SDF-1 Enhances Wound Healing of Critical-Sized Calvarial Defects beyond Self-Repair Capacity

Host blood circulating stem cells are an important cell source that participates in the repair of damaged tissues. The clinical challenge is how to improve the recruitment of circulating stem cells into the local wound area and enhance tissue regeneration. Stromal-derived factor-1 (SDF-1) has been shown to be a potent chemoattractant of blood circulating stem cells into the local wound microenvironment. In order to investigate effects of SDF-1 on bone development and the repair of a large bone defect beyond host self-repair capacity, the BMP-induced subcutaneous ectopic bone formation and calvarial critical-sized defect murine models were used in this preclinical study. A dose escalation of SDF-1 were loaded into collagen scaffolds containing BMP, VEGF, or PDGF, and implanted into subcutaneous sites at mouse dorsa or calvarial critical-sized bone defects for 2 and 4 weeks. The harvested biopsies were examined by microCT and histology. The results demonstrated that while SDF-1 had no effect in the ectopic bone model in promoting de novo osteogenesis, however, in the orthotopic bone model of the critical-sized defects, SDF-1 enhanced calvarial critical-sized bone defect healing similar to VEGF, and PDGF. These results suggest that SDF-1 plays a role in the repair of large critical-sized defect where more cells are needed while not impacting de novo bone formation, which may be associated with the functions of SDF-1 on circulating stem cell recruitment and angiogenesis.     

NBLAST: a cluster variant of BLAST for NxN comparisons

Background  

The BLAST algorithm compares biological sequences to one another in order to determine shared motifs and common ancestry. However, the comparison of all non-redundant (NR) sequences against all other NR sequences is a computationally intensive task. We developed NBLAST as a cluster computer implementation of the BLAST family of sequence comparison programs for the purpose of generating pre-computed BLAST alignments and neighbour lists of NR sequences.     

Cell Population Kinetics of Collagen Scaffolds in Ex Vivo Oral Wound Repair

Biodegradable collagen scaffolds are used clinically for oral soft tissue augmentation to support wound healing. This study sought to provide a novel ex vivo model for analyzing healing kinetics and gene expression of primary human gingival fibroblasts (hGF) within collagen scaffolds. Sponge type and gel type scaffolds with and without platelet-derived growth factor-BB (PDGF) were assessed in an hGF containing matrix. Morphology was evaluated with scanning electron microscopy, and hGF metabolic activity using MTT. We quantitated the population kinetics within the scaffolds based on cell density and distance from the scaffold border of DiI-labled hGFs over a two-week observation period. Gene expression was evaluated with gene array and qPCR. The sponge type scaffolds showed a porous morphology. Absolute cell number and distance was higher in sponge type scaffolds when compared to gel type scaffolds, in particular during the first week of observation. PDGF incorporated scaffolds increased cell numbers, distance, and formazan formation in the MTT assay. Gene expression dynamics revealed the induction of key genes associated with the generation of oral tissue. DKK1, CYR61, CTGF, TGFBR1 levels were increased and integrin ITGA2 levels were decreased in the sponge type scaffolds compared to the gel type scaffold. The results suggest that this novel model of oral wound healing provides insights into population kinetics and gene expression dynamics of biodegradable scaffolds.     

PreBIND and Textomy – mining the biomedical literature for protein-protein interactions using a support vector machine

Background

The majority of experimentally verified molecular interaction and biological pathway data are present in the unstructured text of biomedical journal articles where they are inaccessible to computational methods. The Biomolecular interaction network database (BIND) seeks to capture these data in a machine-readable format. We hypothesized that the formidable task-size of backfilling the database could be reduced by using Support Vector Machine technology to first locate interaction information in the literature. We present an information extraction system that was designed to locate protein-protein interaction data in the literature and present these data to curators and the public for review and entry into BIND.

Results

Cross-validation estimated the support vector machine's test-set precision, accuracy and recall for classifying abstracts describing interaction information was 92%, 90% and 92% respectively. We estimated that the system would be able to recall up to 60% of all non-high throughput interactions present in another yeast-protein interaction database. Finally, this system was applied to a real-world curation problem and its use was found to reduce the task duration by 70% thus saving 176 days.

Conclusions

Machine learning methods are useful as tools to direct interaction and pathway database back-filling; however, this potential can only be realized if these techniques are coupled with human review and entry into a factual database such as BIND. The PreBIND system described here is available to the public at http://bind.ca. Current capabilities allow searching for human, mouse and yeast protein-interaction information.     

