Luminescent Systems for Genomics and Proteomics

The present PhD project was focused on the development of new tools and methods for luminescence-based techniques. In particular, the ultimate goal was to present substantial improvements to the currently available technologies for both research and diagnostic in the fields of biology, proteomics and genomics. Different aspects and problems were investigated, requiring different strategies and approaches. The whole work was thus divided into separate chapters, each based on the study of one specific aspect of luminescence: Chemiluminescence, Fluorescence and Electrochemiluminescence. CHAPTER 1, Chemiluminescence The work on luminol-enhancer solution lead to a new luminol solution formulation with 1 order of magnitude lower detection limit for HRP. This technology was patented with Cyanagen brand and is now sold worldwide for Western Blot and ELISA applications. CHAPTER 2, Fluorescescence The work on dyed-doped silica nanoparticles is marking a new milestone in the development of nanotechnologies for biological applications. While the project is still in progress, preliminary studies on model structures are leading to very promising results. The improved brightness of these nano-sized objects, their simple synthesis and handling, their low toxicity will soon turn them, we strongly believe, into a new generation of fluorescent labels for many applications. CHAPTER 3, Electrochemiluminescence The work on electrochemiluminescence produced interesting results that can potentially turn into great improvements from an analytical point of view. Ru(bpy)3 derivatives were employed both for on-chip microarray (Chapter 3.1) and for microscopic imaging applications (Chapter 3.2). The development of these new techniques is still under investigation, but the obtained results confirm the possibility to achieve the final goal. Furthermore the development of new ECL-active species (Chapter 3.3, 3.4, 3.5) and their use in these applications can significantly improve overall performances, thus helping to spread ECL as powerful analytical tool for routinary techniques. To conclude, the results obtained are of strong value to largely increase the sensitivity of luminescence techniques, thus fulfilling the expectation we had at the beginning of this research work.

From "wet biology" to statistical analysis of structural features with bioinformatics tools

Many new Escherichia coli outer membrane proteins have recently been identified by proteomics techniques. However, poorly expressed proteins and proteins expressed only under certain conditions may escape detection when wild-type cells are grown under standard conditions. Here, we have taken a complementary approach where candidate outer membrane proteins have been identified by bioinformatics prediction, cloned and overexpressed, and finally localized by cell fractionation experiments. Out of eight predicted outer membrane proteins, we have confirmed the outer membrane localization for five—YftM, YaiO, YfaZ, CsgF, and YliI—and also provide preliminary data indicating that a sixth—YfaL—may be an outer membrane autotransporter.

Enabling computationally intensive bioinformatics applications on the Grid platform

Bioinformatics is a recent and emerging discipline which aims at studying biological problems through computational approaches. Most branches of bioinformatics such as Genomics, Proteomics and Molecular Dynamics are particularly computationally intensive, requiring huge amount of computational resources for running algorithms of everincreasing complexity over data of everincreasing size. In the search for computational power, the EGEE Grid platform, world's largest community of interconnected clusters load balanced as a whole, seems particularly promising and is considered the new hope for satisfying the everincreasing computational requirements of bioinformatics, as well as physics and other computational sciences. The EGEE platform, however, is rather new and not yet free of problems. In addition, specific requirements of bioinformatics need to be addressed in order to use this new platform effectively for bioinformatics tasks. In my three years' Ph.D. work I addressed numerous aspects of this Grid platform, with particular attention to those needed by the bioinformatics domain. I hence created three major frameworks, Vnas, GridDBManager and SETest, plus an additional smaller standalone solution, to enhance the support for bioinformatics applications in the Grid environment and to reduce the effort needed to create new applications, additionally addressing numerous existing Grid issues and performing a series of optimizations. The Vnas framework is an advanced system for the submission and monitoring of Grid jobs that provides an abstraction with reliability over the Grid platform. In addition, Vnas greatly simplifies the development of new Grid applications by providing a callback system to simplify the creation of arbitrarily complex multistage computational pipelines and provides an abstracted virtual sandbox which bypasses Grid limitations. Vnas also reduces the usage of Grid bandwidth and storage resources by transparently detecting equality of virtual sandbox files based on content, across different submissions, even when performed by different users. BGBlast, evolution of the earlier project GridBlast, now provides a Grid Database Manager (GridDBManager) component for managing and automatically updating biological flatfile databases in the Grid environment. GridDBManager sports very novel features such as an adaptive replication algorithm that constantly optimizes the number of replicas of the managed databases in the Grid environment, balancing between response times (performances) and storage costs according to a programmed cost formula. GridDBManager also provides a very optimized automated management for older versions of the databases based on reverse delta files, which reduces the storage costs required to keep such older versions available in the Grid environment by two orders of magnitude. The SETest framework provides a way to the user to test and regressiontest Python applications completely scattered with side effects (this is a common case with Grid computational pipelines), which could not easily be tested using the more standard methods of unit testing or test cases. The technique is based on a new concept of datasets containing invocations and results of filtered calls. The framework hence significantly accelerates the development of new applications and computational pipelines for the Grid environment, and the efforts required for maintenance. An analysis of the impact of these solutions will be provided in this thesis. This Ph.D. work originated various publications in journals and conference proceedings as reported in the Appendix. Also, I orally presented my work at numerous international conferences related to Grid and bioinformatics.

