Orientador: Carlos Henrique Inácio Ramos / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Biologia / Made available in DSpace on 2018-08-18T21:37:15Z (GMT). No. of bitstreams: 1 Gava_LisandraMarques_D.pdf: 9573403 bytes, checksum: 4d69a29d08ffc20e4544b876f131fb0d (MD5) Previous issue date: 2011 / Resumo: A função biológica das proteínas está relacionada à sua estrutura tridimensional adquirida pelo processo de enovelamento protéico. Neste contexto, proteínas denominadas, genericamente, de chaperonas moleculares exercem papel fundamental atuando no auxílio do enovelamento correto, no reenovelamento e na dissociação de agregados protéicos. A Hsp90 é uma das chaperonas moleculares mais importantes, é essencial para a viabilidade celular em eucariotos e está normalmente associada a proteínas atuantes no ciclo e sinalização celular, o que torna essa chaperona um alvo bastante interessante para abordagens terapêuticas de diversas doenças. A Hsp90 pode ser modulada por co-chaperonas diversas. Nesse trabalho foram caracterizadas as proteínas CHsp90 (domínio C-terminal da Hsp90 humana), e as co-chaperonas Hop e Tom70, além da interação entre C-Hsp90 e Tom70. Foram aplicadas técnicas de dicroísmo circular e emissão de fluorescência do triptofano; seguidas pela caracterização por ultracentrifugação analítica, gel filtração analítica, espalhamento dinâmico de luz, cromatografia de gel filtração acoplada a espalhamento de luz em multi-ângulos (SEC-MALS) e gel nativo. Para os ensaios de interação foram aplicadas técnicas de pull-down, SEC-MALS e calorimetria de titulação isotérmica. As proteínas foram produzidas puras e enoveladas, com estado oligomérico determinado como dímero para C-Hsp90 e monômero para Hop e Tom70, sendo que essas também foram encontradas como espécies diméricas. A estequiometria de interação entre a C-Hsp90 e Tom70 foi determinada em 1 monômero da Tom70 para 1 dímero da C-Hsp90, com KD de 360 ± 30 nM, ?Happ = -2,6 ± 0,1 kcal/mol e ?S = 21 ± 1 cal/mol.K, sugerindo que a interação é dirigida por entalpia e entropia. Os resultados obtidos nesse trabalho contribuem para uma melhor compreensão do sistema Hsp90, que está envolvido em diversos processos celulares essenciais e patológicos, como doenças neurodegenerativas, processos inflamatórios, infecções e câncer / Abstract: The biological function of proteins is related to its three dimensional structure acquired via protein folding process. In this context, the molecular chaperones play a key role acting as auxiliary protein on protein folding, refolding and dissociation of protein aggregates. Hsp90 is one of the most important molecular chaperones, is essential for cell viability in eukaryotes and is usually associated with proteins involved in cell cycling and cell signaling, which makes these chaperone a very interesting targeting for therapeutic approaches for several diseases. The chaperone activity of Hsp90 can be modulated by other proteins, called co-chaperones. In this work, we characterized the protein C-Hsp90 (Cterminal domain of human Hsp90) and the co-chaperones Hop and Tom70, and also the interaction between C-Hsp90 and Tom70. Circular dichroism and fluorescence emission of tryptophan was first applied for initial characterization of the proteins, followed by analytical ultracentrifugation, analytical gel filtration, dynamic light scattering, size exclusion chromatography - multi angle light scattering (SEC-MALS) and native gel. The interaction between C-Hsp90 and Tom70 were measured by techniques like pull-down, SEC-MALS and isothermal titration calorimetry. The proteins were produced pure and soluble and their oligomeric state were determined as dimer for C-Hsp90, and monomer for Hop and Tom70, these two co-chaperones were also found as dimeric species. The stoichiometry of interaction between C-Hsp90 and Tom70 was determined by SEC-MALS and ITC as been 1 dimer of C-Hsp90 to 1 monomer of Tom70, with a KD of 360 ± 30 nM, ?Happ = -2.6 ± 0.1 kcal/mol and ?S = 21 ± 1 cal/mol.K, suggesting that these interaction is driven by both, enthalpy and entropy. The results contribute to a better understanding of the important Hsp90 machinery, which is involved in many essential cellular and pathological processes, such as neurodegenerative diseases, inflammation, infection and cancer / Doutorado / Bioquimica / Doutor em Biologia Funcional e Molecular

Orientadoesr: Carlos Henrique Inácio Ramos, Gonçalo Amarante Guimarães Pereira / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Biologia / Made available in DSpace on 2018-08-20T06:21:14Z (GMT). No. of bitstreams: 1 Goncalves_DanieliCristina_M.pdf: 10469841 bytes, checksum: df29d5b11d3cdd27679b971b2bbcb032 (MD5) Previous issue date: 2012 / Resumo: Chaperonas moleculares (Heat Shock proteins - HSPs) são componentes chave do sistema de controle de qualidade de proteínas (PQC - Protein Quality Control), que é essencial para a vida, sendo responsável por manter a homeostase proteica e a adequada função de diversas vias. Problemas no processo de enovelamento estão relacionados a doenças degenerativas, amilóides e câncer. Em plantas, as chaperonas moleculares desempenham um papel crucial na proteção contra estresses bióticos e abióticos, pois como organismos sésseis, as plantas devem ser capazes de responder rapidamente a mudanças na temperatura, salinidade, déficit hídrico, entre outros. A chaperona molecular Hsp90 (Heat Shock protein 90 kDa) compreende uma família ubíqua, considerada um 'hub' por interagir com chaperonas, co-chaperonas e ter como clientes proteínas regulatórias essenciais como fatores de transcrição, quinases, receptores de hormônios, entre outros. A Hsp90 age em conjunto com co-chaperonas, as quais modulam e direcionam sua função. Uma destas co-chaperonas é a Hop (Hsp70-Hsp90 organizing protein), capaz de interagir simultaneamente com a Hsp90 e Hsp70, mediando a transferência de substratos. A Hop é composta por três domínios com repetições de tetratricopeptídeos (TPR) (TPR1, TPR2A e TPR2B), responsáveis pela interação com as chaperonas, porém a dinâmica desta interação não está bem entendida, uma vez que ainda não há estrutura da Hop inteira e o estado oligomérico desta co-chaperona ainda é controverso na literatura. Neste trabalho apresentamos a classificação de um gene de Hsp90 de cana-de-açúcar, e o início de sua caracterização funcional através de transgenia em Arabidopsis thaliana. Apresentamos também a caracterização biofísica de uma importante co-chaperona da Hsp90, a Hop (Hsp70-Hsp90 organizing protein) humana. Através da análise de sequências a Hsp90 de cana-de-açúcar foi classificada como Hsp90-3, uma isoforma citosólica. Plantas transgênicas de A. thaliana, produzidas a partir da inserção do gene da Hsp90-3 de cana-de-açúcar, apresentaram níveis reduzidos de Hsp90. Tal perturbação nos níveis de Hsp90 parece ter afetado a expressão de outras proteínas da rede de interações, relacionadas com processos diversos como resposta imune e fotossíntese. As plantas transgênicas também exibiram germinação mais rápida e raízes mais longas em relação ao controle. Sob estresse térmico, linhagens transgênicas apresentaram maior suscetibilidade à alta temperatura em relação ao controle. Tais resultados sugerem que a Hsp90 tem um importante papel na fisiologia celular e no desenvolvimento, e que os níveis de Hsp90 são críticos para a resposta frente a estresses. A caracterização biofísica do mutante