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All cells from simple bacteria to highly differentiated animal cells maintain specialized mechanisms to monitor and respond to changes in their local environments. Unfavorable circumstances that threaten cellular homeostasis will elicit one or more stress response programs in an effort to preserve viability of the organism. The many forms of cellular stress include temperature variation, exposure to toxic compounds, oxidative and reductive stress, ionizing radiation, hypoxia, aging, mechanical injury, and the invasion of pathogens. Mounting the correct response can insure cell survival or initiate an apoptotic program depending on the severity of the stress. Stress responses are also activated in numerous disease states and deficient responses are etiological for afflictions including Parkinson's and Alzheimer's diseases. More recently, stress-regulated genes were intimately linked to aging and shown to be required for the extension of life in model organisms. As a general rule, stress responses remodel relevant cellular pathways to counteract specific effects of the insult.

Protein misfolding is a common cellular event that can produce intrinsically harmful products. To reduce the risk, quality control mechanisms are deployed to detect and eliminate misfolded, aggregated, and unassembled proteins. In the secretory pathway, it is mainly the endoplasmic reticulum-associated degradation (ERAD) pathways that perform this role. Here, specialized factors are organized to monitor and process the folded states of nascent polypeptides. Despite the complex structures, topologies, and posttranslational modifications of client molecules, the ER mechanisms are the best understood among all protein quality-control systems. This is the result of convergent and sometimes serendipitous discoveries by researchers from diverse fields. Although major advances in ER quality control and ERAD came from all model organisms, this review will focus on the discoveries culminating from the simple budding yeast.

Stress pathways monitor intracellular systems and deploy a range of regulatory mechanisms in response to stress. One of the best-characterized pathways, the unfolded protein response (UPR), is responsible for maintaining endoplasmic reticulum (ER) homeostasis. The highly conserved Ire1 branch regulates hundreds of gene targets by activating a UPR-specific transcription factor. To understand how the UPR manages ER stress, a unique genetic approach was applied to reveal how the system corrects disequilibria. The data show that the UPR can address a wide range of dysfunctions that are otherwise lethal if not for its intervention. Transcriptional profiling of stress-alleviated cells shows that the program can be modulated, not just in signal amplitude, but also through differential target gene expression depending on the stress. The breadth of the functions mitigated by the UPR further supports its role as a major mechanism maintaining systems robustness.

ISBN : 978-1-4577-1303-3; International audience; This paper presents significant improvements of Gray Level Size Zone Matrix (GLSZM) which is a bivariate statistical representation of texture, based on the co-occurrences of size/intensity of each flat zone (connected pixels of the same gray level). The first improvement is a multi-scale extension of the matrix which merges various quantizations of gray levels. A second alternative is proposed to take into account radial distribution of zone intensities. The third variant is a generalization of the matrix structure which allows to analyze fibrous textures, by changing the pair intensity/size for the pair length/orientation of each region. The interest of these improved descriptors is illustrated by texture classification problems arising from quantitative cell biology.

The secretory pathway maintains multiple quality control checkpoints. Initially, endoplasmic reticulum-associated degradation pathways monitor protein folding to retain and eliminate aberrant products. Despite its broad client range, some molecules escape detection and traffic to Golgi membranes. There, a poorly understood mechanism termed Golgi quality control routes aberrant proteins for lysosomal/vacuolar degradation. To better understand Golgi quality control, we examined the processing of the obligate substrate Wsc1p. Misfolded Wsc1p does not use routes of typical vacuolar membrane proteins. Instead, it partitions into intralumenal vesicles of the multivesicular body (MVB) pathway, mediated by the E3 ubiquitin ligase Rsp5p. Its subsequent transport to the vacuolar lumen is essential for complete molecule breakdown. Surprisingly, the transport mode plays a second crucial function in neutralizing potential substrate toxicity. Eliminating the MVB sorting signal diverted molecules to the vacuolar limiting membrane, resulting in the generation of toxic by-products. These data demonstrate a new role of the MVB pathway in protein quality control.

