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Resistance to chemotherapy can be studied comparatively to the study of resistance in microorganisms. Among the protein superfamily identified as being responsible for multidrug resistance are RND. Its members are widespread in bacterial organisms, but also in Archaea and Eukaryotes. Ptch1, a transmembrane protein, receptor of morphogen Hedgehog (Hh), a member of the RND, has cholesterol efflux activity, but also of chemotherapeutic drugs which confers resistanceto chemotherapy to cancer cells. In fact, an aberrant activity of the Hh signaling pathway has been observed in nearly 25% of cancers. Among the common features of multidrug resistance in RND is the ability of these transmembrane proteins to efflux a broad spectrum of substrates and drugs using protonmotive force.The goal of this project is the structural study of the drug efflux mechanism of Ptch1.In a first step, since we did not yet have access to a structure of Ptch1, we have performed an analysis of the numerous available structures of its bacterial counterpart AcrB, the RND paradigm model responsible for antibiotic resistance in gram-negative bacteria, in order to better understand the drug efflux mechanism of these proteins. We have implemented a strategy of conformational analysis of all available structures in order to explain the complex mechanism, including the drug efflux mechanism of these proteins, as a function of the structural and dynamic properties of sub-domains. The tools developed have been made available to the community.The structures of Ptch1 published in 2018 and 2019 revealed that the drug efflux mechanism of Ptch1 was probably very different from that of AcrB. In a second step, using these structures, we studied the cholesterol efflux mechanism of Ptch1 by molecular dynamics in order to subsequently study the drug efflux mechanism. We thus identified certain characteristics of the conformational changes that cantake place to allow this efflux. Finally, the docking of chemotherapeutic agents carried by Ptch1 suggests that drugs use the same interaction sites as cholesterol and potentially the same efflux mechanism.; La résistance à la chimiothérapie peut-être étudiée comparativement à l’étude de la résistance chez les microorganismes. Parmi les superfamilles de protéine identifiées comme étant responsables de résistance aux drogues, il y a les RND. Ses membres sont très répandus dans les organismes bactériens, mais aussi les archaea et les eucaryotes. Ptch1, protéine transmembranaire récepteur du morphogène Hedgehog (Hh), membre des RND, a une activité d’efflux de cholestérol, mais aussi de médicaments chimiothérapeutiques qui confère aux cellules cancéreuses une résistance à la chimiothérapie. Or, une activité aberrante de la voie de signalisation Hh a été observée dans près de 25 % des cancers. Parmi les caractéristiques communes à la résistance aux drogues des RND, il y a la capacité de ces protéines transmembranaires à faire de l’efflux d’un large spectre de substrats et de drogues, et ce, en utilisant la force proton motrice.L’objectif de ce projet est l’étude structurale du mécanisme d’efflux de drogues de Ptch1.Dans un premier temps, n’ayant pas encore accès à une structure de Ptch1, nous avons réalisé une analyse des nombreuses structures disponibles de son homologue bactérien AcrB, modèle paradigme des RND responsable de résistance aux antibiotiques chez les bactéries gram négatives, afin de mieux comprendre le mécanisme d’efflux de drogues de ces protéines. Nous avons mis en place une stratégie d’analyse conformationnelle de l’ensemble des structures disponibles de façon à expliquer le mécanisme complexe, notamment ceux d’efflux de drogues de ces protéines, en fonction des propriétés structurales et dynamiques de sous-domaines. Les outils développés ont été mis à disposition de la communauté.Les structures de Ptch1 publiées en 2018 et 2019 ont révélé que le mécanisme d’efflux de drogues de Ptch1 était probablement très différent de celui d’AcrB. Dans un second temps, en utilisant ces structures, nous avons étudié le mécanisme d’efflux de cholestérol de Ptch1 par dynamique moléculaire afin d’étudier par la suite celui des drogues. Nous avons ainsi identifié certaines caractéristiques des changements conformationnels pouvant avoir lieu afin de permettre cet efflux. Enfin, le docking des agents chimiothérapeutiques transportés par Ptch1 suggère que les drogues utilisent les mêmes sites d’interaction que le cholestérol et potentiellement le même mécanisme d’efflux.

