Semantic Biclustering

Tato disertační práce se zaměřuje na problém hledání interpretovatelných a prediktivních vzorů, které jsou vyjádřeny formou dvojshluků, se specializací na biologická data. Prezentované metody jsou souhrnně označovány jako sémantické dvojshlukování, jedná se o podobor dolování dat. Termín sémantické dvojshlukování je použit z toho důvodu, že zohledňuje proces hledání koherentních podmnožin řádků a sloupců, tedy dvojshluků, v 2-dimensionální binární matici a zárove ň bere také v potaz sémantický význam prvků v těchto dvojshlucích. Ačkoliv byla práce motivována biologicky orientovanými daty, vyvinuté algoritmy jsou obecně aplikovatelné v jakémkoli jiném výzkumném oboru. Je nutné pouze dodržet požadavek na formát vstupních dat. Disertační práce představuje dva originální a v tomto ohledu i základní přístupy pro hledání sémantických dvojshluků, jako je Bicluster enrichment analysis a Rule a tree learning. Jelikož tyto metody nevyužívají vlastní hierarchické uspořádání termů v daných ontologiích, obecně je běh těchto algoritmů dlouhý čin může docházet k indukci hypotéz s redundantními termy. Z toho důvodu byl vytvořen nový operátor zjemnění. Tento operátor byl včleněn do dobře známého algoritmu CN2, kde zavádí dvě redukční procedury: Redundant Generalization a Redundant Non-potential. Obě procedury pomáhají dramaticky prořezat prohledávaný prostor pravidel a tím umožňují urychlit proces indukce pravidel v porovnání s tradičním operátorem zjemnění tak, jak je původně prezentován v CN2. Celý algoritmus spolu s redukčními metodami je publikován ve formě R balííčku, který jsme nazvali sem1R. Abychom ukázali i možnost praktického užití metody sémantického dvojshlukování na reálných biologických problémech, v disertační práci dále popisujeme a specificky upravujeme algoritmus sem1R pro dv+ úlohy. Zaprvé, studujeme praktickou aplikaci algoritmu sem1R v analýze E-3 ubikvitin ligázy v trávicí soustavě s ohledem na potenciál regenerace tkáně. Zadruhé, kromě objevování dvojshluků v dat ech genové exprese, adaptujeme algoritmus sem1R pro hledání potenciálne patogenních genetických variant v kohortě pacientů.This thesis focuses on the problem of finding interpretable and predic tive patterns, which are expressed in the form of biclusters, with an orientation to biological data. The presented methods are collectively called semantic biclustering, as a subfield of data mining. The term semantic biclustering is used here because it reflects both a process of finding coherent subsets of rows and columns in a 2-dimensional binary matrix and simultaneously takes into account a mutual semantic meaning of elements in such biclusters. In spite of focusing on applications of algorithms in biological data, the developed algorithms are generally applicable to any other research field, there are only limitations on the format of the input data. The thesis introduces two novel, and in that context basic, approaches for finding semantic biclusters, as Bicluster enrichment analysis and Rule and tree learning. Since these methods do not exploit the native hierarchical order of terms of input ontologies, the run-time of algorithms is relatively long in general or an induced hypothesis might have terms that are redundant. For this reason, a new refinement operator has been invented. The refinement operator was incorporated into the well-known CN2 algorithm and uses two reduction procedures: Redundant Generalization and Redundant Non-potential, both of which help to dramatically prune the rule space and consequently, speed-up the entire process of rule induction in comparison with the traditional refinement operator as is presented in CN2. The reduction procedures were published as an R package that we called sem1R. To show a possible practical usage of semantic biclustering in real biological problems, the thesis also describes and specifically adapts the algorithm for two real biological problems. Firstly, we studied a practical application of sem1R algorithm in an analysis of E-3 ubiquitin ligase in the gastrointestinal tract with respect to tissue regeneration potential. Secondly, besides discovering biclusters in gene expression data, we adapted the sem1R algorithm for a different task, concretely for finding potentially pathogenic genetic variants in a cohort of patients

Proteomic Characterization of the E3 Ubiquitin-Ligase Hakai: Biological Insights and New Therapeutic Strategies