The unfolded protein response (UPR) is an intracellular signal transduction pathway that monitors endoplasmic reticulum (ER) homeostasis. Activation of the UPR is required to alleviate the effects of ER stress. However, our understanding of what physiologically constitutes ER stress or disequilibrium is incomplete. The current view suggests that stress manifests as the functional capacity of the ER becomes limiting. To uncover the range of functions under the purview of the UPR, we previously devised a method to isolate mutants that (1) activate the UPR and (2) require UPR activation for viability. These mutants that represent functions, when compromised, cause specific forms of disequilibrium perceived by the UPR. Making UPR activation essential to these mutants ensures a stringent physiological link and avoids stimuli causing nonproductive UPR activation. Thus far, the screen has revealed that the range of functions monitored is surprisingly diverse. Beyond the importance of the screen to understand UPR physiology, it has proven to be useful in discovering new genes in many aspects of protein biosynthesis and quality control.

The unfolded protein response (UPR) is an intracellular signal transduction pathway that monitors endoplasmic reticulum (ER) homeostasis. Activation of the UPR is required to alleviate the effects of ER stress. However, our understanding of what physiologically constitutes ER stress or disequilibrium is incomplete. The current view suggests that stress manifests as the functional capacity of the ER becomes limiting. To uncover the range of functions under the purview of the UPR, we previously devised a method to isolate mutants that (1) activate the UPR and (2) require UPR activation for viability. These mutants that represent functions, when compromised, cause specific forms of disequilibrium perceived by the UPR. Making UPR activation essential to these mutants ensures a stringent physiological link and avoids stimuli causing nonproductive UPR activation. Thus far, the screen has revealed that the range of functions monitored is surprisingly diverse. Beyond the importance of the screen to understand UPR physiology, it has proven to be useful in discovering new genes in many aspects of protein biosynthesis and quality control.

The Escherichia coli inducible lysine decarboxylase, LdcI/CadA, together with the inner-membrane lysine-cadaverine antiporter, CadB, provide cells with protection against mild acidic conditions (pH∼5). To gain a better understanding of the molecular processes underlying the acid stress response, the X-ray crystal structure of LdcI was determined. The structure revealed that the protein is an oligomer of five dimers that associate to form a decamer. Surprisingly, LdcI was found to co-crystallize with the stringent response effector molecule ppGpp, also known as the alarmone, with 10 ppGpp molecules in the decamer. ppGpp is known to mediate the stringent response, which occurs in response to nutrient deprivation. The alarmone strongly inhibited LdcI enzymatic activity. This inhibition is important for modulating the consumption of lysine in cells during acid stress under nutrient limiting conditions. Hence, our data provide direct evidence for a link between the bacterial acid stress and stringent responses.

This paper present a study on the diagnoses of blood cell nuclei from patients affected by the Progeria disease. Nuclei are characterized with various methods that analyze them shape and texture, and subsequently classify them by learning techniques. These methods extract "measures" from nuclei, which are used for the computation of a set of values named "indexes". These indexes are function bringing up real or discrete values that give information about geometrical, morphological and textural features of nuclei. A description model of nuclei is built based on this data, that is used to classify nuclei.

We present a new method for solving the problem of camera pose and calibration from a limited number of correspondences between noisy 2D and 3D features. We show that the probabilistic estimation problem can be expressed as a partially linear problem, where point and line correspondences are mixed using a common formulation. Our Sampling-Solving algorithm enables to robustly estimate the parameters and evaluate the probability distribution of the estimated parameters. It solves the problem of pose estimation with unknown focal length using a minimum of only four correspondences (five if the principal point is also unknown). To our knowledge, this is the first calibration method using so few correspondences of both points and lines. Experimental results show that the algorithm is very robust to Gaussian noise, even for minimal data sets. Finally, some tests show the potential of global uncertainty estimates on real data sets.

Existing studies have proposed that humans preferentially memorize buildings as a collection of floors. Yet this might stem from the fact that environments were also explored by floors. We have studied this potential bias with a learning and recognition experiment. We have detected a positive influence of the learning route – by floors, and also crucially by columns – on spatial memory performances.

La France pourrait connaitre une remise en cause de sa position de champion dans le secteur des services. Mais il est encore possible de changer la donne.

The AAA+ superfamily is a large superfamily of ATPases that are characterized by a conserved catalytic module, the AAA+ module. Members are involved in an astonishing range of different cellular processes., The AAA+ superfamily is a large and functionally diverse superfamily of NTPases that are characterized by a conserved nucleotide-binding and catalytic module, the AAA+ module. Members are involved in an astonishing range of different cellular processes, attaining this functional diversity through additions of structural motifs and modifications to the core AAA+ module.