Hop D456G, uma mutação no domínio TPR2B, mostrou que esta proteína é uma mistura de monômeros, dímeros e oligômeros maiores, porém com prevalência do estado monomérico. O resíduo D456 pode ter uma participação na dinâmica de dimerização e é possível que o estado oligomérico da Hop seja regulado entre os estados monomérico e dimérico, com a finalidade de facilitar sua atividade adaptadora / Abstract: Molecular chaperones (heat shock proteins - HSPs) are key components of protein quality-control system (PQC - Protein Quality Control), which maintains protein homeostasis and the proper function of several pathways, being essential for life. Defects in folding processes are related to degenerative diseases, amyloidosis and cancer. In plants, which as sessile organisms must be able to respond rapidly to changes in temperature, salinity, water deficit, and others, molecular chaperones play a crucial role in protecting against such biotic and abiotic stresses. Molecular chaperone Hsp90 (Heat Shock Protein 90 kDa) comprise an ubiquitous family, considered a hub as it interacts with chaperones, co-chaperones, and have as clients key regulatory proteins such as transcription factors, kinases, hormone receptors, and others. The chaperone acts together with co-chaperones, which modulate and guide Hsp90 function. The co-chaperone Hop (Hsp70-Hsp90 organizing protein), interacts simultaneously with Hsp90 and Hsp70, mediating substrate transfer. Hop has three TPR domains (TPR1, and TPR2A TPR2B) responsible for interaction with the chaperones, but this interaction dynamics remains unclear, since there is no structure of full length Hop and its oligomeric state is controversial in literature reports. This work presents the classification of an Hsp90 gene from sugarcane, and primary functional characterization studies in Arabidopsis thaliana transgenic lines. We also present the biophysical characterization of the human Hsp90 co-chaperone Hop (Hsp70-Hsp90 organizing protein). Through sequence analysis the Hsp90 from sugarcane has been classified as Hsp90-3, a cytosolic isoform. Transgenic A. thaliana, produced by Hsp90-3 insertion, exhibited reduced transcript levels of Hsp90. This disruption in Hsp90 levels seems to affect the expression of other proteins from the interaction network, which are related to various processes such as immune response and photosynthesis. Transgenics also exhibited faster germination and longer roots than the control. Under heat stress, transgenic lines showed increased susceptibility to high temperature. These results suggest that Hsp90 has an important role in cellular physiology and development; in addition the levels of Hsp90 are critical for responses to stresses. The biophysical characterization of the mutant D456G Hop, a mutation in domain TPR2B showed that this protein is a mixture of monomers, dimers and higher oligomers, but the monomeric state is majoritary. The residue D456 may be involved in dimerization dynamics, and it is possible that Hop is regulated between monomeric and dimeric species, to enable its adaptor functions / Mestrado / Bioquimica / Mestre em Biologia Funcional e Molecular

Les hélicases à ARN de la famille DEAH/RHA sont impliquées dans la plupart des processus essentiels à la vie tels que l'épissage, la biogenèse des ribosomes, la réplication, la transcription ou encore la détection d’ARN viraux. Ces enzymes sont capables de catalyser la dissociation de duplexes d'ARN, la réorganisation de structures secondaires ou de remodeler des complexes ARN-protéines. L'hélicase DEAH/RHA Prp43 présente la particularité d'être bifonctionnelle. Prp43 est impliquée dans l'épissage des Pré-ARNm, où elle assure le recyclage du spliceosome et du lasso, mais aussi dans la biogenèse des ribosomes où elle est impliquée dans la maturation des deux sous-unités. Prp43 est activée et régulée par cinq partenaires protéiques : Ntr1, Gno1, Pfa1, RBM5 et GPATCH2. Ces partenaires protéiques présentent tous un domaine G-patch et sont capables de stimuler les activités hélicase et ATPase de Prp43. La structure cristallographique de Prp43 en complexe avec l'ADP a été résolue au laboratoire. Cette structure a mis en évidence un mode de fixation du nucléotide inédit chez les autres hélicases, notamment au niveau de la base qui s'empile entre la phénylalanine 357 (F357) du domaine RecA2 et l'arginine 159 (R159) du domaine RecA1. Les déterminants de l'activation de Prp43 par les protéines à domaine G-patch demeurent méconnus. Dans ce travail, nous avons cherché à déterminer quel était le rôle de l’empilement de la base dans l’activation de Prp43. Nous présentons ici plusieurs structures cristallographiques de Prp43 en complexe avec tous les nucléotides diphosphates(NDP) et les désoxynucléotides triphosphates (dNDP). Ces structures ont permis de conclure qu'il y avait des différences dans l’empilement de la base selon le (d)NDP considéré. Des dosages d'activité NTPase de Prp43 avec et sans son partenaire protéique Pfa1 montrent que lorsque la base ne s'empile pas avec la F357 et la R159, l'activité de l'enzyme n'est pas correctement régulée par son partenaire protéique. Les dosages d’activité enzymatique sur les mutants ponctuels F357A et R159A révèlent que le résidu F357 permet de moduler l’activité de Prp43. Tous ces résultats nous ont permis de mettre en évidence un modèle de la régulation de Prp43 par les protéines à domaines G-patch et d'expliquer l'importance du mode de fixation de la base à l'enzyme dans cette régulation. / RNA helicases from the DEAH/RHA family are involved in most of essential processes of life such as pre-mRNA splicing, ribosome biogenesis, replication, transcription or viral RNA sensing. These enzymes are able to catalyze RNA unwinding, secondary structures reorganization or RNA-protein complexes remodeling. The DEAH/RHA helicase Prp43 is remarkable because it is bifunctional, as it is involved both in pre-mRNA splicing, where it is responsible of spliceosome and lariat recycling and in the biogenesis of the two ribosomal subunits. Prp43 is activated by five protein partners: Ntr1, Gno1, Pfa1, RBM5 and GPATCH2. These protein partners all possess a G-patch domain and are able to stimulate helicase and ATPase activity of Prp43. The structure of Prp43 in complex with ADP has been solved by X-ray crystallography. The structure reveals that the nucleotide is bound to the enzyme in a novel mode that has never been observed in other known helicase structures. The specific feature of this binding mode is the base, stacked between phenylalanine (F357) from RecA2 domain and an arginine (R159) from RecA1 domain. Features of the activation of Prp43 by G-patch proteins are unclear. In this work, we investigated the role of base stacking in the activation of Prp43. We present several structures of Prp43 bound to all the nucleotide diphosphates (NDP) and deoxynucleotide diphosphates (dNTP). These results indicate that there are differences in stacking according to the (d)NDP bound to the enzyme. NTPase activity assays revealed that when stacking is weakened, Prp43 activity cannot be properly regulated by its protein partner Pfa1. Moreover, point mutations F357A and R159A show that stacking of F357 permits to modulate Prp43 activity. All these results allow us to propose a model of NTPase activity activation of Prp43 by G-patch proteins and to highlight the importance of base stacking in this regulation.

