The myriad ways species interact with each other have always captivated biologists. These interactions—predation, competition, parasitism, and mutualism—are fundamental to the stability of ecological communities and drive the evolution of species they contain. Some mutualistic systems consist of mutually dependent partners that strongly influence each other’s survival, while other mutualistic systems consist of many, diffuse relationships between large assemblages of partners. Critical ecological processes like pollination and seed dispersal are prime examples of such complex systems. Plant-pollinator communities are characterized by extensive pollinator sharing among plant species. My dissertation explores some of the consequences of this reliance on shared pollinators on the structure of plant-pollinator interaction networks, the foraging decisions of pollinators, and the fitness outcomes of plant species. Through several comprehensive field studies, I contribute to our understanding of mutualist interaction patterns at multiple levels of biological hierarchy: the community, species, and individuals. My first chapter examines the forces driving the change in interaction patterns of an entire plant-pollinator community and individual species throughout the flowering season. Nearly all studies of plant-pollinator interaction networks ignore potential intra-annual variation, and in doing so may be missing critical mechanisms contributing to overall community stability. I find that the overall turnover of interactions is high and driven by a process of interaction rewiring in which species frequently shuffle between available partners. Furthermore, I distinguish pollinator species whose interactions are driven by an abundance-based neutral process versus those that change their interactions beyond what is predicted by a neutral, abundance-driven null model. My second chapter uses a network-based framework to consider the fitness consequences for plants participating in a diffuse plant-pollinator network. I analyze the relationship between plant species’ network metrics and pollen deposition. Empirical examples that link patterns of interactions and functional outcomes (e.g., pollination) are scarce, but necessary to establish the utility of characterizing species interaction patterns. My final chapter explores how pollinator composition, local floral neighborhoods, and timing of flowering influence the pollination outcomes of individual Oenothera fruticosa flowers. I demonstrate extensive intraspecific variation in receipt of pollen from other species (‘heterospecific pollen receipt’) and find that this heterospecific pollen has a negative fitness effect if present in sufficiently high amounts. Together, the chapters of my thesis provide novel insights into the consequences of pollinator sharing among co-flowering plant species. / Biology

Investigating similarities among neurological diseases can provide insight into disease processes. Two prominent commonalities of neurological diseases are the formation of amyloid deposits and altered ammonia and glutamate metabolism. Computational techniques were used to explore these processes in several neurological diseases. Residue interaction networks (RINs) abstract protein structure into a series of nodes (representing residues) and edges (representing connections between residues likely to interact). Analyzing the RINs of monomeric forms of amyloidogenic proteins for common network features revealed similarities not previously known. First, amyloidogenic variants of lysozyme were used to demonstrate the usefulness of RINs to the study of amyloidogenic proteins. Next, I compared RINs of amyloidogenic proteins with randomized control networks and a group of real protein controls and found similarities in network structures unique to amyloidogenic proteins. The use of 3D structure data and network structure data of amyloid-beta (1-42) (Abeta42) in a hydrophobic, membrane-mimicking solvent led to the identification of an interaction between Val24 and Ile31 as potentially involved in preventing Abeta aggregation. Since Abeta causes oxidative damage, since the ammonia metabolism enzyme glutamine synthetase is particularly susceptible to oxidative damage, and since glutamate plays a central role in neuronal function, I expanded my research to include the study of ammonia and glutamate metabolism in neurological diseases. A computational model of the effects of the interactions between the amount of dietary protein and the activities of ammonia metabolism enzymes on blood and brain ammonia levels supports potentially important roles for these enzymes in the protection of neural function. Next, I reviewed the role of amino acid catabolism in Alzheimer’s disease (AD). Common tissue pathology and the ability of memantine, an NMDA receptor antagonist, to relieve symptoms in patients and animal models of AD, major depressive disorder (MDD), and type 2 diabetes (T2D) further support a role for ammonia and glutamate metabolism in disease. Lastly, I found that single nucleotide polymorphisms (SNPs) in select ammonia metabolism genes are associated with these three diseases. The results presented in this dissertation demonstrate that investigating neurological diseases using computational approaches can provide great insight into the common underlying pathologies.

No description available.

