Ecdysone triggered PGRP-LC expression controls Drosophila innate immunity.

Throughout the animal kingdom, steroid hormones have been implicated in the defense against microbial infection, but how these systemic signals control immunity is unclear. Here, we show that the steroid hormone ecdysone controls the expression of the pattern recognition receptor PGRP-LC in Drosophila, thereby tightly regulating innate immune recognition and defense against bacterial infection. We identify a group of steroid-regulated transcription factors as well as two GATA transcription factors that act as repressors and activators of the immune response and are required for the proper hormonal control of PGRP-LC expression. Together, our results demonstrate that Drosophila use complex mechanisms to modulate innate immune responses, and identify a transcriptional hierarchy that integrates steroid signalling and immunity in animals.

Generating controlled image sets in cognitive neuroscience research.

The investigation of perceptual and cognitive functions with non-invasive brain imaging methods critically depends on the careful selection of stimuli for use in experiments. For example, it must be verified that any observed effects follow from the parameter of interest (e.g. semantic category) rather than other low-level physical features (e.g. luminance, or spectral properties). Otherwise, interpretation of results is confounded. Often, researchers circumvent this issue by including additional control conditions or tasks, both of which are flawed and also prolong experiments. Here, we present some new approaches for controlling classes of stimuli intended for use in cognitive neuroscience, however these methods can be readily extrapolated to other applications and stimulus modalities. Our approach is comprised of two levels. The first level aims at equalizing individual stimuli in terms of their mean luminance. Each data point in the stimulus is adjusted to a standardized value based on a standard value across the stimulus battery. The second level analyzes two populations of stimuli along their spectral properties (i.e. spatial frequency) using a dissimilarity metric that equals the root mean square of the distance between two populations of objects as a function of spatial frequency along x- and y-dimensions of the image. Randomized permutations are used to obtain a minimal value between the populations to minimize, in a completely data-driven manner, the spectral differences between image sets. While another paper in this issue applies these methods in the case of acoustic stimuli (Aeschlimann et al., Brain Topogr 2008), we illustrate this approach here in detail for complex visual stimuli.

Can MMTV exploit TLR4?

The recognition of microbial pathogens based on their molecular patterns is essential for host defense. Recently, Toll-like receptors have been shown not only to recognize viruses as well as bacteria and fungi, but also to trigger an efficient immune response. A recent publication proposed that the retrovirus mouse mammary tumor virus exploits the pattern-recognition receptor Toll-like receptor 4 to achieve more efficient infection.

The inflammasomes.

Inflammasomes are molecular platforms activated upon cellular infection or stress that trigger the maturation of proinflammatory cytokines such as interleukin-1beta to engage innate immune defenses. Strong associations between dysregulated inflammasome activity and human heritable and acquired inflammatory diseases highlight the importance this pathway in tailoring immune responses. Here, we comprehensively review mechanisms directing normal inflammasome function and its dysregulation in disease. Agonists and activation mechanisms of the NLRP1, NLRP3, IPAF, and AIM2 inflammasomes are discussed. Regulatory mechanisms that potentiate or limit inflammasome activation are examined, as well as emerging links between the inflammasome and pyroptosis and autophagy.

Host innate immune responses to microbial pathogens.

Sepsis is among the leading causes of death worldwide and its incidence is increasing. Defined as the host response to infection, sepsis is a clinical syndrome considered to be the expression of a dysregulated immune reaction induced by danger signals that may lead to organ failure and death. Remarkable progresses have been made in our understanding of the molecular basis of host defenses in recent years. The host defense response is initiated by innate immune sensors of danger signals designated under the collective name of pattern-recognition receptors. Members of the family of microbial sensors include the complement system, the Toll-like receptors, the nucleotide-binding oligomerization domainlike receptors, the RIG-I-like helicases and the C-type lectin receptors. Ligand-activated pattern-recognition receptors kick off a cascade of intracellular events resulting in the expression of co-stimulatory molecules and release of effector molecules playing a fundamental role in the initiation of the innate and adaptive immune responses. Fine tuning of proinflammatory and anti-inflammatory reactions is critical for keeping the innate immune response in check. Overwhelming or dysregulated responses induced by infectious stimuli may have dramatic consequences for the host as shown by the profound derangements observed in sepsis. Unfortunately, translational research approaches aimed at the development of therapies targeting newly identified innate immune pathways have not held their promises. Indeed, all recent clinical investigations of adjunctive anti-sepsis treatments had little, if any, impact on morbidity and all-cause mortality of sepsis. Dissecting the mechanisms underlying the transition from infection to sepsis is essential for solving the sepsis enigma. Important components of the puzzle have already been identified, but the hunt must go on in the laboratory and at the bedside.