Abstract During DNA replication cells accurately copy their DNA to transfer the genetic information to daughter cells. DNA polymerases synthesise the new DNA strand using the old strand as a template. Other functions of DNA polymerases are recombination linked and DNA iamage repair linked DNA synthesis, regulation of replication complex formation and regulation of transcription – a process in which the genetic information is transformed into an RNA sequence needed to guide protein synthesis. In this study, the TopBP1 protein was shown to associate with DNA polymerase epsilon. TopBP1 contains eight BRCT domains mediating interactions between phosphorylated proteins and is a human homolog of bakers yeast Dpb11 and fission yeast Cut5. These yeast proteins act on DNA replication and cell cycle arrest after DNA damage. TopBP1 was found to be phosphorylated and expressed in elevated amounts during S phase suggesting an involvement in DNA replication. This was directly demonstrated by DNA synthesis inhibition by a competing TopBP1 fragment and by an antibody targeted to block TopBP1. Ultraviolet irradiation damages DNA and decreases the amount of TopBP1 in the nucleus. The transcription factor Miz-1 was found to associate with TopBP1 and was released from this interaction after UV damage. Free Miz-1 activated the expression of the cell cycle arresting proteins p15 and p21 cooperatively with other transcription factors and allowed extra time for DNA damage repair. TopBP1 was also found to interact with the breast cancer susceptibility protein 1 and both proteins localised together to arrested DNA synthesis apparatuses. The interaction of TopBP1 with the damage recognition and processing protein Rad9 is still further evidence of a link between TopBP1 and DNA damage. DNA polymerase epsilon forms a complex with Cdc45, a protein involved in DNA replication initiation and elongation. This complex does not interact with Cdc45 complexed with DNA polymerase delta, suggesting that these complexes synthesise DNA independently of each other. Our results are in agreement with the view that polymerase epsilon synthesises the first strand of DNA and polymerase delta the other. Finally,DNA polymerase epsilon binds to the RNA synthesising form of RNA polymerase II and nascent transcripts. The physiological meaning of this interaction needs to be determined.

Spiroplasma citri est un mollicute phytopathogène transmis de plante à plante par des cicadelles du genre Circulifer selon un mode persistant circulant-multipliant. Les franchissements de l’épithélium intestinal et des glandes salivaires sont basés sur un mécanisme d’endocytose/exocytose. Ce processus d’invasion met en jeu, au sein de complexes protéiques, des protéines bactériennes spécifiques qui reconnaissent des motifs déterminés présents à la surface des cellules eucaryotes. La recherche de protéines de l’insecte vecteur interagissant avec S. citri a notamment conduit à l’identification de l’actine. Cette interaction a pu être confirmée à la fois in vitro et in vivo. L’interaction de l’actine avec son partenaire chez S. citri, qui s’est avéré être la phosphoglycérate kinase (PGK), est impliquée dans l’internalisation du spiroplasme dans les cellules de l’insecte. La région minimale de liaison à l’actine de la PGK a également été déterminée.La réalisation d’un mutant de S. citri dépourvu de PGK a été entreprise avec le plasmide navette pGOT mais n’a pas permis la sélection de spiroplasmes mutés dans ce gène essentiel. Néanmoins, la recherche de l’évènement de recombinaison chez les clones obtenus a permis de mettre en évidence la mutation de deux gènes chez ces derniers.L'ensemble des protéines impliquées dans la transmission du spiroplasme, identifiées au préalable chez ce dernier, n’étant pas essentielle au cours de ce processus, une étude préliminaire des complexes multi-protéiques contenant plusieurs de ces protéines a été réalisée. L’identification de complexes impliquant à la fois la PGK, la P32 et les ScARPs pourrait permettre de mieux comprendre les mécanismes régissant la vection de S. citri par son insecte. / Spiroplasma citri is a phytopathogenic mollicute transmitted from plant to plant by leafhoppers of the genus Circulifer in a persistent and propagative manner on condition to cross the intestinal and salivary glands barriers of the insect. These crossings are based on a endocytosis/exocytosis mechanism which involves bacterial protein complexes in order to recognize specific patterns on the surface of eukaryotic cells.Specific molecular interactions between S. citri proteins and those of C. haematoceps were investigated using far Western technology and had notably led to the identification of actin. This interaction has been confirmed both in vitro and in vivo. The interaction of actin with his partner in S. citri, which has been identified as the phosphoglycerate kinase (PGK), is involved in the internalization of spiroplasma into the insect cells. The minimal actin-binding region of PGK was also determined.The realization of a S. citri PGK mutant was carried out using the shuttle plasmid pGOT but the selection of spiroplasmas mutated in this essential gene failed. Nevertheless, findings in the localization of recombination events in S. citri chromosome, allowed us to identify mutations in two genes that could be tested in our experimental transmission system.The set of proteins involved in the spiroplasmal transmission, previously identified as non essential proteins in the invasion process, prompted us to study the role of multi-protein complexes containing several of these proteins. Identification of complexes involving both the PGK, the P32 and ScARPs should enable us to better understand mechanisms governing the transmission of S. citri by its insect.

