Dementia, the most common cause of which is Alzheimer's disease (AD), currently affects 850,000 people in the UK, a figure set to rise to over 1 million by 2025. There is currently no disease modifying therapy available to slow or halt this progressive disease. Current understanding of AD implicates the neurotoxic amyloid-β (Aβ) peptide as the primary initiator in a cascade of events leading to the neuronal cell death and brain atrophy associated with the disease. Therefore, inhibiting the production or enhancing the clearance of Aβ within the brain has become a major target for the production of disease modifying therapeutics. Aβ is produced by brain cells through the sequential proteolytic cleavage of a larger transmembrane protein known as the amyloid precursor protein (APP) by β- and γ-secretases. Several aspects of APP physiology can influence its proteolysis, and thus Aβ production, including the isoform of APP which is expressed, its trafficking and subcellular location and its physical interactions with other proteins in the cellular environment. Here we have investigated the influence of subcellular trafficking and location and protein-protein interactions on the differential proteolysis of two APP isoforms, APP695 and APP751 in a neuroblastoma cell line. We have shown that APP751 undergoes less amyloidogenic proteolysis than APP695 and that retention within the early secretory pathway may contribute to this difference. APP751 shows higher co-localisation to the trans-Golgi network than APP695 in immunofluorescence microscopy studies, while addition of a mutation which causes APP proteolysis in the secretory pathway reduces the large difference in amyloidogenic proteolysis of these two isoforms. Targeting APP endocytosis from the cell surface, thought to be a key determinant in Aβ generation, effects APP isoform proteolysis and Aβ production to a similar extent in both the APP isoforms suggesting differences in proteolysis occur before this trafficking event. We also show by immunoblot analysis that the APP isoforms may be differentially cleaved by proteases other than β- and γ-secretase to produce recently identified proteolytic fragments. Using a liquid chromatography - tandem mass spectrometry approach coupled to prior stable isotope labelling of amino acids in cell culture (SILAC), we have identified the interactomes of the two APP isoforms in our model system. Gene ontology analysis identified enrichment of nuclear and mitochondrial proteins specifically in the APP695 interactome. Using siRNA mediated protein knockdown, we have shown interactions with Fe65 and ataxin-10 specifically influence Aβ generation from the APP695 isoform. Fe65 alters proteolysis at the rate limiting β-secretase cleavage step, while ataxin-10 alters proteolysis by γ-secretase. Interaction with growth-associated protein 43 specifically influences Aβ generation from the APP751 isoform, altering proteolysis at the γ-secretase step. Finally we have shown that recently discovered familial AD-linked mutation and protective mutation within the Aβ region of the APP protein have consistent effects on APP proteolysis in both the APP isoforms.

The highly unstructured interferon regulated transcription factor IRF-1 is a tumour suppressor protein that plays vital roles in the antiviral and DNA damage response pathways. To identify interacting factors that regulate IRF-1 function and expand on the available limited information on its interactome, an in vitro screen was developed using peptide-aptamer affinity chromatography coupled with mass spectrometry. Discrete identified which bind to a number of potential transcriptional regulators including NPM1, YB-1 and TRIM28. The screen also proved useful in identifying binding proteins to the C-terminal Mf1 domain, which is vital for IRF-1-mediated growth suppression and Cdk2 repression, and additionally regulates IRF-1 stability. Thus, an LXXLL motif in the MF1 domain was found to be required for the binding of Hsp70 family members and cooperation with Hsp90 to regulated IRF-1 turnover and activity. These conclusions were supproted by the finding the Hsp90 inhibitors suppressed IRF-1-dependent transcription shortly after treatment, whilst at later time points inhibition of Hsp90 led to an Hsp70-dependent depletion of nuclear IRF-1. Conversely, the half-life of IRF-1 was increase by Hsp90 in an ATPase-dependent manner leading to the accumulation of nuclear, but not cytoplasmic, IRF-1. Additionally, a stress specific interaction between IRF-1 and the Hsp70-associated ubiquitin E3 ligase CHIP, that targets Hsp70/Hsp90 clients for proteasomal degradation, was demonstrated. Consequently, decreases in IRF-1 protein levels in cells exposed to heat stress or heavy metal ions were accompanied by the formation of IRF-1:CHIP complexes. Based on observations that CHIP ubiquitination of IRF-1 occurred both in the presence and absence of Hsp70, a model was proposed wherein Hsp70 serves as a factor that recruits CHIP to its substrates and its dissociation from the complex allosterically activates CHIP-dependent substrate ubiquitination. In support of this model, in vitro and biophysical evidence is presented, showing that CHIP in complex with Hsp70 is less flexible and less effective as an E3 ligase that CHIP alone. Thus, in agreement with recent studies, the work done in this thesis highlights the importance of conformational flexibility and of direct binding or 'docking' of CHIP to its substrate(s) in its mechanism of action.

