Influence of dietary protein intake and glycemic index on the association between TCF7L2 HapA and weight gain

BACKGROUND: Genetic polymorphisms of transcription factor 7-like 2 (TCF7L2) have been associated with type 2 diabetes and BMI. OBJECTIVE: The objective was to investigate whether TCF7L2 HapA is associated with weight development and whether such an association is modulated by protein intake or by the glycemic index (GI). DESIGN: The investigation was based on prospective data from 5 cohort studies nested within the European Prospective Investigation into Cancer and Nutrition. Weight change was followed up for a mean (±SD) of 6.8 ± 2.5 y. TCF7L2 rs7903146 and rs10885406 were successfully genotyped in 11,069 individuals and used to derive HapA. Multiple logistic and linear regression analysis was applied to test for the main effect of HapA and its interaction with dietary protein or GI. Analyses from the cohorts were combined by random-effects meta-analysis. RESULTS: HapA was associated neither with baseline BMI (0.03 ± 0.07 BMI units per allele; P = 0.6) nor with annual weight change (8.8 ± 11.7 g/y per allele; P = 0.5). However, a previously shown positive association between intake of protein, particularly of animal origin, and subsequent weight change in this population proved to be attenuated by TCF7L2 HapA (P-interaction = 0.01). We showed that weight gain becomes independent of protein intake with an increasing number of HapA alleles. Substitution of protein with either fat or carbohydrates showed the same effects. No interaction with GI was observed. CONCLUSION: TCF7L2 HapA attenuates the positive association between animal protein intake and long-term body weight change in middle-aged Europeans but does not interact with the GI of the diet.

Uncoupling protein 2 and 3 gene polymorphisms and their association with type 2 diabetes in asian indians

BACKGROUND: this study examined the association of -866G/A, Ala55Val, 45bpI/D, and -55C/T polymorphisms at the uncoupling protein (UCP) 3-2 loci with type 2 diabetes in Asian Indians. METHODS: a case-control study was performed among 1,406 unrelated subjects (487 with type 2 diabetes and 919 normal glucose-tolerant [NGT]), chosen from the Chennai Urban Rural Epidemiology Study, an ongoing population-based study in Southern India. The polymorphisms were genotyped using polymerase chain reaction-restriction fragment length polymorphism and direct sequencing. Haplotype frequencies were estimated using an expectation-maximization algorithm. Linkage disequilibrium was estimated from the estimates of haplotypic frequencies. RESULTS: the genotype (P = 0.00006) and the allele (P = 0.00007) frequencies of Ala55Val of the UCP2 gene showed a significant protective effect against the development of type 2 diabetes. The odds ratios (adjusted for age, sex, and body mass index) for diabetes for individuals carrying Ala/Val was 0.72, and that for individuals carrying Val/Val was 0.37. Homeostasis insulin resistance model assessment and 2-h plasma glucose were significantly lower among Val-allele carriers compared to the Ala/Ala genotype within the NGT group. The genotype (P = 0.02) and the allele (P = 0.002) frequencies of -55C/T of the UCP3 gene showed a significant protective effect against the development of diabetes. The odds ratio for diabetes for individuals carrying CT was 0.79, and that for individuals carrying TT was 0.61. The haplotype analyses further confirmed the association of Ala55Val with diabetes, where the haplotypes carrying the Ala allele were significantly higher in the cases compared to controls. CONCLUSIONS: Ala55Val and -55C/T polymorphisms at the UCP3-2 loci are associated with a significantly reduced risk of developing type 2 diabetes in Asian Indians.