L'ubiquitylation des protéines est une modification post-traductionnelle qui joue un rôle capital dans la régulation des nombreuses fonctions cellulaires, y compris la croissance cellulaire et la prolifération. Les dysfonctionnements de ce mécanisme sont à l'origine de diverses maladies telles que le cancer par exemple. Le processus d'ubiquitylation implique une série des réactions enzymatiques en cascade, catalysées par une famille des enzymes, structuralement très proches. Cette famille est composée des enzymes activateurs d'ubiquitine (E1s), des enzymes de conjugaison d'ubiquitine (E2s) et des ligases d'ubiquitine (E3s). Les interactions entre E2s et E3s sont dans le centre de la cascade d'ubiquitylation. Une combinaison particulière des pairs E2/E3 va déterminer le type de chaînes d'ubiquitine qui seront attachées à la protéine d'intérêt pour ensuite déterminer la fonction régulatrice de la voie d'ubiquitylation. A ce jour, seulement une petite fraction de paires possibles entre E2 et E3 a été investiguée par des approches biochimiques et in vitro. Cependant ces approches ne reflètent pas forcément des conditions qu'on trouve dans une cellule vivante. Prenant ceci en considération, les principales objectives de ma thèse seront comme suit : identifier et optimiser une méthode de détection et de quantification des interactions E2/E3 dans une cellule vivante de la levure de boulanger (Saccharomyces cerevisiae) ; construire une bibliothèque de souches de la levure qui permettrait d'établir des interactions entre E2 et E3 ; chercher de nouvelles potentielles paires E2/E3 ; caractériser fonctionnellement une potentielle paire E2/E2. Il est difficile de trouver une méthodologie appropriée afin d'étudier les interactions entre E2 et E3 parce qu'ils sont relativement faibles et transitoires. Leurs études nécessitent donc des techniques de détection avec une grande sensibilité. Parmi différentes techniques nous avons testé et choisi la complémentation bimoléculaire de la fluorescence, BiFC. Kurtosis, une mesure permettant localiser et quantifier la fluorescence BiFC-spécifique. Nos résultats nous nous avons permis à identifier 117 putatives paires E2/E3 parmi quels, 23 paires ont été déjà décrit dans la littérature. Parmi 94 nouvelles paires, certains E3s interagissent avec seulement une seule E2 ou d'autres donnent un signal BiFC avec plusieurs E2s. Ubc13, Ubc1 et Ubc4 sont les E2s qui interagissent le plus souvent. Nous avons identifié aussi une interaction entre les protéines Asi1 et Asi3 et les enzymes de conjugaison d'ubiquitine Ubc6 et Ubc7. Asi1 et 3 sont connus de former un complexe Asi1/3 sur la membrane intérieure du noyau impliqué dans la réponse de la cellule aux acides aminés extracellulaires. Ces protéines contiennent un domaine RING caractéristique pour les ligases d'ubiquitine mais cette activité n'était pas démontrée auparavant. / Protein ubiquitylation is a post-translational modification that plays a crucial role in regulating many cellular functions, including cell growth and proliferation. Defects in this control mechanism cause cancer and other diseases. The ubiquitylation process involves a cascade of enzymatic reactions catalyzed by a family of structurally-related enzymes, namely ubiquitin activating enzymes (E1s), ubiquitin conjugating enzymes (E2s) and ubiquitin ligases (E3s). Interactions between E2s and E3s are in the centre of ubiquitylation cascade and it is a combination of particular E2/E3 pairs that determine what types of ubiquitin chains are made, thus determining the regulatory functions of the ubiquitin pathway. To date, only a small fraction of all possible E2/E3 pairs have been investigated, mainly using biochemical and in vitro approaches that may not accurately reflect the conditions that occur in living cells. We aimed to develop a method capable of detecting specific E2-E3 interactions under physiological conditions. Using budding yeast as a model organism, we found that the Bimolecular Fluorescence Complementation (BiFC) enables sensitive detection of the well described Ubc4-Ufd4 pair under endogenous conditions. The assay is specific since the interaction signal is lost in yeasts expressing Ubc4 mutants truncated in its E3 interaction domain. We then used this system to further analyze the physiological network of E2 and E3 enzymes in living yeast. We performed a microscopy screen to assay all interactions between eleven E2s and 56 E3s. Our results show that approximately 20% of all E2/E3 combinations give a detectable BiFC signal. Few E3s interacted only with a single E2, whereas most E3s produced a BiFC signal with multiple E2s. Ubc13, Ubc1 and Ubc4 were found to be the most frequently interacting E2s. Our results match many examples from current literature but we also detected 94 new E2/E3 interactions, in particular we identified an interaction between the proteins Asi1 and Asi3 and E2s Ubc6 and Ubc7. Asi1 and Asi3 are known to form a complex (the Asi1/3 complex) at the inner nuclear membrane and are involved in the regulation of the response to extracellular amino acids. The Asi1/3 complex was suspected to function as a ubiquitin ligases because they contain a RING domain, but this has previously not been demonstrated. We therefore further characterized them functionally.

Protein homology detection has played a central role in the understanding of evolution of protein structures, functions and interactions. Many of the developments in protein bioinformatics can be traced back to an initial step of homology detection. It is not surprising then, that extension of remote homology detection has gained a lot of attention in the recent past. The explosive growth of genome sequences and the slow pace of experimental techniques have thrust computational analyses into the limelight. It is not surprising to see that many of the traditional experimental areas such as gene expression analysis, recognition of function and recognition of 3-D structure have been attempted effectively by computational approaches. The idea behind homology-based bioinformatics work is the fact that the hereditary mechanisms ensure that the parent generation gives rise to a very similar offspring generation. Since biological functions of proteins of an organism are product of expression of its genetic material, it follows that the genes of an organism should show conservation from one generation to another (with very few mutations if parent and offspring generation have to be nearly identical) Thus, if it can be established that two proteins have descended from a common ancestor, then it can be inferred that the biological functions of the two proteins could be very similar. Thus, homology-based information transfer from one protein to another has become a commonly used procedure in protein bioinformatics. The ability to recognize homologs of a protein solely from amino acid sequences has seen a steady increase in the last two decades. However, currently, still there are a large number of proteins of known amino acid sequence and yet unknown function . Thus, a major goal of current computational work is to extend the limits of remote homology detection to enable the functional characterization of proteins of unknown function. Since proteins do not work in isolation in a cell, it has become essential to understand the in vivo context of the function of a protein. For this purpose, it is essential to have an understanding of all the molecules that interact with a particular protein. Thus, another major area of bioinformatics has been to integrate biological information with protein-protein interactions to enable a better understanding of the molecular processes. Such attempts have been made successfully for the interaction network of proteins within an organism. The extension of the interaction network analysis to a host-pathogen scenario can lead to useful insights into pathophysiology of diseases. The work done as part of the thesis explores both the ideas mentioned above, namely, the extension of limits of remote homology detection and prediction of protein-protein interactions between a pathogen and its host. Since the work can logically be divided into two different areas though there is a connection, the thesis is organized as two parts. The first part of the thesis (comprising Chapters 2, 3, 4 and 5) describes the development and application of remote homology detection tools for function/structure annotation. The second part of the thesis (comprising of Chapters 6, 7, 8 and 9) describes the development and application of a homology-based procedure for detection of host-pathogen protein-protein interactions. Chapter 1 provides a background and literature survey in the areas of homology detection and prediction of protein-protein interactions. It is argued that homology-based information transfer is currently an important tool in the prediction and recognition of protein structures, functions and interactions. The development of remote homology detection methods and its effect on function recognition has been highlighted. Recent work in the area of prediction of protein-protein interactions using homology to known interaction templates is described and it is implied to be a successful approach for prediction of protein-protein interactions on a genome scale. The importance of further improvements in remote homology detection (as done in the first part of the thesis), is emphasized for annotation of proteins in newly sequenced genomes. The importance of application of homology detection methods in predicting protein-protein interactions across host-pathogen organisms is also explored. Chapter 2 analyzes the performance of the PSI-BLAST, one of the well-known and very effective approaches for recognition of related proteins, for remote homology detection. The chapter describes in detail the working of the PSI-BLAST algorithm and focuses on three parameters that determine the time required for searching in a large database, and also provide a ceiling for the sensitivity of the search procedure. The parameters that have been analyzed are the window size