Regulation of SRC-3 localization and dynamics by phosphorylation during ERα-dependent transcriptional activation

Transcription is controlled by promoter-selective transcriptional factors (TFs), which bind to cis-regulatory enhancers elements, termed hormone response elements (HREs), in a specific subset of genes. Regulation by these factors involves either the recruitment of coactivators or corepressors and direct interaction with the basal transcriptional machinery (1). Hormone-activated nuclear receptors (NRs) are well characterized transcriptional factors (2) that bind to the promoters of their target genes and recruit primary and secondary coactivator proteins which possess many enzymatic activities required for gene expression (1,3,4). In the present study, using single-cell high-resolution fluorescent microscopy and high throughput microscopy (HTM) coupled to computational imaging analysis, we investigated transcriptional regulation controlled by the estrogen receptor alpha (ERalpha), in terms of large scale chromatin remodeling and interaction with the associated coactivator SRC-3 (Steroid Receptor Coactivator-3), a member of p160 family (28) primary coactivators. ERalpha is a steroid-dependent transcriptional factor (16) that belongs to the NRs superfamily (2,3) and, in response to the hormone 17-ß estradiol (E2), regulates transcription of distinct target genes involved in development, puberty, and homeostasis (8,16). ERalpha spends most of its lifetime in the nucleus and undergoes a rapid (within minutes) intranuclear redistribution following the addition of either agonist or antagonist (17,18,19). We designed a HeLa cell line (PRL-HeLa), engineered with a chromosomeintegrated reporter gene array (PRL-array) containing multicopy hormone response-binding elements for ERalpha that are derived from the physiological enhancer/promoter region of the prolactin gene. Following GFP-ER transfection of PRL-HeLa cells, we were able to observe in situ ligand dependent (i) recruitment to the array of the receptor and associated coregulators, (ii) chromatin remodeling, and (iii) direct transcriptional readout of the reporter gene. Addition of E2 causes a visible opening (decondensation) of the PRL-array, colocalization of RNA Polymerase II, and transcriptional readout of the reporter gene, detected by mRNA FISH. On the contrary, when cells were treated with an ERalpha antagonist (Tamoxifen or ICI), a dramatic condensation of the PRL-array was observed, displacement of RNA Polymerase II, and complete decreasing in the transcriptional FISH signal. All p160 family coactivators (28) colocalize with ERalpha at the PRL-array. Steroid Receptor Coactivator-3 (SRC-3/AIB1/ACTR/pCIP/RAC3/TRAM1) is a p160 family member and a known oncogenic protein (4,34). SRC-3 is regulated by a variety of posttranslational modifications, including methylation, phosphorylation, acetylation, ubiquitination and sumoylation (4,35). These events have been shown to be important for its interaction with other coactivator proteins and NRs and for its oncogenic potential (37,39). A number of extracellular signaling molecules, like steroid hormones, growth factors and cytokines, induce SRC-3 phosphorylation (40). These actions are mediated by a wide range of kinases, including extracellular-regulated kinase 1 and 2 (ERK1-2), c-Jun N-terminal kinase, p38 MAPK, and IkB kinases (IKKs) (41,42,43). Here, we report SRC-3 to be a nucleocytoplasmic shuttling protein, whose cellular localization is regulated by phosphorylation and interaction with ERalpha. Using a combination of high throughput and fluorescence microscopy, we show that both chemical inhibition (with U0126) and siRNA downregulation of the MAP/ERK1/2 kinase (MEK1/2) pathway induce a cytoplasmic shift in SRC-3 localization, whereas stimulation by EGF signaling enhances its nuclear localization by inducing phosphorylation at T24, S857, and S860, known partecipants in the regulation of SRC-3 activity (39). Accordingly, the cytoplasmic localization of a non-phosphorylatable SRC-3 mutant further supports these results. In the presence of ERalpha, U0126 also dramatically reduces: hormone-dependent colocalization of ERalpha and SRC-3 in the nucleus; formation of ER-SRC-3 coimmunoprecipitation complex in cell lysates; localization of SRC-3 at the ER-targeted prolactin promoter array (PRL-array) and transcriptional activity. Finally, we show that SRC-3 can also function as a cotransporter, facilitating the nuclear-cytoplasmic shuttling of estrogen receptor. While a wealth of studies have revealed the molecular functions of NRs and coregulators, there is a paucity of data on how these functions are spatiotemporally organized in the cellular context. Technically and conceptually, our findings have a new impact upon evaluating gene transcriptional control and mechanisms of action of gene regulators.