Phospholipid homeostasis in biological membranes is essential to maintain cellular functions of organelles such as the endoplasmic reticulum (ER). Obesity has been associated to the perturbation of the ratio of the two most abundant phospholipids in the ER, phosphatidylcholine (PC) and phosphatidylethanolamine (PE). PC/PE disequilibrium has also been linked to metabolic diseases such as non-alcoholic fatty liver disease and type II diabetes, but its biological significance remains unclear. This study aims to develop a model of how lipid perturbation (LP) can develop into diseased states. Previously, we reported that Saccharomyces cerevisiae adapts to lipid disequilibrium by upregulating several protein quality control (PQC) pathways such as the endoplasmic reticulum-associated degradation (ERAD) pathway and the unfolded protein response (UPR). We investigated the PQC pathways at their proteomic levels to investigate their effectiveness in response to LP. Surprisingly, we observed certain ER-resident transmembrane proteins (TPs), part of the UPR programme, to be destabilised under LP. Localisation and integration of the TPs to the ER remain unaffected, suggesting that the TPs might be destabilised by changes in ER membrane composition. The ER membrane was found to have undergone fatty acid remodelling and membrane stiffening. Among these, Sbh1, a member of the translocation complex, was prematurely degraded by dissociating from the Sec61 complex. Sbh1 is targeted for degradation through its highly conserved lysine residue near the membrane in a Doa10-dependent ERAD manner. Further investigations revealed Sbh1 destabilisation could result in the translocational defect under LP. Sbh1 overexpression fails to fix the translocational defect, but ameliorate the protein processing defects found under LP. This suggests a novel role of Sbh1 in protein processing. In addition, as LP compromises the UPR, disrupting phospholipid homeostasis may be exploited to target pathogens that upregulate the UPR for survival. Two lipid genes, PfFMP and PfPSD were characterised in Plasmodium falciparum by genetic complementation in yeast. Premature removal of key ER-resident TPs under prolonged LP might be an underlying cause of chronic ER stress in metabolic disorders. ​Doctor of Philosophy (SBS)

Lipid droplets (LDs) have long been regarded as inert cytoplasmic organelles with the primary function of housing excess intracellular lipids. More recently, LDs have been strongly implicated in conditions of lipid and protein dysregulation. Moreover, these conditions are major contributors to the pathophysiology of metabolic diseases and concomitantly activate cellular stress response pathways, namely the unfolded protein response (UPR) and heat shock response (HSR). However, despite the increasing support for the involvement of LDs in other cellular processes, mechanistic insight into the fundamental process of LD biogenesis and its direct physiological relevance to the cell remains rudimentary. The fat storage inducing transmembrane (FIT) family of proteins comprises of evolutionarily conserved endoplasmic reticulum (ER)-resident proteins that have been reported to induce LD formation. Using Saccharomyces cerevisiae as a model, this study aims to dissect the role of LDs in cellular lipid and protein homeostasis through the yeast FIT homologs (ScFIT), SCS3 and YFT2. While LD biogenesis and basal UPR activation remain unaltered in ScFIT mutants, SCS3 was found to be essential for proper stress-induced UPR activation and for viability in the absence of the sole yeast UPR sensor IRE1. Devoid of a functional UPR, scs3Δ mutants exhibited accumulation of triacylglycerol within the ER along with aberrant membrane morphology, indicative of impaired ER-LD lipid partitioning and suggesting a UPR-dependent compensatory mechanism for LD maturation. Surprisingly, the absence of the ScFIT proteins results in the downregulation of the closely-related HSR pathway. In line with this observation, global protein ubiquitination and the turnover of both ER and cytoplasmic misfolded proteins is impaired in ScFITΔ cells, while a screen for interacting partners of Scs3 identifies components of the proteostatic machinery as putative targets. Taken together, these suggest that ScFITs may modulate proteostasis and stress response pathways with lipid metabolism at the interface between the two cellular processes. Doctor of Philosophy