for two-hit method, the threshold for extension of an initial hit to dynamic programming and the extent of dependence on the query as encompassed in the profile generation step. The procedure followed for the analysis is to consider a large database of known evolutionary relationships (SCOP database was chosen for the analysis), and use the PSI-BLAST program at different values of three parameters to find out the effect on sensitivity (defined as the normalized number of correct SCOP superfamily relationships found in a search), and the time required for completion of the search. For the demonstration of the effect on the query dependence, a multiple sequence alignment (MSA) of a SCOP family (generated from all family sequences using ClustalW), was used with multiple queries to derive profiles in PSI-BLAST runs. The increase in sensitivity and the increase in time required for completion of each search were then monitored. The effect of changing the two PSI-BLAST internal parameters of score threshold for extension of word hits and the window size for the two-hit method do not result in a significant increase in sensitivity. Since PSI-BLAST uses the amino acid residues present in the query sequence to derive the Position Specific Scoring Matrix (PSSM) parameters, there is a strong query dependence on the sensitivity of each PSSM. Using multiple PSSMs derived from a single MSA can thus help overcome the query dependence and increase the sensitivity. In this Chapter such an approach, named as MulPSSM, has been demonstrated to have higher sensitivity than single profiles approach, (by up to two times more) in a benchmark dataset of 100 randomly chosen SCOP folds. Strategies to optimize sensitivity and the time required in searching MulPSSM have been explored and it is found that use of a non-redundant set of queries to generate MulPSSM can reduce the time required for each search while not affecting the sensitivity by a large degree. The application of the MulPSSM approach in function annotation of proteins in completely sequenced genomes was explored by searching genomic sequences in a MulPSSM database of Pfam families. The association of function to proteins has been assessed when both single profile per family database and MulPSSM database of families were used. It is found that in a comprehensive list of 291 genomes of Prokaryotes, 44 genomes of Eukaryotes and 40 genomes of Archea, that on an average MulPSSM is able to identify evolutionary relationships for 10% more proteins in a genome than single profiles-based approach. Such an enhancement in the recognition of evolutionary relationships, which has an implication in obtaining clues to functions, can help in more efficient exploration of newly sequenced genomes. Identification of evolutionary relationships involving some of the proteins of M. tuberculosis and M. leprae has been possible due to the use of multiple profiles search approach which is discussed in this chapter. The examples of annotations provided in the chapter include enzymes that are involved in glyco lipids synthesis which are vital for the survival of the pathogens inside the host and such annotations can help in expanding our knowledge of these processes. Chapter 3 describes the development and assessment of a sensitive remote homology detection method. The sensitivity of remote homology detection methods has been steadily increasing in the past decade and profile analysis has become a mainstay of such efforts. The profile is a probabilistic model of substitutions allowed at each position in a sequence family, and hence captures the essential features of a family. Alignment of two such profiles is thus considered to provide a more sensitive and accurate method than the alignment of two sequences. The performance of HMMs (Hidden Markov Models) has been shown to be higher than PSSMs (Position Specific Scoring Matrix). Thus, a profile-profile alignment using HMMs can in principle give the best possible sensitivity in remote homology detection. Many investigators have incorporated residue conservation and secondary structure information to align two HMMs, and such additional information has been demonstrated to provide better sensitivity in remote homology detection (for instance in the HHSearch program). The work presented in Chapter 3, extends the idea of incorporating additional information such as explicit hydrophobicity information, along with conservation and predicted secondary structure over a window of Multiple Sequence Alignment (MSA) columns in aligning HMMs. The new algorithm is named AlignHUSH (Alignment of HMMs Using Secondary structure and Hydrophobicity). The HMMs used in the work are derived from structural alignments using HMMER program and are taken from the publicly available superfamily database which provides HMMs for all the SCOP families. The HMMs are modified into two-state HMMs by collapsing the ‘insert’ and ‘delete’ states into a ‘non-match’ state in the AlignHUSH algorithm. The two state HMMs enables the use of dynamic programming methods and keeps intact the position-specific gap penalties. The two state HMMs can be more readily extended to alignment of PSSMs. The incorporation of secondary structure information is made using secondary structure predictions made using PSIPRED program. The hydrophobicity information is calculated using the Kyte Doolittle hydrophobicity values. The alignment is generated by scoring each position using the values present in a window of residues. The assessment of alignment accuracy is done by comparison to manually curated alignments present in the BaliBASE database. A detailed description of the optimization steps followed for obtaining the values for each score contribution (conservation, secondary structure and hydrophobicity) is provided. The assessment revealed that a high weightage to conservation score (18.0) and low weightage to the secondary structure score (1.5) and hydrophobicity (1.0) is optimal. The use of residue windows in alignment has been shown to dramatically increase the sensitivity (around 30% on a small dataset comprising 10% of total SCOP domains). The sensitivity of AlignHUSH algorithm in comparison to other HMM-HMM alignment methods HHSearch and PRC in an all-against-all comparison of SCOP 1.69 database demonstrates that AlignHUSH has better sensitivity than both HHSearch and PRC (approximately by 10% and 5% respectively). The alignment accuracy calculated as the ratio of correctly aligned residues and all alignment positions in BaliBASE alignments reveals that AlignHUSH algorithm provides an accuracy comparable or marginally higher than both HHSearch and PRC (25% for AlignHUSH and roughly 17% for both HHSearch and PRC). A few examples of structural relationships between SCOP families belonging to different folds and/or classes are presented in the chapter to illustrate the strength of AlignHUSH in detecting very remote relationships. Chapter 4 describes a database of evolutionary relationships identified between Pfam families. The grouping of Pfam families is important for obtaining better understanding on evolutionary relationships and in obtaining clues to functions of proteins in families of yet unknown function. Much effort has been taken by various investigators in bringing many proteins in the sequence databases within homology modeling distance with a protein of known structure. Structural genomics initiatives spend considerable effort in achieving this goal. The results from such experiments suggest that in many cases after the structure has been solved using X-ray crystallography or NMR methods, the protein is seen to have structural similarity to a protein of already known structure. Thus, an inability to detect such remote relationships severely impairs the efficiency of structural genomics initiatives. The development of the SUPFAM method was made earlier in the group to enable detection of distant relationships between Pfam families. In SUPFAM approach, relationships are detected by mapping the Pfam families to SCOP families. Further, using the implicit or explicit evolutionary relationship information present in the SCOP database relationships between Pfam families are detected. The work presented in this chapter is an improvement of previous development using the significantly more sensitive AlignHUSH method to uncover more relationships. The new database follows a procedure slightly different than the older SUPFAM database and hence is called SUPFAM+. The relative improvement brought by SUPFAM+ has been discussed in detail in the chapter. The methodology followed for the analysis is to first generate SUPFAM database by recognition of relationships between Pfam families and SCOP families using PSI BLAST / RPS BLAST. For the generation of SUPFAM+ database, recognition of relationships between Pfam families and SCOP families is done using AlignHUSH. The criteria are kept stringent at this stage to minimize the rate of false positives. In cases of a Pfam family mapping to two or more SCOP superfamilies, a semi-automated decision tree is used to assign the Pfam family to a single SCOP superfamily. Some of the Pfam families which remain without a mapping to a SCOP family are mapped indirectly to a SCOP family by identifying relationships between such Pfam families and other Pfam families which are already mapped to a SCOP family. In the final step, the Pfam families still without a SCOP family mapping are mapped onto one another to form ‘Potential New Superfamilies’ (PNSF), which are excellent targets for structural genomics since none of the proteins in such PNSFs have a recognizable homologue of known structure. The clustering of Pfam families into Superfamilies belonging to SCOP 1.69 version, were then queried to check if a structure has been solved for these Pfam families subsequent to the release of the SCOP 1.69 database. The latest SCOP database reveals that for close to 87 Pfam families a structure was solved which is at best related at a SCOP superfamily level with a family present in SCOP 1.69. An analysis of the mappings provided by SUPFAM+ database reveals that the mappings are correct in 85% of the cases at the SCOP superfamily level. An in-depth analysis revealed that among the rest of the cases, only one can be adjudged as an incorrect mapping. Many of the inconsistent mappings were found to be due to the absence of the SCOP fold in the SCOP 1.69 release, although interestingly the mapping provided by SUPFAM+ database shows structural similarity to the actual fold for the Pfam family found subsequently. A straightforward comparison with a similar database (Pfam Clans database) reveals that the SUPFAM+ database could suggest four times more pairwise relationships between Pfam families than the Pfam Clans database. Thus, since the structural mappings provided in the SUPFAM+ database are very accurate the relationships found in the database could help in function annotation of uncharacterized protein families (explored in Chapter 5). The accuracy of mapping would be similar for the PNSFs, and hence these clusters can be excellent targets for structural genomics initiatives. The classification of families based on sequence/structural similarities can also be useful for function annotation of families of uncharacterized proteins, and such an idea is explored in the next chapter. Chapter 5 describes the attempts made to obtain clues to the structure and/or function of the DUF (Domain of Unknown Function) families present in the Pfam database. Currently, the DUF families populate around 21% of the Pfam database (2260 out of 10340). Thus, although homologues for each of the proteins in these families can be recognized in sequence databases, the homology does not provide obvious insight into the function of these proteins. The annotation of such difficult targets is a major goal of computational biologists in the post-genomic era. The development of a sensitive profile-profile alignment method as part of this thesis, gives an excellent opportunity to increase the number of annotations for proteins, especially in the DUF families, since a profile for these families exists in the Pfam database. The method followed for the analysis is similar to the SUPFAM+ development, and involved generation of Pfam profiles compatible with the AlignHUSH method. For the analysis presented in the chapter, relationships found between DUF families and SCOP families were analyzed. In benchmarks using the AlignHUSH method, it was found that a Z score of 5.0 gives a 10% error rate, and a Z score of 7.5 gives an error rate of 1%, and hence a minimum Z score cutoff of 7.5 was used in the analysis. A very high Z score in AlignHUSH is usually seen in cases, when sequence identity is also high, so a maximum Z score cutoff of 12.0 was used to find DUF families which are difficult to annotate using other profile based methods (such as PSI-BLAST). For some of the DUF families, subsequent structure determination of one of the proteins had been reported in literature, and these cases were used to assess the accuracy of structural annotation using AlignHUSH. In other cases, fold recognition was done using the PHYRE method to ensure that the structure mappings are corroborated by fold recognition. In all cases studied, the alignment of the DUF family with the SCOP family was generated and queried for conservation of active site residues reported for each homologous SCOP family in the CSA (Catalytic Site Atlas) database. The assessment on 8 DUF families for which structure was solved subsequent to the SCOP release used in the analysis, reveals that in all cases, the correct structure was identified using the AlignHUSH procedure. In the eight cases of validated structure annotation, the conservation of active site residues was seen pointing to the effectiveness of AlignHUSH and its use in function annotation. The 27 cases in which a structure for any one of the proteins in the DUF family is not known, the fold recognition attempts suggest that in all cases, the results from fold recognition corroborate the suggestion made by AlignHUSH. The alignments of each of the DUF families with the suggested homologous SCOP family reveals that in many cases the active site residues are not conserved or are substituted by different residues. An in-depth analysis of some cases reveals that the non-conservation of residues occurs between two SCOP families in the same SCOP superfamily. Thus, although structure annotation can be reliably provided for all the DUF families studied, the exact biochemical function could be detected only for those cases in which active site conservation is seen even among distantly related families (such as two SCOP families in the same SCOP superfamily). The development and application of methods for remote homology detection has been made successfully and it has been demonstrated in the first part of the thesis that there is scope for extending the limits of remote homology detection. The use of sequence derived information in aligning profiles makes the procedure generally applicable and has been applied successfully for the case of structure/function recognition in the DUF families. In the next part of the thesis, a method for prediction of protein-protein interactions between a host and pathogen organism and its application to three groups of pathogens is presented. Chapter 6 describes the development of a procedure for prediction of protein-protein interactions (PPI) between a pathogen and its host organism. In the past, prediction of PPI has been attempted for proteins of a given organism. This was often approached by identifying proteins of the organism of interest that are homologous to two interacting proteins of another organism. A study of conservation of interactions as a function of sequence identity has been made in the past by various groups, which reveal that homologues sharing a sequence identity greater than about 30% interact in similar way. This fact can be used, along with a high quality database of protein-protein interactions to predict interactions between proteins of same organism. The work done in this thesis is one of the first attempts at extending the idea to the prediction of interactions between two different organisms. Homology of proteins from a pathogen and its host to proteins which are known to interact with each other would suggest that the proteins from pathogen and host can interact. The feasibility of such an interaction to occur under in vivo conditions need to be addressed for biologically meaningful predictions. These issues have been dealt with in this part of the thesis. One of the main steps in the procedure for the prediction of PPI is identification of homologues of pathogen and host proteins to interacting proteins listed in PPI databases. Two template PPI databases have been used in this work. One of the databases is the DIP database which provides a list of interactions based on genome-scale yeast-two-hybrid data or small scale experiments. The other database used is the iPfam database which provides interaction templates (Pfam families) based on protein complexes of known structure present in Protein Data Bank (PDB). Thus, the two databases are both comprehensive and are of high quality. The search for homologues in the DIP database was made using PSI-BLAST with stringent cutoffs for various parameters to minimize false positives. The search in iPfam database is done using RPS-BLAST and MulPSSM using stringent cutoffs. The cutoffs for the searches were fixed based on an assessment of conservation of putative interacting residues in the host and pathogen proteins as compared to the protein complexes of known structure. The predictions made are analyzed manually to assess the importance to the pathogenesis of the disease under consideration. In this chapter, in order to obtain an idea about robustness of this approach, PPI prediction was made for the phage-bacteria system and the herpes virus – human system which have been experimentally studied extensively and hence opportunities exist to compare the “predictions” with experimental results. The prediction of phage – bacteria interactions suggests that the gross biological features of the pathogenesis have been captured in the predictions. The GO (Gene Ontology) based annotations for the bacterial proteins predicted to interact suggests that the predictions involve proteins participating in DNA replication and protein synthesis. Many of the known interactions such as between the lambda phage repressor and RecA protein of bacteria were also ‘predicted’ in the analysis. A few novel interactions were predicted. For example interaction between a tail component protein and a protein of unknown function, YeeJ in E.coli has been predicted. The prediction of interactions between Herpes Virus 8 and human host and its comparison to a set of experimentally verified interactions reported in literature suggested that close to 50% of the known interactions were ‘predicted’ by the procedure followed. A few novel cases of interaction between the viral proteins and the p53 protein have also been made which might help in understanding the tumorigenesis of the viral disease. A comparison between the procedure followed in this thesis and the results from another genome-scale method (proposed by Andrej Sali and coworkers) suggests that although the proteins involved in predicted interactions from two methods may differ, the functions of the proteins concerned suggested by GO annotations are highly correlated (greater than 98%). In the next few chapters, the prediction of interactions for different host-pathogen systems is described. In the Chapter 7, the prediction of PPI between a Eukaryotic malarial pathogen, P.falciparum and its human host is described. The malarial parasite was chosen because of the extensive work reported in the literature on this pathogen in the recent years. Also, the gene expression patterns in the pathogen are highly correlated to the human tissue types with each stage of the pathogen occurring in a distinct tissue type. Thus, the biological context of the PPI can be explicitly assessed, which makes this example a well suited case