Transcriptional regulation of human mu-opioid receptor gene: functional characterization of activating and inhibitory transcription factors

The organization of the nervous and immune systems is characterized by obvious differences and striking parallels. Both systems need to relay information across very short and very long distances. The nervous system communicates over both long and short ranges primarily by means of more or less hardwired intercellular connections, consisting of axons, dendrites, and synapses. Longrange communication in the immune system occurs mainly via the ordered and guided migration of immune cells and systemically acting soluble factors such as antibodies, cytokines, and chemokines. Its short-range communication either is mediated by locally acting soluble factors or transpires during direct cell–cell contact across specialized areas called “immunological synapses” (Kirschensteiner et al., 2003). These parallels in intercellular communication are complemented by a complex array of factors that induce cell growth and differentiation: these factors in the immune system are called cytokines; in the nervous system, they are called neurotrophic factors. Neither the cytokines nor the neurotrophic factors appear to be completely exclusive to either system (Neumann et al., 2002). In particular, mounting evidence indicates that some of the most potent members of the neurotrophin family, for example, nerve growth factor (NGF) and brainderived neurotrophic factor (BDNF), act on or are produced by immune cells (Kerschensteiner et al., 1999) There are, however, other neurotrophic factors, for example the insulin-like growth factor-1 (IGF-1), that can behave similarly (Kermer et al., 2000). These factors may allow the two systems to “cross-talk” and eventually may provide a molecular explanation for the reports that inflammation after central nervous system (CNS) injury has beneficial effects (Moalem et al., 1999). In order to shed some more light on such a cross-talk, therefore, transcription factors modulating mu-opioid receptor (MOPr) expression in neurons and immune cells are here investigated. More precisely, I focused my attention on IGF-I modulation of MOPr in neurons and T-cell receptor induction of MOPr expression in T-lymphocytes. Three different opioid receptors [mu (MOPr), delta (DOPr), and kappa (KOPr)] belonging to the G-protein coupled receptor super-family have been cloned. They are activated by structurallyrelated exogenous opioids or endogenous opioid peptides, and contribute to the regulation of several functions including pain transmission, respiration, cardiac and gastrointestinal functions, and immune response (Zollner and Stein 2007). MOPr is expressed mainly in the central nervous system where it regulates morphine-induced analgesia, tolerance and dependence (Mayer and Hollt 2006). Recently, induction of MOPr expression in different immune cells induced by cytokines has been reported (Kraus et al., 2001; Kraus et al., 2003). The human mu-opioid receptor gene (OPRM1) promoter is of the TATA-less type and has clusters of potential binding sites for different transcription factors (Law et al. 2004). Several studies, primarily focused on the upstream region of the OPRM1 promoter, have investigated transcriptional regulation of MOPr expression. Presently, however, it is still not completely clear how positive and negative transcription regulators cooperatively coordinate cellor tissue-specific transcription of the OPRM1 gene, and how specific growth factors influence its expression. IGF-I and its receptors are widely distributed throughout the nervous system during development, and their involvement in neurogenesis has been extensively investigated (Arsenijevic et al. 1998; van Golen and Feldman 2000). As previously mentioned, such neurotrophic factors can be also produced and/or act on immune cells (Kerschenseteiner et al., 2003). Most of the physiologic effects of IGF-I are mediated by the type I IGF surface receptor which, after ligand binding-induced autophosphorylation, associates with specific adaptor proteins and activates different second messengers (Bondy and Cheng 2004). These include: phosphatidylinositol 3-kinase, mitogen-activated protein kinase (Vincent and Feldman 2002; Di Toro et al. 2005) and members of the Janus kinase (JAK)/STAT3 signalling pathway (Zong et al. 2000; Yadav et al. 2005). REST plays a complex role in neuronal cells by differentially repressing target gene expression (Lunyak et al. 2004; Coulson 2005; Ballas and Mandel 2005). REST expression decreases during neurogenesis, but has been detected in the adult rat brain (Palm et al. 1998) and is up-regulated in response to global ischemia (Calderone et al. 2003) and induction of epilepsy (Spencer et al. 2006). Thus, the REST concentration seems to influence its function and the expression of neuronal genes, and may have different effects in embryonic and differentiated neurons (Su et al. 2004; Sun et al. 2005). In a previous study, REST was elevated during the early stages of neural induction by IGF-I in neuroblastoma cells. REST may contribute to the down-regulation of genes not yet required by the differentiation program, but its expression decreases after five days of treatment to allow for the acquisition of neural phenotypes. Di Toro et al. proposed a model in which the extent of neurite outgrowth in differentiating neuroblastoma cells was affected by the disappearance of REST (Di Toro et al. 2005). The human mu-opioid receptor gene (OPRM1) promoter contains a DNA sequence binding the repressor element 1 silencing transcription factor (REST) that is implicated in transcriptional repression. Therefore, in the fist part of this thesis, I investigated whether insulin-like growth factor I (IGF-I), which affects various aspects of neuronal induction and