Immunocytochemical Localization of Substance P Receptors (NK-1 Receptors) in Human Gingival Tissue

Substance P (SP) is a member of the structurally related family of neuropeptides known as the tachykinins. In addition to neurotransmitter roles, the tachykinins are also known to modulate local inflammation which depends on signalling between the neuropeptide molecules and target cells and tissues. SP mediates its effects through a specific receptor, known as the substance P receptor or the neurokinin 1 (NK-1) receptor. The NK-1 receptor is a G-protein associated integral membrane protein and although it has been studied in a wide range of tissues, to date there has been no published data on the localisation of the NK-1 receptor in human gingival tissue. Objective: The aim of this study was to examine the distribution of the NK-1 receptor in human gingival tissue using immunocytochemistry. Method: Gingival tissue was obtained from patients undergoing periodontal surgery. Tissue was fixed in paraformaldehyde and embedded in wax for sectioning. Sections were dewaxed in xylene and then rehydrated in alcohols and phosphate buffered saline. Rehydrated sections were probed with rabbit polyclonal antibody to human NK-1 receptor which was subsequently detected using anti-rabbit horseradish peroxidase conjugate and diaminobenzidine as substrate. Results: Immunocytochemistry revealed that the NK-1 receptor was distributed along nerve fibres and blood vessel endothelial cells, suggesting these areas are main targets for the actions of SP via the NK-1 receptor. Conclusion: This is the first immunocytochemical report of NK-1 receptors in human gingival tissue and provides evidence for possible NK-1 mediated biological effects of SP in human gingival tissue from periodontitis patients.

CGRP-cleavage enzyme detection using a biotinylated hydroxymate affinity probe

Introduction: Neuropeptides contribute to the pathophysiology of peripheral inflammation and a neurogenic component has been described for many inflammatory diseases, including periodontitis. Neuropeptides are susceptible to cleavage by peptidases and therefore the exact location and level of expression of peptidases are major determinants of neuropeptide action. Previous studies by our research group suggested that levels of the neuropeptide calcitonin gene-related peptide (CGRP) may be regulated by peptidases present in gingival crevicular fluid (GCF). Objectives: The aim of this work was to purify and partially characterize the GCF enzyme responsible for CGRP degradation using a biotinylated hydroxymate affinity probe (based on the P1-P4 amino acid sequence of the observed cleavage site) which we previously showed to inhibit CGRP degradation. Methods: Pooled healthy and pooled periodontitis GCF samples were subject to a pre-clear step with magnetic streptavadin beads. Healthy and diseased samples were incubated with the biotinylated hydroxymate probe (20 uM) after which biotinylated proteins were purified from the sample using magnetic streptavadin beads. Bound proteins were subjected to SDS-PAGE and western blotting. Biotin incorporated proteins were disclosed using a streptavadin horse radish peroxidase conjugate. Results: A band was disclosed in the periodontitis pooled sample at a molecular weight of approximately 60 kDa. The band was absent in the pooled healthy samples. As expected, when periodontitis samples were pre-boiled to denature proteins before the addition of the hydroxymate probe, no biotin incorporated band was present. Conclusions: This work demonstrates the purification and disclosure of a protein found specifically in periodontitis which binds to the specific biotinylated hydroxymate affinity probe based on the cleavage site of CGRP only when in its native form. We intend to scale up the sample size thus allowing the identification of the putative CGRP degrading peptidase using MALDI-mass spectrometry.
Funded by an IADR/GlaxoSmithKline Innovation in Oral Care Award

Lateral bias and temperament in the domestic cat (Felis silvestris)

Research points to a relationship between lateralization and emotional functioning in humans and many species of animal. The present study explored the association between paw preferences and emotional functioning, specifically temperament, in a species thus far overlooked in this area, the domestic cat. Thirty left-pawed, 30 right-pawed, and 30 ambilateral pet cats were recruited following an assessment of their paw preferences using a food-reaching challenge. The animals’ temperament was subsequently assessed using the Feline Temperament Profile (FTP). Cats’ owners also completed a purpose-designed cat temperament (CAT) scale. Analysis revealed a significant relationship between lateral bias and FTP and CAT scale scores. Ambilateral cats had lower positive (FTP+) scores, and were perceived as less affectionate, obedient, friendly, and more aggressive, than left or right-pawed animals. Left and right pawed cats differed significantly on 1 trait on the CAT scale, namely playfulness. The strength of the cats’ paw preferences was related to the animals’ FTP and CAT scores. Cats with a greater strength of paw preference had higher FTP + scores than those with a weaker strength of paw preference. Animals with stronger paw preferences were perceived as more confident, affectionate, active, and friendly than those with weaker paw preferences. Results suggest that motor laterality in the cat is strongly related to temperament and that the presence or absence of lateralization has greater implications for the expression of emotion in this species than the direction of the lateralized bias.

The role of glycans in the development and progression of prostate cancer

Prostate cancer is a unique and heterogeneous disease. Currently, a major unmet clinical need exists to develop biomarkers that enable indolent disease to be distinguished from aggressive disease. The prostate is an abundant secretor of glycoproteins of all types, and alterations in glycans are, therefore, attractive as potential biomarkers and therapeutic targets. Despite progress over the past decade in profiling the genome and proteome, the prostate cancer glycoproteome remains relatively understudied. A wide range of alterations in the glycoproteins on prostate cancer cells can occur, including increased sialylation and fucosylation, increased O-β-N-acetylglucosamine (GlcNAc) conjugation, the emergence of cryptic and high-mannose N-glycans and alterations to proteoglycans. Glycosylation can alter protein function and has a key role in many important biological processes in cancer including cell adhesion, migration, interactions with the cell matrix, immune surveillance, cell signalling and cellular metabolism; altered glycosylation in prostate cancer might modify some, or all of these processes. In the past three years, powerful tools such as glycosylation-specific antibodies and glycosylation gene signatures have been developed, which enable detailed analyses of changes in glycosylation. Thus, emerging data on these often overlooked modifications have the potential to improve risk stratification and therapeutic strategies in patients with prostate cancer.

Network signatures based on gene pair expression ratios improve classification and the analysis of muscle-invasive urothelial cancer

Urothelial cancer (UC) is highly recurrent and can progress from non-invasive (NMIUC) to a more aggressive muscle-invasive (MIUC) subtype that invades the muscle tissue layer of the bladder. We present a proof of principle study that network-based features of gene pairs can be used to improve classifier performance and the functional analysis of urothelial cancer gene expression data. In the first step of our procedure each individual sample of a UC gene expression dataset is inflated by gene pair expression ratios that are defined based on a given network structure. In the second step an elastic net feature selection procedure for network-based signatures is applied to discriminate between NMIUC and MIUC samples. We performed a repeated random subsampling cross validation in three independent datasets. The network signatures were characterized by a functional enrichment analysis and studied for the enrichment of known cancer genes. We observed that the network-based gene signatures from meta collections of proteinprotein interaction (PPI) databases such as CPDB and the PPI databases HPRD and BioGrid improved the classification performance compared to single gene based signatures. The network based signatures that were derived from PPI databases showed a prominent enrichment of cancer genes (e.g., TP53, TRIM27 and HNRNPA2Bl). We provide a novel integrative approach for large-scale gene expression analysis for the identification and development of novel diagnostical targets in bladder cancer. Further, our method allowed to link cancer gene associations to network-based expression signatures that are not observed in gene-based expression signatures.