Molecular cloning and characterization of NcROP2Fam-1, a member of the ROP2 family of rhoptry proteins in Neospora caninum that is targeted by antibodies neutralizing host cell invasion in vitro.

Recent publications demonstrated that a fragment of a Neospora caninum ROP2 family member antigen represents a promising vaccine candidate. We here report on the cloning of the cDNA encoding this protein, N. caninum ROP2 family member 1 (NcROP2Fam-1), its molecular characterization and localization. The protein possesses the hallmarks of ROP2 family members and is apparently devoid of catalytic activity. NcROP2Fam-1 is synthesized as a pre-pro-protein that is matured to 2 proteins of 49 and 55 kDa that localize to rhoptry bulbs. Upon invasion the protein is associated with the nascent parasitophorous vacuole membrane (PVM), evacuoles surrounding the host cell nucleus and, in some instances, the surface of intracellular parasites. Staining was also observed within the cyst wall of 'cysts' produced in vitro. Interestingly, NcROP2Fam-1 was also detected on the surface of extracellular parasites entering the host cells and antibodies directed against NcROP2Fam-1-specific peptides partially neutralized invasion in vitro. We conclude that, in spite of the general belief that ROP2 family proteins are intracellular antigens, NcROP2Fam-1 can also be considered as an extracellular antigen, a property that should be taken into account in further experiments employing ROP2 family proteins as vaccines.

Multi-Scale Modeling for Image Analysis of Brain Tumor Studies

Image-based modeling of tumor growth combines methods from cancer simulation and medical imaging. In this context, we present a novel approach to adapt a healthy brain atlas to MR images of tumor patients. In order to establish correspondence between a healthy atlas and a pathologic patient image, tumor growth modeling in combination with registration algorithms is employed. In a first step, the tumor is grown in the atlas based on a new multi-scale, multi-physics model including growth simulation from the cellular level up to the biomechanical level, accounting for cell proliferation and tissue deformations. Large-scale deformations are handled with an Eulerian approach for finite element computations, which can operate directly on the image voxel mesh. Subsequently, dense correspondence between the modified atlas and patient image is established using nonrigid registration. The method offers opportunities in atlasbased segmentation of tumor-bearing brain images as well as for improved patient-specific simulation and prognosis of tumor progression.

Simulating Cortical Development as a Self Constructing Process: A Novel Multi-Scale Approach Combining Molecular and Physical Aspects

Current models of embryological development focus on intracellular processes such as gene expression and protein networks, rather than on the complex relationship between subcellular processes and the collective cellular organization these processes support. We have explored this collective behavior in the context of neocortical development, by modeling the expansion of a small number of progenitor cells into a laminated cortex with layer and cell type specific projections. The developmental process is steered by a formal language analogous to genomic instructions, and takes place in a physically realistic three-dimensional environment. A common genome inserted into individual cells control their individual behaviors, and thereby gives rise to collective developmental sequences in a biologically plausible manner. The simulation begins with a single progenitor cell containing the artificial genome. This progenitor then gives rise through a lineage of offspring to distinct populations of neuronal precursors that migrate to form the cortical laminae. The precursors differentiate by extending dendrites and axons, which reproduce the experimentally determined branching patterns of a number of different neuronal cell types observed in the cat visual cortex. This result is the first comprehensive demonstration of the principles of self-construction whereby the cortical architecture develops. In addition, our model makes several testable predictions concerning cell migration and branching mechanisms.

Coupling biomechanics to a cellular level model: An approach to patient-specific image driven multi-scale and multi-physics tumor simulation