Programa Oficial de Doutoramento en Bioloxía Celular e Molecular . 5004V01[Resumen] El carcinoma es el tipo más común de cáncer y surge de las células epiteliales. La transición del adenoma al carcinoma se asocia con la pérdida de E-cadherina y, en consecuencia, de los contactos intercelulares. La E-cadherina es un supresor tumoral que está regulado negativamente durante la transición epitelio-mesénquima (EMT) y su pérdida es un marcador de mal pronóstico durante la progresión tumoral. Hakai es una E3 ubiquitina-ligasa que media en la ubiquitinación de la E-cadherina, su endocitosis y consecuente degradación. Aunque la E-cadherina es el sustrato más conocido de Hakai, otras dianas moleculares reguladas por Hakai pueden estar involucradas en la plasticidad celular durante la progresión tumoral. En este trabajo, empleamos la técnica iTRAQ para explorar nuevas rutas moleculares involucradas en la EMT inducida por Hakai. Nuestros resultados muestran que Hakai puede tener una influencia importante sobre proteínas relacionadas con el citoesqueleto, proteínas extracelulares asociadas con el exosoma, proteínas relacionadas con el ARN y proteínas involucradas en metabolismo. Entre las proteínas reguladas por Hakai, describimos la Anexina A2 como un nuevo posible sustrato de Hakai. Además, nuestros resultados revelan que la inhibición farmacológica de Hsp90 con geldanamicina resulta en la degradación de Hakai vía lisosoma. Así, proponemos a Hakai como una nueva proteína cliente de la chaperona Hsp90, destacando un mecanismo novedoso por el cual los inhibidores de Hsp90 pueden influir en el proceso EMT mediado por Hakai y el tratamiento del cáncer.[Resumo] O carcinoma é o tipo de cancro máis común e xorde das células epiteliais. A transición do adenoma ao carcinoma está asociada á perda de E-cadherina e, en consecuencia, aos contactos intercelulares. A E-cadherina é un supresor tumoral que se encontra regulado negativamente durante a transición epitelio-mesénquima (EMT), e a súa perda é un marcador de mala prognose durante a progresión do tumor. Hakai é unha E3 ubiquitina-ligasa que media a ubiquitinización da E-cadherina, a súa endocitose e a súa conseguinte degradación. Aínda que a E-cadherina é o substrato máis coñecido de Hakai, outras dianas moleculares reguladas por Hakai poden estar implicadas na plasticidade celular durante a progresión tumoral. Neste traballo empregamos a técnica iTRAQ para explorar novas vías moleculares implicadas na EMT inducida por Hakai. Os nosos resultados mostran que Hakai pode ter unha influencia importante sobre proteínas relacionadas co citoesqueleto, proteínas extracelulares asociadas co exosoma, proteínas relacionadas co ARN e proteínas implicadas no metabolismo. Entre as proteínas reguladas por Hakai, describimos a Anexina A2 coma un novo posible substrato de Hakai. Ademáis, describimos una relación entre Hakai e o complexo chaperona da proteína Heat shock protein 90 (Hsp90). Tamén, os nosos resultados revelan que a inhibición farmacolóxica de Hsp90 con geldanamicina resulta na degradación de Hakai vía lisosoma. Así, propoñemos a Hakai como unha nova proteína cliente da chaperona Hsp90, destacando un novo mecanismo polo cal os inhibidores de Hsp90 poden influir no proceso de EMT mediado por Hakai e no tratamento do cancro.[Abstract] Carcinoma is the most common type of cancer and arises from epithelial cells. Transition from adenoma to carcinoma is associated with the loss of E-cadherin and, in consequence, the disruption of cell−cell contacts. E-cadherin is a tumor suppressor which is down-regulated during epithelial-to-mesenchymal transition (EMT), and its loss is a predictor of poor prognosis during tumor progression. Hakai is an E3 ubiquitin-ligase that mediates E-cadherin ubiquitination, endocytosis and consequent degradation. Although E-cadherin is the most established substrate for Hakai activity, other regulated molecular targets for Hakai may be involved in cancer cell plasticity during tumor progression. In this work we employed an iTRAQ approach to explore novel molecular pathways involved in Hakai-driven EMT. Our results show that Hakai may have an important influence on cytoskeleton-related proteins, extracellular exosome-associated proteins, RNA-related proteins and proteins involved in metabolism. Among Hakai-down-regulated proteins, we describe Annexin A2 as a new possible susbtrate for Hakai. Moreover, we also report an interaction between Hakai and the heat shock protein 90 (Hsp90) chaperone complex. Besides, our results reveal that the pharmacological inhibition of Hsp90 with geldanamycin results in the degradation of Hakai in a lysosome-dependent manner. Based on that, we propose Hakai as a new client protein of Hsp90 chaperone highlighting a new mechanism by which Hsp90 inhibitors may influence Hakai-mediated EMT process and cancer treatment