Prebiotics are increasingly used as food supplements, especially in infant formulas, to modify the functioning and composition of the microbiota. However, little is currently known about the mechanisms of prebiotic recognition and transport by gut bacteria, while these steps are crucial in their metabolism. In this study, we established a new strategy to profile the specificity of oligosaccharide transporters, combining microbiomics, genetic locus and strain engineering, and state-of-the art metabolomics. We revisited the transporter classification database and proposed a new way to classify these membrane proteins based on their structural and mechanistic similarities. Based on these developments, we identified and characterized, at the molecular level, a fructooligosaccharide transporting phosphotransferase system, which constitutes a biomarker of diet and gut pathology. The deciphering of this prebiotic metabolization mechanism by a nonbeneficial bacterium highlights the controversial use of prebiotics, especially in the context of chronic gut diseases., Prebiotic oligosaccharides, such as fructooligosaccharides, are increasingly being used to modulate the composition and activity of the gut microbiota. However, carbohydrate utilization analyses and metagenomic studies recently revealed the ability of deleterious and uncultured human gut bacterial species to metabolize these functional foods. Moreover, because of the difficulties of functionally profiling transmembrane proteins, only a few prebiotic transporters have been biochemically characterized to date, while carbohydrate binding and transport are the first and thus crucial steps in their metabolization. Here, we describe the molecular mechanism of a phosphotransferase system, highlighted as a dietary and pathology biomarker in the human gut microbiome. This transporter is encoded by a metagenomic locus that is highly conserved in several human gut Firmicutes, including Dorea species. We developed a generic strategy to deeply analyze, in vitro and in cellulo, the specificity and functionality of recombinant transporters in Escherichia coli, combining carbohydrate utilization locus and host genome engineering and quantification of the binding, transport, and growth rates with analysis of phosphorylated carbohydrates by mass spectrometry. We demonstrated that the Dorea fructooligosaccharide transporter is specific for kestose, whether for binding, transport, or phosphorylation. This constitutes the biochemical proof of effective phosphorylation of glycosides with a degree of polymerization of more than 2, extending the known functional diversity of phosphotransferase systems. Based on these new findings, we revisited the classification of these carbohydrate transporters. IMPORTANCE Prebiotics are increasingly used as food supplements, especially in infant formulas, to modify the functioning and composition of the microbiota. However, little is currently known about the mechanisms of prebiotic recognition and transport by gut bacteria, while these steps are crucial in their metabolism. In this study, we established a new strategy to profile the specificity of oligosaccharide transporters, combining microbiomics, genetic locus and strain engineering, and state-of-the art metabolomics. We revisited the transporter classification database and proposed a new way to classify these membrane proteins based on their structural and mechanistic similarities. Based on these developments, we identified and characterized, at the molecular level, a fructooligosaccharide transporting phosphotransferase system, which constitutes a biomarker of diet and gut pathology. The deciphering of this prebiotic metabolization mechanism by a nonbeneficial bacterium highlights the controversial use of prebiotics, especially in the context of chronic gut diseases.