An automated method for finding molecular complexes in large protein interaction networks

Background  

Recent advances in proteomics technologies such as two-hybrid, phage display and mass spectrometry have enabled us to create a detailed map of biomolecular interaction networks. Initial mapping efforts have already produced a wealth of data. As the size of the interaction set increases, databases and computational methods will be required to store, visualize and analyze the information in order to effectively aid in knowledge discovery.     

Adenoviral gene transfer of PDGF downregulates gas gene product PDGFalphaR and prolongs ERK and Akt/PKB activation

The delivery of platelet-derivedgrowth factor (PDGF) for tissue engineering of skin and periodontalwounds has become an active area of interest. However, little is knownregarding the extended effects of PDGF on cell signaling via genetherapy and how such an approach facilitates the exiting of cells fromgrowth arrest and entry to competence required for cell cycling. Weshow in vitro expression and secretion of PDGF-AA by recombinantadenovirus encoding the PDGF-A gene (Ad-PDGF-A). The bioactivePDGF-AA protein released induces sustained downregulation of PDGFRthat is encoded by a growth arrest-specific (gas)gene. Ad-PDGF-A induces sustained phosphorylation of PDGFR as wellas prolonged phosphorylation of downstream extracellularsignal-regulated kinase 1/2 and Akt signaling pathways. Furthermore,the phosphorylation of PDGFR is abolished by cotransducing cellswith adenovirus encoding a dominant negative mutant of the PDGF-A genethat disrupts PDGF bioactivity. These findings demonstrate theprolonged effects of adenoviral delivery of PDGF and aid in the betterunderstanding of sustained PDGF signaling.

     

Domain-based small molecule binding site annotation

Background  

Accurate small molecule binding site information for a protein can facilitate studies in drug docking, drug discovery and function prediction, but small molecule binding site protein sequence annotation is sparse. The Small Molecule Interaction Database (SMID), a database of protein domain-small molecule interactions, was created using structural data from the Protein Data Bank (PDB). More importantly it provides a means to predict small molecule binding sites on proteins with a known or unknown structure and unlike prior approaches, removes large numbers of false positive hits arising from transitive alignment errors, non-biologically significant small molecules and crystallographic conditions that overpredict ion binding sites.     

Porphyromonas gingivalis oral infection exacerbates the development and severity of collagen-induced arthritis

Introduction

Clinical studies suggest a direct influence of periodontal disease (PD) on serum inflammatory markers and disease assessment of patients with established rheumatoid arthritis (RA). However, the influence of PD on arthritis development remains unclear. This investigation was undertaken to determine the contribution of chronic PD to immune activation and development of joint inflammation using the collagen-induced arthritis (CIA) model.

Methods

DBA1/J mice orally infected with Porphyromonas gingivalis were administered with collagen II (CII) emulsified in complete Freund’s adjuvant (CFA) or incomplete Freund’s adjuvant (IFA) to induce arthritis. Arthritis development was assessed by visual scoring of paw swelling, caliper measurement of the paws, mRNA expression, paw micro-computed tomography (micro-CT) analysis, histology, and tartrate resistant acid phosphatase for osteoclast detection (TRAP)-positive immunohistochemistry. Serum and reactivated splenocytes were evaluated for cytokine expression.

Results

Mice induced for PD and/or arthritis developed periodontal disease, shown by decreased alveolar bone and alteration of mRNA expression in gingival tissues and submandibular lymph nodes compared to vehicle. P. gingivalis oral infection increased paw swelling and osteoclast numbers in mice immunized with CFA/CII. Arthritis incidence and severity were increased by P. gingivalis in mice that received IFA/CII immunizations. Increased synovitis, bone erosions, and osteoclast numbers in the paws were observed following IFA/CII immunizations in mice infected with P gingivalis. Furthermore, cytokine analysis showed a trend toward increased serum Th17/Th1 ratios when P. gingivalis infection was present in mice receiving either CFA/CII or IFA/CII immunizations. Significant cytokine increases induced by P. gingivalis oral infection were mostly associated to Th17-related cytokines of reactivated splenic cells, including IL-1β, IL-6, and IL-22 in the CFA/CII group and IL-1β, tumor necrosis factor-α, transforming growth factor-β, IL-6 and IL-23 in the IFA/CII group.

Conclusions

Chronic P. gingivalis oral infection prior to arthritis induction increases the immune system activation favoring Th17 cell responses, and ultimately accelerating arthritis development. These results suggest that chronic oral infection may influence RA development mainly through activation of Th17-related pathways.