Context detection and abstraction in smart environments

Context-aware computing is currently considered the most promising approach to overcome information overload and to speed up access to relevant information and services. Context-awareness may be derived from many sources, including user profile and preferences, network information, sensor analysis; usually context-awareness relies on the ability of computing devices to interact with the physical world, i.e. with the natural and artificial objects hosted within the "environment”. Ideally, context-aware applications should not be intrusive and should be able to react according to user’s context, with minimum user effort. Context is an application dependent multidimensional space and the location is an important part of it since the very beginning. Location can be used to guide applications, in providing information or functions that are most appropriate for a specific position. Hence location systems play a crucial role. There are several technologies and systems for computing location to a vary degree of accuracy and tailored for specific space model, i.e. indoors or outdoors, structured spaces or unstructured spaces. The research challenge faced by this thesis is related to pedestrian positioning in heterogeneous environments. Particularly, the focus will be on pedestrian identification, localization, orientation and activity recognition. This research was mainly carried out within the “mobile and ambient systems” workgroup of EPOCH, a 6FP NoE on the application of ICT to Cultural Heritage. Therefore applications in Cultural Heritage sites were the main target of the context-aware services discussed. Cultural Heritage sites are considered significant test-beds in Context-aware computing for many reasons. For example building a smart environment in museums or in protected sites is a challenging task, because localization and tracking are usually based on technologies that are difficult to hide or harmonize within the environment. Therefore it is expected that the experience made with this research may be useful also in domains other than Cultural Heritage. This work presents three different approaches to the pedestrian identification, positioning and tracking: Pedestrian navigation by means of a wearable inertial sensing platform assisted by the vision based tracking system for initial settings an real-time calibration; Pedestrian navigation by means of a wearable inertial sensing platform augmented with GPS measurements; Pedestrian identification and tracking, combining the vision based tracking system with WiFi localization. The proposed localization systems have been mainly used to enhance Cultural Heritage applications in providing information and services depending on the user’s actual context, in particular depending on the user’s location.

Target Tracking in UWB Multistatic Radars

Detection, localization and tracking of non-collaborative objects moving inside an area is of great interest to many surveillance applications. An ultra- wideband (UWB) multistatic radar is considered as a good infrastructure for such anti-intruder systems, due to the high range resolution provided by the UWB impulse-radio and the spatial diversity achieved with a multistatic configuration. Detection of targets, which are typically human beings, is a challenging task due to reflections from unwanted objects in the area, shadowing, antenna cross-talks, low transmit power, and the blind zones arised from intrinsic peculiarities of UWB multistatic radars. Hence, we propose more effective detection, localization, as well as clutter removal techniques for these systems. However, the majority of the thesis effort is devoted to the tracking phase, which is an essential part for improving the localization accuracy, predicting the target position and filling out the missed detections. Since UWB radars are not linear Gaussian systems, the widely used tracking filters, such as the Kalman filter, are not expected to provide a satisfactory performance. Thus, we propose the Bayesian filter as an appropriate candidate for UWB radars. In particular, we develop tracking algorithms based on particle filtering, which is the most common approximation of Bayesian filtering, for both single and multiple target scenarios. Also, we propose some effective detection and tracking algorithms based on image processing tools. We evaluate the performance of our proposed approaches by numerical simulations. Moreover, we provide experimental results by channel measurements for tracking a person walking in an indoor area, with the presence of a significant clutter. We discuss the existing practical issues and address them by proposing more robust algorithms.