Cell membranes are composed of a lipid bilayer, crowded with transmembrane proteins that mediate nearly all of the membrane functions, such as detoxification and communication. There is a tight interaction between lipids and transmembrane proteins. Membrane can apply mechanical stress and impact transmembrane proteins shape and function. Reciprocally, the inclusion of a transmembrane protein can bend or stretch the membrane. In particular, this interplay might play a crucial role for proteins that change conformation to mediate cargoes transport. We study BmrA, a bacterial ABC exporter from B.subtillis. ABC (ATP Binding Cassette) transporters represent one of the largest families of membrane proteins. Some ABC exporters lead to a phenotype of multi-drug resistance, such as human P-glycoprotein (P-gp) which transports anti-cancer agents out the cell. BmrA shares high homology with P-gp and is expected to undergo a large conformational change between “open” and “closed” conformations. The objective is to characterize the interplay between the conformation cycle of BmrA and membrane curvature, at the single molecule level. BmrA is purified in detergent, labelled with dyes suitable for FRET experiments, and incorporated in small liposomes. Conformations of BmrA are probed by single-molecule FRET in TIRF microscopy: a low (resp. high) FRET efficiency corresponds to a protein in open (resp. closed) conformation. Three different liposome sizes are used in order to vary the membrane curvature: diameter 140, 60 and 40nm. We have found a different protein behavior in 40nm liposomes as compared to larger ones, indicating an effect of the membrane curvature on BmrA conformations., Les membranes des cellules sont composées d’une bicouche lipidique et de protéines transmembranaires qui sont responsables de la plupart des fonctions membranaires. Les membranes peuvent exercer une contrainte mécanique capable d’altérer la forme de la protéine et donc sa fonction. Réciproquement, une inclusion dans la membrane peut lui imposer une tension ou une courbure. Cette interaction peut s’avérer cruciale pour des protéines qui subissent un changement de conformation. Nous étudions BmrA, un transporteur ABC bactérien issu de B.subtillis. Les transporteurs ABC (ATP Binding Cassette) sont une des plus grande familles de protéines membranaires. Le transporteur humain P-glycoprotéine (P-gp) exporte des agents anti-cancéreux à l’extérieur de la cellule et crée ainsi un phénotype de résistance aux médicaments. BmrA est un homologue de P-gp et subit un large changement de conformation entre une forme dite « ouverte » et une « fermée ». L’objectif est d’étudier l’interaction entre le cycle conformationnel de BmrA et la courbure membranaire à l’échelle de la molécule unique. Les différentes conformations sont discriminées grâce à la méthode FRET en microscopie TIRF : une faible (resp. haute) efficacité de FRET correspond à la conformation ouverte (resp. fermée). BmrA est purifiée, marquée avec des sondes fluorescentes compatibles avec la méthode FRET et incorporée dans des petits liposomes. Trois tailles de liposomes sont étudiées pour faire varier la courbure membranaire avec des diamètres de 140, 60 et 40nm. Nous avons observé un comportement différent pour la protéine dans les liposomes de 40nm, indiquant un effet de la courbure membranaire sur les conformations de BmrA.

Glioblastoma are the most common and aggressive nervous system tumors. With a median overall survival smaller than 2 years, usual therapies remain inefficient. This failure could be explained in part by the existence of cancer stem cells. These cells share several properties with stem cells which make them resistant to glioblastoma treatments. This is why it is important to identify and target them to suppress the whole tumor.The goal of this thesis work is to identify glioblastoma stem cells (gCSCs) biomarkers. To this end, we first developed a global method predicting cancer antigens from microarray data. Then, by studying gCSCs we identified several putative biomarkers and generated insights concerning the calcium signals which are deregulated in numerous cancers., Les glioblastomes sont les tumeurs du système nerveux central les plus fréquentes et agressives. Avec une survie médiane inférieure à 2 ans, les thérapies actuelles restent inefficaces. Cet échec pourrait être expliqué en partie par l’existence de cellules particulières, les cellules souches cancéreuses. Ces cellules ont plusieurs propriétés communes aux cellules souches, qui les rendent résistantes aux traitements des glioblastomes. Il est donc important de pouvoir les identifier et les cibler pour pouvoir éliminer totalement la tumeur. L’objectif de ce travail de thèse est de déterminer des biomarqueurs des cellules souches de glioblastomes (gCSCs). Pour cela, nous avons d’abord développé une méthode générique permettant de prédire des antigènes spécifiques de cancer à partir de données de puces d’expression. Puis, nous avons travaillé sur les gCSCs, en identifiant des biomarqueurs potentiels, puis en étudiant les modifications du signal calcium, dérégulé dans de nombreux cancers.

