15 resultados para MOLECULAR-FIELD ANALYSIS
em AMS Tesi di Dottorato - Alm@DL - Università di Bologna
Resumo:
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.
Resumo:
Design parameters, process flows, electro-thermal-fluidic simulations and experimental characterizations of Micro-Electro-Mechanical-Systems (MEMS) suited for gas-chromatographic (GC) applications are presented and thoroughly described in this thesis, whose topic belongs to the research activities the Institute for Microelectronics and Microsystems (IMM)-Bologna is involved since several years, i.e. the development of micro-systems for chemical analysis, based on silicon micro-machining techniques and able to perform analysis of complex gaseous mixtures, especially in the field of environmental monitoring. In this regard, attention has been focused on the development of micro-fabricated devices to be employed in a portable mini-GC system for the analysis of aromatic Volatile Organic Compounds (VOC) like Benzene, Toluene, Ethyl-benzene and Xylene (BTEX), i.e. chemical compounds which can significantly affect environment and human health because of their demonstrated carcinogenicity (benzene) or toxicity (toluene, xylene) even at parts per billion (ppb) concentrations. The most significant results achieved through the laboratory functional characterization of the mini-GC system have been reported, together with in-field analysis results carried out in a station of the Bologna air monitoring network and compared with those provided by a commercial GC system. The development of more advanced prototypes of micro-fabricated devices specifically suited for FAST-GC have been also presented (silicon capillary columns, Ultra-Low-Power (ULP) Metal OXide (MOX) sensor, Thermal Conductivity Detector (TCD)), together with the technological processes for their fabrication. The experimentally demonstrated very high sensitivity of ULP-MOX sensors to VOCs, coupled with the extremely low power consumption, makes the developed ULP-MOX sensor the most performing metal oxide sensor reported up to now in literature, while preliminary test results proved that the developed silicon capillary columns are capable of performances comparable to those of the best fused silica capillary columns. Finally, the development and the validation of a coupled electro-thermal Finite Element Model suited for both steady-state and transient analysis of the micro-devices has been described, and subsequently implemented with a fluidic part to investigate devices behaviour in presence of a gas flowing with certain volumetric flow rates.
Resumo:
BTES (borehole thermal energy storage)systems exchange thermal energy by conduction with the surrounding ground through borehole materials. The spatial variability of the geological properties and the space-time variability of hydrogeological conditions affect the real power rate of heat exchangers and, consequently, the amount of energy extracted from / injected into the ground. For this reason, it is not an easy task to identify the underground thermal properties to use when designing. At the current state of technology, Thermal Response Test (TRT) is the in situ test for the characterization of ground thermal properties with the higher degree of accuracy, but it doesn’t fully solve the problem of characterizing the thermal properties of a shallow geothermal reservoir, simply because it characterizes only the neighborhood of the heat exchanger at hand and only for the test duration. Different analytical and numerical models exist for the characterization of shallow geothermal reservoir, but they are still inadequate and not exhaustive: more sophisticated models must be taken into account and a geostatistical approach is needed to tackle natural variability and estimates uncertainty. The approach adopted for reservoir characterization is the “inverse problem”, typical of oil&gas field analysis. Similarly, we create different realizations of thermal properties by direct sequential simulation and we find the best one fitting real production data (fluid temperature along time). The software used to develop heat production simulation is FEFLOW 5.4 (Finite Element subsurface FLOW system). A geostatistical reservoir model has been set up based on literature thermal properties data and spatial variability hypotheses, and a real TRT has been tested. Then we analyzed and used as well two other codes (SA-Geotherm and FV-Geotherm) which are two implementation of the same numerical model of FEFLOW (Al-Khoury model).