Cooperative Wireless Networks for Localization

This thesis adresses the problem of localization, and analyzes its crucial aspects, within the context of cooperative WSNs. The three main issues discussed in the following are: network synchronization, position estimate and tracking. Time synchronization is a fundamental requirement for every network. In this context, a new approach based on the estimation theory is proposed to evaluate the ultimate performance limit in network time synchronization. In particular the lower bound on the variance of the average synchronization error in a fully connected network is derived by taking into account the statistical characterization of the Message Delivering Time (MDT) . Sensor network localization algorithms estimate the locations of sensors with initially unknown location information by using knowledge of the absolute positions of a few sensors and inter-sensor measurements such as distance and bearing measurements. Concerning this issue, i.e. the position estimate problem, two main contributions are given. The first is a new Semidefinite Programming (SDP) framework to analyze and solve the problem of flip-ambiguity that afflicts range-based network localization algorithms with incomplete ranging information. The occurrence of flip-ambiguous nodes and errors due to flip ambiguity is studied, then with this information a new SDP formulation of the localization problem is built. Finally a flip-ambiguity-robust network localization algorithm is derived and its performance is studied by Monte-Carlo simulations. The second contribution in the field of position estimate is about multihop networks. A multihop network is a network with a low degree of connectivity, in which couples of given any nodes, in order to communicate, they have to rely on one or more intermediate nodes (hops). Two new distance-based source localization algorithms, highly robust to distance overestimates, typically present in multihop networks, are presented and studied. The last point of this thesis discuss a new low-complexity tracking algorithm, inspired by the Fano’s sequential decoding algorithm for the position tracking of a user in a WLAN-based indoor localization system.

Scene Reconstruction And Understanding By RGB-D Sensors

This thesis investigates interactive scene reconstruction and understanding using RGB-D data only. Indeed, we believe that depth cameras will still be in the near future a cheap and low-power 3D sensing alternative suitable for mobile devices too. Therefore, our contributions build on top of state-of-the-art approaches to achieve advances in three main challenging scenarios, namely mobile mapping, large scale surface reconstruction and semantic modeling. First, we will describe an effective approach dealing with Simultaneous Localization And Mapping (SLAM) on platforms with limited resources, such as a tablet device. Unlike previous methods, dense reconstruction is achieved by reprojection of RGB-D frames, while local consistency is maintained by deploying relative bundle adjustment principles. We will show quantitative results comparing our technique to the state-of-the-art as well as detailed reconstruction of various environments ranging from rooms to small apartments. Then, we will address large scale surface modeling from depth maps exploiting parallel GPU computing. We will develop a real-time camera tracking method based on the popular KinectFusion system and an online surface alignment technique capable of counteracting drift errors and closing small loops. We will show very high quality meshes outperforming existing methods on publicly available datasets as well as on data recorded with our RGB-D camera even in complete darkness. Finally, we will move to our Semantic Bundle Adjustment framework to effectively combine object detection and SLAM in a unified system. Though the mathematical framework we will describe does not restrict to a particular sensing technology, in the experimental section we will refer, again, only to RGB-D sensing. We will discuss successful implementations of our algorithm showing the benefit of a joint object detection, camera tracking and environment mapping.

Do Academic and Private Entrepreneurs differ? An empirical analysis of the Micro-Foundation of Entrepreneurial Orientation

This Doctoral Thesis focuses on the study of individual behaviours as a result of organizational affiliation. The objective is to assess the Entrepreneurial Orientation of individuals proving the existence of a set of antecedents to that measure returning a structural model of its micro-foundation. Relying on the developed measurement model, I address the issue whether some Entrepreneurs experience different behaviours as a result of their academic affiliation, comparing a sample of ‘Academic Entrepreneurs’ to a control sample of ‘Private Entrepreneurs’ affiliated to a matched sample of Academic Spin-offs and Private Start-ups. Building on the Theory of the Planned Behaviour, proposed by Ajzen (1991), I present a model of causal antecedents of Entrepreneurial Orientation on constructs extensively used and validated, both from a theoretical and empirical perspective, in sociological and psychological studies. I focus my investigation on five major domains: (a) Situationally Specific Motivation, (b) Personal Traits and Characteristics, (c) Individual Skills, (d) Perception of the Business Environment and (e) Entrepreneurial Orientation Related Dimensions. I rely on a sample of 200 Entrepreneurs, affiliated to a matched sample of 72 Academic Spin-offs and Private Start-ups. Firms are matched by Industry, Year of Establishment and Localization and they are all located in the Emilia Romagna region, in northern Italy. I’ve gathered data by face to face interviews and used a Structural Equation Modeling technique (Lisrel 8.80, Joreskog, K., & Sorbom, D. 2006) to perform the empirical analysis. The results show that Entrepreneurial Orientation is a multi-dimensional micro-founded construct which can be better represented by a Second-Order Model. The t-tests on the latent means reveal that the Academic Entrepreneurs differ in terms of: Risk taking, Passion, Procedural and Organizational Skills, Perception of the Government, Context and University Supports. The Structural models also reveal that the main differences between the two groups lay in the predicting power of Technical Skills, Perceived Context Support and Perceived University Support in explaining the Entrepreneurial Orientation Related Dimensions.