Cell membrane proteins are involved in a variety of biochemical pathways and therefore constitute important targets for therapy and development of new drugs. Bioanalytical platforms and binding assays using these membrane protein receptors for drug screening or diagnostic require the construction of well-characterized liposome and lipid bilayer arrays that act as support to prevent protein denaturation during biochip processing. Quantification of the protein receptors in the lipid membrane arrays is a key issue in order to produce reproducible and well-characterized chips. Herein, we report a novel immunochemical analytical approach for the quantification of membrane proteins (i.e., G-protein-coupled receptor, GPCR) in nanovesicles (NVs). The procedure allows direct determination of tagged receptors (i.e., c-myc tag) without any previous protein purification or extraction steps. The immunochemical method is based on a microplate ELISA format and quantifies this tag on proteins embedded in NVs with detectability in the picomolar range, using protein bioconjugates as reference standards. The applicability of the method is demonstrated through the quantification of the c-myc-olfactory receptor (OR, c-myc-OR1740) in the cell membrane NVs. The reported method opens the possibility to develop well-characterized drug-screening platforms based on G-coupled proteins embedded on membranes.

International audience; The transmembrane proteins MreC and MreD are present in a wide variety of bacteria and are thought to be involved in cell shape determination. Together with the actin homologue MreB and other morphological elements, they play an essential role in the synthesis of the lateral cell wall in rod-shaped bacteria. In ovococcus, which lack MreB homologues, mreCD are also essential and have been implicated in peripheral cell wall synthesis. In this work we addressed the possible roles of MreC and MreD in the spherical pathogen Staphylococcus aureus. We show that MreC and MreD are not essential for cell viability and do not seem to affect cell morphology, cell volume or cell cycle control. MreC and MreD localize preferentially to the division septa, but do not appear to influence peptidoglycan composition, nor the susceptibility to different antibiotics and to oxidative and osmotic stress agents. Our results suggest that the function of MreCD in S. aureus is not critical for cell division and cell shape determination.

International audience; Background: The locations of the TM segments inside the membrane proteins are the consequence of a cascade of several events: the localizing of the nascent chain to the membrane, its insertion through the translocon, and the conformation adopted to reach its stable state inside the lipid bilayer. Even though the hydrophobic h-region of signal peptides and a typical TM segment are both composed of mostly hydrophobic side chains, the translocon has the ability to determine whether a given segment is to be inserted into the membrane. Our goal is to acquire robust biological insights into the influence of the translocon on membrane insertion of helices, obtained from the in silico discrimination between signal peptides and transmembrane segments of bitopic proteins. Therefore, by exploiting this subtle difference, we produce an optimized scale that evaluates the tendency of each amino acid to form sequences destined for membrane insertion by the translocon. Results: The learning phase of our approach is conducted on carefully chosen data and easily converges on an optimal solution called the PMIscale (Potential Membrane Insertion scale). Our study leads to two striking results. Firstly, with a very simple sliding-window prediction method, PMIscale enables an efficient discrimination between signal peptides and signal anchors. Secondly, PMIscale is also able to identify TM segments and to localize them within protein sequences. Conclusions: Despite its simplicity, the localization method based on PMIscale nearly attains the highest level of TM topography prediction accuracy as the current state-of-the-art prediction methods. These observations confirm the prominent role of the translocon in the localization of TM segments and suggest several biological hypotheses about the physical properties of the translocon.