Proteins and their function play one of the most essential roles in various biological processes. The study of PPI is of considerable importance. PPI network data are of great scientific value, however, they are incomplete and experimental identification is time and money consuming. Available computational methods perform well on model organisms’ PPI prediction but perform poorly for a novel organism. Due to the incompleteness of interaction data, it is challenging to train a model for a novel organism. Also, millions to billions of interactions need to be verified which is extremely compute-intensive. We aim to improve the performance of predicting whether a pair of proteins will interact, with only two sequences as input. And also efficiently predict a PPI network with a proteome of sequences as input. We hypothesize that information about cellular locations where proteins are active and proteins' 3D structures can help us to significantly improve predict performance. To overcome the lack of experimental data, we use predicted structures by AlphaFold2 and cellular locations by DeepGoPlus. We believe that proteins belonging to disjoint biological components have very little chance to interact. We manually choose several disjoint pairs and further confirmed it by experimental PPI. We generate new no-interaction pairs with disjoint classes to update the D-SCRIPT dataset. As result, the AUPR has improved by 10% compared to the D-SCRIPT dataset. Besides, we pre-filter the negatives instead of enumerating all the potential PPI for de-novo PPI network prediction. For E.coli, we can pass around a million negative interactions. To combine the structure and sequence information, we generate a graph for each protein. A graph convolution network using Self-Attention Graph Pooling in Siamese architecture is used to learn these graphs for PPI prediction. In this way, we can improve around 20% in AUPR compared to our baseline model D-SCRIPT.

Recent breakthroughs in high-throughput biotechnology have promoted the integration of multi-platform data to investigate signal transduction pathways within a cell. In order to model complicated dynamics and heterogeneity of biological pathways, sophisticated computational models are needed to address unique properties of both the biological hypothesis and the data. In this dissertation work, we have proposed and developed methods using Markov Chain Monte Carlo (MCMC) techniques to solve complex modeling problems in human cancer research by integrating multi-platform data. We focus on two research topics: 1) identification of transcriptional regulatory networks and 2) uncovering of aberrant intracellular signal transduction pathways. We propose a robust method, called GibbsOS, to identify condition specific gene regulatory patterns between transcription factors and their target genes. A Gibbs sampler is employed to sample target genes from the marginal function of outlier sum of regression t statistic. Numerical simulation has demonstrated significant performance improvement of GibbsOS over existing methods against noise and false positive connections in binding data. We have applied GibbsOS to breast cancer cell line datasets and identified condition specific regulatory rewiring in human breast cancer. We also propose a novel method, namely Gibbs sampler to Infer Signal Transduction (GIST), to detect aberrant pathways that are highly associated with biological phenotypes or clinical information. By converting predefined potential functions into a Gibbs distribution, GIST estimates edge directions by learning the distribution of linear signaling pathway structures. Through the sampling process, the algorithm is able to infer signal transduction directions which are jointly determined by both gene expression and network topology. We demonstrate the advantage of the proposed algorithms on simulation data with respect to different settings of noise level in gene expression and false-positive connections in protein-protein interaction (PPI) network. Another major contribution of the dissertation work is that we have improved traditional perspective towards understanding aberrant signal transductions by further investigating structural linkage of signaling pathways. We develop a method called Structural Organization to Uncover pathway Landscape (SOUL), which emphasizes on modularized pathways structures from reconstructed pathway landscape. GIST and SOUL provide a very unique angle to computationally model alternative pathways and pathway crosstalk. The proposed new methods can bring insight to drug discovery research by targeting nodal proteins that oversee multiple signaling pathways, rather than treating individual pathways separately. A complete pathway identification protocol, namely Infer Modularization of PAthway CrossTalk (IMPACT), is developed to bridge downstream regulatory networks with upstream signaling cascades. We have applied IMPACT to breast cancer treated patient datasets to investigate how estrogen receptor (ER) signaling pathways are related to drug resistance. The identified pathway proteins from patient datasets are well supported by breast cancer cell line models. We hypothesize from computational results that HSP90AA1 protein is an important nodal protein that oversees multiple signaling pathways to drive drug resistance. Cell viability analysis has supported our hypothesis by showing a significant decrease in viability of endocrine resistant cells compared with non-resistant cells when 17-AAG (a drug that inhibits HSP90AA1) is applied. We believe that this dissertation work not only offers novel computational tools towards understanding complicated biological problems, but more importantly, it provides a valuable paradigm where systems biology connects data with hypotheses using computational modeling. Initial success of using microarray datasets to study endocrine resistance in breast cancer has shed light on translating results from high throughput datasets to biological discoveries in complicated human disease studies. As the next generation biotechnology becomes more cost-effective, the power of the proposed methods to untangle complicated aberrant signaling rewiring and pathway crosstalk will be finally unleashed. / Ph. D.

