Transcriptional regulation of CRMP5 controls neurite outgrowth through Sox5.

Transcriptional regulation of proteins involved in neuronal polarity is a key process that underlies the ability of neurons to transfer information in the central nervous system. The Collapsin Response Mediator Protein (CRMP) family is best known for its role in neurite outgrowth regulation conducting to neuronal polarity and axonal guidance, including CRMP5 that drives dendrite differentiation. Although CRMP5 is able to control dendritic development, the regulation of its expression remains poorly understood. Here we identify a Sox5 consensus binding sequence in the putative promoter sequence upstream of the CRMP5 gene. By luciferase assays we show that Sox5 increases CRMP5 promoter activity, but not if the putative Sox5 binding site is mutated. We demonstrate that Sox5 can physically bind to the CRMP5 promoter DNA in gel mobility shift and chromatin immunoprecipitation assays. Using a combination of real-time RT-PCR and quantitative immunocytochemistry, we provide further evidence for a Sox5-dependent upregulation of CRMP5 transcription and protein expression in N1E115 cells: a commonly used cell line model for neuronal differentiation. Furthermore, we report that increasing Sox5 levels in this neuronal cell line inhibits neurite outgrowth. This inhibition requires CRMP5 because CRMP5 knockdown prevents the Sox5-dependent effect. We confirm the physiological relevance of the Sox5-CRMP5 pathway in the regulation of neurite outgrowth using mouse primary hippocampal neurons. These findings identify Sox5 as a critical modulator of neurite outgrowth through the selective activation of CRMP5 expression.

In silico study of the influence of intensity and duration of blood flow reduction on cell death through necrosis or apoptosis during acute ischemic stroke.

Ischemic stroke involves numerous and complex pathophysiological mechanisms including blood flow reduction, ionic exchanges, spreading depressions and cell death through necrosis or apoptosis. We used a mathematical model based on these phenomena to study the influences of intensity and duration of ischemia on the final size of the infarcted area. This model relies on a set of ordinary and partial differential equations. After a sensibility study, the model was used to carry out in silico experiments in various ischemic conditions. The simulation results show that the proportion of apoptotic cells increases when the intensity of ischemia decreases, which contributes to the model validation. The simulation results also show that the influence of ischemia duration on the infarct size is more complicated. They suggest that reperfusion is beneficial when performed in the early stroke but may be either inefficacious or even deleterious when performed later after the stroke onset. This aggravation could be explained by the depolarisation waves which might continue to spread ischemic damage and by the speeding up of the apoptotic process leading to cell death. The effect of reperfusion on cell death through these two phenomena needs to be further studied in order to develop new therapeutic strategies for stroke patients.

A modelling approach to explore some hypotheses of the failure of neuroprotective trials in ischemic stroke patients.

Ischemic stroke is the third cause of death in industrialised countries, but no satisfactory treatment is currently available. The hundreds of neuroprotective drugs developed to block the ischemic cascade gave very promising results in animal models but the clinical trials performed with these drugs showed no beneficial effects in stroke patients. Many hypotheses were advanced to explain this discrepancy, among which the morphological and functional differences between human and rodent brains. This discrepancy could be partly due to the differences in white matter and glial cell proportions between human and rodent brains. In order to test this hypothesis, we built a mathematical model of the main early pathophysiological mechanisms of stroke in rodent and in human brains. This model is a two-scale model and relies on a set of ordinary differential equations. We built two versions of this model (for human and rodent brains) differing in their white matter and glial cell proportions. Then, we carried out in silico experiments with various neuroprotective drugs. The simulation results obtained with a sodium channel blocker show that the proportion of penumbra recovery is much higher in rodent than in human brain and the results are similar with some other neuroprotective drugs tested during phase III trials. This in silico investigation suggests that the proportions of glial cells and white matter have an influence on neuroprotective drug efficacy. It reinforces the hypothesis that histological and morphological differences between rodent and human brains can partly explain the failure of these agents in clinical trials.

Modelling methodology in physiopathology.

Diseases are complex systems. Modelling them, i.e. systems physiopathology, is a quite demanding, complicated, multidimensional, multiscale process. As such, in order to achieve the goal of the model and further to optimise a rather-time and resource-consuming process, a relevant and easy to practice methodology is required. It includes guidance for validation. Also, the model development should be managed as a complicated process, along a strategy which has been elaborated in the beginning. It should be flexible enough to meet every case. A model is a representation of the available knowledge. All available knowledge does not have the same level of evidence and, further, there is a large variability of the values of all parameters (e.g. affinity constant or ionic current) across the literature. In addition, in a complex biological system there are always values lacking for a few or sometimes many parameters. All these three aspects are sources of uncertainty on the range of validity of the models and raise unsolved problems for designing a relevant model. Tools and techniques for integrating the parameter range of experimental values, level of evidence and missing data are needed.

Role of astrocytes in grey matter during stroke: a modelling approach.