Global Analysis of SUMO-binding proteins identifies SUMOylation as a key regulator of the INO80 chromatin remodeling complex

The functional protein microarray is a powerful and versatile systems biology and proteomics tool that allows the rapid activity profiling of thousands of proteins in parallel. Applications of functional protein microarrays range from the identification of protein- binding properties, to surveying targets of posttranslational modifications, to uncovering novel enzymatic activities. Since the development of the yeast proteome microarray over 10 years ago, more recent work has seen the development of complete and near-complete proteome arrays representing viruses, bacteria and plants. However, most existing human protein microarrays are comprised of only a minority of the human proteome. We have recently developed a human proteome microarray, the HuProt array, which includes nearly 20,000 full-length human proteins. SUMOylation is an essential posttranslational modification in most organisms that is thought to function through its ability to modulate the protein-protein interactions of a SUMO target protein. Accordingly, the function of SUMOylation can be better understood through the identification of SUMO-modified targets as well as downstream SUMO- interacting proteins. Recently, we have conducted SUMOylation assays using the HuProt microarray to identify numerous previously uncharacterized SUMO E3 ligase-dependent substrates using a subset of human SUMO E3 ligases. In order to identify novel SUMO- interacting proteins, we developed a SUMO-binding assay using the human proteome microarray. We then integrated SUMO-binding and SUMOylation data, as well as protein- protein interaction data from publicly available databases to perform network motif analysis. We focused on a single network motif we termed a SUMOmod PPI (SUMO-modulated Protein-Protein Interaction) that included the INO80 chromatin remodeling complex subunits TFPT and INO80E. We validated the SUMO-binding activity of INO80E and that TFPT is a SUMO substrate both in vitro and in vivo. We then went on to demonstrate a key role for SUMOylation in mediating the interaction between these two proteins, both in vitro and in vivo. By demonstrating a key role for SUMOylation in regulating the INO80 chromatin remodeling complex, this work illustrates the power of bioinformatics analysis of large datasets in predicting novel biological phenomena

Understanding the role of CaMKIIa in Angelman Syndrome by looking at its potential interactors through proximity labelling

280 p.El Síndrome de Angelman es una enfermedad rara que se caracteriza por la ausencia de la E3 ligasa de ubicuitina UBE3A en las neuronas. Numerosos datos sugieren una relación entre CAMKII y UBE3A. En esta tesis se emplea el etiquetado por proximidad con BioID2 y TurboID, tanto en cultivos celulares como en Drosophila melanogaster, con el fin de identificar posibles interactores. Mediante esta estrategia hemos sido capaces de identificar la E3 ligasa de ubicuitina ITCH como la responsable de monoubicuitinar a CAMKIIa y a la deubiquitinasa MYSM1 como un mediador indirecto de la ubicuitinación de CAMKIIa. Además, cuando CaMKIIa se encuentra más ubicuitinada, su fosforilación en la T286 y, por tanto, activación se ve reducida. Los experimentos en mosca permitieron identificar varias proteínas relacionadas con enfermedades neurodegenerativas y la proteína Nbea, también identificada como posible sustrato de UBE3A, involucrada en el espectro autista. Por otro lado, nuestro grupo recientemente ha identificado la proteína Neurocondrina (NCDN) como un sustrato de UBE3A en el cerebro de ratón. NCDN regula de forma negativa la fosforilación de T286 de CaMKII, reduciendo así su actividad. Observamos que las cadenas a través de la lisina 48 son las que se forman en NCDN por UBE3A y la envían a su degradación. Finalmente, realizamos un estudio sobre cuáles eran las lisinas de NCDN que tendían a ser ubicuitinadas por UBE3A. Los resultados, aunque prometedores, no identificaban de manera significativa ninguna lisina dentro de la secuencia de NCDN

Comparative analysis of Saccharomyces cerevisiae WW domains and their interacting proteins