3D models are often used in order to plan the maintenance of industrial environments.When it comes to the simulation of maintenance interventions, these 3D models have todescribe accurately the actual state of the scenes they stand for. These representationsare usually built from 3D point clouds that are huge set of 3D measurements acquiredin industrial sites, which guarantees the accuracy of the resulting 3D model. Althoughthere exists many works addressing the reconstruction problem, there is no solution toour knowledge which can provide results that are reliable enough to be further used inindustrial applications. Therefore this task is in fact handled by human experts nowadays.This thesis aims at providing a solution automating the reconstruction of industrialsites from 3D point clouds and providing highly reliable results. For that purpose, ourapproach relies on some available a priori knowledge and data about the scene to beprocessed. First, we consider that the 3D models of industrial sites are made of simpleprimitive shapes. Indeed, in the Computer Aided Design (CAD) field, this kind of scenesare described as assemblies of shapes such as planes, spheres, cylinders, cones, tori, . . . Ourown work focuses on planes, cylinders and tori since these three kind of shapes allow thedescription of most of the main components in industrial environment. Furthermore, weset some a priori rules about the way shapes should be assembled in a CAD model standingfor an industrial facility, which are based on expert knowledge about these environments.Eventually, we suppose that a CAD model standing for a scene which is similar to theone to be processed is available. This a priori CAO model typically comes from the priorreconstruction of a scene which looks like the one we are interested in. Despite the factthat they are similar theoretically, there may be significant differences between the sitessince each one has its own life cycle.Our work first states the reconstruction task as a Bayesian problem in which we haveto find the most probable CAD Model with respect to both the point cloud and the a prioriexpectations. In order to reach the CAD model maximizing the target probability, wepropose an iterative approach which improves the solution under construction each time anew randomly generated shape is tried to be inserted in it. Thus, the CAD model is builtstep by step by adding and removing shapes, until the algorithm gets to a local maximumof the target probability., Certaines opérations de maintenance sur sites industriels nécessitent une planification à partir de modèles numériques 3D des scènes où se déroulent les interventions. Pour permettre la simulation de ces opérations, les modèles 3D utilisés doivent représenter fidèlement la réalité du terrain. Ces représentations virtuelles sont habituellement construites à partir de nuages de points relevés sur le site, constituant une description métrologique exacte de l’environnement sans toutefois fournir une description géométrique de haut niveau.Il existe une grande quantité de travaux abordant le problème de la reconstruction de modèles 3D à partir de nuages de points, mais peu sont en mesure de fournir des résultats suffisamment fiables dans un contexte industriel et cette tâche nécessite en pratique l’intervention d’opérateurs humains.Les travaux réalisés dans le cadre de cette thèse visent l’automatisation de la reconstruction,avec comme principal objectif la fiabilité des résultats obtenus à l’issu du processus. Au vu de la complexité de ce problème, nous proposons d’exploiter des connaissances et données a priori pour guider la reconstruction. Le premier a priori concerne la compositiondes modèles 3D : en Conception Assistée par Ordinateur (CAO), les scènes industrielles sont couramment décrites comme des assemblages de primitives géométriques simples telles que les plans, sphères, cylindres, cônes, tores, etc. Nous hiérarchisons l’analyse en traitant dans un premier temps les plans et les cylindres, comme un préalable à la détection de stores. On obtient ainsi une description fiable des principaux composants d’intérêt dans les environnements industriels. Nous proposons en outre d’exploiter un certain nombre de règles régissant la manière dont ces primitives s’assemblent en un modèle CAO, basées surdes connaissances ”métier” caractérisant les scènes industrielles que nous traitons. De plus,nous tirons parti d’un modèle CAO existant d´ecrivant une scène similaire à celle que nous souhaitons reconstruire, provenant typiquement de la reconstruction antérieure d’un site semblable au site d’intérêt. Bien que semblables en théorie, ces scènes peuvent présenterdes différences significatives qui s’accentuent au cours de leur exploitation.La méthode que nous développons se fonde sur une formulation Bayésienne du problème de reconstruction : il s’agit de retrouver le modèle CAO le plus probable vis à visdes différentes attentes portées par les données et les a priori sur le modèle à reconstruire. Les diverses sources d’a priori s’expriment naturellement dans cette formulation. Pour permettre la recherche du modèle CAO optimal, nous proposons une approche basée surdes tentatives d’insertion d’objets générés aléatoirement. L’acceptation ou le rejet de ces objets repose ensuite sur l’am´elioration systématique de la solution en cours de construction. Le modèle CAO se construit ainsi progressivement, par ajout et suppression d’objets, jusqu’à obtention d’une solution localement optimale.