The problems of equivalence in advertising translation: examples from English and Russian

Abstract The academic environment has recently recognized the importance and benefits that an extensive research on the translation of advertising can have for translation studies. Despite the growing interest and increasing research activity in the field it is still difficult to speak about a theory of advertising translation in general. There is a need for further study encompassing different languages and both heterogeneous and homogenous cultures that will give the possibility to receive a more complete map of what the translation of advertising is and should be. Previous studies have been concentrated, for the most part, on Western European language pairs. This study is a research into perfume and cosmetics print advertisements translated from English into Russian where both visual and verbal elements are considered. Three broad translation approaches have been identified in what concerns the verbal message: Translated message, parallel translation, recreated adverts, and three approaches in dealing with the image: similar images, modified images, completely different images. The thesis shows that where Russian advertisements for perfume products tend to have a message, or create one, this is often lacking in the English copy. The article ends by suggesting that perfume advertisements favor the standardization approach when entering Russian market. The attempts to localize the advert have also been noticed although they are obviously less numerous in perfume adverts and are rather instances of adaptation - a mix between the localization and standardization approaches since they keep drawing on the same globally accepted universals about female beauty and concern for ‘woman’s identity’ (we focused our analysis on products designed for female consumers). This study, complementing previous studies, aims to be a contribution to the description of laws and strategies that guide the translation of advertising texts into Russian.

Reconstruction of CNGS neutrino events in the emulsions of the OPERA experiment

The OPERA experiment aims at the direct observation of ν_mu -> ν_tau oscillations in the CNGS (CERN Neutrinos to Gran Sasso) neutrino beam produced at CERN; since the ν_e contamination in the CNGS beam is low, OPERA will also be able to study the sub-dominant oscillation channel ν_mu -> ν_e. OPERA is a large scale hybrid apparatus divided in two supermodules, each equipped with electronic detectors, an iron spectrometer and a highly segmented ~0.7 kton target section made of Emulsion Cloud Chamber (ECC) units. During my research work in the Bologna Lab. I have taken part to the set-up of the automatic scanning microscopes studying and tuning the scanning system performances and efficiencies with emulsions exposed to a test beam at CERN in 2007. Once the triggered bricks were distributed to the collaboration laboratories, my work was centered on the procedure used for the localization and the reconstruction of neutrino events.

Studio della trasduzione del Segnale Nucleare Inositide-Dipendente: identificazione di eEF1A2 come nuovo Fosfosubstrato di PKC βI

Introduction Phospholipase Cb1 (PLC-β1) is a key player in the regulation of nuclear inositol lipid signaling and of a wide range of cellular functions, such as proliferation and differentiation (1,2,3). PLCb1 signaling depends on the cleavage of phosphatidylinositol 4,5-bisphosphate and the formation of the second messengers diacylglycerol and Inositol tris-phosphate which activate canonical protein kinase C (cPKC) isoforms. Here we describe a proteomic approach to find out a potential effector of nuclear PLC-b1 dependent signaling during insulin stimulated myogenic differentiation. Methods Nuclear lysates obtained from insulin induced C2C12 myoblasts were immunoprecipitated with anti-phospho-substrate cPKC antibody. Proteins, stained with Comassie blue, were excised, digested and subsequently analysed in LC-MS/MS. For peptide sequence searching, the mass spectra were processed and analyzed using the Mascot MS/MS ion search program with the NCBI database. Western blotting, GST-pull down and co-immunoprecipitation were performed to study the interaction between eEF1A2 and cPKCs. Site direct mutagenesis was performed to confirm the phosphorylated motif recognized by the antibody. Immunofluorescence analysis, GFP-tagged eEF1A2 vector and subcellular fractionation were performed to study nuclear localization and relative distribution of eEF1A2. Results We have previously shown that PLC-β1 is greatly increased at the nuclear level during insulin-induced myoblasts differentiation and that this nuclear localization is essential for induction of differentiation. Thus, nuclear proteins of insulin stimulated C2C12 myoblasts, were immunoprecipitated with an anti-phospho-substrate cPKC antibody. After Electrophoretic gel separation of proteins immunoprecipitated, several molecules were identified by LC-MS/MS. Among these most relevant and unexpected was eukaryotic elongation factor 1 alpha 2 (eEF1A2). We found that eEF1A2 is phosphorylated by PKCb1 and that these two molecules coimmunolocalized at the nucleolar level. eEF1A2 could be phosphorylated in many sites among which both threonine and serine residues. By site direct mutagenesis we demonstrated that it is the serine residue of the motif recognized by the antibody that is specifically phosphorylated by PKCb1. The silencing of PLCb1 gives rise to a reduction of expression and phosphorylation levels of eEF1A2 indicating this molecule as a target of nuclear PLCb1 regulatory network during myoblasts differentiation.