The relationship between a pathogen and its host is a complex series of events that occurs at the molecular level and is controlled by transcriptional and protein interactions. To facilitate the understanding of these mechanisms in Aspergillus flavus and Zea mays, three approaches were taken: 1) the development of a predicted interactome for Z. mays (PiZeaM), 2) the development of co-expression networks for Z. mays and A. flavus from RNA-seq data, and 3) the development of causal inference networks depicting interactions between the host and the pathogen. PiZeaM is the genome-wide roadmap of protein-protein interactions that occur within Z. mays. PiZeaM helps create a novel map of the interactions in Z. mays in response to biotic and abiotic stresses. To further support the predicted interactions, an analysis of microarray-based gene expression was used to produce a gene co-expression network. PiZeaM was able to capture conserved resistance pathways involved involved in the response to pathogens, abiotic stress and development. Gene Co-expression networks were developed by the simultaneous use of correlations to develop networks for differentially expressed genes, resistance marker genes, pathogenicity genes, and genes involved is secondary metabolism in Z. mays and A. flavus. From these networks, correlation and anti-correlation of host and pathogen gene expression was detected, revealing genes that potentially interact at different stages of pathogenesis. Finally, causal gene regulatory relationships were inferred using partial correlation analysis of Z. mays infected with A. flavus over a 3 day period. The gene regulatory network (GRN) sheds light on the specifics of the mechanisms of pathogenesis and resistance that govern the Z. mays-A. flavus interaction. The direct product of this research is the understanding of key transcription factors and signaling genes involved in resistance. This body of research highlights how PPIs and GRNs can be utilized to identify biomarkers and gene functions in both Z. mays and A. flavus.

Le domaine PDZ participe aux réseaux moléculaires à l’origine de fonctions cellulaires touchées lors de pathologies diverses. L’exploration de ce réseau par double hybride a permis d’attribuer de nouvelles fonctions putatives aux ligands protéiques des domaines PDZ du ver Caenorhabditis elegans. Les interactions ont laissé apparaitre une proportion inattendue de ligands atypiques interagissant par une séquence interne. Nous avons ensuite validé fonctionnellement in silico des groupes d’interactions de notre interactome qui forment des micro-réseaux co-exprimés par l’intégration de données de profils d’expression. Finalement, ce travail a permis la construction d’un outil exploratoire, le PIPE (PDZ Interacting Protein Explorer) qui permet de cribler l’ensemble des domaines PDZ du ver à la recherche d’interactions avec une protéine d’intérêt révélant déjà de nombreuses interactions supplémentaires entre domaines PDZ et ligands / PDZ domains allow the organization of molecular networks responsible for cellular functions essential for multicellularity as polarization or transduction of extracellular signals. Exploration of this network by two-hybrid revealed a functional diversity for ligands of Caenorhabditis elegans’s PDZ domains. New putative functions were being observed through GO-terms and an unexpected proportion of internal ligands appeared, confirmed by Co-IP. We then functionally validated in silico groups of interactions that form our interactome microarrays co-expressed by the integration of data from expression profiles. Finally, this work has enabled the construction of an exploratory tool, the PIPE (PDZ Interacting Protein Explorer) that allows screening of all PDZ domains looking for interactions with a protein of interest and had already showed many additional interactions between PDZ domains and ligands

Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a secreted glycoprotein that promotes degradation of low-density lipoprotein receptors. Gain- and loss-of-function variants of PCSK9 cause hypercholesterolemia and hypocholesterolemia, respectively. Although it has been a decade since the discovery of PCSK9, its effect in terms of global protein changes and interactions still require further understanding. This study provided a global outlook at the protein changes caused by PCSK9 and its variants in human hepatic HUH7 cell line. First, a proteomics-based method for protein subcellular distribution analysis has been developed. Second, through secretome analyses, six apolipoproteins and six proteins involved in the coagulation pathway were found with >2-fold changes between wild type PCSK9 and its variants. Third, through secreted interactome analyses, a list of 159 PCSK9 interactor candidates was identified. Two interacting proteins, FASN and PSMD2, were validated and demonstrated with dynamic interacting patterns between PCSK9 and its variants.

