Cytosolic Glucosylceramide regulates endolysosomal function in Niemann-Pick type C disease

A new paradigm for Niemann-Pick C disease is presented where lysosomal storage leads to a deficit in cytoplasmic glucosylceramide (GlcCer) where it performs important functions. Previously it had been reported that Gaucher cells have defective endolysosomal pH. GlcCer also accumulates in Niemann-Pick C disease and also shows this defect. Niemann-Pick C cells were found to have reduced cytoplasmic glucosylceramide (GlcCer) transport. Inhibiting cytoplasmic glucocerebrosidase (GBA2), increased GlcCer, decreased endolysosomal pH in normal cells, reversed increases in endolysosomal pH and restored disrupted BODIPY-LacCer trafficking and increased expression of vATPase a subunit in Niemann-Pick C fibroblasts. The results are consistent with a model where both endolysosomal pH and Golgi targeting of BODIPY-LacCer are dependent on adequate levels of cytosolic GlcCer which are reduced in NPC disease. This work consequently suggests GBA2 and vATPase as new therapeutic targets in Niemann-Pick C and related neurodegenerative diseases. The work was in collaboration with colleagues in the Netherlands and Leicester University. The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Niemann-Pick type C disease (NPCD) is a neurodegenerative disease associated with increases in cellular cholesterol and glycolipids and most commonly caused by defective NPC1, a late endosomal protein. Using ratiometric probes we find that NPCD cells show increased endolysosomal pH. In addition U18666A, an inhibitor of NPC1, was found to increase endolysosomal pH, and the number, size and heterogeneity of endolysosomal vesicles. NPCD fibroblasts and cells treated with U18666A also show disrupted targeting of fluorescent lipid BODIPY-LacCer to high pH vesicles. Inhibiting non-lysosomal glucocerebrosidase (GBA2) reversed increases in endolysosomal pH and restored disrupted BODIPY-LacCer trafficking in NPCD fibroblasts. GBA2 KO cells also show decreased endolysosomal pH. NPCD fibroblasts also show increased expression of a key subunit of the lysosomal proton pump vATPase on GBA2 inhibition. The results are consistent with a model where both endolysosomal pH and Golgi targeting of BODIPY-LacCer are dependent on adequate levels of cytosolic-facing GlcCer, which are reduced in NPC disease

L1 and NCAM adhesion molecules as signaling coreceptors in neuronal migration and process outgrowth

Neural cell adhesion molecules (CAMs) of the immunoglobulin superfamily engage in multiple neuronal interactions that influence cell migration, axonal and dendritic projection, and synaptic targeting. Their downstream signal transduction events specify whether a cell moves or projects axons and dendrites to targets in the brain. Many of the diverse functions of CAMs are brought about through homophilic and heterophilic interactions with other cell surface receptors. An emerging concept is that CAMs act as co-receptors to assist in intracellular signal transduction, and to provide cytoskeletal linkage necessary for cell and growth cone motility. Here we will focus on new discoveries that have revealed novel co-receptor functions for the best understood CAMs - L1, CHL1, and NCAM- important for neuronal migration and axon guidance. We will also discuss how dysregulation of CAMs may also bear on neuropsychiatric disease and cancer

An ensemble approach to assess hydrological models’ contribution to uncertainties in the analysis of climate change impact on water resources

Over the recent years, several research efforts investigated the impact of climate change on water resources for different regions of the world. The projection of future river flows is affected by different sources of uncertainty in the hydro-climatic modelling chain. One of the aims of the QBic3 5 project (Que´bec-Bavarian International Collaboration on Climate Change) is to assess the contribution to uncertainty of hydrological models by using an ensemble of hydrological models presenting a diversity of structural complexity (i.e. lumped, semi distributed and distributed models). The study investigates two humid, mid-latitude catchments with natural flow conditions; one located in 10 Southern Que´bec (Canada) and one in Southern Bavaria (Germany). Daily flow is simulated with four different hydrological models, forced by outputs from regional climate models driven by a given number of GCMs’ members over a reference (1971–2000) and a future (2041–2070) periods. The results show that the choice of the hydrological model does strongly affect the climate change response of selected hydrological indicators, especially those related to low flows. Indicators related to high flows seem less sensitive on the choice of the hydrological model. Therefore, the computationally less demanding models (usually simple, lumped and conceptual) give a significant level of trust for high and overall mean flows

