989 resultados para metabolic profiling


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The interaction between the gut microbiota and their mammalian host is known to have far-reaching consequences with respect to metabolism and health. We investigated the effects of eight days of oral antibiotic exposure (penicillin and streptomycin sulfate) on gut microbial composition and host metabolic phenotype in male Han-Wistar rats (n = 6) compared to matched controls. Early recolonization was assessed in a third group exposed to antibiotics for four days followed by four days recovery (n = 6). Fluorescence in situ hybridization analysis of the intestinal contents collected at eight days showed a significant reduction in all bacterial groups measured (control, 1010.7 cells/g feces; antibiotic-treated, 108.4). Bacterial suppression reduced the excretion of mammalian-microbial urinary cometabolites including hippurate, phenylpropionic acid, phenylacetylglycine and indoxyl-sulfate whereas taurine, glycine, citrate, 2-oxoglutarate, and fumarate excretion was elevated. While total bacterial counts remained notably lower in the recolonized animals (109.1 cells/g faeces) compared to the controls, two cage-dependent subgroups emerged with Lactobacillus/Enterococcus probe counts dominant in one subgroup. This dichotomous profile manifested in the metabolic phenotypes with subgroup differences in tricarboxylic acid cycle metabolites and indoxyl-sulfate excretion. Fecal short chain fatty acids were diminished in all treated animals. Antibiotic treatment induced a profound effect on the microbiome structure, which was reflected in the metabotype. Moreover, the recolonization process was sensitive to the microenvironment, which may impact on understanding downstream consequences of antibiotic consumption in human populations.

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Metabolic stable isotope labeling is increasingly employed for accurate protein (and metabolite) quantitation using mass spectrometry (MS). It provides sample-specific isotopologues that can be used to facilitate comparative analysis of two or more samples. Stable Isotope Labeling by Amino acids in Cell culture (SILAC) has been used for almost a decade in proteomic research and analytical software solutions have been established that provide an easy and integrated workflow for elucidating sample abundance ratios for most MS data formats. While SILAC is a discrete labeling method using specific amino acids, global metabolic stable isotope labeling using isotopes such as (15)N labels the entire element content of the sample, i.e. for (15)N the entire peptide backbone in addition to all nitrogen-containing side chains. Although global metabolic labeling can deliver advantages with regard to isotope incorporation and costs, the requirements for data analysis are more demanding because, for instance for polypeptides, the mass difference introduced by the label depends on the amino acid composition. Consequently, there has been less progress on the automation of the data processing and mining steps for this type of protein quantitation. Here, we present a new integrated software solution for the quantitative analysis of protein expression in differential samples and show the benefits of high-resolution MS data in quantitative proteomic analyses.

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Background: Calpain-10 protein (intracellular Ca2+-dependent cysteine protease) may play a role in glucose metabolism, pancreatic β cell function, and regulation of thermogenesis. Several CAPN10 polymorphic sites have been studied for their potential use as risk markers for type 2 diabetes and the metabolic syndrome (MetS). Fatty acids are key metabolic regulators that may interact with genetic factors and influence glucose metabolism. Objective: The objective was to examine whether the genetic variability at the CAPN10 gene locus is associated with the degree of insulin resistance and plasma fatty acid concentrations in subjects with MetS. Design: The insulin sensitivity index, glucose effectiveness, insulin resistance [homeostasis model assessment of insulin resistance (HOMA-IR)], insulin secretion (disposition index, acute insulin response, and HOMA of β cell function), plasma fatty acid composition, and 5 CAPN10 single nucleotide polymorphisms (SNPs) were determined in a cross-sectional analysis of 452 subjects with MetS participating in the LIPGENE dietary intervention cohort. Results: The rs2953171 SNP interacted with plasma total saturated fatty acid (SFA) concentrations, which were significantly associated with insulin sensitivity (P < 0.031 for fasting insulin, P < 0.028 for HOMA-IR, and P < 0.012 for glucose effectiveness). The G/G genotype was associated with lower fasting insulin concentrations, lower HOMA-IR, and higher glucose effectiveness in subjects with low SFA concentrations (below the median) than in subjects with the minor A allele (G/A and A/A). In contrast, subjects with the G/G allele with the highest SFA concentrations (above the median) had higher fasting insulin and HOMA-IR values and lower glucose effectiveness than did subjects with the A allele. Conclusion: The rs2953171 polymorphism at the CAPN10 gene locus may influence insulin sensitivity by interacting with the plasma fatty acid composition in subjects with MetS. This trial was registered at clinicaltrials.gov as NCT00429195.

