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.

New approaches to open problems in gene expression microarray data

In the past decade, the advent of efficient genome sequencing tools and high-throughput experimental biotechnology has lead to enormous progress in the life science. Among the most important innovations is the microarray tecnology. It allows to quantify the expression for thousands of genes simultaneously by measurin the hybridization from a tissue of interest to probes on a small glass or plastic slide. The characteristics of these data include a fair amount of random noise, a predictor dimension in the thousand, and a sample noise in the dozens. One of the most exciting areas to which microarray technology has been applied is the challenge of deciphering complex disease such as cancer. In these studies, samples are taken from two or more groups of individuals with heterogeneous phenotypes, pathologies, or clinical outcomes. these samples are hybridized to microarrays in an effort to find a small number of genes which are strongly correlated with the group of individuals. Eventhough today methods to analyse the data are welle developed and close to reach a standard organization (through the effort of preposed International project like Microarray Gene Expression Data -MGED- Society [1]) it is not unfrequant to stumble in a clinician's question that do not have a compelling statistical method that could permit to answer it.The contribution of this dissertation in deciphering disease regards the development of new approaches aiming at handle open problems posed by clinicians in handle specific experimental designs. In Chapter 1 starting from a biological necessary introduction, we revise the microarray tecnologies and all the important steps that involve an experiment from the production of the array, to the quality controls ending with preprocessing steps that will be used into the data analysis in the rest of the dissertation. While in Chapter 2 a critical review of standard analysis methods are provided stressing most of problems that In Chapter 3 is introduced a method to adress the issue of unbalanced design of miacroarray experiments. In microarray experiments, experimental design is a crucial starting-point for obtaining reasonable results. In a two-class problem, an equal or similar number of samples it should be collected between the two classes. However in some cases, e.g. rare pathologies, the approach to be taken is less evident. We propose to address this issue by applying a modified version of SAM [2]. MultiSAM consists in a reiterated application of a SAM analysis, comparing the less populated class (LPC) with 1,000 random samplings of the same size from the more populated class (MPC) A list of the differentially expressed genes is generated for each SAM application. After 1,000 reiterations, each single probe given a "score" ranging from 0 to 1,000 based on its recurrence in the 1,000 lists as differentially expressed. The performance of MultiSAM was compared to the performance of SAM and LIMMA [3] over two simulated data sets via beta and exponential distribution. The results of all three algorithms over low- noise data sets seems acceptable However, on a real unbalanced two-channel data set reagardin Chronic Lymphocitic Leukemia, LIMMA finds no significant probe, SAM finds 23 significantly changed probes but cannot separate the two classes, while MultiSAM finds 122 probes with score >300 and separates the data into two clusters by hierarchical clustering. We also report extra-assay validation in terms of differentially expressed genes Although standard algorithms perform well over low-noise simulated data sets, multi-SAM seems to be the only one able to reveal subtle differences in gene expression profiles on real unbalanced data. In Chapter 4 a method to adress similarities evaluation in a three-class prblem by means of Relevance Vector Machine [4] is described. In fact, looking at microarray data in a prognostic and diagnostic clinical framework, not only differences could have a crucial role. In some cases similarities can give useful and, sometimes even more, important information. The goal, given three classes, could be to establish, with a certain level of confidence, if the third one is similar to the first or the second one. In this work we show that Relevance Vector Machine (RVM) [2] could be a possible solutions to the limitation of standard supervised classification. In fact, RVM offers many advantages compared, for example, with his well-known precursor (Support Vector Machine - SVM [3]). Among these advantages, the estimate of posterior probability of class membership represents a key feature to address the similarity issue. This is a highly important, but often overlooked, option of any practical pattern recognition system. We focused on Tumor-Grade-three-class problem, so we have 67 samples of grade I (G1), 54 samples of grade 3 (G3) and 100 samples of grade 2 (G2). The goal is to find a model able to separate G1 from G3, then evaluate the third class G2 as test-set to obtain the probability for samples of G2 to be member of class G1 or class G3. The analysis showed that breast cancer samples of grade II have a molecular profile more similar to breast cancer samples of grade I. Looking at the literature this result have been guessed, but no measure of significance was gived before.

A candidate gene approach to identify DNA markers associated with meat quality and production traits: investigation of several cathepsin genes in Italian heavy pigs.