for the procedure described in the Chapter 6 of this thesis. The pathogen is important from a medical perspective since there has been a recent emergence of P.falciparum induced malaria which is unresponsive to conventional drugs. Thus, studies of this parasite have gained an importance in the post genomic era. The difficulty in identifying homologues of many of the P.falciparum proteins makes this a challenging case study. Prediction of PPI between the malarial parasite and the human proteins has been approached in the same way as described in Chapter 6, with the cutoffs in homology searches kept stringent. However, in this case effective use of available additional biological data has been possible. The tissue specific expression information for human proteins has been obtained from the Atlas of Human transcriptome, and the NCBI GEO database. The pathogen stage-specific expression data has been obtained from multiple genome-scale experiments reported in the literature. The subcellular localization of both human and pathogen proteins has been predicted and hence this information is given low weightage in subsequent analysis. The prediction of PPI between malarial parasite and human, resulted in a total of more than 30,000 interactions which were compatible in an in vivo condition according to the expression data. Further reduction in the set of predicted interactions was made by incorporating the subcellular localization predictions (reduced to around 2000 interactions). Manual analysis of each of these interactions taking aid from literature on malarial parasites reveals that many of the known PPI are also ‘predicted’ in the analysis such as the interaction between SSP2 protein of P.falciparum and human ICAMs. For many proteins known to be important for pathogenesis, such as the RESA antigen, novel interactions were predicted that could help in better understanding of the pathogen. For some of the novel predicted interactions, such as that between the parasite Plasmepsin and human Spectrin, there exists circumstantial experimental evidence of interaction. Among many other novel interactions, the procedure used could predict interactions for 441 ‘hypothetical proteins’ of unknown function coded in the genome of the pathogen. The comprehensive list of predictions made using the procedure and an exploration of its biological significance can lead to novel hypothesis regarding the parthenogenesis of malaria and hence the work presented in this chapter can be helpful for further experimental exploration of the pathogen. The success of the procedure in predicting known interactions as well as novel interactions in a Eukaryotic pathogen suggests that the procedure developed is generally applicable. However it must be pointed out that in many cases of host-pathogen systems, such extensive expression and localization data may not be available, which makes the analysis difficult due to the large number of interactions predicted. One of such difficult cases is the interactions between Mycobacterial species and human host which is described in the next chapter. Chapter 8 describes the prediction of PPI between human and M.tuberculosis as well as three pathogens closely related to M.tuberculosis. Each of the pathogens has seen to re-emerge due to drug resistance and other causes. M.tuberculosis is becoming a global problem due to the limited number of drugs available to treat TB, which is susceptible to resistance. M.leprae has also shown signs of emergence of drug resistance, whereas C.diptheriae another pathogen studied in this chapter is seen as an emerging pathogen in Eastern Europe and in Indian subcontinent. Nocardial infections have also seen a rise due to the prevalence of AIDS which leads to susceptibility to the Nocardia infections. Thus, there is a need to understand further the pathogens in this important family, in order to better direct drug development. An important area for such endeavors is the mapping of the PPI between the pathogens and the human host. The procedure developed as part of the thesis can be used to predict such interactions. The procedure for prediction of interactions is the same as followed in Chapter 6 and involves identifications of homologues for the pathogen and host proteins among the proteins listed in the two template datasets DIP and iPfam using PSI-BLAST and RPS-BLAST (MulPSSM). In addition to the homology to the proteins involved in PPI, information / prediction on subcellular localization is used to assess biological significance of the interaction. An experimentally derived dataset of exported proteins in the M.tuberculosis was used to supplement the predictions from PSORTb database that provides subcellular localization for bacterial proteins. In order to minimize the number of predictions explored manually and to maximize the biological relevance of predicted interactions,, the predictions were made only for proteins present on the membrane of the pathogen or which are exported into the host. Prediction of interactions between human proteins and the proteins of four pathogens studied revealed that, some of the interactions which were known from earlier experiments were “predicted” by the present procedure. For example, the M.leprae exported Serine protease is known to interact with Ras-like proteins in the human host, and this interaction was ‘predicted’. Among other predicted interactions, several novel interactions have been suggested for proteins important for pathogenesis such as the MPT70 protein of M.tuberculosis which has been predicted to interact with TGFβ associated proteins which could play an important role in the pathogenesis of the disease. Some of the human proteins are known to play important role in pathogenesis, especially the toll-like receptors. A C.diphtheriae protein Mycosin, has been predicted to interact with the toll-like receptors raising the possibility that the Mycosins may play an important role in pathogenesis. Several hypothetical proteins of unknown function in the pathogens have been predicted to interact with human proteins. A few of such cases from M.tuberculosis have been described in the thesis and these proteins are predicted to interact with proteins involved in post-transnational modification in the human host. The prediction of novel interactions along with known interactions in four bacterial species thus points to the fact that the procedure can be used for almost any host-pathogen pair. In the next chapter, the application of the method to three other bacterial species belonging to the Enterobacteriaciae family is presented. Chapter 9 describes the analysis performed on the predicted interactions between human and three pathogens in the Enterobact

Le paludisme et le sepsis sont des maladies infectieuses très répandues causant plusieurs centaines de milliers de morts tous les ans. Elles sont toutes deux multifactorielles. Les devenirs de ces infections sont influencés par des facteurs environnementaux, par des facteurs sociaux-économiques, politiques et comportementaux mais aussi par des variables dépendant du patient comme son âge. De nombreux arguments existent en faveur d'un contrôle génétique de la résistance au paludisme et au sepsis. Ces deux maladies sont considérées comme proches par les spécialistes car leur physiopathologie est liée notamment à une inflammation systémique non contrôlée responsable des formes les plus graves. Afin d'identifier de nouveaux gènes potentiellement impliqués dans la résistance à ces deux maladies, nous avons effectué des études génétiques pangénomiques dans deux populations vivant en zone endémique pour le paludisme à Plasmodium falciparum au Burkina-Faso et dans une cohorte de patients atteints de sepsis.Enfin nous avons réalisé les deux premières études d'association pangénomiques identifiant des associations significatives avec la mortalité suite à un choc septique. Nous avons obtenu 32 SNPs significativement associés à la mortalité précoce et 108 significativement associés à la mortalité tardive. Le réseau des interactions protéine-protéine impliquant les protéines codées par les gènes associés a permis d'établir une liste non exhaustive des fonctions altérées durant le choc septique, notamment liées à la réponse immune, et a révélé, malgré les différences au niveau des gènes impliqués, un mécanisme commun participant à la susceptibilité précoce et tardive au choc septique. / Malaria and sepsis are widespread infectious diseases causing hundreds of thousands deaths each year. There is a growing body of evidence for a genetic control of malaria and sepsis resistance. Both diseases are considered close because they are characterized by a systemic inflammation, some common organ dysfunctions, and disorders of coagulation. In order to identify new genes potentially involved in disease resistance, we performed genomewide genetic studies in two populations living in endemic regions for Plasmodium falciparum malaria in Burkina-Faso and in a cohort of septic shock patients. Genetic linkage studies revealed significant genetic linkages on chromosome 6p21.3 and 17p12 with, respectively, mild malaria and asymptomatic parasitaemia. We also performed the first genetic linkage studies concerning immunoglobulin G and their sub-classes against Plasmodium falciparum antigens. We detected significant linkages of IgG3 sub-class with chromosomes 8p22-p21 and 20q13 and between IgG4 sub-class and chromosome 9q34. Finally we performed the first two genomewide association studies identifying significant associations with all-causes mortality after a septic shock. We identified 32 SNPs significantly associated with early mortality and 108 SNPs significantly associated with late mortality. We identified a protein-protein network containing proteins associated with both early and late mortality. Furthermore, the network of protein-protein interactions involving proteins encoded by associated genes allowed us to establish a list of some altered functions during septic shock, most of them being related to the immune responses or the renin-angiotensin-aldosterone system.

