Periodontal regeneration and mesenchymal stem cells

The ultimate goal of periodontal therapy is to regenerate periodontal supporting tissues, but this is hard to achieve as the results of periodontal techniques for regeneration are clinically unpredictable. Stem cells owing to their plasticity and proliferation potential provides a new paradigm for periodontal regeneration. Stem cells from mesenchyme can self renew and generate new dental tissues (including dentin and cementum), alveolar bone and periodontal ligament, and thus they have great potential in periodontal regeneration. This chapter presents an insight into mesenchymal stem cells and their potential use in periodontal regeneration. In this chapter the cellular and molecular biology in periodontal regeneration will be introduced, followed by a range of conventional surgical procedures for periodontal regeneration will be discussed. Mesenchymal stem cells applied in regenerated periodontal tissue and their biological characterizations in vitro will be also introduced. Lastly, the use of mesenchymal stem cell to repair periodontal tissues in large animal models will be also reviewed.

Probability distributed time delays: integrating spatial effects into temporal models

Background In order to provide insights into the complex biochemical processes inside a cell, modelling approaches must find a balance between achieving an adequate representation of the physical phenomena and keeping the associated computational cost within reasonable limits. This issue is particularly stressed when spatial inhomogeneities have a significant effect on system's behaviour. In such cases, a spatially-resolved stochastic method can better portray the biological reality, but the corresponding computer simulations can in turn be prohibitively expensive. Results We present a method that incorporates spatial information by means of tailored, probability distributed time-delays. These distributions can be directly obtained by single in silico or a suitable set of in vitro experiments and are subsequently fed into a delay stochastic simulation algorithm (DSSA), achieving a good compromise between computational costs and a much more accurate representation of spatial processes such as molecular diffusion and translocation between cell compartments. Additionally, we present a novel alternative approach based on delay differential equations (DDE) that can be used in scenarios of high molecular concentrations and low noise propagation. Conclusions Our proposed methodologies accurately capture and incorporate certain spatial processes into temporal stochastic and deterministic simulations, increasing their accuracy at low computational costs. This is of particular importance given that time spans of cellular processes are generally larger (possibly by several orders of magnitude) than those achievable by current spatially-resolved stochastic simulators. Hence, our methodology allows users to explore cellular scenarios under the effects of diffusion and stochasticity in time spans that were, until now, simply unfeasible. Our methodologies are supported by theoretical considerations on the different modelling regimes, i.e. spatial vs. delay-temporal, as indicated by the corresponding Master Equations and presented elsewhere.

The waddlia genome: A window into chlamydial biology

Growing evidence suggests that a novel member of the Chlamydiales order, Waddlia chondrophila, is a potential agent of miscarriage in humans and abortion in ruminants. Due to the lack of genetic tools to manipulate chlamydia, genomic analysis is proving to be the most incisive tool in stimulating investigations into the biology of these obligate intracellular bacteria. 454/Roche and Solexa/Illumina technologies were thus used to sequence and assemble de novo the full genome of the first representative of the Waddliaceae family, W. chondrophila. The bacteria possesses a 2′116′312bp chromosome and a 15′593 bp low-copy number plasmid that might integrate into the bacterial chromosome. The Waddlia genome displays numerous repeated sequences indicating different genome dynamics from classical chlamydia which almost completely lack repetitive elements. Moreover, W. chondrophila exhibits many virulence factors also present in classical chlamydia, including a functional type III secretion system, but also a large complement of specific factors for resistance to host or environmental stresses. Large families of outer membrane proteins were identified indicating that these highly immunogenic proteins are not Chlamydiaceae specific and might have been present in their last common ancestor. Enhanced metabolic capability for the synthesis of nucleotides, amino acids, lipids and other co-factors suggests that the common ancestor of the modern Chlamydiales may have been less dependent on their eukaryotic host. The fine-detailed analysis of biosynthetic pathways brings us closer to possibly developing a synthetic medium to grow W. chondrophila, a critical step in the development of genetic tools. As a whole, the availability of the W. chondrophila genome opens new possibilities in Chlamydiales research, providing new insights into the evolution of members of the order Chlamydiales and the biology of the Waddliaceae.