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Background: Adiponectin gene expression is modulated by peroxisome proliferator–activated receptor γ, which is a transcription factor activated by unsaturated fatty acids. Objective: We investigated the effect of the interaction between variants at the ADIPOQ gene locus, age, sex, body mass index (BMI), ethnicity, and the replacement of dietary saturated fatty acids (SFAs) with monounsaturated fatty acids (MUFAs) or carbohydrates on serum adiponectin concentrations. Design: The RISCK (Reading, Imperial, Surrey, Cambridge, and Kings) study is a parallel-design, randomized controlled trial. Serum adiponectin concentrations were measured after a 4-wk high-SFA (HS) diet and a 24-wk intervention with reference (HS), high-MUFA (HM), and low-fat (LF) diets. Single nucleotide polymorphisms at the ADIPOQ locus −11391 G/A (rs17300539), −10066 G/A (rs182052), −7734 A/C (rs16861209), and +276 G/T (rs1501299) were genotyped in 448 participants. Results: In white Europeans, +276 T was associated with higher serum adiponectin concentrations (n = 340; P = 0.006) and −10066 A was associated with lower serum adiponectin concentrations (n = 360; P = 0.03), after adjustment for age, BMI, and sex. After the HM diet, −10066 G/G subjects showed a 3.8% increase (95% CI: −0.1%, 7.7%) and G/A+A/A subjects a 2.6% decrease (95% CI: −5.6%, 0.4%) in serum adiponectin (P = 0.006 for difference after adjustment for the change in BMI, age, and sex). In −10066 G/G homozygotes, serum adiponectin increased with age after the HM diet and decreased after the LF diet. Conclusion: In white −10066 G/G homozygotes, an HM diet may help to increase adiponectin concentrations with advancing age. This trial was registered at clinicaltrials.gov as ISRCTN29111298.

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Glucokinase Regulatory Protein (GCKR) plays a central role regulating both hepatic triglyceride and glucose metabolism. Fatty acids are key metabolic regulators, which interact with genetic factors and influence glucose metabolism and other metabolic traits. Omega-3 polyunsaturated fatty acids (n-3 PUFA) have been of considerable interest, due to their potential to reduce metabolic syndrome (MetS) risk. Objective To examine whether genetic variability at the GCKR gene locus was associated with the degree of insulin resistance, plasma concentrations of C-reactive protein (CRP) and n-3 PUFA in MetS subjects. Design Homeostasis model assessment of insulin resistance (HOMA-IR), HOMA-B, plasma concentrations of C-peptide, CRP, fatty acid composition and the GCKR rs1260326-P446L polymorphism, were determined in a cross-sectional analysis of 379 subjects with MetS participating in the LIPGENE dietary cohort. Results Among subjects with n-3 PUFA levels below the population median, carriers of the common C/C genotype had higher plasma concentrations of fasting insulin (P = 0.019), C-peptide (P = 0.004), HOMA-IR (P = 0.008) and CRP (P = 0.032) as compared with subjects carrying the minor T-allele (Leu446). In contrast, homozygous C/C carriers with n-3 PUFA levels above the median showed lower plasma concentrations of fasting insulin, peptide C, HOMA-IR and CRP, as compared with individuals with the T-allele. Conclusions We have demonstrated a significant interaction between the GCKR rs1260326-P446L polymorphism and plasma n-3 PUFA levels modulating insulin resistance and inflammatory markers in MetS subjects. Further studies are needed to confirm this gene-diet interaction in the general population and whether targeted dietary recommendations can prevent MetS in genetically susceptible individuals.