Resumo:
In 2010, 2011 and 2012 growing seasons, the occurrence of the ascomycetes Podosphaera fusca and Golovinomyces orontii, causal agents of powdery mildew disease, was monitored on cultivated cucurbits located in Bologna and Mantua provinces to determine the epidemiology of the species. To identify the pathogens, both morphological and molecular identifications were performed on infected leaf samples and a Multiplex-PCR was performed to identify the mating type genes of P. fusca isolates. The investigations indicated a temporal succession of the two species with the earlier infections caused by G. orontii, that seems to be the predominant species till the middle of July when it progressively disappears and P. fusca becomes the main species infecting cucurbits till the end of October. The temporal variation is likely due to the different overwintering strategies of the two species instead of climatic conditions. Only chasmothecia of P. fusca were recorded and mating type alleles ratio tended to be 1:1. Considering that only chasmothecia of P. fusca were found, molecular-genetic analysis were carried out to find some evidence of recombination within this species by MLST and AFLP methods. Surprisingly, no variations were observed within isolates for the 8 MLST markers used. According to this result, AFLP analysis showed a high similarity within isolates, with SM similarity coefficient ranging between 0.91-1.00 and also, sequencing of 12 polymorphic bands revealed identity to some gene involved in mutation and selection. The results suggest that populations of P. fusca are likely to be a clonal population with some differences among isolates probably due to agricultural practices such as fungicides treatments and cultivated hosts. Therefore, asexual reproduction, producing a lot of fungal biomass that can be easily transported by wind, is the most common and useful way to the spread and colonization of the pathogen.
Resumo:
The vast majority of known proteins have not yet been experimentally characterized and little is known about their function. The design and implementation of computational tools can provide insight into the function of proteins based on their sequence, their structure, their evolutionary history and their association with other proteins. Knowledge of the three-dimensional (3D) structure of a protein can lead to a deep understanding of its mode of action and interaction, but currently the structures of <1% of sequences have been experimentally solved. For this reason, it became urgent to develop new methods that are able to computationally extract relevant information from protein sequence and structure. The starting point of my work has been the study of the properties of contacts between protein residues, since they constrain protein folding and characterize different protein structures. Prediction of residue contacts in proteins is an interesting problem whose solution may be useful in protein folding recognition and de novo design. The prediction of these contacts requires the study of the protein inter-residue distances related to the specific type of amino acid pair that are encoded in the so-called contact map. An interesting new way of analyzing those structures came out when network studies were introduced, with pivotal papers demonstrating that protein contact networks also exhibit small-world behavior. In order to highlight constraints for the prediction of protein contact maps and for applications in the field of protein structure prediction and/or reconstruction from experimentally determined contact maps, I studied to which extent the characteristic path length and clustering coefficient of the protein contacts network are values that reveal characteristic features of protein contact maps. Provided that residue contacts are known for a protein sequence, the major features of its 3D structure could be deduced by combining this knowledge with correctly predicted motifs of secondary structure. In the second part of my work I focused on a particular protein structural motif, the coiled-coil, known to mediate a variety of fundamental biological interactions. Coiled-coils are found in a variety of structural forms and in a wide range of proteins including, for example, small units such as leucine zippers that drive the dimerization of many transcription factors or more complex structures such as the family of viral proteins responsible for virus-host membrane fusion. The coiled-coil structural motif is estimated to account for 5-10% of the protein sequences in the various genomes. Given their biological importance, in my work I introduced a Hidden Markov Model (HMM) that exploits the evolutionary information derived from multiple sequence alignments, to predict coiled-coil regions and to discriminate coiled-coil sequences. The results indicate that the new HMM outperforms all the existing programs and can be adopted for the coiled-coil prediction and for large-scale genome annotation. Genome annotation is a key issue in modern computational biology, being the starting point towards the understanding of the complex processes involved in biological networks. The rapid growth in the number of protein sequences and structures available poses new fundamental problems that still deserve an interpretation. Nevertheless, these data are at the basis of the design of new strategies for tackling problems such as the prediction of protein structure and function. Experimental determination of the functions of all these proteins would be a hugely time-consuming and costly task and, in most instances, has not been carried out. As an example, currently, approximately only 20% of annotated proteins in the Homo sapiens genome have been experimentally characterized. A commonly adopted procedure for annotating protein sequences relies on the "inheritance through homology" based on the notion that similar sequences share similar functions and structures. This procedure consists in the assignment of sequences to a specific group of functionally related sequences which had been grouped through clustering techniques. The clustering procedure is based on suitable similarity rules, since predicting protein structure and function from sequence largely depends on the value of sequence identity. However, additional levels of complexity are due to multi-domain proteins, to proteins that share common domains but that do not necessarily share the same function, to the finding that different combinations of shared domains can lead to different biological roles. In the last part of this study I developed and validate a system that contributes to sequence annotation by taking advantage of a validated transfer through inheritance procedure of the molecular functions and of the structural templates. After a cross-genome comparison with the BLAST program, clusters were built on the basis of two stringent constraints on sequence identity and coverage of the alignment. The adopted measure explicity answers to the problem of multi-domain proteins annotation and allows a fine grain division of the whole set of proteomes used, that ensures cluster homogeneity in terms of sequence length. A high level of coverage of structure templates on the length of protein sequences within clusters ensures that multi-domain proteins when present can be templates for sequences of similar length. This annotation procedure includes the possibility of reliably transferring statistically validated functions and structures to sequences considering information available in the present data bases of molecular functions and structures.