[EN] Our understanding of the biological mechanisms for most common human diseases is far from complete. Even with well established genetic landscapes, our capacity to make accurate phenotypical predictions or determine personalised disease risk using genetics alone is not possible for most diseases due to our lack of understanding of the mechanisms by which genetic alterations cause disease. Several suggestions have been proposed to explain this manifested lack of direct relation between genotype and phenotype, including interactions with other molecules, pleiotropy and environmental perturbations. Due to their essential role in carrying cellular functions, proteins and its interactions seem crucial to translate genomic data to phenotypic states. In this thesis I present three different and independent approaches to integrate human genomic data with prior knowledge in terms of protein-protein interactions (PPIs). The overall objective is, by making use of the interactome structure, to propose functional hypotheses that help to interpret the genetic variability observed in different human phenotypes. First I developed a methodology to extract the network component associated to any gene list ranked by any experimental parameter, as the one coming from case-control genome-wide associations studies. Second I performed a systematic analysis of human variants in the context of the protein interactome. There I study how the interactome structure can help us to explain the amount of apparently deleterious variation observed in actual populations and, therefore, give insight in its role in shaping the patterns of variability. Results are compared against somatic mutation found in Leukemia patients. Finally, I structurally resolved the protein interactome and used it to study how somatic mutations found in primary tumours distribute across the interacting interfaces and identify those with a potential role in driving oncogenesis. Although each chapter covers a different question, all of them demonstrate the potential of the interactome in helping to interpret genomic variation observed under diverse research scenarios. / [ES] Nuestro conocimiento acerca de los mecanismos biológicos causantes de la mayoría de enfermedades humanas comunes es aun pobre. Incluso con mapas genéticos de alta resolución, nuestra capacidad para hacer predicciones fenotípicas certeras o determinar el riesgo de una persona a padecer una enfermedad utilizando solamente marcadores genéticos es muy baja. Entre las principales causas de esta aparente falta de relación directa entre genotipo y fenotipo están las interacciones moleculares, los fenómenos de pleiotropía y la influencia de los factores externos. Debido al papel esencial que ejercen en llevar a cabo las funciones celulares, las proteínas y sus interacciones han adquirido una atención especial en la traducción de los datos genotípicos a estados fenotípicos. En esta tesis se presentan tres estrategias diferentes para la integración de datos genómicos humanos con la red de interacciones proteicas (interactoma). El objetivo común de todas ellas es, haciendo uso de la estructura del interactoma, proponer hipótesis funcionales que ayuden a interpretar los patrones de variabilidad observados en diferentes estados fenotípicos humanos. Primero, se propone una metodología para extraer el componente del interactoma asociado a los genes relevantes en una lista ranqueada por cualquier parámetro experimental, como el estadístico derivado de los estudios de asociación genómicos. Es segundo lugar se describe un análisis sistemático de las variantes genéticas observadas en humanos sanos en el contexto del interactoma. En él se estudia cómo la estructura del interactoma puede ayudar en explicar la aparentemente elevada cantidad de variantes deletéreas observadas en los últimos estudios poblacionales de secuenciación de genomas. Los resultados son comparados con las mutaciones somáticas observadas en pacientes de Leucemia. Finalmente, se presenta un estudio de las mutaciones somáticas observadas en tumores primarios utilizando una versión del interactoma que incluye la estructura tridimensional de las proteínas. Aunque cada estudio presentado en la tesis pretende resolver preguntas diferentes, todos ellos demuestran el potencial del interactoma