The molecular mechanisms and hidden dynamics governing ERK activation by the angiotensin II type 1A receptor are studied and deciphered, revealing a signal balancing mechanism that is found to be relevant to a range of other seven transmembrane receptors., An ODE-based dynamical model of ERK activation by the prototypical angiotensin II type-1A seven transmembrane receptor has been built and validated. In order to deal with a limited number of experimental read-outs, unknown parameters have been inferred by simultaneously fitting control and perturbed conditions. In addition to its well-established function in G-protein uncoupling, G protein-coupled receptor kinase 2 has been shown to exert a strong negative effect on β-arrestin-dependent signaling and by doing so, to balance G-protein and β-arrestin signaling. This novel function of G protein-coupled receptor kinase 2 has also been evidenced in primary vascular smooth muscle cells naturally expressing the AT1AR and in HEK293 cells expressing other 7TMRs., Seven-transmembrane receptors (7TMRs) are involved in nearly all aspects of chemical communications and represent major drug targets. 7TMRs transmit their signals not only via heterotrimeric G proteins but also through β-arrestins, whose recruitment to the activated receptor is regulated by G protein-coupled receptor kinases (GRKs). In this paper, we combined experimental approaches with computational modeling to decipher the molecular mechanisms as well as the hidden dynamics governing extracellular signal-regulated kinase (ERK) activation by the angiotensin II type 1A receptor (AT1AR) in human embryonic kidney (HEK)293 cells. We built an abstracted ordinary differential equations (ODE)-based model that captured the available knowledge and experimental data. We inferred the unknown parameters by simultaneously fitting experimental data generated in both control and perturbed conditions. We demonstrate that, in addition to its well-established function in the desensitization of G-protein activation, GRK2 exerts a strong negative effect on β-arrestin-dependent signaling through its competition with GRK5 and 6 for receptor phosphorylation. Importantly, we experimentally confirmed the validity of this novel GRK2-dependent mechanism in both primary vascular smooth muscle cells naturally expressing the AT1AR, and HEK293 cells expressing other 7TMRs.

We report the finding of a new putative cholesterol-recognition motif in the transmembrane region of membrane proteins like the nicotinic acetylcholine receptor (AChR) and other members of the Cys-loop superfamily of neurotransmitters involved in rapid synaptic transmission, as well as in members of the important superfamily of G protein coupled receptors (GPCRs) involved in Alzheimer's disease. The motif is an inverted CRAC domain (cholesterol recognition/interaction amino acid consensus) which we have named CARC and is present in the transmembrane regions of the receptor subunits having extensive contact with the surrounding lipid, predominantly in the first (TM1) segment in the case of the AChR, and optimally suited to convey cholesterol-mediated signaling. Three cholesterol molecules could be docked on the transmembrane regions of the five human AChR subunits, rendering a total of 15 cholesterol molecules per AChR molecule, adding up to a total of about 200 kJ.mol-1 per receptor molecule, i.e. ∼40% of the total lipid solvation free energies for the whole AChR molecule. The novel motif is remarkably conserved among Cys-loop receptors along the phylogenetic scale, from prokaryotes to humans, its high degree of conservation suggesting that it could be responsible for some of the structural/functional properties of these transduction macromolecules.Reference: Baier, C.J., Fantini, J. and Barrantes, F.J. (2011). Sci. Rep. 1:00069.

The transmembrane β-barrel proteins (TMBs) are found in the outer membrane of Gram-negative bacteria, mitochondria and chloroplasts. They entirely span the biological membrane and perform a wide range of important functions. As the number of TMB structures known today is very limited, due to difficulties in experimental methods, it is arguable whether the learning-based prediction methods could work well for recognizing and folding TMBs which are not homologous to those currently known. We present a novel graph-theoretic model for classification and prediction of permuted super-secondary structures of TMBs from their amino acid sequence, based on energy minimization. The model does not essentially depend on learning. The algorithms are fast, robust with comparable performance to the best currently known learning-based methods. This method can be thus a useful tool for the genome screening. Besides the performance on prediction and classification, this study gives an insight into TMB structures regarding the physicochemical constraints of biological membranes. The predicted permuted structures can also enhance the understanding on the folding mechanism of TMBs., Les protéines transmembranaires canaux-β (TMBs) se trouvent dans les membranes externes des bactéries à Gram négatif, des mitochondries ainsi que des chloroplastes. Elles traversent entièrement la membrane cellulaire et exercent différentes fonctions importantes. Vu qu'il y a un petit nombre des structures des TMBs déterminées, en raison des difficultés avec les méthodes expérimentales, il est douteux que ces approches puis- sent bien trouver et prédire les TMBs qui ne sont pas homologues avec celles connues. Nous construisons un modèle de graphe pour la classification et la prédiction de structures super-secondaires permutées des TMBs à partir de leur séquence d'acides aminés, en se basant sur la minimisation d'énergie. Le modèle ne dépend essentiellement pas de l'apprentissage. Les algorithmes sont rapides, robustes avec des performances com- parables à celles des meilleures méthodes actuelles qui utilisent l'apprentissage. Cette méthode peut être donc utile pour le screening des génomes. Outre la performance de prédiction et de classification, cette étude donne une vue plus profonde de la structure des TMBs en tenant compte des contraintes physicochimiques des membranes biologiques. Les structures permutées prédites peuvent aussi aider à mieux comprendre le mécanisme du repliement des TMBs.