A genome-based strategy uncovers frequent BRAF mutations in melanoma

Using a genome-scanning approach to search for oncogenes, a recent report identifies somatic mutations in the signaling gene BRAF that are particularly prevalent in melanoma.

Lucky draw in the gene raffle

The Cancer Genome Project intends to search every human gene for cancer-related mutations. Its first success is the discovery of such mutations in the BRAF gene.

High frequency of BRAF mutations in nevi

To evaluate the timing of mutations in BRAF (v-raf murine sarcoma viral oncogene homolog B1) during melanocytic neoplasia, we carried out mutation analysis on microdissected melanoma and nevi samples. We observed mutations resulting in the V599E amino-acid substitution in 41 of 60 (68%) melanoma metastases, 4 of 5 (80%) primary melanomas and, unexpectedly, in 63 of 77 (82%) nevi. These data suggest that mutational activation of the RAS/RAF/MAPK pathway in nevi is a critical step in the initiation of melanocytic neoplasia but alone is insufficient for melanoma tumorigenesis.

A biphasic scaffold design combined with cell sheet technology for simultaneous regeneration of alveolar bone/periodontal ligament complex

This study describes the design of a biphasic scaffold composed of a Fused Deposition Modeling scaffold (bone compartment) and an electrospun membrane (periodontal compartment) for periodontal regeneration. In order to achieve simultaneous alveolar bone and periodontal ligament regeneration a cell-based strategy was carried out by combining osteoblast culture in the bone compartment and placement of multiple periodontal ligament (PDL) cell sheets on the electrospun membrane. In vitro data showed that the osteoblasts formed mineralized matrix in the bone compartment after 21 days in culture and that the PDL cell sheet harvesting did not induce significant cell death. The cell-seeded biphasic scaffolds were placed onto a dentin block and implanted for 8 weeks in an athymic rat subcutaneous model. The scaffolds were analyzed by μCT, immunohistochemistry and histology. In the bone compartment, a more intense ALP staining was obtained following seeding with osteoblasts, confirming the μCT results which showed higher mineralization density for these scaffolds. A thin mineralized cementum-like tissue was deposited on the dentin surface for the scaffolds incorporating the multiple PDL cell sheets, as observed by H&E and Azan staining. These scaffolds also demonstrated better attachment onto the dentin surface compared to no attachment when no cell sheets were used. In addition, immunohistochemistry revealed the presence of CEMP1 protein at the interface with the dentine. These results demonstrated that the combination of multiple PDL cell sheets and a biphasic scaffold allows the simultaneous delivery of the cells necessary for in vivo regeneration of alveolar bone, periodontal ligament and cementum. © 2012 Elsevier Ltd.

An analytical tool that quantifies cellular morphology changes from three-dimensional fluorescence images