BACKGROUND: The WW domain is found in a large number of eukaryotic proteins implicated in a variety of cellular processes. WW domains bind proline-rich protein and peptide ligands, but the protein interaction partners of many WW domain-containing proteins in Saccharomyces cerevisiae are largely unknown. RESULTS: We used protein microarray technology to generate a protein interaction map for 12 of the 13 WW domains present in proteins of the yeast S. cerevisiae. We observed 587 interactions between these 12 domains and 207 proteins, most of which have not previously been described. We analyzed the representation of functional annotations within the network, identifying enrichments for proteins with peroxisomal localization, as well as for proteins involved in protein turnover and cofactor biosynthesis. We compared orthologs of the interacting proteins to identify conserved motifs known to mediate WW domain interactions, and found substantial evidence for the structural conservation of such binding motifs throughout the yeast lineages. The comparative approach also revealed that several of the WW domain-containing proteins themselves have evolutionarily conserved WW domain binding sites, suggesting a functional role for inter- or intramolecular association between proteins that harbor WW domains. On the basis of these results, we propose a model for the tuning of interactions between WW domains and their protein interaction partners. CONCLUSION: Protein microarrays provide an appealing alternative to existing techniques for the construction of protein interaction networks. Here we built a network composed of WW domain-protein interactions that illuminates novel features of WW domain-containing proteins and their protein interaction partners

Discovery and effects of pharmacological inhibition of the E3 ligase Skp2 by small molecule protein-protein interaction disruptors

Skp2 (S-phase kinase-associated protein 2), one component of the SCF E3 ubiquitin ligase complex, directly interacts with Skp1 and indirectly associates with Cullin1 and Rbx1 to bridge the E2 conjugating enzyme with its protein substrate to execute its E3 ligase activity. Skp2 is an Fbox protein (due to it containing an Fbox domain) and it is the rate-limiting component of the SCF complex. Skp2 targets several cell-cycle regulatory proteins for ubiquitination and degradation; most notable and significant for cancer are the cyclin-dependent kinase inhibitor, p27. Skp2 is an oncogene and studies have shown that over-expression of Skp2 leads to increased degradation of p27 and increased proliferation in several tumor types. Additionally, Skp2 is over-expressed in multiple human cancers. Clearly, Skp2 represents an attractive target for attenuating p27 ubiquitination and subsequent cell cycle progression. However, Skp2 does not have an easily identifiable and druggable “pocket” on which small molecules can bind; it interacts with Skp1 through the Fbox domain and binds to an accessory protein called Cks1 to bind to p27. Despite this hurdle, in this study, two selective small molecule inhibitors of the Skp2 SCF complex were discovered via an in silico screen that disrupt two places: the Skp1/Skp2 interaction site and the p27 binding site via targeting hot-spot residues. The Skp1/Skp2 inhibitor disruption resulted in restoring p27 levels in the nucleus and blocks cancer progression and cancer stem cell traits. Additionally, the inhibitors phenocopy the effects of genetic Skp2 deficiency. Two specific residues on Skp2 were predicted to bind to this Skp1/Skp2 inhibitor: Trp97 and Asp98. When these residues were mutated to alanine, the inhibitor lost its ability to bind to Skp2. To investigate the flexibility and understand the conformational change upon inhibitor binding and dynamics of the SCF complex, molecular dynamics simulations, homology models, and structural analysis was carried out on the complex with and without the inhibitors. These simulations showed that the contributions of the N-terminal tail region of Skp2 does not contribute directly to the binding of these inhibitors; but its conformation is important in the context of the other members of the SCF complex. Further dynamics analysis validated the mutagenesis results, showing that the two Skp2 mutants (Trp97Ala, Asp98Ala) that retained Skp1 binding but blocked inhibitor binding were stable, whereas the mutant that was unable to retain Skp1 binding (Trp127Ala) showed destabilization in the Fbox domain. Finally, active recruitment events after post-translational modifications are shown to be possible by the interaction of phosphorylated Ser256 on Skp2 with Lys104 loop region on Cul1 The model shows that this is due to the significant flexibility in the F-box domain of Skp2, making this interaction very likely. These results show that Skp2 is a promising target on which protein-protein interaction disruptors can be designed, and consideration of the dynamics of protein complexes is required to understand ligand binding

Relative Protein Lifetime Measurement in Plants Using Tandem Fluorescent Protein Timers

Targeted protein degradation plays a wide range of important roles in plant growth and development, but analyzing protein turnover in vivo is technically challenging. Until recently, there has been no straightforward methodology for quantifying protein dynamics at subcellular resolution during cellular transitions in plants. A tandem fluorescent protein timer (tFT) is a fusion of two different fluorescent proteins with distinct fluorophore maturation kinetics, which allows estimation of relative protein age from the ratio of fluorescence intensities of the two fluorescent proteins. Here, we describe approaches to use this technology to report relative protein lifetime in both transient and stable plant transformation systems. tFTs enable in vivo, real-time protein lifetime assessment within subcellular compartments and across tissues, permitting the analysis of protein degradation dynamics in response to stresses or developmental cues and in different genetic backgrounds