Resumo:
Nuclear Magnetic Resonance (NMR) is a branch of spectroscopy that is based on the fact that many atomic nuclei may be oriented by a strong magnetic field and will absorb radiofrequency radiation at characteristic frequencies. The parameters that can be measured on the resulting spectral lines (line positions, intensities, line widths, multiplicities and transients in time-dependent experi-ments) can be interpreted in terms of molecular structure, conformation, molecular motion and other rate processes. In this way, high resolution (HR) NMR allows performing qualitative and quantitative analysis of samples in solution, in order to determine the structure of molecules in solution and not only. In the past, high-field NMR spectroscopy has mainly concerned with the elucidation of chemical structure in solution, but today is emerging as a powerful exploratory tool for probing biochemical and physical processes. It represents a versatile tool for the analysis of foods. In literature many NMR studies have been reported on different type of food such as wine, olive oil, coffee, fruit juices, milk, meat, egg, starch granules, flour, etc using different NMR techniques. Traditionally, univariate analytical methods have been used to ex-plore spectroscopic data. This method is useful to measure or to se-lect a single descriptive variable from the whole spectrum and , at the end, only this variable is analyzed. This univariate methods ap-proach, applied to HR-NMR data, lead to different problems due especially to the complexity of an NMR spectrum. In fact, the lat-ter is composed of different signals belonging to different mole-cules, but it is also true that the same molecules can be represented by different signals, generally strongly correlated. The univariate methods, in this case, takes in account only one or a few variables, causing a loss of information. Thus, when dealing with complex samples like foodstuff, univariate analysis of spectra data results not enough powerful. Spectra need to be considered in their wholeness and, for analysing them, it must be taken in consideration the whole data matrix: chemometric methods are designed to treat such multivariate data. Multivariate data analysis is used for a number of distinct, differ-ent purposes and the aims can be divided into three main groups: • data description (explorative data structure modelling of any ge-neric n-dimensional data matrix, PCA for example); • regression and prediction (PLS); • classification and prediction of class belongings for new samples (LDA and PLS-DA and ECVA). The aim of this PhD thesis was to verify the possibility of identify-ing and classifying plants or foodstuffs, in different classes, based on the concerted variation in metabolite levels, detected by NMR spectra and using the multivariate data analysis as a tool to inter-pret NMR information. It is important to underline that the results obtained are useful to point out the metabolic consequences of a specific modification on foodstuffs, avoiding the use of a targeted analysis for the different metabolites. The data analysis is performed by applying chemomet-ric multivariate techniques to the NMR dataset of spectra acquired. The research work presented in this thesis is the result of a three years PhD study. This thesis reports the main results obtained from these two main activities: A1) Evaluation of a data pre-processing system in order to mini-mize unwanted sources of variations, due to different instrumental set up, manual spectra processing and to sample preparations arte-facts; A2) Application of multivariate chemiometric models in data analy-sis.