The project goals for this dissertation were to manipulate Populus trichocarpa source-sink relationships to optimize this woody crop species for specific agricultural traits such as increased growth rate, stress tolerance and/or improvements in overall biomass accumulation. We targeted specific tissues such as xylem, where alterations in the relationship of source and sink tissues can lead to the control of xylem cell deposition or of various wood properties. This led to the characterization of 165 protein-protein interactions and 20 protein-DNA interaction which constitute numerous woody tissue related subnetworks. One such network, centered on the DIVARACATA and RADIALIS INTERACTING FACTOR (PtrDRIF), identified PtrWOX13c as an interacting protein. Characterization of PtrWOX13c shows that it displays the ability to control promoters related to lignin biosynthesis genes and overexpression phenotypes show alterations in axillary branch activity. Genes which control the differentiation and specialization of cells such as members of the WOX family are also highly responsive to abiotic stress which can force major changes in plant metabolism and nutrient mobilization. ABA, a prominent plant phytohormone with known roles in the adaptation to stress has shown novel connections in the regulation of growth promoting complexes such as TOR through antagonistic regulatory actions of the SnRK2 protein kinase in Arabidopsis. Characterization of the core ABA signaling in P. trichocarpa has identified a regulatory clade A protein phosphatase which interacts with numerous PtrSnRK2 proteins and when overexpressed in hybrid poplar results in increased height and node production potentially by indirect control of growth promoting complexes like TOR through SnRK2 inhibition. This work has also demonstrated that in addition to the involvement of phytohormones in the regulation of plant development, sugar phosphates such as T6P can exert significant control of plant architecture. Together, these studies comprise the discovery and subsequent characterization of novel wood associated networks, hormone pathways and sugar signaling in the manipulation of P. trichocarpa source-sink relationships for the promotion of biomass accumulation. / PHD / Detailed analyses of gene activity in different tissues or under the influence of various environmental conditions have identified numerous genes that control desirable traits and plant characteristics. However, the activities and functions of the proteins produced from these genes is less understood. One of the ways proteins work is through the formation of complexes with other proteins. Using the commercially valuable tree Populus trichocarpa (poplar) as our research model, we have identified novel complexes of interacting proteins with the potential to sense and respond to the environment and to promote plant growth. We tested the function of some of the members of these newly discovered protein complexes using transgenic poplar. As a result, we revealed previously unknown functions for two poplar proteins: PtrWOX13c promoted increased branching and PtrHAB2 promoted an increase in tree height. Independent of these functional analyses of poplar proteins, we also tested the ability of a sugar phosphate, trehalose6-phosphate, known from previous work to regulate plant growth, for its ability to promote poplar growth. We found that reducing levels of trehalose-6-phosphate resulted in increased branch growth, similar to the impact of the PtrWOX13c protein. In summary, identification of new protein complexes is a valuable strategy for the discovery of proteins that can increase tree growth. Additionally, combining targeted changes in both proteins and regulatory sugars may be a promising path toward future crop improvement and tree domestication.