IL-13 induces expression of CD36 in human monocytes through PPARgamma activation.

The class B scavenger receptor CD36 is a component of the pattern recognition receptors on monocytes that recognizes a variety of molecules. CD36 expression in monocytes depends on exposure to soluble mediators. We demonstrate here that CD36 expression is induced in human monocytes following exposure to IL-13, a Th2 cytokine, via the peroxisome proliferator-activated receptor (PPAR)gamma pathway. Induction of CD36 protein was paralleled by an increase in CD36 mRNA. The PPARgamma pathway was demonstrated using transfection of a PPARgamma expression plasmid into the murine macrophage cell line RAW264.7, expressing very low levels of PPARgamma, and in peritoneal macrophages from PPARgamma-conditional null mice. We also show that CD36 induction by IL-13 via PPARgamma is dependent on phospholipase A2 activation and that IL-13 induces the production of endogenous 15-deoxy-Delta12,14-prostaglandin J2, an endogenous PPARgamma ligand, and its nuclear localization in human monocytes. Finally, we demonstrate that CD36 and PPARgamma are involved in IL-13-mediated phagocytosis of Plasmodium falciparum-parasitized erythrocytes. These results reveal a novel role for PPARgamma in the alternative activation of monocytes by IL-13, suggesting that endogenous PPARgamma ligands, produced by phospholipase A2 activation, could contribute to the biochemical and cellular functions of CD36.

Innate receptors for adaptive immunity.

Pattern recognition receptors (PRRs) are commonly known as sensor proteins crucial for the early detection of microbial or host-derived stress signals by innate immune cells. Interestingly, some PRRs are also expressed and functional in cells of the adaptive immune system. These receptors provide lymphocytes with innate sensing abilities; for example, B cells express Toll-like receptors, which are important for the humoral response. Strikingly, certain other NOD-like receptors are not only highly expressed in adaptive immune cells, but also exert functions related specifically to adaptive immune system pathways, such as regulating antigen presentation. In this review, we will focus particularly on the current understanding of PRR functions intrinsic to B and T lymphocytes; a developing aspect of PRR biology.

Comparing Multilevel Clustering Methods on Weighted Graphs : The Case of Worldwide Air Passenger Traffic 2000-2004

Specific properties emerge from the structure of large networks, such as that of worldwide air traffic, including a highly hierarchical node structure and multi-level small world sub-groups that strongly influence future dynamics. We have developed clustering methods to understand the form of these structures, to identify structural properties, and to evaluate the effects of these properties. Graph clustering methods are often constructed from different components: a metric, a clustering index, and a modularity measure to assess the quality of a clustering method. To understand the impact of each of these components on the clustering method, we explore and compare different combinations. These different combinations are used to compare multilevel clustering methods to delineate the effects of geographical distance, hubs, network densities, and bridges on worldwide air passenger traffic. The ultimate goal of this methodological research is to demonstrate evidence of combined effects in the development of an air traffic network. In fact, the network can be divided into different levels of âeurooecohesionâeuro, which can be qualified and measured by comparative studies (Newman, 2002; Guimera et al., 2005; Sales-Pardo et al., 2007).

Structural Analysis of Networks

Network analysis naturally relies on graph theory and, more particularly, on the use of node and edge metrics to identify the salient properties in graphs. When building visual maps of networks, these metrics are turned into useful visual cues or are used interactively to filter out parts of a graph while querying it, for instance. Over the years, analysts from different application domains have designed metrics to serve specific needs. Network science is an inherently cross-disciplinary field, which leads to the publication of metrics with similar goals; different names and descriptions of their analytics often mask the similarity between two metrics that originated in different fields. Here, we study a set of graph metrics and compare their relative values and behaviors in an effort to survey their potential contributions to the spatial analysis of networks.