Resumo:
The project was developed into three parts: the analysis of p63 isoform in breast tumours; the study of intra-tumour eterogeneicity in metaplastic breast carcinoma; the analysis of oncocytic breast carcinoma. p63 is a sequence-specific DNA-binding factor, homologue of the tumour suppressor and transcription factor p53. The human p63 gene is composed of 15 exons and transcription can occur from two distinct promoters: the transactivating isoforms (TAp63) are generated by a promoter upstream of exon 1, while the alternative promoter located in intron 3 leads to the expression of N-terminal truncated isoforms (ΔNp63). It has been demonstrated that anti-p63 antibodies decorate the majority of squamous cell carcinomas of different organs; moreover tumours with myoepithelial differentiation of the breast show nuclear p63 expression. Two new isoforms have been described with the same sequence as TAp63 and ΔNp63 but lacking exon 4: d4TAp63 and ΔNp73L, respectively. Purpose of the study was to investigate the molecular expression of N-terminal p63 isoforms in benign and malignant breast tissues. In the present study 40 specimens from normal breast, benign lesions, DIN/DCIS, and invasive carcinomas were analyzed by immunohistochemistry and RT-PCR (Reverse Transcriptase-PCR) in order to disclose the patterns of p63 expression. We have observed that the full-length isoforms can be detected in non neoplastic and neoplastic lesions, while the short isoforms are only present in the neoplastic cells of invasive carcinomas. Metaplastic carcinomas of the breast are a heterogeneous group of neoplasms which exhibit varied patterns of metaplasia and differentiation. The existence of such non-modal populations harbouring distinct genetic aberrations may explain the phenotypic diversity observed within a given tumour. Intra-tumour morphological heterogeneity is not uncommon in breast cancer and it can often be appreciated in metaplastic breast carcinomas. Aim of this study was to determine the existence of intra-tumour genetic heterogeneity in metaplastic breast cancers and whether areas with distinct morphological features in a given tumour might be underpinned by distinct patterns of genetic aberrations. 47 cases of metaplastic breast carcinomas were retrieved. Out of the 47 cases, 9 had areas that were of sufficient dimensions to be independently microdissected. Our results indicate that at least some breast cancers are composed of multiple non-modal populations of clonally related cells and provide direct evidence that at least some types of metaplastic breast cancers are composed of multiple non-modal clones harbouring distinct genetic aberrations. Oncocytic tumours represent a distinctive set of lesions with typical granular cytoplasmatic eosinophilia of the neoplastic cells. Only rare example of breast oncocytic carcinomas have been reported in literature and the incidence is probably underestimated. In this study we have analysed 33 cases of oncocytic invasive breast carcinoma of the breast, selected according to morphological and immunohistochemical criteria. These tumours were morphologically classified and studied by immunohistochemistry and aCGH. We have concluded that oncocytic breast carcinoma is a morphologic entity with distinctive ultrastructural and histological features; immunohistochemically is characterized by a luminal profile, it has a frequency of 19.8%, has not distinctive clinical features and, at molecular level, shows a specific constellation of genetic aberration.
Resumo:
Sigma (σ) receptors are well established as a non-opioid, non-phencyclidine, and haloperidol-sensitive receptor family with its own binding profile and a characteristic distribution in the central nervous system (CNS) as well as in endocrine, immune, and some peripheral tissues. Two σ receptors subtypes, termed σ1 and σ2, have been pharmacologically characterized, but, to date, only the σ1 has also been cloned. Activation of σ1 receptors alter several neurotransmitter systems and dopamine (DA) neurotrasmission has been often shown to constitute an important target of σ receptors in different experimental models; however the exact role of σ1 receptor in dopaminergic neurotransmission remains unclear. The DA transporter (DAT) modulates the spatial and temporal aspects of dopaminergic synaptic transmission and interprer the primary mechanism by wich dopaminergic neurons terminate the signal transmission. For this reason present studies have been focused in understanding whether, in cell models, the human subtype of σ1 (hσ1) receptor is able to directly modulate the human DA transporter (hDAT). In the first part of this thesis, HEK-293 and SH-SY5Y cells were permanently transfected with the hσ1 receptor. Subsequently, they were transfected with another plasmid for transiently expressing the hDAT. The hDAT activity was estimated using the described [3H]DA uptake assay and the effects of σ ligands were evaluated by measuring the uptaken [3H]DA after treating the cells with known σ agonists and antagonists. Results illustrated in this thesis demonstrate that activation