On the need for bias correction in regional climate scenarios to assess climate change impacts on river runoff

In climate change impact research, the assessment of future river runoff as well as the catchment scale water balance is impeded by different sources of modeling uncertainty. Some research has already been done in order to quantify the uncertainty of climate 5 projections originating from the climate models and the downscaling techniques as well as from the internal variability evaluated from climate model member ensembles. Yet, the use of hydrological models adds another layer of incertitude. Within the QBic3 project (Qu´ebec-Bavaria International Collaboration on Climate Change) the relative contributions to the overall uncertainty from the whole model chain (from global climate 10 models to water management models) are investigated using an ensemble of multiple climate and hydrological models. Although there are many options to downscale global climate projections to the regional scale, recent impact studies tend to use Regional Climate Models (RCMs). One reason for that is that the physical coherence between atmospheric and land-surface 15 variables is preserved. The coherence between temperature and precipitation is of particular interest in hydrology. However, the regional climate model outputs often are biased compared to the observed climatology of a given region. Therefore, biases in those outputs are often corrected to reproduce historic runoff conditions from hydrological models using them, even if those corrections alter the relationship between temperature and precipitation. So, as bias correction may affect the consistency between RCM output variables, the use of correction techniques and even the use of (biased) climate model data itself is sometimes disputed among scientists. For those reasons, the effect of bias correction on simulated runoff regimes and the relative change in selected runoff indicators is explored. If it affects the conclusion of climate change analysis in 25 hydrology, we should consider it as a source of uncertainty. If not, the application of bias correction methods is either unnecessary in hydro-climatic projections, or safe to use as it does not alter the change signal of river runoff. The results of the present paper highlight the analysis of daily runoff simulated with four different hydrological models in two natural-flow catchments, driven by different regional climate models for a reference and a future period. As expected, bias correction of climate model outputs is important for the reproduction of the runoff regime of the 5 past regardless of the hydrological model used. Then again, its impact on the relative change of flow indicators between reference and future period is weak for most indicators with the exception of the timing of the spring flood peak. Still, our results indicate that the impact of bias correction on runoff indicators increases with bias in the climate simulations

A Coupled Mathematical Model of the Intracellular Replication of Dengue Virus and the Host Cell Immune Response to Infection

Dengue virus (DV) is a positive-strand RNA virus of the Flavivirus genus. It is one of the most prevalent mosquito-borne viruses, infecting globally 390 million individuals per year. The clinical spectrum of DV infection ranges from an asymptomatic course to severe complications such as dengue hemorrhagic fever (DHF) and dengue shock syndrome (DSS), the latter because of severe plasma leakage. Given that the outcome of infection is likely determined by the kinetics of viral replication and the antiviral host cell immune response (HIR) it is of importance to understand the interaction between these two parameters. In this study, we use mathematical modeling to characterize and understand the complex interplay between intracellular DV replication and the host cells' defense mechanisms. We first measured viral RNA, viral protein, and virus particle production in Huh7 cells, which exhibit a notoriously weak intrinsic antiviral response. Based on these measurements, we developed a detailed intracellular DV replication model. We then measured replication in IFN competent A549 cells and used this data to couple the replication model with a model describing IFN activation and production of IFN stimulated genes (ISGs), as well as their interplay with DV replication. By comparing the cell line specific DV replication, we found that host factors involved in replication complex formation and virus particle production are crucial for replication efficiency. Regarding possible modes of action of the HIR, our model fits suggest that the HIR mainly affects DV RNA translation initiation, cytosolic DV RNA degradation, and naïve cell infection. We further analyzed the potential of direct acting antiviral drugs targeting different processes of the DV lifecycle in silico and found that targeting RNA synthesis and virus assembly and release are the most promising anti-DV drug targets