de proteínas en ayudar a interpretar la variación genómica humana observada en un contexto tanto evolutivo como de enfermedad. / [CAT] El nostre coneixement sobre els mecanismes biològics causants de la majoria de malalties humanes comuns es encara pobre. Tot i que en l'actualitat tenim mapes genètics d'alta resolució, la nostra capacitat per a fer prediccions fenotípiques certeres utilitzant únicament marcadors genètics es encara molt baixa degut a que no entenem les bases moleculars a traves de les quals les alteracions genètiques condicionen un fenotip de malaltia. Entre les principals causes d'aquesta aparent falta de relació directa entre genotip i fenotip estan la complexitat introduïda per les interacciones moleculars, els fenòmens de peleiotropia i la influencia dels factors externs. Degut al paper clau en dur a terme la majoria de funcions cel·lulars, les proteïnes i les seues interaccions han adquirit una especial atenció en la traducció de les dades genotípiques en estats fenotípics. Aquesta tesi presenta tres estartègies diferents per a la integració de dades genòmiques humanes amb la xarxa d'interaccions proteiques (interactoma). L'objectiu comú es, fent ús de l'estructura del interactoma, proposar hipòtesis funcionals que ajuden a interpretar els patrons de variabilitat genètica observats en diferents estats fenotípics. En primer lloc, es proposa una metodologia per a extraure el component de l'interactoma associat als gens rellevants en una llista ranquejada per qualsevol paràmetre experimental, com l'estadístic derivat d'estudis d'assocaició de genoma. En segon lloc, es descriu un anàlisi sistemàtic de les variants genètiques observades en humans sans en el context del interactoma. Ací s'analitza com l'estructura del interactoma pot ajudar a explicar l'aparent elevada quantitat de variants deletèries observades en els últims estudis poblacionals de sequenciació de genomes. Els resultats son comparats amb les mutacions somàtiques observades en pacients de Leucèmia. Finalment, es presenta un estudi de les mutacions somàtiques observades en tumors primaris de més de 20 tipus utilitzant una versió del interactoma més resolutiva, que inclou l'estructura tridimensional de les proteïnes. Encara que cada estudi presentat en la tesi planteja resoldre qüestions diferents, tots ells demostren el potencial del interactoma de proteïnes en ajudar a interpretar la variació genòmica humana observada en un context tant poblacional com de malaltia. / García Alonso, LM. (2015). Functional profiling of human genomic data using the protein interactome [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/55848 / TESIS

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京都大学 / 新制・課程博士 / 博士(医学) / 甲第24187号 / 医博第4881号 / 新制||医||1060(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 伊藤 貴浩, 教授 滝田 順子, 教授 小川 誠司 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

La leishmaniose est causée par un parasite protozoaire du genre Leishmania. Cette maladie infecte environ 12 millions de personnes dans le monde et en menace 350 millions dans 98 pays. Il existe trois formes majeures de leishmaniose : cutanée, mucocutanée et viscérale. L'infection se produit par le dépôt des parasites sous forme de promastigotes dans la peau de l'hôte mammifère via la piqûre d’un phlébotome. Les parasites peuvent migrer au sein de la matrice extracellulaire avant d’infecter les macrophages. Bien que la plupart des études réalisées jusqu’ici aient été consacrées aux interactions des parasites Leishmania avec leurs cellules cibles, quelques interactants extracellulaires ont déjà été identifiés. Dans cette étude, nous avons étudié pour la première fois le répertoire d’interactions de 24 souches de promastigotes intacts, vivants (6 espèces aux différents tropismes) avec environ ~70 biomolécules de la matrice extracellulaire de l’hôte à l’échelle moléculaire en utilisant des puces à protéines et à glycosaminoglycanes et la résonance plasmonique de surface en mode imagerie. Nous avons identifié 27 nouveaux partenaires (23 protéines et 4 glycosaminoglycanes) des promastigotes de Leishmania. Les souches partagent des partenaires communs tels que le plasminogène, TEM-8 et la tropoélastine, qui est dégradée in vitro par la majorité des souches. Les Leishmania se lient à plusieurs