The most common software analysis tools available for measuring fluorescence images are for two-dimensional (2D) data that rely on manual settings for inclusion and exclusion of data points, and computer-aided pattern recognition to support the interpretation and findings of the analysis. It has become increasingly important to be able to measure fluorescence images constructed from three-dimensional (3D) datasets in order to be able to capture the complexity of cellular dynamics and understand the basis of cellular plasticity within biological systems. Sophisticated microscopy instruments have permitted the visualization of 3D fluorescence images through the acquisition of multispectral fluorescence images and powerful analytical software that reconstructs the images from confocal stacks that then provide a 3D representation of the collected 2D images. Advanced design-based stereology methods have progressed from the approximation and assumptions of the original model-based stereology(1) even in complex tissue sections(2). Despite these scientific advances in microscopy, a need remains for an automated analytic method that fully exploits the intrinsic 3D data to allow for the analysis and quantification of the complex changes in cell morphology, protein localization and receptor trafficking. Current techniques available to quantify fluorescence images include Meta-Morph (Molecular Devices, Sunnyvale, CA) and Image J (NIH) which provide manual analysis. Imaris (Andor Technology, Belfast, Northern Ireland) software provides the feature MeasurementPro, which allows the manual creation of measurement points that can be placed in a volume image or drawn on a series of 2D slices to create a 3D object. This method is useful for single-click point measurements to measure a line distance between two objects or to create a polygon that encloses a region of interest, but it is difficult to apply to complex cellular network structures. Filament Tracer (Andor) allows automatic detection of the 3D neuronal filament-like however, this module has been developed to measure defined structures such as neurons, which are comprised of dendrites, axons and spines (tree-like structure). This module has been ingeniously utilized to make morphological measurements to non-neuronal cells(3), however, the output data provide information of an extended cellular network by using a software that depends on a defined cell shape rather than being an amorphous-shaped cellular model. To overcome the issue of analyzing amorphous-shaped cells and making the software more suitable to a biological application, Imaris developed Imaris Cell. This was a scientific project with the Eidgenössische Technische Hochschule, which has been developed to calculate the relationship between cells and organelles. While the software enables the detection of biological constraints, by forcing one nucleus per cell and using cell membranes to segment cells, it cannot be utilized to analyze fluorescence data that are not continuous because ideally it builds cell surface without void spaces. To our knowledge, at present no user-modifiable automated approach that provides morphometric information from 3D fluorescence images has been developed that achieves cellular spatial information of an undefined shape (Figure 1). We have developed an analytical platform using the Imaris core software module and Imaris XT interfaced to MATLAB (Mat Works, Inc.). These tools allow the 3D measurement of cells without a pre-defined shape and with inconsistent fluorescence network components. Furthermore, this method will allow researchers who have extended expertise in biological systems, but not familiarity to computer applications, to perform quantification of morphological changes in cell dynamics.

Vitronectin – master controller or micromanager?

The concept of the cellular glycoprotein vitronectin acts as a biological ‘glue’ and key controller of mammalian tissue repair and remodelling activity is emerging from nearly 50 years of experimental in vitro and in vivo data. Unexpectedly, the vitronectin-knock-out mouse was found to be viable and to have largely normal phenotype. However, diligent observation revealed that the VN-KO animal exhibits delayed coagulation and poor wound healing. This is interpreted to indicate that vitronectin occupies a role in the earliest events of thrombogenesis and tissue repair. That role is as a foundation upon which the thrombus grows in an organised structure. In addition to closing the wound, the thrombus also serves to protect the underlying tissue from oxidation, is a reservoir of mitogens and tissue repair mediators and provides a provisional scaffold for the repairing tissue. In the absence of vitronectin (e.g. VN-KO animal) this cascade is disrupted before it begins. Our data demonstrates that a wide variety of biologically active species associate with VN. While initial studies were focused on mitogens, other classes of bioactives (e.g. glycosaminoglycans, metalloproteinases) are now also known to specifically interact with VN. Many of these interactions are long-lived, often resulting in multi-protein complexes, while others are stable for prolonged periods. Multiprotein complexes provide several advantages: prolonging molecular interaction; sustaining local concentrations, facilitating co-stimulation of cell surface receptors and thereby enhancing cellular / biological responses. We contend that these, or equivalent, multi-protein complexes mediate vitronectin functionality in vivo. It is also likely that many of the species demonstrated to associate with vitronectin in vitro, also associate with vitronectin in vivo in similar multi-protein complexes. Thus the predominant biological function of vitronectin is that of a master controller of the extracellular environment; informing, and possibly instructing cells ‘where’ to behave, ‘when’ to behave, and ‘how’ to behave (i.e. appropriately for the current circumstance).