maturation, regulates OPRM1 transcription in neuronal cells in the context of the potential influence of REST. A series of OPRM1-luciferase promoter/reporter constructs were transfected into two neuronal cell models, neuroblastoma-derived SH-SY5Y cells and PC12 cells. In the former, endogenous levels of human mu-opioid receptor (hMOPr) mRNA were evaluated by real-time PCR. IGF-I upregulated OPRM1 transcription in: PC12 cells lacking REST, in SH-SY5Y cells transfected with constructs deficient in the REST DNA binding element, or when REST was down-regulated in retinoic acid-differentiated cells. IGF-I activates the signal transducer and activator of transcription-3 (STAT3) signaling pathway and this transcription factor, binding to the STAT1/3 DNA element located in the promoter, increases OPRM1 transcription. T-cell receptor (TCR) recognizes peptide antigens displayed in the context of the major histocompatibility complex (MHC) and gives rise to a potent as well as branched intracellular signalling that convert naïve T-cells in mature effectors, thus significantly contributing to the genesis of a specific immune response. In the second part of my work I exposed wild type Jurkat CD4+ T-cells to a mixture of CD3 and CD28 antigens in order to fully activate TCR and study whether its signalling influence OPRM1 expression. Results were that TCR engagement determined a significant induction of OPRM1 expression through the activation of transcription factors AP-1, NF-kB and NFAT. Eventually, I investigated MOPr turnover once it has been expressed on T-cells outer membrane. It turned out that DAMGO induced MOPr internalisation and recycling, whereas morphine did not. Overall, from the data collected in this thesis we can conclude that that a reduction in REST is a critical switch enabling IGF-I to up-regulate human MOPr, helping these findings clarify how human MOPr expression is regulated in neuronal cells, and that TCR engagement up-regulates OPRM1 transcription in T-cells. My results that neurotrophic factors a and TCR engagement, as well as it is reported for cytokines, seem to up-regulate OPRM1 in both neurons and immune cells suggest an important role for MOPr as a molecular bridge between neurons and immune cells; therefore, MOPr could play a key role in the cross-talk between immune system and nervous system and in particular in the balance between pro-inflammatory and pro-nociceptive stimuli and analgesic and neuroprotective effects.

Architectures and design patterns for functional design of logic control and diagnostics in industrial automation

Recently in most of the industrial automation process an ever increasing degree of automation has been observed. This increasing is motivated by the higher requirement of systems with great performance in terms of quality of products/services generated, productivity, efficiency and low costs in the design, realization and maintenance. This trend in the growth of complex automation systems is rapidly spreading over automated manufacturing systems (AMS), where the integration of the mechanical and electronic technology, typical of the Mechatronics, is merging with other technologies such as Informatics and the communication networks. An AMS is a very complex system that can be thought constituted by a set of flexible working stations, one or more transportation systems. To understand how this machine are important in our society let considerate that every day most of us use bottles of water or soda, buy product in box like food or cigarets and so on. Another important consideration from its complexity derive from the fact that the the consortium of machine producers has estimated around 350 types of manufacturing machine. A large number of manufacturing machine industry are presented in Italy and notably packaging machine industry,in particular a great concentration of this kind of industry is located in Bologna area; for this reason the Bologna area is called “packaging valley”. Usually, the various parts of the AMS interact among them in a concurrent and asynchronous way, and coordinate the parts of the machine to obtain a desiderated overall behaviour is an hard task. Often, this is the case in large scale systems, organized in a modular and distributed manner. Even if the success of a modern AMS from a functional and behavioural point of view is still to attribute to the design choices operated in the definition of the mechanical structure and electrical electronic architecture, the system that governs the control of the plant is becoming crucial, because of the large number of duties associated to it. Apart from the activity inherent to the automation of themachine cycles, the supervisory system is called to perform other main functions such as: emulating the behaviour of traditional mechanical members thus allowing a drastic constructive simplification of the machine and a crucial functional flexibility; dynamically adapting the control strategies according to the different productive needs and to the different operational scenarios; obtaining a high quality of the final product through the verification of the correctness of the processing; addressing the operator devoted to themachine to promptly and carefully take the actions devoted to establish or restore the optimal operating conditions; managing in real time information on diagnostics, as a support of the maintenance operations of the machine. The kind of facilities that designers can directly find on themarket, in terms of software component libraries provides in fact an adequate support as regard the implementation of either top-level or bottom-level functionalities, typically pertaining to the domains of user-friendly HMIs, closed-loop regulation and motion control, fieldbus-based interconnection of remote smart devices. What is still lacking is a reference