of overexpressed hσ1 receptors by (+)-pentazocine, the σ1 agonist prototype, determines an increase of 40% of the extracellular [3H]DA uptake, in comparison to non-treated controls and the σ1 antagonists BD-1047 and NE-100 prevent the positive effect of (+)-pentazocine on DA reuptake DA is likely to be considered a neurotoxic molecule. In fact, when levels of intracellular DA abnormally invrease, vescicles can’t sequester the DA which is metabolized by MAO (A and B) and COMT with consequent overproduction of oxygen reactive species and toxic catabolites. Stress induced by these molecules leads cells to death. Thus, for the second part of this thesis, experiments have been performed in order to investigate functional alterations caused by the (+)-pentazocine-mediated increase of DA uptake; particularly it has been investigated if the increase of intracellular [DA] could affect cells viability. Results obtained from this study demonstrate that (+)-pentazocine alone increases DA cell toxicity in a concentration-dependent manner only in cells co-expressing hσ1 and hDAT and σ1 antagonists are able to revert the (+)-pentazocine-induced increase of cell susceptibility to DA toxicity. In the last part of this thesis, the functional cross-talking between hσ1 receptor and hDAT has been further investigated using confocal microscopy. From the acquired data it could be suggested that, following exposure to (+)-pentazocine, the hσ1 receptors massively translocate towards the plasma membrane and colocalize with the hDATs. However, any physical interaction between the two proteins remains to be proved. In conclusion, the presented study shows for the first time that, in cell models, hσ1 receptors directly modulate the hDAT activity. Facilitation of DA uptake induced by (+)-pentazocine is reflected on the increased cell susceptibility to DA toxicity; these effects are prevented by σ1 selective antagonists. Since numerous compounds, including several drugs of abuse, bind to σ1 receptors and activating them could facilitate the damage of dopaminergic neurons, the reported protective effect showed by σ1 antagonists would represent the pharmacological basis to test these compounds in experimental models of dopaminergic neurodegenerative diseases (i.e. Parkinson’s Disease).
Resumo:
Bioremediation implies the use of living organisms, primarily microorganisms, to convert environmental contaminants into less toxic forms. The impact of the consequences of hydrocarbon release in the environment maintain a high research interest in the study of microbial metabolisms associated with the biodegradation of aromatic and aliphatic hydrocarbons but also in the analysis of microbial enzymes that can convert petroleum substrates to value-added products. The studies described in this Thesis fall within the research field that directs the efforts into identifying gene/proteins involved in the catabolism of n-alkanes and into studying the regulatory mechanisms leading to their oxidation. In particular the studies were aimed at investigating the molecular aspects of the ability of Rhodococcus sp. BCP1 to grow on aliphatic hydrocarbons as sole carbon and energy sources. We studied the ability of Rhodococcus sp. BCP1 to grow on gaseous (C2-C4), liquid (C5-C16) and solid (C17-C28) n-alkanes that resulted to be biochemically correlated with the activity of one or more monooxygenases. In order to identify the alkane monooxygenase that is involved in the n-alkanes degradation pathway in Rhodococcus sp. BCP1, PCR-based methodology was applied by using degenerate primers targeting AlkB monooxygenase family members. As result, a chromosomal region, including the alkB gene cluster, was cloned from Rhodococcus sp. BCP1 genome. We characterized the products of this alkB gene cluster and the products of the orfs included in the flanking regions by comparative analysis with the homologues in the database. alkB gene expression studies were carried out by RT-PCR and by the construction of a promoter probe vector containing the lacZ gene downstream of the alkB promoter. B-galactosidase assays revealed the alkB promoter activity induced by n-alkanes and by n-alkanes metabolic products. Furthermore, the transcriptional start of alkB gene was determined by primer extension procedure. A proteomic approach was subsequently applied to compare the protein patterns expressed by BCP1 growing on n-butane, n-hexane, n-hexadecane or n-eicosane with the protein pattern expressed by BCP1 growing on succinate. The accumulation of enzymes specifically induced on n-alkanes was determined. These enzymes were identified by tandem mass spectrometry (LC/MS/MS). Finally, a prm gene, homologue to the gene family coding for soluble di-iron monooxygenases (SDIMOs), has been isolated from Rhodococcus sp. BCP1 genome. This gene product could be involved in the degradation of gaseous n-alkanes in this Rhodococcus strain. The versatility in utilizing hydrocarbons and the discovery of new remarkable metabolic activities outline the potential applications of this microorganism in environmental and industrial biotechnologies.