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Objective To examine the impact of increasing numbers of metabolic syndrome (MetS) components on postprandial lipaemia. Methods Healthy men (n = 112) underwent a sequential meal postprandial investigation, in which blood samples were taken at regular intervals after a test breakfast (0 min) and lunch (330 min). Lipids and glucose were measured in the fasting sample, with triacylglycerol (TAG), non-esterified fatty acids and glucose analysed in the postprandial samples. Results Subjects were grouped according to the number of MetS components regardless of the combinations of components (0/1, 2, 3 and 4/5). As expected, there was a trend for an increase in body mass index, blood pressure, fasting TAG, glucose and insulin, and a decrease in fasting high-density lipoprotein cholesterol with increasing numbers of MetS components (P≤0.0004). A similar trend was observed for the summary measures of the postprandial TAG and glucose responses. For TAG, the area under the curve (AUC) and maximum concentration (maxC) were significantly greater in men with ≥ 3 than < 3 components (P < 0.001), whereas incremental AUC was greater in those with 3 than 0/1 and 2, and 4/5 compared with 2 components (P < 0.04). For glucose, maxC after the test breakfast (0-330 min) and total AUC (0-480 min) were higher in men with ≥ 3 than < 3 components (P≤0.001). Conclusions Our data analysis has revealed a linear trend between increasing numbers of MetS components and magnitude (AUC) of the postprandial TAG and glucose responses. Furthermore, the two meal challenge discriminated a worsening of postprandial lipaemic control in subjects with ≥ 3 MetS components.

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This paper describes advances in ground-based thermodynamic profiling of the lower troposphere through sensor synergy. The well-documented integrated profiling technique (IPT), which uses a microwave profiler, a cloud radar, and a ceilometer to simultaneously retrieve vertical profiles of temperature, humidity, and liquid water content (LWC) of nonprecipitating clouds, is further developed toward an enhanced performance in the boundary layer and lower troposphere. For a more accurate temperature profile, this is accomplished by including an elevation scanning measurement modus of the microwave profiler. Height-dependent RMS accuracies of temperature (humidity) ranging from 0.3 to 0.9 K (0.5–0.8 g m−3) in the boundary layer are derived from retrieval simulations and confirmed experimentally with measurements at distinct heights taken during the 2005 International Lindenberg Campaign for Assessment of Humidity and Cloud Profiling Systems and its Impact on High-Resolution Modeling (LAUNCH) of the German Weather Service. Temperature inversions, especially of the lower boundary layer, are captured in a very satisfactory way by using the elevation scanning mode. To improve the quality of liquid water content measurements in clouds the authors incorporate a sophisticated target classification scheme developed within the European cloud observing network CloudNet. It allows the detailed discrimination between different types of backscatterers detected by cloud radar and ceilometer. Finally, to allow IPT application also to drizzling cases, an LWC profiling method is integrated. This technique classifies the detected hydrometeors into three different size classes using certain thresholds determined by radar reflectivity and/or ceilometer extinction profiles. By inclusion into IPT, the retrieved profiles are made consistent with the measurements of the microwave profiler and an LWC a priori profile. Results of IPT application to 13 days of the LAUNCH campaign are analyzed, and the importance of integrated profiling for model evaluation is underlined.

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The pig is a single-stomached omnivorous mammal and is an important model of human disease and nutrition. As such, it is necessary to establish a metabolic framework from which pathology-based variation can be compared. Here, a combination of one and two-dimensional (1)H and (13)C nuclear magnetic resonance spectroscopy (NMR) and high-resolution magic angle spinning (HR-MAS) NMR was used to provide a systems overview of porcine metabolism via characterisation of the urine, serum, liver and kidney metabolomes. The metabolites observed in each of these biological compartments were found to be qualitatively comparable to the metabolic signature of the same biological matrices in humans and rodents. The data were modelled using a combination of principal components analysis and Venn diagram mapping. Urine represented the most metabolically distinct biological compartment studied, with a relatively greater number of NMR detectable metabolites present, many of which are implicated in gut-microbial co-metabolic processes. The major inter-species differences observed were in the phase II conjugation of extra-genomic metabolites; the pig was observed to conjugate p-cresol, a gut microbial metabolite of tyrosine, with glucuronide rather than sulfate as seen in man. These observations are important to note when considering the translatability of experimental data derived from porcine models.