A tumour-derived mutant allele of XRCC2 preferentially suppresses homologous recombination at DNA replication forks

Homologous recombination repair (HRR) is required for both the repair of DNA double strand breaks (DSBs) and the maintenance of the integrity of DNA replication forks. To determine the effect of a mutant allele of the RAD51 paralog XRCC2 (342delT) found in an HRR-defective tumour cell line, 342delT was introduced into HRR proficient cells containing a recombination reporter substrate. In one set of transfectants, expression of 342delT conferred sensitivity to thymidine and mitomycin C and suppressed HRR induced at the recombination reporter by thymidine but not by DSBs. In a second set of transfectants, the expression of 342delT was accompanied by a decreased level of the full-length XRCC2. These cells were defective in the induction of HRR by either thymidine or DSBs. Thus 342delT suppresses recombination induced by thymidine in a dominant negative manner while recombination induced by DSBs appears to depend upon the level of XRCC2 as well as the expression of the mutant XRCC2 allele. These results suggest that HRR pathways responding to stalled replication forks or DSBs are genetically distinguishable. They further suggest a critical role for XRCC2 in HRR at replication forks, possibly in the loading of RAD51 onto gapped DNA.

Secretome and degradome profiling shows that Kallikrein-related peptidases 4, 5, 6, and 7 induce TGFβ-1 signaling in ovarian cancer cells

Kallikrein-related peptidases, in particular KLK4, 5, 6 and 7 (4-7), often have elevated expression levels in ovarian cancer. In OV-MZ-6 ovarian cancer cells, combined expression of KLK4-7 reduces cell adhesion and increases cell invasion and resistance to paclitaxel. The present work investigates how KLK4-7 shape the secreted proteome ("secretome") and proteolytic profile ("degradome") of ovarian cancer cells. The secretome comparison consistently identified >900 proteins in three replicate analyses. Expression of KLK4-7 predominantly affected the abundance of proteins involved in cell-cell communication. Among others, this includes increased levels of transforming growth factor β-1 (TGFβ-1). KLK4-7 co-transfected OV-MZ-6 cells share prominent features of elevated TGFβ-1 signaling, including increased abundance of neural cell adhesion molecule L1 (L1CAM). Augmented levels of TGFβ-1 and L1CAM upon expression of KLK4-7 were corroborated in vivo by an ovarian cancer xenograft model. The degradomic analysis showed that KLK4-7 expression mostly affected cleavage sites C-terminal to arginine, corresponding to the preference of kallikreins 4, 5 and 6. Putative kallikrein substrates include chemokines, such as growth differentiation factor 15 (GDF 15) and macrophage migration inhibitory factor (MIF). Proteolytic maturation of TGFβ-1 was also elevated. KLK4-7 have a pronounced, yet non-degrading impact on the secreted proteome, with a strong association between these proteases and TGFβ-1 signaling in tumor biology. © 2013 Federation of European Biochemical Societies.

A multiscale road map of cancer spheroids : incorporating experimental and mathematical modelling to understand cancer progression

Computational models represent a highly suitable framework, not only for testing biological hypotheses and generating new ones but also for optimising experimental strategies. As one surveys the literature devoted to cancer modelling, it is obvious that immense progress has been made in applying simulation techniques to the study of cancer biology, although the full impact has yet to be realised. For example, there are excellent models to describe cancer incidence rates or factors for early disease detection, but these predictions are unable to explain the functional and molecular changes that are associated with tumour progression. In addition, it is crucial that interactions between mechanical effects, and intracellular and intercellular signalling are incorporated in order to understand cancer growth, its interaction with the extracellular microenvironment and invasion of secondary sites. There is a compelling need to tailor new, physiologically relevant in silico models that are specialised for particular types of cancer, such as ovarian cancer owing to its unique route of metastasis, which are capable of investigating anti-cancer therapies, and generating both qualitative and quantitative predictions. This Commentary will focus on how computational simulation approaches can advance our understanding of ovarian cancer progression and treatment, in particular, with the help of multicellular cancer spheroids, and thus, can inform biological hypothesis and experimental design.