Histone deacetylase inhibitors impair innate immune responses

SUMMARYThe innate immune system plays a central role in host defenses against invading pathogens. Innate immune cells sense the presence of pathogens through pattern recognition receptors that trigger intracellular signaling, leading to the production of pro-inflammatory mediators like cytokines, which shape innate and adaptive immune responses. Both by excess and by default inflammation may be detrimental to the host. Indeed, severe sepsis and septic shock are lethal complications of infections characterized by a dysregulated inflammatory response.In recent years, members of the superfamily of histone deacetylases have been the focus of great interest. In mammals, histone deacetylases are broadly classified into two main subfamilies comprising histone deacetylases 1-11 (HDAC1-11) and sirtuins 1-7 (SIRT1-7). These enzymes influence gene expression by deacetylating histones and numerous non-histone proteins. Histone deacetylases have been involved in the development of oncologic, metabolic, cardiovascular, neurodegenerative and autoimmune diseases. Pharmacological modulators of histone deacetylase activity, principally inhibitors, have been developed for the treatment of cancer and metabolic diseases. When we initiated this project, several studies suggested that inhibitors of HDAC 1-11 have anti-inflammatory activity. Yet, their influence on innate immune responses was largely uncharacterized. The present study was initiated to fill in this gap.In the first part of this work, we report the first comprehensive study of the effects of HDAC 1- 11 inhibitors on innate immune responses in vitro and in vivo. Strikingly, expression studies revealed that HDAC1-11 inhibitors act essentially as negative regulators of basal and microbial product- induced expression of critical immune receptors and antimicrobial products by mouse and human innate immune cells like macrophages and dendritic cells. Furthermore, we describe a new molecular mechanism whereby HDAC1-11 inhibitors repress pro-inflammatory cytokine expression through the induction of the expression and the activity of the transcriptional repressor Μί-2β. HDAC1-11 inhibitors also impair the potential of macrophages to engulf and kill bacteria. Finally, mice treated with an HDAC inhibitor are more susceptible to non-severe bacterial and fungal infection, but are protected against toxic and septic shock. Altogether these data support the concept that HDAC 1-11 inhibitors have potent anti-inflammatory and immunomodulatory activities in vitro and in vivo.Macrophage migration inhibitory factor (MIF) is a pro-inflammatory cytokine that plays a central role in innate immune responses, cell proliferation and oncogenesis. In the second part of this manuscript, we demonstrate that HDAC1-11 inhibitors inhibit MIF expression in vitro and in vivo and describe a novel molecular mechanism accounting for these effects. We propose that inhibition of MIF expression by HDAC 1-11 inhibitors may contribute to the antitumorigenic and anti-inflammatory effects of these drugs.NAD+ is an essential cofactor of sirtuins activity and one of the major sources of energy within the cells. Therefore, sirtuins link deacetylation to NAD+ metabolism and energy status. In the last part of this thesis, we report preliminary results indicating that a pharmacological inhibitor of SIRT1-2 drastically decreases pro-inflammatory cytokine production (RNA and protein) and interferes with MAP kinase intracellular signal transduction pathway in macrophages. Moreover, administration of the SIRT1-2 inhibitor protects mice from lethal endotoxic shock and septic shock.Overall, our studies demonstrate that inhibitors of HDAC1-11 and sirtuins are powerful anti-inflammatory molecules. Given their profound negative impact on the host antimicrobial defence response, these inhibitors might increase the susceptibility to opportunistic infections, especially in immunocompromised cancer patients. Yet, these inhibitors might be useful to control the inflammatory response in severely ill septic patients or in patients suffering from chronic inflammatory diseases.

MAMOT: hidden Markov modeling tool.