Machine learning methods for prediction of disulphide bonding states of cysteine residues in proteins

The goal of this thesis work is to develop a computational method based on machine learning techniques for predicting disulfide-bonding states of cysteine residues in proteins, which is a sub-problem of a bigger and yet unsolved problem of protein structure prediction. Improvement in the prediction of disulfide bonding states of cysteine residues will help in putting a constraint in the three dimensional (3D) space of the respective protein structure, and thus will eventually help in the prediction of 3D structure of proteins. Results of this work will have direct implications in site-directed mutational studies of proteins, proteins engineering and the problem of protein folding. We have used a combination of Artificial Neural Network (ANN) and Hidden Markov Model (HMM), the so-called Hidden Neural Network (HNN) as a machine learning technique to develop our prediction method. By using different global and local features of proteins (specifically profiles, parity of cysteine residues, average cysteine conservation, correlated mutation, sub-cellular localization, and signal peptide) as inputs and considering Eukaryotes and Prokaryotes separately we have reached to a remarkable accuracy of 94% on cysteine basis for both Eukaryotic and Prokaryotic datasets, and an accuracy of 90% and 93% on protein basis for Eukaryotic dataset and Prokaryotic dataset respectively. These accuracies are best so far ever reached by any existing prediction methods, and thus our prediction method has outperformed all the previously developed approaches and therefore is more reliable. Most interesting part of this thesis work is the differences in the prediction performances of Eukaryotes and Prokaryotes at the basic level of input coding when ‘profile’ information was given as input to our prediction method. And one of the reasons for this we discover is the difference in the amino acid composition of the local environment of bonded and free cysteine residues in Eukaryotes and Prokaryotes. Eukaryotic bonded cysteine examples have a ‘symmetric-cysteine-rich’ environment, where as Prokaryotic bonded examples lack it.

Development of muliplexed analytical methods based on bioluminescent whole-cell biosensors

