Proteomics of synapse

Large-scale phosphoproteome analysis on synaptosome and preparation of post-synaptic density (PSD) were investigated. It was found that protein phosphor is a common event in the synapse, which is consistent with the presence of diverse classes of kinases and phosphatases in the synapse. Synaptic proteomics analysis required the purification of subcellular organelles from the brain regions of interest. Multiple steps of discontinuous density gradient ultra-centrifugation were employed to enrich the distinct organelles. Two-dimensional gel electrophoresis was used to separate and quantify proteins, including post-translational modified forms, from synaptic structures. It was observed that proteomic analysis of the synaptic vesicle identified 36 proteins, including seven integral membrane proteins and vesicle regulatory proteins

CDK5 Is Essential for Soluble Amyloid β-Induced Degradation of GKAP and Remodeling of the Synaptic Actin Cytoskeleton

The early stages of Alzheimer's disease are marked by synaptic dysfunction and loss. This process results from the disassembly and degradation of synaptic components, in particular of scaffolding proteins that compose the post-synaptic density (PSD), namely PSD95, Homer and Shank. Here we investigated in rat frontal cortex dissociated culture the mechanisms involved in the downregulation of GKAP (SAPAP1), which links the PSD95 complex to the Shank complex and cytoskeletal structures within the PSD. We show that Aβ causes the rapid loss of GKAP from synapses through a pathway that critically requires cdk5 activity, and is set in motion by NMDAR activity and Ca2+ influx. We show that GKAP is a direct substrate of cdk5 and that its phosphorylation results in polyubiquitination and proteasomal degradation of GKAP and remodeling (collapse) of the synaptic actin cytoskeleton; the latter effect is abolished in neurons expressing GKAP mutants that are resistant to phosphorylation by cdk5. Given that cdk5 also regulates degradation of PSD95, these results underscore the central position of cdk5 in mediating Aβ-induced PSD disassembly and synapse loss

Supporting genetics in primary care: investigating how theory can inform professional education

Evidence indicates that many barriers exist to the integration of genetic case finding into primary care. We conducted an exploratory study of the determinants of three specific behaviours related to using breast cancer genetics referral guidelines effectively: 'taking a family history', 'making a risk assessment', and 'making a referral decision'. We developed vignettes of primary care consultations with hypothetical patients, representing a wide range of genetic risk for which different referral decisions would be appropriate. We used the Theory of Planned Behavior to develop a survey instrument to capture data on behavioural intention and its predictors (attitude, subjective norm, and perceived behavioural control) for each of the three behaviours and mailed it to a sample of Canadian family physicians. We used correlation and regression analyses to explore the relationships between predictor and dependent variables. The response rate was 96/125 (77%). The predictor variables explained 38-83% of the variance in intention across the three behaviours. Family physicians' intentions were lower for 'making a risk assessment' (perceived as the most difficult) than for the other two behaviours. We illustrate how understanding psychological factors salient to behaviour can be used to tailor professional educational interventions; for example, considering the approach of behavioural rehearsal to improve confidence in skills (perceived behavioural control), or vicarious reinforcement as where participants are sceptical that genetics is consistent with their role (subjective norm)

Identification of Novel Predictor Classifiers for Inflammatory Bowel Disease by Gene Expression Profiling

BACKGROUND: Improvement of patient quality of life is the ultimate goal of biomedical research, particularly when dealing with complex, chronic and debilitating conditions such as inflammatory bowel disease (IBD). This is largely dependent on receiving an accurate and rapid diagnose, an effective treatment and in the prediction and prevention of side effects and complications. The low sensitivity and specificity of current markers burden their general use in the clinical practice. New biomarkers with accurate predictive ability are needed to achieve a personalized approach that take the inter-individual differences into consideration. METHODS: We performed a high throughput approach using microarray gene expression profiling of colon pinch biopsies from IBD patients to identify predictive transcriptional signatures associated with intestinal inflammation, differential diagnosis (Crohn's disease or ulcerative colitis), response to glucocorticoids (resistance and dependence) or prognosis (need for surgery). Class prediction was performed with self-validating Prophet software package. RESULTS: Transcriptional profiling divided patients in two subgroups that associated with degree of inflammation. Class predictors were identified with predictive accuracy ranging from 67 to 100%. The expression accuracy was confirmed by real time-PCR quantification. Functional analysis of the predictor genes showed that they play a role in immune responses to bacteria (PTN, OLFM4 and LILRA2), autophagy and endocytocis processes (ATG16L1, DNAJC6, VPS26B, RABGEF1, ITSN1 and TMEM127) and glucocorticoid receptor degradation (STS and MMD2). CONCLUSIONS: We conclude that using analytical algorithms for class prediction discovery can be useful to uncover gene expression profiles and identify classifier genes with potential stratification utility of IBD patients, a major step towards personalized therapy