Hidden Markov models (HMMs) are probabilistic models that are well adapted to many tasks in bioinformatics, for example, for predicting the occurrence of specific motifs in biological sequences. MAMOT is a command-line program for Unix-like operating systems, including MacOS X, that we developed to allow scientists to apply HMMs more easily in their research. One can define the architecture and initial parameters of the model in a text file and then use MAMOT for parameter optimization on example data, decoding (like predicting motif occurrence in sequences) and the production of stochastic sequences generated according to the probabilistic model. Two examples for which models are provided are coiled-coil domains in protein sequences and protein binding sites in DNA. A wealth of useful features include the use of pseudocounts, state tying and fixing of selected parameters in learning, and the inclusion of prior probabilities in decoding. AVAILABILITY: MAMOT is implemented in C++, and is distributed under the GNU General Public Licence (GPL). The software, documentation, and example model files can be found at http://bcf.isb-sib.ch/mamot

Machine learning algorithms for spatial data. Case studies: Environmental pollution, natural hazards, renewable resources

This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.

Bacterial flagellin elicits innate immune defenses and cardiac dysfunction in vivo

Résumé Les agents pathogènes responsables d'infection entraînent chez l'hôte deux types de réponses immunes, la première, non spécifique, dite immunité innée, la seconde, spécifique à l'agent concerné, dite immunité adaptative. L'immunité innée, qui représente la première ligne de défense contre les pathogènes, est liée à la reconnaissance par les cellules de l'hôte de structures moléculaires propres aux micro-organismes (« Pathogen-Associated Molecular Patterns », PAMPs), grâce à des récepteurs membranaires et cytoplasmiques (« Pattern Recognition Receptors », PRRs) identifiant de manière spécifique ces motifs moléculaires. Les récepteurs membranaires impliqués dans ce processus sont dénommés toll-like récepteurs, ou TLRS. Lorsqu'ils sont activés par leur ligand spécifique, ces récepteurs activent des voies de signalisation intracellulaires initiant la réponse inflammatoire non spécifique et visant à éradiquer l'agent pathogène. Les deux voies de signalisation impliquées dans ce processus sont la voie des « Mitogen-Activated Protein Kinases » (MAPKs) et celle du « Nuclear Factor kappaB » (NF-κB), dont l'activation entraîne in fine l'expression de protéines de l'inflammation dénommées cytokines, ainsi que certaines enzymes produisant divers autres médiateurs inflammatoires. Dans certaines situations, cette réponse immune peut être amplifiée de manière inadéquate, entraînant chez l'hôte une réaction inflammatoire systémique exagérée, appelée sepsis. Le sepsis peut se compliquer de dysfonctions d'organes multiples (sepsis sévère), et dans sa forme la plus grave, d'un collapsus cardiovasculaire, définissant le choc septique. La défaillance circulatoire du choc septique touche les vaisseaux sanguins d'une part, le coeur d'autre part, réalisant un tableau de «dysfonction cardiaque septique », dont on connaît mal les mécanismes pathogéniques. Les bactéries à Gram négatif peuvent déclencher de tels phénomènes, notamment en libérant de l'endotoxine, qui active les voies de l'immunité innée par son interaction avec un toll récepteur, le TLR4. Outre l'endotoxine, la plupart des bactéries à Gram négatif relâchent également dans leur environnement une protéine, la flagelline, qui est le constituant majeur du flagelle bactérien, organelle assurant la mobilité de ces micro-organismes. Des données récentes ont indiqué que la flagelline active, dans certaines cellules, les voies de l'immunité innée en se liant au récepteur TLRS. On ne connaît toutefois pas les conséquences de l'interaction flagelline-TLRS sur le développement de l'inflammation et des dysfonctions d'organes au cours du sepsis. Nous avons par conséquent élaboré le présent travail en formulant l'hypothèse que la flagelline pourrait déclencher une telle inflammation et représenter ainsi un médiateur potentiel de la dysfonction d'organes au cours du sepsis à Gram négatif, en nous intéressant plus particulièrement àl'inflammation et à la dysfonction cardiaque. Dans la première partie de ce travail, nous avons étudié les effets de la flagelline sur l'activation du NF-κB et des MAPKs, et sur l'expression de cytokines inflammatoires au niveau du myocarde in vitro (cardiomyocytes en culture) et in vivo (injection de flagelline recombinante à des souris). Nous avons observé tout d'abord que le récepteur TLRS est fortement exprimé au niveau du myocarde. Nous avons ensuite démontré que la flagelline active la voie du NF-κB et des MAP kinases (p38 et JNK), stimule la production de cytokines et de chemokines inflammatoires in vitro et in vivo, et entraîne l'activation de polynucléaires neutrophiles dans le tissu cardiaque in vivo. Finalement, au plan fonctionnel, nous avons pu montrer que la flagelline entraîne une dilatation et une réduction aiguë de la contractilité du ventricule gauche chez la souris, reproduisant les caractéristiques de la dysfonction cardiaque septique. Dans la deuxième partie, nous avons déterminé la distribution du récepteur TLRS dans les autres organes majeurs de la souris (poumon, foie, intestin et rein}, et avons caractérisé dans ces organes l'effet de la flagelline sur l'activation du NF-κB et des MAPKs, l'expression de cytokines, et