framework comprising a comprehensive set of highly reusable logic control components that, focussing on the cross-cutting functionalities characterizing the automation domain, may help the designers in the process of modelling and structuring their applications according to the specific needs. Historically, the design and verification process for complex automated industrial systems is performed in empirical way, without a clear distinction between functional and technological-implementation concepts and without a systematic method to organically deal with the complete system. Traditionally, in the field of analog and digital control design and verification through formal and simulation tools have been adopted since a long time ago, at least for multivariable and/or nonlinear controllers for complex time-driven dynamics as in the fields of vehicles, aircrafts, robots, electric drives and complex power electronics equipments. Moving to the field of logic control, typical for industrial manufacturing automation, the design and verification process is approached in a completely different way, usually very “unstructured”. No clear distinction between functions and implementations, between functional architectures and technological architectures and platforms is considered. Probably this difference is due to the different “dynamical framework”of logic control with respect to analog/digital control. As a matter of facts, in logic control discrete-events dynamics replace time-driven dynamics; hence most of the formal and mathematical tools of analog/digital control cannot be directly migrated to logic control to enlighten the distinction between functions and implementations. In addition, in the common view of application technicians, logic control design is strictly connected to the adopted implementation technology (relays in the past, software nowadays), leading again to a deep confusion among functional view and technological view. In Industrial automation software engineering, concepts as modularity, encapsulation, composability and reusability are strongly emphasized and profitably realized in the so-calledobject-oriented methodologies. Industrial automation is receiving lately this approach, as testified by some IEC standards IEC 611313, IEC 61499 which have been considered in commercial products only recently. On the other hand, in the scientific and technical literature many contributions have been already proposed to establish a suitable modelling framework for industrial automation. During last years it was possible to note a considerable growth in the exploitation of innovative concepts and technologies from ICT world in industrial automation systems. For what concerns the logic control design, Model Based Design (MBD) is being imported in industrial automation from software engineering field. Another key-point in industrial automated systems is the growth of requirements in terms of availability, reliability and safety for technological systems. In other words, the control system should not only deal with the nominal behaviour, but should also deal with other important duties, such as diagnosis and faults isolations, recovery and safety management. Indeed, together with high performance, in complex systems fault occurrences increase. This is a consequence of the fact that, as it typically occurs in reliable mechatronic systems, in complex systems such as AMS, together with reliable mechanical elements, an increasing number of electronic devices are also present, that are more vulnerable by their own nature. The diagnosis problem and the faults isolation in a generic dynamical system consists in the design of an elaboration unit that, appropriately processing the inputs and outputs of the dynamical system, is also capable of detecting incipient faults on the plant devices, reconfiguring the control system so as to guarantee satisfactory performance. The designer should be able to formally verify the product, certifying that, in its final implementation, it will perform itsrequired function guarantying the desired level of reliability and safety; the next step is that of preventing faults and eventually reconfiguring the control system so that faults are tolerated. On this topic an important improvement to formal verification of logic control, fault diagnosis and fault tolerant control results derive from Discrete Event Systems theory. The aimof this work is to define a design pattern and a control architecture to help the designer of control logic in industrial automated systems. The work starts with a brief discussion on main characteristics and description of industrial automated systems on Chapter 1. In Chapter 2 a survey on the state of the software engineering paradigm applied to industrial automation is discussed. Chapter 3 presentes a architecture for industrial automated systems based on the new concept of Generalized Actuator showing its benefits, while in Chapter 4 this architecture is refined using a novel entity, the Generalized Device in order to have a better reusability and modularity of the control logic. In Chapter 5 a new approach will be present based on Discrete Event Systems for the problemof software formal verification and an active fault tolerant control architecture using online diagnostic. Finally conclusive remarks and some ideas on new directions to explore are given. In Appendix A are briefly reported some concepts and results about Discrete Event Systems which should help the reader in understanding some crucial points in chapter 5; while in Appendix B an overview on the experimental testbed of the Laboratory of Automation of University of Bologna, is reported to validated the approach presented in chapter 3, chapter 4 and chapter 5. In Appendix C some components model used in chapter 5 for formal verification are reported.