Dans ce travail, nous nous intéressons à la localisation des protéines adressées vers la membrane du réticulum endoplasmique, et plus spécifiquement à la reconnaissance des segments transmembranaires et des peptides signaux. En utilisant les dernières connaissances acquises sur les mécanismes d'insertion d'un segment dans la membrane, nous proposons une méthode de discrimination de ces deux types de séquences basée sur le potentiel d';insertion de chaque acide aminé dans la membrane. Cela amène à rechercher pour chaque acide aminé une courbe donnant son potentiel d'insertion en fonction de sa place dans une fenêtre correspondant à l'épaisseur de la membrane. Notre objectif est de déterminer "in silico" une courbe pour chaque acide aminé, afin d'obtenir les meilleures performances pour notre méthode de classification. L'optimisation, sur des jeux de données construits à partir des banques de données de protéines, des courbes est un problème difficile que nous abordons grâce aux méthodes méta-heuristiques. Nous présentons tout d'abord un premier algorithme de recherche locale permettant d'apprendre un ensemble de courbes. Son évaluation sur les différents jeux de données montre de bons résultats de classification. Cependant, nous constatons une difficulté d'ajustement pour les courbes de certains acides aminés. La restriction de l'espace de recherche grâce à des informations pertinentes sur les acides aminés et l'introduction d'un voisinage multiple nous permettent d'améliorer les performances de notre méthode et en même temps de stabiliser les courbes apprises. Nous présentons également un algorithme génétique développé afin d'explorer de manière plus diversifiée l'espace de recherche de ce problème., In this work, we are interested in the localization of proteins transported towards the endoplasmic reticulum membrane, and more specifically to the recognition of transmembrane segments and signal peptides. By using the last knowledges acquired on the mechanisms of insertion of a segment in the membrane, we propose a discrimination method of these two types of sequences based on the potential of insertion of each amino acid in the membrane. This leads to search for each amino acid a curve giving its potential of insertion according to its place in a window corresponding to the thickness of the membrane. Our goal is to determine ”in silico” a curve for each amino acid to obtain the best performances for our method of classification. The optimization, on data sets constructed from data banks of proteins, of the curves is a difficult problem that we address through the meta-heuristic methods.We first present a local search algorithm for learning a set of curves. Its assessment on the different data sets shows good classification results. However, we notice a difficulty in adjusting the curves of certain amino acids. The restriction of the search space with relevant information on amino acids and the introductionof multiple neighborhood allow us to improve the performances of our method and at the same time to stabilize the learnt curves. We also developed a genetic algorithm to explore in a more diversified way the space of search for this problem

International audience; Although ions play important roles in the cell and chloroplast metabolism, little is known about ion transport across the chloroplast envelope. Using a proteomic approach specifically targeted to the Arabidopsis chloroplast envelope, we have identified HMA1, which belongs to the metal-transporting P1B-type ATPases family. HMA1 is mainly expressed in green tissues, and we validated its chloroplast envelope localization. Yeast expression experiments demonstrated that HMA1 is involved in copper homeostasis and that deletion of its N-terminal His-domain partially affects the metal transport. Characterization of hma1 Arabidopsis mutants revealed a lower chloroplast copper content and a diminution of the total chloroplast superoxide dismutase activity. No effect was observed on the plastocyanin content in these lines. The hma1 insertional mutants grew like WT plants in standard condition but presented a photosensitivity phenotype under high light. Finally, direct biochemical ATPase assays performed on purified chloroplast envelope membranes showed that the ATPase activity of HMA1 is specifically stimulated by copper. Our results demonstrate that HMA1 offers an additional way to the previously characterized chloroplast envelope Cu-ATPase PAA1 to import copper in the chloroplast.