régulateurs de l’angiogenèse et à des glycosaminoglycanes. Dans une seconde partie, nous avons cloné deux protéines de L. major, l’énolase et la superoxyde dismutase, toutes deux identifiées dans le sécrétome de Leishmania, afin d’étudier leur répertoire d’interactions. L’énolase possède un répertoire d’interactions (13 partenaires) supérieur à celui de la superoxyde dismutase (6 partenaires) mais toutes deux interagissent également avec le plasminogène, l’ectodomaine de TEM-8, l’endostatine et l’héparine. Enfin, dans une troisième partie, nous avons créé une base de données, LeishMatrixDB, qui recense toutes les interactions des parasites Leishmania, ou leurs molécules, avec les composants de la matrice extracellulaire de l’hôte décrites dans la littérature / Leishmaniasis is a vector-borne disease caused by parasitic protozoa of the genus Leishmania. 12 million people are presently infected worldwide and the disease threatens 350 million people in 98 countries around the world. There are three main types of the disease: cutaneous, mucocutaneous and visceral. Infection occurs by the deposition of promastigote form into the mammalian skin via the bite of phlebotomine sandflies within the extracellular matrix proteins prior infecting macrophages. Most studies have focused on the interaction of Leishmania promastigotes with their cellular targets, some extracellular partners have been identified. In this study, we investigated for the first time the interplay between 24 strains of intact, live, parasites (6 species of different tropisms) and ~70 biomolecules of the host extracellular matrix at the molecular level using protein and glycosaminoglycan arrays probed by surface plasmon resonance imaging. We have identified 27 new partners (23 proteins and 4 glycosaminoglycans) of Leishmania promastigotes. All strains tested shared 3 common partners such as plasminogen, TEM-8 and tropoelastin, which is degraded in vitro by most Leishmania tested. Leishmania bound to several regulators of angiogenesis and to glycosaminoglycans. In a second part, we cloned two L. major proteins, enolase and superoxyde dismutase, both identified in Leishmania secretome in order to study their interaction repertoire. Enolase had a larger interaction repertoire (13 partners) than superoxide dismutase (6 partners) but both bound to plasminogen, ectodomain of TEM-8, endostatin and heparin. In a third part, we have created a database, LeishMatrixDB, which lists all the interactions of Leishmania, or their molecules, with host extracellular components from the literature

Le récepteur atypique ACKR3 et le récepteur CXCR4 sont des récepteurs couplés aux protéines G appartenant à la famille des récepteurs CXC des chimiokines. Ces deux récepteurs sont activés par la chimiokine CXCL12 et sont surexprimés dans de nombreux cancers comme les gliomes, dont ils favorisent la prolifération et le caractère invasif. Le récepteur CXCR4 active des voies de signalisation qui dépendent de la protéine Gi et des β-arrestines et s’associe à plusieurs protéines impliquées dans la transduction du signal, le trafic et la localisation cellulaire du récepteur. Par contre, les mécanismes de signalisation impliqués dans les effets d’ACKR3 restent mal connus. Le récepteur déclenche une signalisation dépendant des β-arrestines, mais son couplage aux protéines G dépend du type cellulaire ou se fait par un mécanisme indirect via son association au récepteur CXCR4. Le récepteur ACKR3 s’associe également au récepteur de l’EGF pour induire la prolifération cellulaire par un mécanisme indépendant de sa stimulation par un agoniste. Ces données illustrent l’intérêt de caractériser de façon systématique l’interactome de ces récepteurs pour comprendre leurs rôles physiologiques et pathologiques. Cette thèse a poursuivi cet objectif grâce à la mise en œuvre d’une approche protéomique combinant la purification des partenaires des deux récepteurs par affinité suivie de leur identification par spectrométrie de masse. J’ai ainsi identifié respectivement 19 et 151 partenaires protéiques potentiels des récepteurs CXCR4 et ACKR3 exprimés dans les cellules HEK-293T. Parmi les protéines recrutées par ACKR3, nous nous sommes focalisés sur la connexine 43 (Cx43, une des protéines constituant les jonctions Gap) du fait de la similitude