Modeling of tumor growth has been performed according to various approaches addressing different biocomplexity levels and spatiotemporal scales. Mathematical treatments range from partial differential equation based diffusion models to rule-based cellular level simulators, aiming at both improving our quantitative understanding of the underlying biological processes and, in the mid- and long term, constructing reliable multi-scale predictive platforms to support patient-individualized treatment planning and optimization. The aim of this paper is to establish a multi-scale and multi-physics approach to tumor modeling taking into account both the cellular and the macroscopic mechanical level. Therefore, an already developed biomodel of clinical tumor growth and response to treatment is self-consistently coupled with a biomechanical model. Results are presented for the free growth case of the imageable component of an initially point-like glioblastoma multiforme tumor. The composite model leads to significant tumor shape corrections that are achieved through the utilization of environmental pressure information and the application of biomechanical principles. Using the ratio of smallest to largest moment of inertia of the tumor material to quantify the effect of our coupled approach, we have found a tumor shape correction of 20\% by coupling biomechanics to the cellular simulator as compared to a cellular simulation without preferred growth directions. We conclude that the integration of the two models provides additional morphological insight into realistic tumor growth behavior. Therefore, it might be used for the development of an advanced oncosimulator focusing on tumor types for which morphology plays an important role in surgical and/or radio-therapeutic treatment planning.

Multi-scale micro-structure generation strategy for up-scaling transport in clays

Clays and claystones are used as backfill and barrier materials in the design of waste repositories, because they act as hydraulic barriers and retain contaminants. Transport through such barriers occurs mainly by molecular diffusion. There is thus an interest to relate the diffusion properties of clays to their structural properties. In previous work, we have developed a concept for up-scaling pore-scale molecular diffusion coefficients using a grid-based model for the sample pore structure. Here we present an operational algorithm which can generate such model pore structures of polymineral materials. The obtained pore maps match the rock’s mineralogical components and its macroscopic properties such as porosity, grain and pore size distributions. Representative ensembles of grains in 2D or 3D are created by a lattice Monte Carlo (MC) method, which minimizes the interfacial energy of grains starting from an initial grain distribution. Pores are generated at grain boundaries and/or within grains. The method is general and allows to generate anisotropic structures with grains of approximately predetermined shapes, or with mixtures of different grain types. A specific focus of this study was on the simulation of clay-like materials. The generated clay pore maps were then used to derive upscaled effective diffusion coefficients for non-sorbing tracers using a homogenization technique. The large number of generated maps allowed to check the relations between micro-structural features of clays and their effective transport parameters, as is required to explain and extrapolate experimental diffusion results. As examples, we present a set of 2D and 3D simulations and investigated the effects of nanopores within particles (interlayer pores) and micropores between particles. Archie’s simple power law is followed in systems with only micropores. When nanopores are present, additional parameters are required; the data reveal that effective diffusion coefficients could be described by a sum of two power functions, related to the micro- and nanoporosity. We further used the model to investigate the relationships between particle orientation and effective transport properties of the sample.

Mechanisms of recognition and binding of α-TTP to the plasma membrane by multi-scale molecular dynamics simulations

We used multiple sets of simulations both at the atomistic and coarse-grained level of resolution to investigate interaction and binding of α-tochoperol transfer protein (α-TTP) to phosphatidylinositol phosphate lipids (PIPs). Our calculations indicate that enrichment of membranes with such lipids facilitate membrane anchoring. Atomistic models suggest that PIP can be incorporated into the binding cavity of α-TTP and therefore confirm that such protein can work as lipid exchanger between the endosome and the plasma membrane. Comparison of the atomistic models of the α-TTP-PIPs complex with membrane-bound α-TTP revealed different roles for the various basic residues composing the basic patch that is key for the protein/ligand interaction. Such residues are of critical importance as several point mutations at their position lead to severe forms of ataxia with vitamin E deficiency (AVED) phenotypes. Specifically, R221 is main residue responsible for the stabilization of the complex. R68 and R192 exchange strong interactions in the protein or in the membrane complex only, suggesting that the two residues alternate contact formation, thus facilitating lipid flipping from the membrane into the protein cavity during the lipid exchange process. Finally, R59 shows weaker interactions with PIPs anyway with a clear preference for specific phosphorylation positions, hinting a role in early membrane selectivity for the protein. Altogether, our simulations reveal significant aspects at the atomistic scale of interactions of α-TTP with the plasma membrane and with PIP, providing clarifications on the mechanism of intracellular vitamin E trafficking and helping establishing the role of key residue for the functionality of α-TTP.