Reactive astrocytes potentiate tumor aggressiveness in a murine glioma resection and recurrence model

Surgical resection is a universal component of glioma therapy. Little is known about the postoperative microenvironment due to limited preclinical models. Thus, we sought to develop a glioma resection and recurrence model in syngeneic immune-competent mice to understand how surgical resection influences tumor biology and the local microenvironment

3 1 integrin modulates neuronal migration and placement during early stages of cerebral cortical development

We show that alpha3 integrin mutation disrupts distinct aspects of neuronal migration and placement in the cerebral cortex. The preplate develops normally in alpha3 integrin mutant mice. However, time lapse imaging of migrating neurons in embryonic cortical slices indicates retarded radial and tangential migration of neurons, but not ventricular zone-directed migration. Examination of the actin cytoskeleton of alpha3 integrin mutant cortical cells reveals aberrant actin cytoskeletal dynamics at the leading edges. Deficits are also evident in the ability of developing neurons to probe their cellular environment with filopodial and lamellipodial activity. Calbindin or calretinin positive upper layer neurons as well as the deep layer neurons of alpha3 integrin mutant mice expressing EGFP were misplaced. These results suggest that alpha3beta1 integrin deficiency impairs distinct patterns of neuronal migration and placement through dysregulated actin dynamics and defective ability to search and respond to migration modulating cues in the developing cortex

Core pathway mutations induce de-differentiation of murine astrocytes into glioblastoma stem cells that are sensitive to radiation but resistant to temozolomide

Glioma stem cells (GSCs) from human glioblastomas (GBMs) are resistant to radiation and chemotherapy and may drive recurrence. Treatment efficacy may depend on GSCs, expression of DNA repair enzymes such as methylguanine methyltransferase (MGMT), or transcriptome subtype

Modeling Astrocytoma Pathogenesis <em>In Vitro</em> and <em>In Vivo</em> Using Cortical Astrocytes or Neural Stem Cells from Conditional, Genetically Engineered Mice

Current astrocytoma models are limited in their ability to define the roles of oncogenic mutations in specific brain cell types during disease pathogenesis and their utility for preclinical drug development. In order to design a better model system for these applications, phenotypically wild-type cortical astrocytes and neural stem cells (NSC) from conditional, genetically engineered mice (GEM) that harbor various combinations of floxed oncogenic alleles were harvested and grown in culture. Genetic recombination was induced in vitro using adenoviral Cre-mediated recombination, resulting in expression of mutated oncogenes and deletion of tumor suppressor genes. The phenotypic consequences of these mutations were defined by measuring proliferation, transformation, and drug response in vitro. Orthotopic allograft models, whereby transformed cells are stereotactically injected into the brains of immune-competent, syngeneic littermates, were developed to define the role of oncogenic mutations and cell type on tumorigenesis in vivo. Unlike most established human glioblastoma cell line xenografts, injection of transformed GEM-derived cortical astrocytes into the brains of immune-competent littermates produced astrocytomas, including the most aggressive subtype, glioblastoma, that recapitulated the histopathological hallmarks of human astrocytomas, including diffuse invasion of normal brain parenchyma. Bioluminescence imaging of orthotopic allografts from transformed astrocytes engineered to express luciferase was utilized to monitor in vivo tumor growth over time. Thus, astrocytoma models using astrocytes and NSC harvested from GEM with conditional oncogenic alleles provide an integrated system to study the genetics and cell biology of astrocytoma pathogenesis in vitro and in vivo and may be useful in preclinical drug development for these devastating diseases

Cooperativity between MAPK and PI3K signaling activation is required for glioblastoma pathogenesis

Glioblastoma (GBM) genomes feature recurrent genetic alterations that dysregulate core intracellular signaling pathways, including the G1/S cell cycle checkpoint and the MAPK and PI3K effector arms of receptor tyrosine kinase (RTK) signaling. Elucidation of the phenotypic consequences of activated RTK effectors is required for the design of effective therapeutic and diagnostic strategies