des effets du récepteur et de la Cx43 dans la pénétration des leucocytes dans le parenchyme cérébral, la migration des interneurones et la progression des gliomes. J’ai confirmé par Western blot et par BRET l’association spécifique de la Cx43 à l’ACKR3 et non pas au CXCR4. De la même façon, j’ai montré une co-localisation de la Cx43 et de l’ACKR3 dans des cellules de gliome humain, ainsi que dans les astrocytes de la zone sous-ventriculaire et les pieds astrocytaires entourant les capillaires cérébraux chez la souris, suggérant que les deux protéines forment un complexe protéique dans un contexte biologique authentique. Des études fonctionnelles ont révélé que l’ACKR3 module les fonctions de la Cx43 par différents mécanismes. L’expression de l’ACKR3 dans les cellules HEK-293T (mimant la surexpression du récepteur dans les tumeurs), induit par elle-même une inhibition de l’activité jonctionnelle de la Cx43. De même, la stimulation du récepteur par un agoniste réduit l’activité jonctionnelle de la Cx43 par un mécanisme impliquant l’activation d’une protéine Gi, la β-arrestine2 et l’internalisation de la Cx43. Cette thèse établit donc pour la première fois un lien fonctionnel entre le système constitué par les chimiokines CXCL11, CXCL12 et leur récepteur ACKR3 d’une part et les jonctions Gap d’autre part qui pourrait jouer un rôle critique dans la progression des gliomes. / The Atypical Chemokine Receptor 3 (ACKR3) and CXCR4 are two G protein-coupled receptors (GPCR) belonging to the CXC chemokine receptor family. Both receptors are activated upon CXCL12 binding and are over-expressed in various tumours, including glioma, where they have been found to promote proliferation and invasive behaviours. Upon CXCL12 binding, CXCR4 activates canonical GPCR signalling pathways involving Gαi protein and β-arrestins. In addition, CXCR4 was found to interact with several proteins able to modify its signalling, trafficking and localization. In contrast, the cellular pathways underlying ACKR3-dependent effects remain poorly characterized. Several reports show that ACKR3 engages β-arrestin-dependent signalling pathways, but its coupling to G proteins is restricted to either specific cellular populations, including astrocytes, or occurs indirectly via its interaction with CXCR4. ACKR3 also associates with the epidermal growth factor receptor to promote proliferation of tumour cells in an agonist-independent manner. These examples suggest that the extensive characterization of ACKR3 and CXCR4 interactomes might be a key step in understanding or clarifying their roles in physiological and pathological contexts. This thesis addressed this issue employing an affinity purification coupled to high-resolution mass spectrometry proteomic strategy that identified 19 and 151 potential protein partners of CXCR4 and ACKR3 transiently expressed in HEK-293T cells, respectively. Amongst ACKR3 interacting proteins identified, we paid particular attention on the gap junction protein Connexin-43 (Cx43), in line with its overlapping roles with the receptor in the control of leukocyte entry into the brain, interneuron migration and glioma progression. Western blotting and BRET confirmed the specific association of Cx43 with ACKR3 compared to CXCR4. Likewise, Cx43 is co-localized with ACKR3 but not CXCR4 in glioma initiating cell lines, and ACKR3 and Cx43 are co-expressed in astrocytes of the sub-ventricular zone and surrounding blood vessels in adult mouse brain, suggesting that both proteins form a complex in authentic cell or tissue contexts. Further functional studies showed that ACKR3 influences Cx43 trafficking and functionality at multiple levels. Transient expression of ACKR3 in HEK-293T cells to mimic ACKR3 overexpression detected in several cancer types, induces Gap Junctional Intercellular Communication (GJIC) inhibition in an agonist-independent manner. In addition, agonist stimulation of endogenously expressed ACKR3 in primary cultured astrocytes inhibits Cx43-mediated GJIC through a mechanism that requires activation of Gαi protein, and dynamin- and β-arrestin2-dependent Cx43 internalisation. Therefore, this thesis work provides the first functional link between the CXCL11/CXCL12/ACKR3 axis and gap junctions that might underlie their critical role in glioma progression.