The subject of this Ph.D. research thesis is the development and application of multiplexed analytical methods based on bioluminescent whole-cell biosensors. One of the main goals of analytical chemistry is multianalyte testing in which two or more analytes are measured simultaneously in a single assay. The advantages of multianalyte testing are work simplification, high throughput, and reduction in the overall cost per test. The availability of multiplexed portable analytical systems is of particular interest for on-field analysis of clinical, environmental or food samples as well as for the drug discovery process. To allow highly sensitive and selective analysis, these devices should combine biospecific molecular recognition with ultrasensitive detection systems. To address the current need for rapid, highly sensitive and inexpensive devices for obtaining more data from each sample,genetically engineered whole-cell biosensors as biospecific recognition element were combined with ultrasensitive bioluminescence detection techniques. Genetically engineered cell-based sensing systems were obtained by introducing into bacterial, yeast or mammalian cells a vector expressing a reporter protein whose expression is controlled by regulatory proteins and promoter sequences. The regulatory protein is able to recognize the presence of the analyte (e.g., compounds with hormone-like activity, heavy metals…) and to consequently activate the expression of the reporter protein that can be readily measured and directly related to the analyte bioavailable concentration in the sample. Bioluminescence represents the ideal detection principle for miniaturized analytical devices and multiplexed assays thanks to high detectability in small sample volumes allowing an accurate signal localization and quantification. In the first chapter of this dissertation is discussed the obtainment of improved bioluminescent proteins emitting at different wavelenghts, in term of increased thermostability, enhanced emission decay kinetic and spectral resolution. The second chapter is mainly focused on the use of these proteins in the development of whole-cell based assay with improved analytical performance. In particular since the main drawback of whole-cell biosensors is the high variability of their analyte specific response mainly caused by variations in cell viability due to aspecific effects of the sample’s matrix, an additional bioluminescent reporter has been introduced to correct the analytical response thus increasing the robustness of the bioassays. The feasibility of using a combination of two or more bioluminescent proteins for obtaining biosensors with internal signal correction or for the simultaneous detection of multiple analytes has been demonstrated by developing a dual reporter yeast based biosensor for androgenic activity measurement and a triple reporter mammalian cell-based biosensor for the simultaneous monitoring of two CYP450 enzymes activation, involved in cholesterol degradation, with the use of two spectrally resolved intracellular luciferases and a secreted luciferase as a control for cells viability. In the third chapter is presented the development of a portable multianalyte detection system. In order to develop a portable system that can be used also outside the laboratory environment even by non skilled personnel, cells have been immobilized into a new biocompatible and transparent polymeric matrix within a modified clear bottom black 384 -well microtiter plate to obtain a bioluminescent cell array. The cell array was placed in contact with a portable charge-coupled device (CCD) light sensor able to localize and quantify the luminescent signal produced by different bioluminescent whole-cell biosensors. This multiplexed biosensing platform containing whole-cell biosensors was successfully used to measure the overall toxicity of a given sample as well as to obtain dose response curves for heavy metals and to detect hormonal activity in clinical samples (PCT/IB2010/050625: “Portable device based on immobilized cells for the detection of analytes.” Michelini E, Roda A, Dolci LS, Mezzanotte L, Cevenini L , 2010). At the end of the dissertation some future development steps are also discussed in order to develop a point of care (POCT) device that combine portability, minimum sample pre-treatment and highly sensitive multiplexed assays in a short assay time. In this POCT perspective, field-flow fractionation (FFF) techniques, in particular gravitational variant (GrFFF) that exploit the earth gravitational field to structure the separation, have been investigated for cells fractionation, characterization and isolation. Thanks to the simplicity of its equipment, amenable to miniaturization, the GrFFF techniques appears to be particularly suited for its implementation in POCT devices and may be used as pre-analytical integrated module to be applied directly to drive target analytes of raw samples to the modules where biospecifc recognition reactions based on ultrasensitive bioluminescence detection occurs, providing an increase in overall analytical output.

Nonlinear Control of Magnetically Actuated Spacecraft

The topic of this thesis is the feedback stabilization of the attitude of magnetically actuated spacecraft. The use of magnetic coils is an attractive solution for the generation of control torques on small satellites flying inclined low Earth orbits, since magnetic control systems are characterized by reduced weight and cost, higher reliability, and require less power with respect to other kinds of actuators. At the same time, the possibility of smooth modulation of control torques reduces coupling of the attitude control system with flexible modes, thus preserving pointing precision with respect to the case when pulse-modulated thrusters are used. The principle based on the interaction between the Earth's magnetic field and the magnetic field generated by the set of coils introduces an inherent nonlinearity, because control torques can be delivered only in a plane that is orthogonal to the direction of the geomagnetic field vector. In other words, the system is underactuated, because the rotational degrees of freedom of the spacecraft, modeled as a rigid body, exceed the number of independent control actions. The solution of the control issue for underactuated spacecraft is also interesting in the case of actuator failure, e.g. after the loss of a reaction-wheel in a three-axes stabilized spacecraft with no redundancy. The application of well known control strategies is no longer possible in this case for both regulation and tracking, so that new methods have been suggested for tackling this particular problem. The main contribution of this thesis is to propose continuous time-varying controllers that globally stabilize the attitude of a spacecraft, when magneto-torquers alone are used and when a momentum-wheel supports magnetic control in order to overcome the inherent underactuation. A kinematic maneuver planning scheme, stability analyses, and detailed simulation results are also provided, with new theoretical developments and particular attention toward application considerations.