MicroRNA-21 suppression impedes medulloblastoma cell migration

Medulloblastoma (MB), the most common malignant brain tumour in children, is characterised by a high risk of leptomeningeal dissemination. But little is known about the molecular mechanisms that promote cancer cell migration in MB. Aberrant expression of miR-21 is recognised to be causatively linked to metastasis in a variety of human neoplasms including brain tumours; however its function in MB is still unknown. In this study we investigated the expression level and the role of miR-21 in MB cell migration. miR-21 was found to be up-regulated, compared to normal cerebellum, in 29/29 MB primary samples and 6/6 MB-derived cell lines. Inverse correlation was observed between miR-21 expression and the metastasis suppressor PDCD4, while miR-21 repression increased the release of PDCD4 protein, suggesting negative regulation of PDCD4 by miR-21 in MB cells. Anti-miR-21 decreased protein expression of the tumour cell invasion mediators MAP4K1 and JNK, which are also known to be negatively regulated by PDCD4, and down-regulated integrin protein that is essential for MB leptomeningeal dissemination. Moreover miR-21 knockdown in MB cells increased the expression of two eminent negative modulators of cancer cell migration, E-Cadherin and TIMP2 proteins that are known to be positively regulated by PDCD4. Finally and importantly, suppression of miR-21 decreased the motility of MB cells and reduced their migration across basement membranes in vitro. Together, these compelling data propose miR-21 pathway as a novel mechanism impacting MB cell dissemination and raises the possibility that curability of selected MB may be improved by pharmaceutical strategies directed towards microRNA-21.

Besnoitia besnoiti protein disulfide isomerase (BbPDI): molecular characterization, expression and in silico modelling

Besnoitia besnoiti is an apicomplexan parasite responsible for bovine besnoitiosis, a disease with a high prevalence in tropical and subtropical regions and re-emerging in Europe. Despite the great economical losses associated with besnoitiosis, this disease has been underestimated and poorly studied, and neither an effective therapy nor an efficacious vaccine is available. Protein disulfide isomerase (PDI) is an essential enzyme for the acquisition of the correct three-dimensional structure of proteins. Current evidence suggests that in Neosporacaninum and Toxoplasmagondii, which are closely related to B. besnoiti, PDI play an important role in host cell invasion, is a relevant target for the host immune response, and represents a promising drug target and/or vaccine candidate. In this work, we present the nucleotide sequence of the B. besnoiti PDI gene. BbPDI belongs to the thioredoxin-like superfamily (cluster 00388) and is included in the PDI_a family (cluster defined cd02961) and the PDI_a_PDI_a'_c subfamily (cd02995). A 3D theoretical model was built by comparative homology using Swiss-Model server, using as a template the crystallographic deduced model of Tapasin-ERp57 (PDB code 3F8U chain C). Analysis of the phylogenetic tree for PDI within the phylum apicomplexa reinforces the close relationship among B. besnoiti, N. caninum and T. gondii. When subjected to a PDI-assay based on the polymerisation of reduced insulin, recombinant BbPDI expressed in E. coli exhibited enzymatic activity, which was inhibited by bacitracin. Antiserum directed against recombinant BbPDI reacted with PDI in Western blots and by immunofluorescence with B. besnoiti tachyzoites and bradyzoites.

PSGL-1 and E/P-selectins are essential for T-cell rolling in inflamed CNS microvessels but dispensable for initiation of EAE

T-cell migration across the blood-brain barrier is a crucial step in the pathogenesis of EAE, an animal model for MS. Live cell imaging studies demonstrated that P-selectin glycoprotein ligand-1 (PSGL-1) and its endothelial ligands E- and P-selectin mediate the initial rolling of T cells in brain vessels during EAE. As functional absence of PSGL-1 or E/P-selectins does not result in ameliorated EAE, we speculated that T-cell entry into the spinal cord is independent of PSGL-1 and E/P-selectin. Performing intravital microscopy, we observed the interaction of WT or PSGL-1(-/-) proteolipid protein-specific T cells in inflamed spinal cord microvessels of WT or E/P-selectin(-/-) SJL/J mice during EAE. T-cell rolling but not T-cell capture was completely abrogated in the absence of either PSGL-1 or E- and P-selectin, resulting in a significantly reduced number of T cells able to firmly adhere in the inflamed spinal cord microvessels, but did not lead to reduced T-cell invasion into the CNS parenchyma. Thus, PSGL-1 interaction with E/P-selectin is essential for T-cell rolling in inflamed spinal cord microvessels during EAE. Taken together with previous observations, our findings show that T-cell rolling is not required for successful T-cell entry into the CNS and initiation of EAE.