Resumo:
The scope of my research project is to produce and characterize new crystalline forms of organic compounds, focusing the attention on co-crystals and then transferring these notions on APIs to produce co-crystals of potential interest in the pharmaceutical field. In the first part of this work co-crystallization experiments were performed using as building blocks the family of aliphatic dicarboxylic acids HOOC-(CH2)n-COOH, with n= 2-8. This class of compounds has always been an object of study because it is characterized by an interesting phenomenon of alternation of melting points: the acids with an even number of carbon atoms show a melting point higher than those with an odd one. The acids were co-crystallized with four dipyridyl molecules (formed by two pyridine rings with a different number of bridging carbon atoms) through the formation of intermolecular interactions N•••(H)O. The bases used were: 4,4’-bipyridine (BPY), 1,2-bis(4-pyridyl)ethane (BPA), 1,2-(di-4-pyridyl)ethylene (BPE) and 1,2-bis(4-pyridyl)propane (BPP). The co-crystals obtained by solution synthesis were characterized by different solid-state techniques to determine the structure and to see how the melting points in co-crystals change. In the second part of this study we tried to obtain new crystal forms of compounds of pharmaceutical interest. The APIs studied are: O-desmethylvenlafaxine, Lidocaine, Nalidixic Acid and Sulfadiazine. Each API was subjected to Polymorph Screening and Salt/Co-crystal Screening experiments to identify new crystal forms characterized by different properties. In a typical Salt/Co-crystal Screening the sample was made to react with a co-former (solid or liquid) through different methods: crystallization by solution, grinding, kneading and solid-gas reactions. The new crystal forms obtained were characterized by different solid state techniques (X-ray single crystal diffraction, X-ray powder diffraction, Differential Scanning Calorimetry, Thermogravimetric Analysis, Evolved gas analysis, FT-IR – ATR, Solid State N.M.R).
Resumo:
Beet necrotic yellow vein virus (BNYVV), the leading infectious agent that affects sugar beet, is included within viruses transmitted through the soil from plasmodiophorid as Polymyxa betae. BNYVV is the causal agent of Rhizomania, which induces abnormal rootlet proliferation and is widespread in the sugar beet growing areas in Europe, Asia and America; for review see (Peltier et al., 2008). In this latter continent, Beet soil-borne mosaic virus (BSBMV) has been identified (Lee et al., 2001) and belongs to the benyvirus genus together with BNYVV, both vectored by P. betae. BSBMV is widely distributed only in the United States and it has not been reported yet in others countries. It was first identified in Texas as a sugar beet virus morphologically similar but serologically distinct to BNYVV. Subsequent sequence analysis of BSBMV RNAs evidenced similar genomic organization to that of BNYVV but sufficient molecular differences to distinct BSBMV and BNYVV in two different species (Rush et al., 2003). Benyviruses field isolates usually consist of four RNA species but some BNYVV isolates contain a fifth RNA. RNAs -1 contains a single long ORF encoding polypeptide that shares amino acid homology with known viral RNA-dependent RNA polymerases (RdRp) and helicases. RNAs -2 contains six ORFs: capsid protein (CP), one readthrough protein, triple gene block proteins (TGB) that are required for cell-to-cell virus movement and the sixth 14 kDa ORF is a post-translation gene silencing suppressor. RNAs -3 is involved on disease symptoms and is essential for virus systemic movement. BSBMV RNA-3 can be trans-replicated, trans-encapsidated by the BNYVV helper strain (RNA-1 and -2) (Ratti et al., 2009). BNYVV RNA-4 encoded one 31 kDa protein and is essential for vector interactions and virus transmission by P. betae (Rahim et al., 2007). BNYVV RNA-5 encoded 26 kDa protein that improve virus infections and accumulation in the hosts. We are interest on BSBMV effect on Rhizomania studies using powerful tools as full-length infectious cDNA clones. B-type full-length infectious cDNA clones are available (Quillet et al., 1989) as