Orientador: Lucilene Arilho Ribeiro Bicudo / Resumo: A Síndrome de Microdeleção 22q11 (SD22q11), causada por uma deleção de aproximadamente 3Mb na região 22q11, apresenta uma frequencia média de 1 em 4000 a 9800 nascidos vivos sendo considera a síndrome de microdeleção mais frequente e a segunda causa mais comum de atraso no desenvolvimento e de doença congênita grave, após a síndrome de Down. De acordo com o tamanho e a localização da deleção, diferentes genes podem ser afetados e o principal gene considerado como responsável pelos sinais clássicos da síndrome é o TBX1. A SD22q11 caracteriza-se por um espectro fenotípico bastante amplo, com efeitos pleiotrópicos que resultam no acometimento de praticamente todos os órgãos e/ou sistemas, altamente variáveis com mais de 180 sinais clínicos já descritos, tanto físicos como comportamentais. Nesse trabalho aplicamos ferramentas de bioinformática com o intuito de descobrir padrões clínicos e sistêmicos da deleção 22q11, classificando casos sindrômicos em típicos e atípicos e estudando o impacto da deleção em redes de interação proteína-proteína (PPI). Para avaliação dos sinais clínicos que pudessem diferenciar pacientes sindrômicos foi aplicado uma metodologia baseada em aprendizado de máquina para classificar os casos em típico e atípico de acordo com os sinais clínicos através do algoritmo J48 (um algoritmo de árvore de decisão). As árvores de decisão selecionadas foram altamente precisas. Sinais clínicos como fissura oral, insuficiência velofaríngea, atraso no desenvolvimento de ... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The 22q11 Microdeletion Syndrome (22q11DS), caused by a deletion of approximately 3Mb in the 22q11 region, has an average frequency of 1 in 4000 to 9800 live births and is considered the most frequent microdeletion syndrome and the second most common cause of developmental delay and severe congenital disease after Down syndrome. According to the size and location of the deletion, different genes may be affected and the main gene considered to be responsible for the classic signs of the syndrome is TBX1. 22q11DS is characterized by a very broad phenotypic spectrum with pleiotropic effects that result in the involvement of variable organs and/or systems with more than 180 clinical signs already described, both physical and behavioral. In this work, we applied bioinformatics tools to detect clinical and systemic patterns of 22q11 deletion, classifying typical and atypical syndromic cases, and studying the impact of deletion on protein-protein interaction (PPI) networks. To evaluate clinical signs that could differentiate syndromic patients, a machine-learning based methodology was used to classify the cases into typical and atypical according to the clinical signs through the algorithm J48 (a decision tree algorithm). The selected decision trees were highly accurate. Clinical signs such as oral fissure, velopharyngeal insufficiency, speech and language development delay, specific learning disability, behavioral abnormality and growth delay were indicative for case classification... (Complete abstract click electronic access below) / Mestre

Ecological communities are collections of species bound together by their influences on one another. Community structure, therefore, refers to the way in which these influences are organised. As a result, ecologists are mainly interested in the factors driving the structure, functioning, and persistence of communities. The traditional focus, however, has been on the feeding relationships among species (direct trophic interactions), whereas relationships mediated by a third species or the environment (indirect interactions) have been largely overlooked. I investigated the role of indirect interactions in structuring communities through a series of field experiments in a diverse assemblage of arthropods living on a Brazilian shrub species. I experimentally reduced the abundance of the commonest galler on the shrub and found that the perturbation resonated across the food web, affecting its structure and robustness. Since there was no potential for these effects to be propagated directly or indirectly via the documented trophic links, the effects must have spread non-trophically and/or through trophic links not included in the web. Thus, I investigated non-trophic propagation of effects in the system. I demonstrate that hatched galls of the commonest galler, which serve as habitat for other species, can mediate non-trophic interactions that feedback to the galler modifying its interactions with parasitoids and inquiline aphids. I performed further manipulative experiments, excluding ants, live galls and hatched galls, to reveal mechanisms for the non-trophic interaction modifications observed in this system. Finally, I explored how non-trophic interaction modification could affect the structure and stability of a discrete ecological community in the field. I investigated how the densities of certain pairs of groups relate to each other, and how their relationship changes in relation to a third group. Then, I assembled an "effect network" revealing, for the first time in an empirical community, a hidden web of non-trophic indirect interactions modifying the direct interactions and modifying each other. Overall, the thesis presents evidence that communities are strongly interconnected through non-trophic indirect interactions. This is one of the first empirical demonstrations of the context-dependent modification of interactions via non-trophic interactions. However, determining the mechanisms behind such interaction modifications may be unfeasible. Understanding how the observed effects relate to community structuring requires shifting our focus from bipartite interaction networks to a more holistic approach.