Expression of the hyaluronan-mediated motility receptor RHAMM in tumor budding cells identifies aggressive colorectal cancers.

Expression of the hyaluronan-mediated motility receptor (RHAMM, CD168) predicts adverse clinicopathological features and decreased survival for colorectal cancer (CRC) patients. Using full tissue sections, we investigated the expression of RHAMM in tumor budding cells of 103 primary CRCs to characterize the biological processes driving single-cell invasion and early metastatic dissemination. RHAMM expression in tumor buds was analyzed with clinicopathological data, molecular features and survival. Tumor budding cells at the invasive front of CRC expressed RHAMM in 68% of cases. Detection of RHAMM-positive tumor budding cells was significantly associated with poor survival outcome (P = .0312), independent of TNM stage and adjuvant therapy in multivariate analysis (P = .0201). RHAMM-positive tumor buds were associated with frequent lymphatic invasion (P = .0007), higher tumor grade (P = .0296), and nodal metastasis (P = .0364). Importantly, the prognostic impact of RHAMM expression in tumor buds was maintained independently of the number of tumor buds found in an individual case (P = .0246). No impact of KRAS/BRAF mutation, mismatch repair deficiency and CpG island methylation was observed. RHAMM expression identifies an aggressive subpopulation of tumor budding cells and is an independent adverse prognostic factor for CRC patients. These data support ongoing efforts to develop RHAMM as a target for precision therapy.

The Src inhibitor AZD0530 blocks invasion and may act as a radiosensitizer in lung cancer cells

BACKGROUND: With the emergence of Src inhibitors in clinical trials, improved knowledge of the molecular responses of cancer cells to these agents is warranted. This will facilitate the development of tests to identify patients who may benefit from these agents, allow drug activity to be monitored and rationalize the combination of these agents with other treatment modalities. METHODS: This study evaluated the molecular and functional effects of Src inhibitor AZD0530 in human lung cancer cells, by Western blotting and reverse transcription-polymerase chain reaction, and by assays for cell viability, migration, and invasion. RESULTS: Src was activated in four of five cell lines tested and the level corresponded with the invasive potential and the histologic subtype. Clinically relevant, submicromolar concentrations of AZD0530 blocked Src and focal adhesion kinase, resulting in significant inhibition of cell migration and Matrigel invasion. Reactivation of STAT3 and up-regulation of JAK indicated a potential mechanism of resistance. AZD0530 gave a potent and sustained blockage of AKT and enhanced the sensitivity to irradiation. CONCLUSIONS: The results indicated that AZD0530, aside from being a potent inhibitor of tumor cell invasion which could translate to inhibition of disease progression in the clinic, may also lower resistance of lung cancer cells to pro-apoptotic signals.

Integrated Segmentation of Brain Tumor Images for Radiotherapy and Neurosurgery

Image-based modeling of tumor growth combines methods from cancer simulation and medical imaging. In this context, we present a novel approach to adapt a healthy brain atlas to MR images of tumor patients. In order to establish correspondence between a healthy atlas and a pathologic patient image, tumor growth modeling in combination with registration algorithms is employed. In a first step, the tumor is grown in the atlas based on a new multi-scale, multi-physics model including growth simulation from the cellular level up to the biomechanical level, accounting for cell proliferation and tissue deformations. Large-scale deformations are handled with an Eulerian approach for finite element computations, which can operate directly on the image voxel mesh. Subsequently, dense correspondence between the modified atlas and patient image is established using nonrigid registration. The method offers opportunities in atlasbased segmentation of tumor-bearing brain images as well as for improved patient-specific simulation and prognosis of tumor progression.