well as A/P-type RNA-3, -4 and -5 from BNYVV (unpublished). A-type BNYVV full-length clones are also available, but RNA-1 cDNA clone still need to be modified. During the PhD program, we start production of BSBMV full-length cDNA clones and we investigate molecular interactions between plant and Benyviruses exploiting biological, epidemiological and molecular similarities/divergences between BSBMV and BNYVV. During my PhD researchrs we obtained full length infectious cDNA clones of BSBMV RNA-1 and -2 and we demonstrate that they transcripts are replicated and packaged in planta and able to substitute BNYVV RNA-1 or RNA-2 in a chimeric viral progeny (BSBMV RNA-1 + BNYVV RNA-2 or BNYVV RNA-1 + BSBMV RNA-2). During BSBMV full-length cDNA clones production, unexpected 1,730 nts long form of BSBMV RNA-4 has been detected from sugar beet roots grown on BSBMV infected soil. Sequence analysis of the new BSBMV RNA-4 form revealed high identity (~100%) with published version of BSBMV RNA-4 sequence (NC_003508) between nucleotides 1-608 and 1,138-1,730, however the new form shows 528 additionally nucleotides between positions 608-1,138 (FJ424610). Two putative ORFs has been identified, the first one (nucleotides 383 to 1,234), encode a protein with predicted mass of 32 kDa (p32) and the second one (nucleotides 885 to 1,244) express an expected product of 13 kDa (p13). As for BSBMV RNA-3 (Ratti et al., 2009), full-length BSBMV RNA-4 cDNA clone permitted to obtain infectious transcripts that BNYVV viral machinery (Stras12) is able to replicate and to encapsidate in planta. Moreover, we demonstrated that BSBMV RNA-4 can substitute BNYVV RNA-4 for an efficient transmission through the vector P. betae in Beta vulgaris plants, demonstrating a very high correlation between BNYVV and BSBMV. At the same time, using BNYVV helper strain, we studied BSBMV RNA-4’s protein expression in planta. We associated a local necrotic lesions phenotype to the p32 protein expression onto mechanically inoculated C. quinoa. Flag or GFP-tagged sequences of p32 and p13 have been expressed in viral context, using Rep3 replicons, based on BNYVV RNA-3. Western blot analyses of local lesions contents, using FLAG-specific antibody, revealed a high molecular weight protein, which suggest either a strong interaction of BSBMV RNA4’s protein with host protein(s) or post translational modifications. GFP-fusion sequences permitted the subcellular localization of BSBMV RNA4’s proteins. Moreover we demonstrated the absence of self-activation domains on p32 by yeast two hybrid system approaches. We also confirmed that p32 protein is essential for virus transmission by P. betae using BNYVV helper strain and BNYVV RNA-3 and we investigated its role by the use of different deleted forms of p32 protein. Serial mechanical inoculation of wild-type BSBMV on C. quinoa plants were performed every 7 days. Deleted form of BSBMV RNA-4 (1298 bp) appeared after 14 passages and its sequence analysis shows deletion of 433 nucleotides between positions 611 and 1044 of RNA-4 new form. We demonstrated that this deleted form can’t support transmission by P. betae using BNYVV helper strain and BNYVV RNA-3, moreover we confirmed our hypothesis that BSBMV RNA-4 described by Lee et al. (2001) is a deleted form. Interesting after 21 passages we identifed one chimeric form of BSBMV RNA-4 and BSBMV RNA-3 (1146 bp). Two putative ORFs has been identified on its sequence, the first one (nucleotides 383 to 562), encode a protein with predicted mass of 7 kDa (p7), corresponding to the N-terminal of p32 protein encoded by BSBMV RNA-4; the second one (nucleotides 562 to 789) express an expected product of 9 kDa (p9) corresponding to the C-terminal of p29 encoded by BSBMV RNA-3. Results obtained by our research in this topic opened new research lines that our laboratories will develop in a closely future. In particular BSBMV p32 and its mutated forms will be used to identify factors, as host or vector protein(s), involved in the virus transmission through P. betae. The new results could allow selection or production of sugar beet plants able to prevent virus transmission then able to reduce viral inoculum in the soil.