La protéine chaperonne CDC48 (Cell division cycle 48) est un acteur important du contrôle qualité des protéines chez les eucaryotes et est associée à divers processus physio(patho)logiques chez les mammifères. En revanche, son rôle au sein du règne végétal a été peu appréhendé. Ce travail de thèse s’inscrit dans l’étude des fonctions de CDC48 chez les plantes et concerne plus particulièrement son implication dans la réponse immunité induite chez le tabac par cryptogéine produite par l’oomycète phytophthora cryptogea.Trois stratégies ont été adoptées. Premièrement, la dynamique d’accumulation de la protéine CDC48 ainsi que les événements intracellulaires sous-jacents à la réponse immunitaire ont été étudiés à la fois dans des cellules de tabac sauvages et des cellules sur-exprimant la protéine CDC48 (lignée CDC48-TAP). Deuxièmement, une liste de protéines interagissant avec CDC48 a été établie suite à des expériences d’immuno-précipitation de CDC48 suivit d’analyses de spectrométrie de masse. Parmi celles-ci, la forme cytosolique de l’ascorbate peroxydase (cAPX), une enzyme impliquée dans la détoxication du H2O2 intracellulaire, a fait l’objet d’une étude ciblée. Enfin, ces travaux ont été complétés par une analyse bio-informatique de l’ensemble des partenaires de CDC48 identifiés chez le tabac et d’établissement du réseau d’interaction protéique de CDC48 chez Arabidopsis thaliana.Les principaux résultats obtenus ont montré que l’activation de la réponse immunitaire s’accompagne de l’induction d’une accumulation des transcrits et la protéine CDC48. De plus, une mort cellulaire précoce a été observée chez les cellules CDC48-TAP, suggérant un rôle de cette dernière dans la régulation de la réponse hypersensible. L’interaction physique entre CDC48 et cAPX a été confirmée par différentes approches. De façon intéressante, il s’est avéré que l’activité et la dynamique d’accumulation de cAPX sont fortement impactées par la surexpression de CDC48. En accord avec ses résultats, le statut rédox s’est également révélé altéré dans la lignée surexpresseur. Enfin, l’analyse bio-informatique du réseau d’interaction protéique de CDC48 a permis de dégager de nouvelles protéines cibles, en particulier celles impliquées dans le métabolisme de la S-adenosylméthionine, une molécule substrat des réactions de trans-méthylation et précurseur de l’éthylène et de la nicotianamine. De plus, cette analyse a confirmé son rôle dans du système de dégradation Ubiquitine/protéasome.Pour conclure, ce travail de thèse apporte de nouvelles informations quant au rôle de CDC48 dans la biologie des plantes. Il indique que celle-ci est mobilisée dans les cellules végétales exprimant une réponse immunitaire et impacte le statut rédox via la régulation du turnover de cAPX. De nouvelles pistes de recherche ont été dégagées, en particulier un rôle probable de CDC48 dans la régulation de la synthèse de la S-adenosylméthionine et de la réponse hypersensible suivant des mécanismes restant à déterminer. / The chaperone protein CDC48 (Cell division cycle 48) is a major regulator of the quality control of proteins and is involved in various cellular processes in animals and yeast. In contrast, the role of CDC48 in plants is poorly known. In the present work, we investigated the function of CDC48 in plant immunity thanks to the cryptogein/tobacco biological model, cryptogein being produced by the oomycete phytophthora cryptogea.Three strategies were carried out. First, the dynamic of accumulation CDC48 together with intracellular events inherent to the immune response were analyzed in both wild-type and CDC48 overexpressing tobacco cells (CDC48-TAP line). Second, a list if CDC48 partners was established based on immunoprecipitation assays followed by mass spectroscopy analysis. Among those partners the cytosolic form of acorbate peroxidase (cAPX), a central enzyme of the regulation of the redox status regulation, has been specifically studied. Finally, a computational analysis of the partner list of CDC48 and the subsequent generation of the protein-protein interaction (PPI) network of CDC48 in Arabidopsis thaliana were undertook.Our data indicated that the activation of the immune response is accompanied by an induction of the accumulation of both CDC48 transcript and protein. In addition, an early and exacerbated cell death was observed in the CDC48-TAP line, suggesting a role for CDC48 in the hypersensitive response. The interaction between CDC48 and cAPX was confirmed by different approaches. Interestingly, the activity of CDC48 and its dynamic of accumulation were strongly impacted in the CDC48 overexpressing line. Accordingly, a dysregulation of the redox status also occurred in this line. Finally, the computational analysis of the CDC48 PPI network highlighted new potential target proteins including proteins involved in the metabolism of S-adenosylmethionine, a substrate molecule of trans-methylation reactions and precursor of ethylene and nicotianamine.To summarize, this work provides new information about CDC48 in plant biology. It indicates that CDC48 is mobilized by plant cells undergoing an immune response and impacts the redox status through the regulation of the cAPX turnover. New research avenues emerged from our study, notably a putative role of CDC48 in the regulation of S-adenosylmethionine biosynthesis and in the establishment of hypersensitive response through process which remain to be investigated