IntFOLD: an integrated server for modelling protein structures and functions from amino acid sequences

IntFOLD is an independent web server that integrates our leading methods for structure and function prediction. The server provides a simple unified interface that aims to make complex protein modelling data more accessible to life scientists. The server web interface is designed to be intuitive and integrates a complex set of quantitative data, so that 3D modelling results can be viewed on a single page and interpreted by non-expert modellers at a glance. The only required input to the server is an amino acid sequence for the target protein. Here we describe major performance and user interface updates to the server, which comprises an integrated pipeline of methods for: tertiary structure prediction, global and local 3D model quality assessment, disorder prediction, structural domain prediction, function prediction and modelling of protein-ligand interactions. The server has been independently validated during numerous CASP (Critical Assessment of Techniques for Protein Structure Prediction) experiments, as well as being continuously evaluated by the CAMEO (Continuous Automated Model Evaluation) project. The IntFOLD server is available at: http://www.reading.ac.uk/bioinf/IntFOLD/

Disorder prediction methods, their applicability to different protein targets and their usefulness for guiding experimental studies

The role and function of a given protein is dependent on its structure. In recent years, however, numerous studies have highlighted the importance of unstructured, or disordered regions in governing a protein’s function. Disordered proteins have been found to play important roles in pivotal cellular functions, such as DNA binding and signalling cascades. Studying proteins with extended disordered regions is often problematic as they can be challenging to express, purify and crystallise. This means that interpretable experimental data on protein disorder is hard to generate. As a result, predictive computational tools have been developed with the aim of predicting the level and location of disorder within a protein. Currently, over 60 prediction servers exist, utilizing different methods for classifying disorder and different training sets. Here we review several good performing, publicly available prediction methods, comparing their application and discussing how disorder prediction servers can be used to aid the experimental solution of protein structure. The use of disorder prediction methods allows us to adopt a more targeted approach to experimental studies by accurately identifying the boundaries of ordered protein domains so that they may be investigated separately, thereby increasing the likelihood of their successful experimental solution.

A high-density immunoblotting methodology for quantification of total protein levels and phosphorylation modifications

The components of many signaling pathways have been identified and there is now a need to conduct quantitative data-rich temporal experiments for systems biology and modeling approaches to better understand pathway dynamics and regulation. Here we present a modified Western blotting method that allows the rapid and reproducible quantification and analysis of hundreds of data points per day on proteins and their phosphorylation state at individual sites. The approach is of particular use where samples show a high degree of sample-to-sample variability such as primary cells from multiple donors. We present a case study on the analysis of >800 phosphorylation data points from three phosphorylation sites in three signaling proteins over multiple time points from platelets isolated from ten donors, demonstrating the technique's potential to determine kinetic and regulatory information from limited cell numbers and to investigate signaling variation within a population. We envisage the approach being of use in the analysis of many cellular processes such as signaling pathway dynamics to identify regulatory feedback loops and the investigation of potential drug/inhibitor responses, using primary cells and tissues, to generate information about how a cell's physiological state changes over time.

Molecular mechanisms of crosstalk between thyroid hormones and estrogens

Purpose of review Novel analyses of the relations between thyroid hormone receptor signaling and estrogen receptor—dependent mechanisms are timely for two sets of reasons. Clinically, both affect mood and foster neuronal growth and regeneration. Mechanistically, they overlap at the levels of DNA recognition elements, coactivators, and signal transduction systems. Crosstalk between thyroid hormone receptors and estrogen receptors is possibly important to integrate external signals to transcription within neurons. Recent findings It has been shown that reproductive functions, including behaviors, driven by estrogens can be antagonized by thyroid hormones, and it has been argued that such crosstalk is biologically adaptive to ensure optimal reproduction. Transcriptional facilitation during transient transfunction studies show that the interactions between thyroid receptor isoforms and estrogen receptor isoforms depend on cell type and promoter context. Overall, this pattern of interactions assures multiple and flexible means of transcriptional regulation. Surprisingly, in some brain areas, thyroid hormone actions can synergize with estrogenic effects, particularly when nongenomic modes of action are considered, such as kinase activation, which, as has been reported, affect later estrogen receptor—induced genomic events. Summary In summary, recent work with nerve cells has contributed to a paradigm shift in how the molecular and behavioral effects of hormones which act through nuclear receptors are viewed.

Study of tyrosine kinases and protein tyrosine phosphorylation

In recent years, our increased understanding of the complex signal transduction mechanisms that regulate cellular function has fueled huge advances in all aspects of biomedical science and cell biology. Platelet and megakaryocyte function is no exception to this. In the last 10 yr our understanding of the receptor biochemistry and the systems that they control has been pivotal in the development of new strategies to inhibit platelet function and thereby prevent thrombosis. Experimental techniques have become more and more elegant, however; the basic toolbox that a researcher requires to study signaling in platelets and megakaryoctes is described in this and several subsequent chapters.