The cathepsin enzymes represent an important family of lysosomal proteinases with a broad spectrum of functions in many, if not in all, tissues and cell types. In addition to their primary role during the normal protein turnover, they possess highly specific proteolytic activities, including antigen processing in the immune response and a direct role in the development of obesity and tumours. In pigs, the involvement of cathepsin enzymes in proteolytic processes have important effects during the conversion of muscle to meat, due to their influence on meat texture and sensory characteristics, mainly in seasoned products. Their contribution is fundamental in flavour development of dry-curing hams. However, several authors have demonstrated that high cathepsin activity, in particular of cathepsin B, is correlated to defects of these products, such as an excessive meat softness together with abnormal free tyrosine content, astringent or metallic aftertastes and formation of a white film on the cut surface. Thus, investigation of their genetic variability could be useful to identify DNA markers associated with these dry cured hams parameters, but also with meat quality, production and carcass traits in Italian heavy pigs. Unfortunately, no association has been found between cathepsin markers and meat quality traits so far, in particular with cathepsin B activity, suggesting that other genes, besides these, affect meat quality parameters. Nevertheless, significant associations were observed with several carcass and production traits in pigs. A recent study has demonstrated that different single nucleotide polymorphisms (SNPs) localized in cathepsin D (CTSD), F (CTSF), H and Z genes were highly associated with growth, fat deposition and production traits in an Italian Large White pig population. The aim of this thesis was to confirm some of these results in other pig populations and identify new cathepsin markers in order to evaluate their effects on cathepsin activity and other production traits. Furthermore, starting from the data obtained in previous studies on CTSD gene, we also analyzed the known polymorphism located in the insulin-like growth factor 2 gene (IGF2 intron3-g.3072G>A). This marker is considered the causative mutation for the quantitative trait loci (QTL) affecting muscle mass and fat deposition in pigs. Since IGF2 maps very close to CTSD on porcine chromosome (SSC) 2, we wanted to clarify if the effects of the CTSD marker were due to linkage disequilibrium with the IGF2 intron3-g.3072G>A mutation or not. In the first chapter, we reported the results from these two SSC2 gene markers. First of all, we evaluated the effects of the IGF2 intron3-g.3072G>A polymorphism in the Italian Large White breed, for which no previous studies have analysed this marker. Highly significant associations were identified with all estimated breeding values for production and carcass traits (P<0.00001), while no effects were observed for meat quality traits. Instead, the IGF2 intron3-g.3072G>A mutation did not show any associations with the analyzed traits in the Italian Duroc pigs, probably due to the low level of variability at this polymorphic site for this breed. In the same Duroc pig population, significant associations were obtained for the CTSD marker for all production and carcass traits (P < 0.001), after excluding possible confounding effects of the IGF2 mutation. The effects of the CTSD g.70G>A polymorphism were also confirmed in a group of Italian Large White pigs homozygous for the IGF2 intron3-g.3072G allele G (IGF2 intron3-g.3072GG) and by haplotype analysis between the markers of the two considered genes. Taken together, all these data indicated that the IGF2 intron3-g.3072G>A mutation is not the only polymorphism affecting fatness and muscle deposition in pigs. In the second chapter, we reported the analysis of two new SNPs identified in cathepsin L (CTSL) and cathepsin S (CTSS) genes and the association results with meat quality parameters (including cathepsin B activity) and several production traits in an Italian Large White pig population. Allele frequencies of these two markers were evaluated in 7 different pig breeds. Furthermore, we mapped using a radiation hybrid panel the CTSS gene on SSC4. Association studies with several production traits, carried out in 268 Italian Large White pigs, indicated positive effects of the CTSL polymorphism on average daily gain, weight of lean cuts and backfat thickness (P<0.05). The results for these latter traits were also confirmed using a selective genotype approach in other Italian Large White pigs (P<0.01). In the 268 pig group, the CTSS polymorphism was associated with feed:gain ratio and average daily gain (P<0.05). Instead, no association was observed between the analysed markers and meat quality parameters. Finally, we wanted to verify if the positive results obtained for the cathepsin L and S markers and for other previous identified SNPs (cathepsin F, cathepsin Z and their inhibitor cystatin B) were confirmed in the Italian Duroc pig breed (third chapter). We analysed them in two groups of Duroc pigs: the first group was made of 218 performance-tested pigs not selected by any phenotypic criteria, the second group was made of 100 Italian Duroc pigs extreme and divergent for visible intermuscular fat trait. In the first group, the CTSL polymorphism was associated with weight of lean cuts (P<0.05), while suggestive associations were obtained for average daily gain and backfat thickness (P<0.10). Allele frequencies of the CTSL gene marker also differed positively among the visible intermuscular extreme tails. Instead, no positive effects were observed for the other DNA markers on the analysed traits. In conclusion, in agreement with the present data and for the biological role of these enzymes, the porcine CTSD and CTSL markers: a) may have a direct effect in the biological mechanisms involved in determining fat and lean meat content in pigs, or b) these markers could be very close to the putative functional mutation(s) present in other genes. These findings have important practical applications, in particular the CTSD and CTSL mutations could be applied in a marker assisted selection (MAS) both in the Italian Large White and Italian Duroc breeds. Marker assisted selection could also increase in efficiency by adding information from the cathepsin S genotype, but only in the Italian Large White breed.