Orientador: Jörg Kobarg / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Biologia / Made available in DSpace on 2018-08-25T14:15:32Z (GMT). No. of bitstreams: 1 Basei_FernandaLuisa_D.pdf: 43645148 bytes, checksum: 4cb7da11417bc57aea32c2db81dddc18 (MD5) Previous issue date: 2014 / Resumo: As Neks são proteínas quinases similares a NIMA, proteína que é indispensável para a entrada em mitose de células de Aspergillus nidulans. Em humanos foram identificadas 11 Neks (1-11) e, estudos crescentes vêm demonstrando a participação destas em diversas funções celulares além do controle do ciclo e divisão celular. A Nek4 é um dos maiores membros dessa família e sua relação com a manutenção ciliar e resposta ao DNA danificado já foi demonstrada. Contudo, seus parceiros de interação e substratos são ainda desconhecidos. Para melhor compreender o papel da Nek4 foi realizado um estudo de interatoma para identificar novos processos biológicos com os quais a Nek4 está envolvida. Inicialmente foi identificada uma nova isoforma para a Nek4 e assim, realizou-se o estudo de interatoma para as duas isoformas com a finalidade de comparar o perfil de interação das duas proteínas. As duas isoformas da Nek4 foram expressas em células humanas e após imunoprecipitação seguida de identificação por espectrometria de massas, foram identificadas 474 proteínas que interagem com a isoforma 1 da Nek4, Nek4.1 e 149 para a isoforma 2, Nek4.2. Dentre as proteínas identificadas, 102 interagem com ambas isoformas da Nek4. Nossos resultados confirmam o envolvimento da Nek4 com a resposta ao DNA danificado, função ciliar, estabilização dos microtúbulos e ainda sugerem o envolvimento da Nek4 em funções completamente novas, como processamento de RNAm, resposta ao estresse, controle de qualidade das proteínas e apoptose. Entre os parceiros de interação encontramos importantes proteínas como TRAP-1, Whirlin, PCNA, 14-3-3?, Btf, PARP-1, SRSF1, PAI-RBP1 e KAP-1. As duas isoformas compartilham funções que não foram ainda descritas para os membros da família Nek e a isoforma 1 ainda apresenta funções que já foram descritas para outros membros da família. Aliado ao resultado da imunoprecipitação ainda foram realizadas imunofluorescências que permitiram verificar a localização da Nek4 em diferentes estruturas celulares, como os speckles nucleares e a mitocôndria, corroborando com a função no processamento de RNAm e apoptose. O experimento de imunoprecipitação seguido de identificação por espectrometria de massas também apontou para a possibilidade de autofosforilação e dimerização da Nek4. Além disso, foi possível observar diferenças entre o perfil de interação das duas isoformas da Nek4, sendo que a isoforma 1 interage com proteínas que mantém funções biológicas similares a outras Neks, que a isoforma 2 não apresenta / Abstract: Neks are serine-threonine kinases that are similar to NIMA, a protein found in Aspergillus nidulans which is essential for cell division. In humans there are eleven Neks (1-11) which are involved in different biological functions besides the cell cycle control. Nek4 is one of largest members of the Neks family and has been related to the primary cilia formation and in DNA damage response. However, its substrates and interaction partners are still unknown. Thus in an attempt to better understand the role of Nek4 we performed an interactomics study to find new biological processes in which Nek4 is involved. Besides, we described here a novel Nek4 isoform and compared the interactomics profile of these two Nek4 proteins. Isoform 1 and isoform 2 of Nek4 were expressed in human cells and after an immunoprecipitation followed by mass spectrometry, 474 interacting proteins were identified for isoform 1 and 149 for isoform 2 of Nek4. 102 proteins are common interactors between both isoforms. Our results confirm Nek4 involvement in the DNA damage response, cilia maintenance and microtubules stabilization, and raise the possibility of new functional contexts including mRNA processing, apoptosis signaling, stress response, translation and protein quality control. Among the interaction partners, we found important proteins such as TRAP-1, Whirlin, PCNA, 14-3-3?, Btf, PARP-1, SRSF1, PAI-RBP1 and KAP-1. We could observe that both isoforms share functions that are new to the Nek family, and isoform 1 apparently has also maintained functions which have already been established to other Nek family members. From our immunoprecipitation followed by mass spectrometry experiment a possible site for Nek4 autophosphorylation and dimerization was identified. This study provides new insights into Nek4 functions, identifying new interaction partners, localization to new cellular compartment and further suggests an interesting difference between isoform 1 and the novel isoform 2 of Nek4. Nek4 isoform 1 may have maintained similar roles compared to other Neks and these roles are not related to isoform 2 / Doutorado / Bioquimica / Doutora em Biologia Funcional e Molecular