Protein kinase D isoforms are expressed in rat and mouse primary sensory neurons and are activated by agonists of protease-activated receptor 2

Serine proteases generated during injury and inflammation cleave protease-activated receptor 2 (PAR(2)) on primary sensory neurons to induce neurogenic inflammation and hyperalgesia. Hyperalgesia requires sensitization of transient receptor potential vanilloid (TRPV) ion channels by mechanisms involving phospholipase C and protein kinase C (PKC). The protein kinase D (PKD) serine/threonine kinases are activated by diacylglycerol and PKCs and can phosphorylate TRPV1. Thus, PKDs may participate in novel signal transduction pathways triggered by serine proteases during inflammation and pain. However, it is not known whether PAR(2) activates PKD, and the expression of PKD isoforms by nociceptive neurons is poorly characterized. By using HEK293 cells transfected with PKDs, we found that PAR(2) stimulation promoted plasma membrane translocation and phosphorylation of PKD1, PKD2, and PKD3, indicating activation. This effect was partially dependent on PKCepsilon. By immunofluorescence and confocal microscopy, with antibodies against PKD1/PKD2 and PKD3 and neuronal markers, we found that PKDs were expressed in rat and mouse dorsal root ganglia (DRG) neurons, including nociceptive neurons that expressed TRPV1, PAR(2), and neuropeptides. PAR(2) agonist induced phosphorylation of PKD in cultured DRG neurons, indicating PKD activation. Intraplantar injection of PAR(2) agonist also caused phosphorylation of PKD in neurons of lumbar DRG, confirming activation in vivo. Thus, PKD1, PKD2, and PKD3 are expressed in primary sensory neurons that mediate neurogenic inflammation and pain transmission, and PAR(2) agonists activate PKDs in HEK293 cells and DRG neurons in culture and in intact animals. PKD may be a novel component of a signal transduction pathway for protease-induced activation of nociceptive neurons and an important new target for antiinflammatory and analgesic therapies.

Phenolic acid intake, delivered via moderate champagne wine consumption, improves spatial working memory via the modulation of hippocampal and cortical protein expression/activation.

Aims: While much data exist for the effects of flavonoid-rich foods on spatial memory in rodents, there are no such data for foods/beverages predominantly containing hydroxycinnamates and phenolic acids. To address this, we investigated the effects of moderate Champagne wine intake, which is rich in these components, on spatial memory and related mechanisms relative to the alcohol- and energy-matched controls. Results: In contrast to the isocaloric and alcohol-matched controls, supplementation with Champagne wine (1.78 ml/kg BW, alcohol 12.5% vol.) for 6 weeks led to an improvement in spatial working memory in aged rodents. Targeted protein arrays indicated that these behavioral effects were paralleled by the differential expression of a number of hippocampal and cortical proteins (relative to the isocaloric control group), including those involved in signal transduction, neuroplasticity, apoptosis, and cell cycle regulation. Western immunoblotting confirmed the differential modulation of brain-derived neurotrophic factor, cAMP response-element-binding protein (CREB), p38, dystrophin, 2',3'-cyclic-nucleotide 3'-phosphodiesterase, mammalian target of rapamycin (mTOR), and Bcl-xL in response to Champagne supplementation compared to the control drink, and the modulation of mTOR, Bcl-xL, and CREB in response to alcohol supplementation. Innovation: Our data suggest that smaller phenolics such as gallic acid, protocatechuic acid, tyrosol, caftaric acid, and caffeic acid, in addition to flavonoids, are capable of exerting improvements in spatial memory via the modulation in hippocampal signaling and protein expression. Conclusion: Changes in spatial working memory induced by the Champagne supplementation are linked to the effects of absorbed phenolics on cytoskeletal proteins, neurotrophin expression, and the effects of alcohol on the regulation of apoptotic events in the hippocampus and cortex. Antioxid. Redox Signal. 00, 000-000.