Role of SP-A gene polymorphism in lung transplantation

Lung transplantation is a widely accepted therapeutic option for end stage lung disease. Clinical outcome is yet challenged by primary graft failure responsible for the majority of the early mortality, by chronic allograft dysfunction and chronic rejection accounting for more than 30% of deaths after the third postoperative year. Pulmonary surfactant proteins (SP) A, B, C and D are one of the first host defense mechanisms the lung can mount. SP-A in particular, produced by the type II pneumocytes, is active in the innate and adaptive immune system being an opsonin, but also regulating the macrophage and lymphocyte response. The main hypothesis for this project is that pulmonary surfactant protein A polymorphism may determine the early and long term lung allograft survival. Of note SP-A biologic activity seems to be genetically determined and SP-A polymorphisms have been associated to various lung disease. The two SP-A genes SP-A1 and SP-A2 have several polymorphisms within the coding region, SP-A1 (6A, 6A2-20), and SP-A2(1A, 1A0-13). The SP-A gene expression is regulated by cAMP, TTF-1 and glucocorticoids. In vitro studies have indicated that SP-A1 and SP-A2 gene variants may have a variable response to glucocorticoids. We proposed to determine if SP-A gene polymorphism predicts primary graft dysfunction and/or chronic lung allograft dysfunction and if SP-A may serve as a biomarker of lung allograft dysfunction. We also proposed to study the interaction between immunosuppressive drugs and SP-A expression and determine whether this is dependent on SP-A polymorphisms. This study will generate novel information improving our understanding of lung allograft dysfunction. It is conceivable that the information will stimulate the interest for a multi centre study to investigate if SP-A polymorphism may be integrated in the donor lung selection criteria and/or to implement post transplant tailored immunosuppression.

Genetic Manipulation, Gene Silencing and Biomarker Development in Multiple Experimental Models.

The thesis is set in three different parts, according to the relative experimental models. First, the domestic pig (Sus scrofa) is part of the study on reproductive biotechnologies: the transgenesis technique of Sperm Mediated Gene Transfer is widely studied starting from the quality of the semen, through the study of multiple uptakes of exogenous DNA and lastly used in the production of multi-transgenic blastocysts. Finally we managed to couple the transgenesis pipeline with sperm sorting and therefore produced transgenic embryos of predetermined sex. In the second part of the thesis the attention is on the fruit fly (Drosophila melanogaster) and on its derived cell line: the S2 cells. The in vitro and in vivo models are used to develop and validate an efficient way to knock down the myc gene. First an efficient in vitro protocol is described, than we demonstrate how the decrease in myc transcript remarkably affects the ribosome biogenesis through the study of Polysome gradients, rRNA content and qPCR. In vivo we identified two optimal drivers for the conditional silencing of myc, once the flies are fed with RU486: the first one is throughout the whole body (Tubulin), while the second is a head fat body driver (S32). With these results we present a very efficient model to study the role of myc in multiple aspects of translation. In the third and last part, the focus is on human derived lung fibroblasts (hLF-1), mouse tail fibroblasts and mouse tissues. We developed an efficient assay to quantify the total protein content of the nucleus on a single cell level via fluorescence. We coupled the protocol with classical immunofluorescence so to have at the same time general and particular information, demonstrating that during senescence nuclear proteins increase by 1.8 fold either in human cells, mouse cells and mouse tissues.