Low NKp30, NKp46 and NKG2D expression and reduced cytotoxic activity on NK cells in cervical cancer and precursor lesions

<p>Abstract</p> <p>Background</p> <p>Persistent high risk HPV infection can lead to cervical cancer, the second most common malignant tumor in women worldwide. NK cells play a crucial role against tumors and virus-infected cells through a fine balance between activating and inhibitory receptors. Expression of triggering receptors NKp30, NKp44, NKp46 and NKG2D on NK cells correlates with cytolytic activity against tumor cells, but these receptors have not been studied in cervical cancer and precursor lesions. The aim of the present work was to study NKp30, NKp46, NKG2D, NKp80 and 2B4 expression in NK cells from patients with cervical cancer and precursor lesions, in the context of HPV infection.</p> <p>Methods</p> <p>NKp30, NKp46, NKG2D, NKp80 and 2B4 expression was analyzed by flow cytometry on NK cells from 59 patients with cervical cancer and squamous intraepithelial lesions. NK cell cytotoxicity was evaluated in a 4 hour CFSE/7-AAD flow cytometry assay. HPV types were identified by PCR assays.</p> <p>Results</p> <p>We report here for the first time that NK cell-activating receptors NKp30 and NKp46 are significantly down-regulated in cervical cancer and high grade squamous intraepithelial lesion (HGSIL) patients. NCRs down-regulation correlated with low cytolytic activity, HPV-16 infection and clinical stage. NKG2D was also down-regulated in cervical cancer patients.</p> <p>Conclusion</p> <p>Our results suggest that NKp30, NKp46 and NKG2D down-regulation represent an evasion mechanism associated to low NK cell activity, HPV-16 infection and cervical cancer progression.</p

TGFBR1 Intralocus Epistatic Interaction as a Risk Factor for Colorectal Cancer

In colorectal cancer (CRC), an inherited susceptibility risk affects about 35% of patients, whereas high-penetrance germline mutations account for <6% of cases. A considerable proportion of sporadic tumors could be explained by the coinheritance of multiple low-penetrance variants, some of which are common. We assessed the susceptibility to CRC conferred by genetic variants at the TGFBR1 locus. We analyzed 14 polymorphisms and the allele-specific expression (ASE) of TGFBR1 in 1025 individuals from the Spanish population. A case-control study was undertaken with 504 controls and 521 patients with sporadic CRC. Fourteen polymorphisms located at the TGFBR1 locus were genotyped with the iPLEX Gold (MassARRAY-Sequenom) technology. Descriptive analyses of the polymorphisms and haplotypes and association studies were performed with the SNPator workpackage. No relevant associations were detected between individual polymorphisms or haplotypes and the risk of CRC. The TGFBR1*9A/6A polymorphism was used for the ASE analysis. Heterozygous individuals were analyzed for ASE by fragment analysis using cDNA from normal tissue. The relative level of allelic expression was extrapolated from a standard curve. The cutoff value was calculated with Youden's index. ASE was found in 25.4% of patients and 16.4% of controls. Considering both bimodal and continuous types of distribution, no significant differences between the ASE values of patients and controls were identified. Interestingly, a combined analysis of the polymorphisms and ASE for the association with CRC occurrence revealed that ASE-positive individuals carrying one of the most common haplotypes (H2: 20.7%) showed remarkable susceptibility to CRC (RR: 5.25; 95% CI: 2.547–5.250; p<0.001) with a synergy factor of 3.7. In our study, 54.1% of sporadic CRC cases were attributable to the coinheritance of the H2 haplotype and TGFBR1 ASE. These results support the hypothesis that the allelic architecture of cancer genes, rather than individual polymorphisms, more accurately defines the CRC risk