The astrocytic response to stroke is extremely complex and incompletely understood. On the one hand, astrocytes are known to be neuroprotective when extracellular glutamate or potassium is slightly increased. But, on the other hand, they are considered to contribute to the extracellular glutamate increase during severe ischaemia. A mathematical model is used to reproduce the dynamics of the membrane potentials, intracellular and extracellular concentrations and volumes of neurons and astrocytes during ischaemia in order to study the role of astrocytes in grey matter during the first hour of a stroke. Under conditions of mild ischaemia, astrocytes are observed to take up glutamate via the glutamate transporter, and potassium via the Na/K/Cl cotransporter, which limits glutamate and potassium increase in the extracellular space. On the contrary, under conditions of severe ischaemia, astrocytes appear to be unable to maintain potassium homeostasis. Moreover, they are shown to contribute to the excitotoxicity process by expelling glutamate out of the cells via the reversed glutamate transporter. A detailed understanding of astrocytic function and influence on neuron survival during stroke is necessary to improve the neuroprotective strategies for stroke patients.

[New approaches in pharmacology: numerical modelling and simulation]. / Modélisation numérique et simulation: nouvelles applications en pharmacologie.

The complexity of pathophysiological mechanisms is beyond the capabilities of traditional approaches. Many of the decision-making problems in public health, such as initiating mass screening, are complex. Progress in genomics and proteomics, and the resulting extraordinary increase in knowledge with regard to interactions between gene expression, the environment and behaviour, the customisation of risk factors and the need to combine therapies that individually have minimal though well documented efficacy, has led doctors to raise new questions: how to optimise choice and the application of therapeutic strategies at the individual rather than the group level, while taking into account all the available evidence? This is essentially a problem of complexity with dimensions similar to the previous ones: multiple parameters with nonlinear relationships between them, varying time scales that cannot be ignored etc. Numerical modelling and simulation (in silico investigations) have the potential to meet these challenges. Such approaches are considered in drug innovation and development. They require a multidisciplinary approach, and this will involve modification of the way research in pharmacology is conducted.

Exploration of beneficial and deleterious effects of inflammation in stroke: dynamics of inflammation cells.

The inflammatory process during stroke consists of activation of resident brain microglia and recruitment of leucocytes, namely neutrophils and monocytes/macrophages. During inflammation, microglial cells, neutrophils and macrophages secrete inflammatory cytokines and chemokines, and phagocytize dead cells. The recruitment of blood cells (neutrophils and macrophages) is mediated by the leucocyte-endothelium interactions and more specifically by cell adhesion molecules. A mathematical model is proposed to represent the dynamics of various brain cells and of immune cells (neutrophils and macrophages). This model is based on a set of six ordinary differential equations and explores the beneficial and deleterious effects of inflammation, respectively phagocytosis by immune cells and the release of pro-inflammatory mediators and nitric oxide (NO). The results of our simulations are qualitatively consistent with those observed in experiments in vivo and would suggest that the increase of phagocytosis could contribute to the increase of the percentage of living cells. The inhibition of the production of cytokines and NO and the blocking of neutrophil and macrophage infiltration into the brain parenchyma led also to the improvement of brain cell survival. This approach may help to explore the respective contributions of the beneficial and deleterious roles of the inflammatory process in stroke, and to study various therapeutic strategies in order to reduce stroke damage.

A mathematical model of ion movements in grey matter during a stroke.

The development of cytotoxic oedema during a stroke consists in cell swelling and shrinking of the extracellular space. This phenomenon is triggered by ion movements through voltage-gated channels, exchangers and pumps. During ischaemia, sodium, calcium and chloride enter the neurons whereas potassium and glutamate are expelled out of the cells. A mathematical model is proposed to represent the long-term dynamics of membrane potentials, cell volumes and ionic concentrations in intracellular and extracellular spaces during a stroke and to study the influence of each ionic current on cell swelling. The model relies on electrophysiological mechanisms and takes into account the behaviour of two types of cells: neurons and also astrocytes known to play a key role in the excitotoxic process in grey matter. The results obtained when a severe or a moderate ischaemia is simulated are consistent with those observed in the in vitro and in vivo experiments. As this model appears to be robust, it is used to perform illustrative simulations aimed at studying the effect of some channel blockers on cell swelling. This approach may help to explore new therapeutic strategies in order to reduce stroke damage.

Mathematical modelling of an ischemic stroke: an integrative approach.

Understanding the mechanisms and the time and spatial evolution of penumbra following an ischemic stroke is crucially important for developing therapeutics aimed at preventing this area from evolving towards infarction. To help in integrating the available data, we decided to build a formal model. We first collected and categorised the major available evidence from animal models and human observations and summarized this knowledge in a flow-chart with the potential key components of an evolving stroke. Components were grouped in ten sub-models that could be modelled and tested independently: the sub-models of tissue reactions, ionic movements, oedema development, glutamate excitotoxicity, spreading depression, NO synthesis, inflammation, necrosis, apoptosis, and reperfusion. Then, we figured out markers, identified mediators and chose the level of complexity to model these sub-models. We first applied this integrative approach to build a model based on cytotoxic oedema development following a stroke. Although this model includes only three sub-models and would need to integrate more mechanisms in each of these sub-models, the characteristics and the time and spatial evolution of penumbra obtained by simulation are qualitatively and, to some extent, quantitatively consistent with those observed using medical imaging after a permanent occlusion or after an occlusion followed by a reperfusion.