Il existe de nombreux mécanismes impliqués dans le développement des tissus qui nécessitent que des cellules ou des groupes de cellules s’orientent et se polarisent. Les protéines de la voie de la polarité planaire (PP) s’associent pour former des complexes à la membrane et créer des asymétries proximo-distale. Vangl2 et Scrib1 ont été identifiés comme les deux premiers gènes impliqués dans la PP chez les mammifères. Lors de ma thèse, je me suis intéressé à ces deux protéines et à certains des complexes dans lesquelles elles sont impliquées. Dans un premier temps, nous avons montré l’implication directe de Scribble1 dans le trafic après endocytose des récepteurs NMDA. Scrib1 interagit avec les récepteurs NMDA grâce à ses domaines PDZ. Scribble1 peut interagir avec le complexe AP2 qui intervient dans l’endocytose des récepteurs. Cette étude a permis de définir un nouveau mécanisme dans lequel Scrib1 régule la quantité de récepteurs NMDA à la membrane et donc participe à la plasticité synaptique. Vangl2 est l’une des protéines transmembranaires les plus en amont de la voie de la PP. Nous avons identifié un nouveau partenaire nommé "Axin Interaction partner and Dorsalization Antagonist" (AIDA). Nous avons montré, par double hybride en levure et pull down, l’interaction de Vangl2 avec les deux isoformes de AIDA et leur colocalisation en COS7 et neurones. Ensemble, ces données présentent AIDA comme un très bon candidat pour le maintien de Vangl2 aux jonctions adhérentes et/ou pour son adressage à la membrane. Ces études nous ont permis d’améliorer notre compréhension des mécanismes impliquant les protéines de la polarité planaire. / There are many mechanisms involved in the development of tissues that require cells or groups of cells orient and polarize. The proteins of the planar cell polarity (PCP) combine to form complexes with the membrane and create proximal-distal asymmetries. Vangl2 and Scrib1 have been identified as the first two genes involved in the PCP in mammals. In this study, I am interested in these two proteins and some of the complex in which they are involved. At first, using techniques of biochemistry, cell biology and biophysics, we showed the direct involvement of Scribble1 in traffic after endocytosis of NMDA receptors. Scrib1 interacts with NMDA receptors through its PDZ domains. Due to this binding motif between PDZ1 and PDZ2 of Scrib1, it can interact with the AP2 complex which is involved in receptor endocytosis. This study has identified a new mechanism in which Scrib1 regulates the amount of NMDA receptors on the membrane and is therefore involved in synaptic plasticity. Vangl2 is a transmembrane protein of the most upstream of the PCP pathway. We have identified a new partner named "Axin Interaction partner and Dorsalization Antagonist" (AIDA). We have shown, by yeast two-hybrid and pull down the interaction of Vangl2 with two isoforms of AIDA and collocation in COS7 and neurons. Together, these data show AIDA as a very good candidate for maintaining Vangl2 to adherens junctions and/or its membrane targeting. These studies have allowed us to improve our understanding of the mechanisms involving the planar polarity proteins.

Eukaryotic translation initiation is a complex and highly regulated process involving the ribosome, mRNA and proteins called eukaryotic initiation factors (eIFs). The overall aim of translation initiation is to position the ribosome at the initiation codon of the mRNA. eIF2, in its GTP-bound conformation, binds the initiator tRNA (Met-tRNAiMet) and delivers it to the 40S ribosomal subunit. When the anticodon of the tRNA is bound to the initiation codon, the GTP on eIF2 is hydrolysed to GDP. The guanine nucleotide exchange factor (GEF) eIF2B regenerates eIF2-GTP. eIF2 and eIF2B are multisubunit/multidomain protein complexes. Because information regarding the interface between each complex is limited, particularly the interface on the eIF2γ subunit, which binds the guanine-nucleotides and Met-tRNAiMet, interactions between the minimal GEF domain of eIF2Bε, εGEF, and eIF2 were mapped using mutagenesis and an in vitro cysteine cross-linking approach, with the cross-linker Mts-Atf-Biotin. Site-directed mutagenesis (SDM) was used to mutate five N-terminal and five C-terminal surface-exposed εGEF residues to cysteines. The mutant alleles were analysed in Saccharomyces cerevisiae and it was found that the gcd6-R574C allele was lethal and the gcd6-T572C was Gcd-. Further gcd6-R574 mutant alleles were also found to be lethal in yeast but expressed in vivo.εGEF-R574C has dramatically reduced GEF activity in vitro and binding assays showed that this mutant has significantly reduced affinity for eIF2. The εGEF-T572C and εGEF-S576C mutants also have severe and minor eIF2-binding defects respectively, while the C-terminal εGEF-Cys mutants have slightly reduced affinity for eIF2. The N-terminal εGEF-Cys mutants cross-link specifically to eIF2γ, while the C-terminal εGEF-Cys mutants interact predominantly with eIF2β. From the data obtained in this study, we propose a new model for eIF2B-mediated guanine-nucleotide exchange that reduces the importance of eIF2β and suggests εGEF resembles other GEFs in binding primarily to its G protein partner eIF2γ.