Evolution of complexity in the zebrafish synapse proteome

The proteome of human brain synapses is highly complex and mutated in over 130 diseases. This complexity arose from two whole genome duplications early in the vertebrate lineage. Zebrafish are used in modelling human diseases, however its synapse proteome is uncharacterised and whether the teleost-specific genome duplication (TSGD) influenced complexity is unknown. We report the characterisation of the proteomes and ultrastructure of central synapses in zebrafish and analyse the importance of the TSGD. While the TSGD increases overall synapse proteome complexity, the Post Synaptic Density (PSD) proteome of zebrafish has lower complexity than mammals. A highly conserved set of ~1000 proteins is shared across vertebrates. PSD ultrastructural features are also conserved. Lineage-specific proteome differences indicate vertebrate species evolved distinct synapse types and functions. The datasets are a resource for a wide range of studies and have important implications for the use of zebrafish in modelling human synaptic diseases

Protein structure and evolution: are they constrained globally by a principle derived from information theory?

That the physicochemical properties of amino acids constrain the structure, function and evolution of proteins is not in doubt. However, principles derived from information theory may also set bounds on the structure (and thus also the evolution) of proteins. Here we analyze the global properties of the full set of proteins in release 13-11 of the SwissProt database, showing by experimental test of predictions from information theory that their collective structure exhibits properties that are consistent with their being guided by a conservation principle. This principle (Conservation of Information) defines the global properties of systems composed of discrete components each of which is in turn assembled from discrete smaller pieces. In the system of proteins, each protein is a component, and each protein is assembled from amino acids. Central to this principle is the inter-relationship of the unique amino acid count and total length of a protein and its implications for both average protein length and occurrence of proteins with specific unique amino acid counts. The unique amino acid count is simply the number of distinct amino acids (including those that are post-translationally modified) that occur in a protein, and is independent of the number of times that the particular amino acid occurs in the sequence. Conservation of Information does not operate at the local level (it is independent of the physicochemical properties of the amino acids) where the influences of natural selection are manifest in the variety of protein structure and function that is well understood. Rather, this analysis implies that Conservation of Information would define the global bounds within which the whole system of proteins is constrained; thus it appears to be acting to constrain evolution at a level different from natural selection, a conclusion that appears counter-intuitive but is supported by the studies described herein

Differential Proteomic Analysis of Mammalian Tissues Using SILAM

Differential expression of proteins between tissues underlies organ-specific functions. Under certain pathological conditions, this may also lead to tissue vulnerability. Furthermore, post-translational modifications exist between different cell types and pathological conditions. We employed SILAM (Stable Isotope Labeling in Mammals) combined with mass spectrometry to quantify the proteome between mammalian tissues. Using 15N labeled rat tissue, we quantified 3742 phosphorylated peptides in nuclear extracts from liver and brain tissue. Analysis of the phosphorylation sites revealed tissue specific kinase motifs. Although these tissues are quite different in their composition and function, more than 500 protein identifications were common to both tissues. Specifically, we identified an up-regulation in the brain of the phosphoprotein, ZFHX1B, in which a genetic deletion causes the neurological disorder Mowat–Wilson syndrome. Finally, pathway analysis revealed distinct nuclear pathways enriched in each tissue. Our findings provide a valuable resource as a starting point for further understanding of tissue specific gene regulation and demonstrate SILAM as a useful strategy for the differential proteomic analysis of mammalian tissues

Identification of Extracellular Segments by Mass Spectrometry Improves Topology Prediction of Transmembrane Proteins

Transmembrane proteins play crucial role in signaling, ion transport, nutrient uptake, as well as in maintaining the dynamic equilibrium between the internal and external environment of cells. Despite their important biological functions and abundance, less than 2% of all determined structures are transmembrane proteins. Given the persisting technical difficulties associated with high resolution structure determination of transmembrane proteins, additional methods, including computational and experimental techniques remain vital in promoting our understanding of their topologies, 3D structures, functions and interactions. Here we report a method for the high-throughput determination of extracellular segments of transmembrane proteins based on the identification of surface labeled and biotin captured peptide fragments by LC/MS/MS. We show that reliable identification of extracellular protein segments increases the accuracy and reliability of existing topology prediction algorithms. Using the experimental topology data as constraints, our improved prediction tool provides accurate and reliable topology models for hundreds of human transmembrane proteins