l'induction de l'apoptose. Nous avons démontré que le TLRS est exprimé de façon constitutive dans ces organes, et que l'injection de flagelline y déclenche les cascades de l'immunité innée et de processus apoptotiques. Finalement, nous avons également déterminé que la flagelline entraîne une augmentation significative de multiples cytokines dans le plasma une à six heures après son injection. En résumé, nos données démontrent que la flagelline bactérienne (a) entraîne une inflammation et une dysfonction importantes du myocarde et (b) active de manière très significative les mécanismes d'immunité innée dans les principaux organes et entraîne une réponse inflammatoire systémique. Par conséquent, la flagelline peut représenter un médiateur puissant de l'inflammation et de la dysfonction d'organes, notamment du coeur, au cours du choc septique déclenché par les bactéries à Gram négatif. Summary Pathogenic microorganisms trigger two kinds of immune responses in the host. The first one is immediate and non-specific and is termed innate immunity, whereas the second one, specifically targeted at the invading agent, is termed adaptative immunity. Innate immunity, which represents the first line of defense against invading pathogens, confers the host the ability to recognize molecular structures common to many microbial pathogens, ("Pathogen-Associated Molecular Patterns", PAMPs), through cytosolic or membrane-associated receptors ("Pattern Recognition Receptors", PRRs), the latter being represented by a family of receptors termed "toll-like receptors or TLRs". Once activated by the binding of their specific ligand, these receptors activate intracellular signaling pathways, which initiate the non-specific inflammatory response aimed at eradicating the pathogens. The two pathways implicated in this process are the mitogen-activated protein kinases (MAPK) and the nuclear factor kappa B (NF-κB) signaling pathways, whose activation elicit in fine the expression of inflammatory proteins termed cytokines, as well as various enzymes producing a wealth of additional inflammatory mediators. In some circumstances, the innate immune response can become amplified and dysregulated, triggering an overwhelming systemic inflammatory response in the host, identified as sepsis. Sepsis can be associated with multiple organ dysfunction (severe sepsis), and in its most severe form, with cardiovascular collapse, defming septic shock. The cardiovascular failure associated with septic shock affects blood vessels as well as the heart, resulting in a particular form of acute heart failure termed "septic cardiac dysfunction ", whose pathogenic mechanisms remain partly undefined. Gram-negative bacteria can initiate such phenomena, notably by releasing lipopolysaccharide (LPS), which activates innate immune signaling by interacting with its specific toll receptor, the TLR4. Besides LPS, most Gram-negative bacteria also release flagellin into their environment, which is the main structural protein of the bacterial flagellum, an appendage extending from the outer bacterial membrane, responsible for the motility of the microorganism. Recent data indicated that flagellin activate immune responses upon binding to its receptor, TLRS, in various cell types. However, the role of flagellin/TLRS interaction in the development of inflammation and organ dysfunction during sepsis is not known. Therefore, we designed the present work to address the hypothesis that flagellin might trigger such inflammatory responses and thus represent a potential mediator of organ dysfunction during Gram-negative sepsis, with a particular emphasis on cardiac inflammation and contractile dysfunction. In the first part of this work, we investigated the effects of flagellin on NF-κB and MAPK activation and the generation of pro-inflammatory mediators within the heart in vitro (cultured cardiomyocytes) and in vivo (injection of recombinant flagellin into mice). We first observed that TLRS protein is strongly expressed by the myocardium. We then demonstrated that flagellin activates NF-κB and MAP kinases (p38 and JNK), upregulates the transcription of pro-inflammatory cytokines and chemokines in vitro and in vivo, and stimulates the activation of polymorphonuclear neutrophils within the heart in vivo. Finally, we demonstrated that flagellin triggers acute cardiac dilation, and a significant reduction of left ventricular contractility, mimicking characteristics of clinical septic cardiac dysfunction. In the second part, we determined the TLRS distribution in other mice major organs (lung, liver, gut and kidney) and we characterized in these organs the effects of flagellin on NF-κB and MAPK activation, on the expression of pro-inflammatory çytokines, and on the induction of apoptosis. We demonstrated that TLRS protein is constitutively expressed and that flagellin activates prototypical innate immune responses and pro-apoptotic pathways in all these organs. Finally, we also observed that flagellin induces a significant increase of multiple cytokines in the plasma from 1 to 6 hours after its intravenous administration. Altogether, these data provide evidence that bacterial flagellin (a) triggers an important inflammatory response and an acute dysfunction of the myocardium, and (b) significantly activates the mechanisms of innate immunity in most major organs and elicits a systemic inflammatory response. In consequence, flagellin may represent a potent mediator of inflammation and multiple organ failure, notably cardiac dysfunction, during Gram-negative septic shock.