Resumo:
The goal of many plant scientists’ research is to explain natural phenotypic variation in term of simple changes in DNA sequence. DNA-based molecular markers are extensively used for the construction of genome-wide molecular maps and to perform genetic analysis for simple and complex traits. The PhD thesis was divided into two main research lines according to the different approaches adopted. The first research line is to analyze the genetic diversity in an Italian apple germplasm collection for the identification of markers tightly linked to targeted genes by an association genetic method. This made it possible to identify synomym and homonym accessions and triploids. The fruit red skin color trait has been used to test the reliability of the genetic approaches in this species. The second line is related to the development of molecular markers closely linked to the Rvi13 and Rvi5 scab resistance genes, previously mapped on apple’s chromosome 10 and 17 respectively by using the traditional linkage mapping method. Both region have been fine-mapped with various type of markers that could be used for marker-assisted selection in future breeding programs and to isolate the two resistance genes.
Resumo:
Tractor rollover represent a primary cause of death or serious injury in agriculture and despite the mandatory Roll-Over Protective Structures (ROPS), that reduced the number of injuries, tractor accidents are still of great concern. Because of their versatility and wide use many studies on safety are concerned with the stability of tractors, but they often prefer controlled tests or laboratory tests. The evaluation of tractors working in field, instead, is a very complex issue because the rollover could be influenced by the interaction among operator, tractor and environment. Recent studies are oriented towards the evaluation of the actual working conditions developing prototypes for driver assistance and data acquisition. Currently these devices are produced and sold by manufacturers. A warning device was assessed in this study with the aim to evaluate its performance and to collect data on different variables influencing the dynamics of tractors in field by monitoring continuously the working conditions of tractors operating at the experimental farm of the Bologna University. The device consists of accelerometers, gyroscope, GSM/GPRS, GPS for geo-referencing and a transceiver for the automatic recognition of tractor-connected equipment. A microprocessor processes data and provides information, through a dedicated algorithm requiring data on the geometry of the tested tractor, on the level of risk for the operator in terms of probable loss of stability and suggests corrective measures to reduce the potential instability of the tractor.
Resumo:
Natural systems face pressures exerted by natural physical-chemical forcings and a myriad of co-occurring human stressors that may interact to cause larger than expected effects, thereby presenting a challenge to ecosystem management. This thesis aimed to develop new information that can contribute to reduce the existing knowledge gaps hampering the holistic management of multiple stressors. I undertook a review of the state-of-the-art methods to detect, quantify and predict stressor interactions, identifying techniques that could be applied in this thesis research. Then, I conducted a systematic review of saltmarsh multiple stressor studies in conjunction with a multiple stressor mapping exercise for the study system in order to infer potential important synergistic stressor interactions. This analysis identified key stressors that are affecting the study system, but also pointed to data gaps in terms of driver and pressure data and raised issues for potentially overlooked stressors. Using field mesocosms, I explored how a local stressor (nutrient availability) affects the responses of saltmarsh vegetation to a global stressor (increased inundation) in different soil types. Results indicate that saltmarsh vegetation would be more drastically affected by increased inundation in low than in medium organic matter soils, and especially in estuaries already under high nutrient availability. In another field experiment, I examined the challenges of managing co-occurring and potentially interacting local stressors on saltmarsh vegetation: recreational trampling and smothering by deposition of excess macroalgal wrack due to high nutrient loads. Trampling and wrack prevention had interacting effects, causing non-linear responses of the vegetation to simulated management of these stressors, such that vegetation recovered only in those treatments simulating the combined prevention of both stressors. During this research I detected, using molecular genetic methods, a widespread presence of S. anglica (and to a lesser extent S. townsendii), two previously unrecorded non-native Spartinas in the study areas.