local synthesis of triglycerides.


Subject(s)
Coenzyme A Ligases/metabolism , Endoplasmic Reticulum/enzymology , Lipid Droplets/enzymology , Triglycerides/biosynthesis , Cell Line, Tumor , Humans
2.
J Biol Chem ; 293(6): 2115-2124, 2018 02 09.
Article in English | MEDLINE | ID: mdl-29259131

ABSTRACT

Intestinal fructose uptake is mainly mediated by glucose transporter 5 (GLUT5/SLC2A5). Its closest relative, GLUT7, is also expressed in the intestine but does not transport fructose. For rat Glut5, a change of glutamine to glutamic acid at codon 166 (p.Q166E) has been reported to alter the substrate-binding specificity by shifting Glut5-mediated transport from fructose to glucose. Using chimeric proteins of GLUT5 and GLUT7, here we identified amino acid residues of GLUT5 that define its substrate specificity. The proteins were expressed in NIH-3T3 fibroblasts, and their activities were determined by fructose radiotracer flux. We divided the human GLUT5 sequence into 26 fragments and then replaced each fragment with the corresponding region in GLUT7. All fragments that yielded reduced fructose uptake were analyzed further by assessing the role of individual amino acid residues. Various positions in the first extracellular loop, in the fifth, seventh, eighth, ninth, and tenth transmembrane domains (TMDs), and in the regions between the ninth and tenth TMDs and tenth and 11th TMDs were identified as being important for proper fructose uptake. Although the p.Q167E change did not render the human protein into a glucose transporter, molecular dynamics simulations revealed a drastic change in the dynamics and a movement of the intracellular loop connecting the sixth and seventh TMDs, which covers the exit of the ligand. Finally, we generated a GLUT7-GLUT5 chimera consisting of the N-terminal part of GLUT7 and the C-terminal part of GLUT5. Although this chimera was inactive, we demonstrate fructose transport after introduction of four amino acids derived from GLUT5.


Subject(s)
Amino Acids/physiology , Fructose/metabolism , Glucose Transport Proteins, Facilitative/metabolism , Glucose Transporter Type 5/metabolism , Amino Acid Sequence/genetics , Amino Acid Sequence/physiology , Animals , Glucose Transport Proteins, Facilitative/chemistry , Glucose Transporter Type 5/chemistry , Humans , Mice , NIH 3T3 Cells , Peptide Fragments/genetics , Peptide Fragments/physiology , Rats , Recombinant Fusion Proteins/metabolism , Substrate Specificity
3.
Diabetes Metab Res Rev ; 32(3): 308-15, 2016 Mar.
Article in English | MEDLINE | ID: mdl-26408959

ABSTRACT

BACKGROUND: We investigated whether parental history of type 2 diabetes mellitus (T2D) is associated with age, lifestyle, anthropometric factors, and clinical severity at the time of T2D diagnosis. METHODS: We conducted a cross-sectional study based on the Danish Centre for Strategic Research in Type 2 Diabetes cohort. We examined the prevalence ratios (PR) of demographic, lifestyle, anthropometric, and clinical factors according to parental history, using Poisson regression adjusting for age and gender. RESULTS: Of 2825 T2D patients, 34% (n = 964) had a parental history of T2D. Parental history was associated with younger age at diagnosis [adjusted (a)PR 1.66, 95% confidence interval: 1.19, 2.31) for age <40 years; aPR 1.36 (95% confidence interval: 1.24, 1.48) for ages 40-59 years] and with higher baseline fasting plasma glucose [≥7.5 mmol/L, aPR 1.47 (95% confidence interval: 1.20, 1.80)], and also tended to be associated with lower beta cell function. In contrast, patients both with and without a parental history had similar occurrence of central obesity [91% vs. 91%], weight gain ≥30 kg since age 20 [52% vs. 53%], and lack of regular physical activity [60% vs. 58%]. Presence of diabetes complications or comorbidities at T2D diagnosis was not associated with parental history. CONCLUSIONS: The lack of an association between parental history and adverse lifestyle factors indicates that T2D patients do not inherit a particular propensity for overeating or inactivity, whereas patients with a parental history may have more severe pancreatic beta cell dysfunction at diagnosis.


Subject(s)
Body Mass Index , Diabetes Mellitus, Type 2/diagnosis , Diabetes Mellitus, Type 2/epidemiology , Life Style , Severity of Illness Index , Adult , Age Factors , Anthropometry , Cross-Sectional Studies , Denmark/epidemiology , Female , Humans , Male , Middle Aged , Prevalence , Risk Factors , Weight Gain
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