Innate signaling promotes formation of regulatory nitric oxide-producing dendritic cells limiting T-cell expansion in experimental autoimmune myocarditis.

BACKGROUND: Activation of innate pattern-recognition receptors promotes CD4+ T-cell-mediated autoimmune myocarditis and subsequent inflammatory cardiomyopathy. Mechanisms that counterregulate exaggerated heart-specific autoimmunity are poorly understood. METHODS AND RESULTS: Experimental autoimmune myocarditis was induced in BALB/c mice by immunization with α-myosin heavy chain peptide and complete Freund's adjuvant. Together with interferon-γ, heat-killed Mycobacterium tuberculosis, an essential component of complete Freund's adjuvant, converted CD11b(hi)CD11c(-) monocytes into tumor necrosis factor-α- and nitric oxide synthase 2-producing dendritic cells (TipDCs). Heat-killed M. tuberculosis stimulated production of nitric oxide synthase 2 via Toll-like receptor 2-mediated nuclear factor-κB activation. TipDCs limited antigen-specific T-cell expansion through nitric oxide synthase 2-dependent nitric oxide production. Moreover, they promoted nitric oxide synthase 2 production in hematopoietic and stromal cells in a paracrine manner. Consequently, nitric oxide synthase 2 production by both radiosensitive hematopoietic and radioresistant stromal cells prevented exacerbation of autoimmune myocarditis in vivo. CONCLUSIONS: Innate Toll-like receptor 2 stimulation promotes formation of regulatory TipDCs, which confine autoreactive T-cell responses in experimental autoimmune myocarditis via nitric oxide. Therefore, activation of innate pattern-recognition receptors is critical not only for disease induction but also for counterregulatory mechanisms, protecting the heart from exaggerated autoimmunity.

Representing diffusion MRI in 5D for segmentation of white matter tracts with a level set method.

We present a method for segmenting white matter tracts from high angular resolution diffusion MR. images by representing the data in a 5 dimensional space of position and orientation. Whereas crossing fiber tracts cannot be separated in 3D position space, they clearly disentangle in 5D position-orientation space. The segmentation is done using a 5D level set method applied to hyper-surfaces evolving in 5D position-orientation space. In this paper we present a methodology for constructing the position-orientation space. We then show how to implement the standard level set method in such a non-Euclidean high dimensional space. The level set theory is basically defined for N-dimensions but there are several practical implementation details to consider, such as mean curvature. Finally, we will show results from a synthetic model and a few preliminary results on real data of a human brain acquired by high angular resolution diffusion MRI.