Analytical challenges in the fields of Nanobioscience and Nanobiotecnology: integrated methods for separation and characterization

Nano(bio)science and nano(bio)technology play a growing and tremendous interest both on academic and industrial aspects. They are undergoing rapid developments on many fronts such as genomics, proteomics, system biology, and medical applications. However, the lack of characterization tools for nano(bio)systems is currently considered as a major limiting factor to the final establishment of nano(bio)technologies. Flow Field-Flow Fractionation (FlFFF) is a separation technique that is definitely emerging in the bioanalytical field, and the number of applications on nano(bio)analytes such as high molar-mass proteins and protein complexes, sub-cellular units, viruses, and functionalized nanoparticles is constantly increasing. This can be ascribed to the intrinsic advantages of FlFFF for the separation of nano(bio)analytes. FlFFF is ideally suited to separate particles over a broad size range (1 nm-1 μm) according to their hydrodynamic radius (rh). The fractionation is carried out in an empty channel by a flow stream of a mobile phase of any composition. For these reasons, fractionation is developed without surface interaction of the analyte with packing or gel media, and there is no stationary phase able to induce mechanical or shear stress on nanosized analytes, which are for these reasons kept in their native state. Characterization of nano(bio)analytes is made possible after fractionation by interfacing the FlFFF system with detection techniques for morphological, optical or mass characterization. For instance, FlFFF coupling with multi-angle light scattering (MALS) detection allows for absolute molecular weight and size determination, and mass spectrometry has made FlFFF enter the field of proteomics. Potentialities of FlFFF couplings with multi-detection systems are discussed in the first section of this dissertation. The second and the third sections are dedicated to new methods that have been developed for the analysis and characterization of different samples of interest in the fields of diagnostics, pharmaceutics, and nanomedicine. The second section focuses on biological samples such as protein complexes and protein aggregates. In particular it focuses on FlFFF methods developed to give new insights into: a) chemical composition and morphological features of blood serum lipoprotein classes, b) time-dependent aggregation pattern of the amyloid protein Aβ1-42, and c) aggregation state of antibody therapeutics in their formulation buffers. The third section is dedicated to the analysis and characterization of structured nanoparticles designed for nanomedicine applications. The discussed results indicate that FlFFF with on-line MALS and fluorescence detection (FD) may become the unparallel methodology for the analysis and characterization of new, structured, fluorescent nanomaterials.

Analisi proteomica dei meccanismi sottesi alla malatia da reflusso gastroesofageo

La malattia da reflusso gastroesofageo (GERD) si divide in due categorie: malattia non erosiva (NERD) ed erosiva (ERD). Questi due fenotipi di GERD mostrano caratteristiche patofisiologiche e cliniche differenti. NERD è la forma più comune. Anche se ERD e NERD sono difficili da distinguere a livello clinico, la forma NERD possiede caratteristiche fisiologiche, patofisiologiche, anatomiche, e istologiche uniche. La replicazione cellulare dello strato basale si pensa sia una delle cause implicate nella resistenza della mucosa e nella difesa strutturale dell’epitelio. Diversi studi hanno dimostrato che la proliferazione cellulare è ridotta nella mucosa esofagea esposta ad insulti acidi e peptici cronici, in pazienti GERD, in più uno studio recente ha dimostrato che il recettore per i cannabinoidi CB1 era implicato nella riparazione delle ferite nella mucosa del colon. Sulla base di questi dati abbiamo valutato la presenza del recettore CB1 in biopsie della mucosa esofagea, di pazienti ERD, NERD e di controlli sani, tramite analisi Western Blot, Immunoistochimica e Real-Time PCR, dimostrando per la prima volta la presenza di questo recettore nell’epitelio dell’esofago e una riduzione dei suoi livelli di espressione nei pazienti ERD, camparati con i NERD e con i controlli sani. Successivamente, per chiarire meglio i meccanismi molecolari che caratterizzano ERD e NERD, abbiamo effettuato un analisi proteomica con la tecnica shotgun, la quale ha evidenziato un patter proteico di 33 proteine differenzialmente espresse in pazienti NERD vs ERD, sette delle quali confermate in wester Blot, e quattro in immunoistochimica. Concludendo i nostri risultati hanno confermato che ERD e NERD sono due entità distinte a livello proteico, e hanno proposto dei candidati biomarker per la diagnosi differenziale di ERD e NERD.

Characterization of the Staphylococcus aureus bone sialoprotein-binding protein SdrE and the serine protease EpiP

In an attempt to develop a Staphylococcus aureus vaccine, we have applied reverse vaccinology approach, mainly based on in silico screening and proteomics. By using this approach SdrE, a protein belonging to serine-aspartate repeat protein family was identified as potential vaccine antigen against S. aureus. We have investigated the biochemical properties as well as the vaccine potential of SdrE and its highly conserved CnaBE3 domain. We found the protein SdrE to be resistant to trypsin. Further analysis of the resistant fragment revealed that it comprises a CnaBE3 domain, which also showed partial trypsin resistant behavior. Furthermore, intact mass spectrometry of rCnaBE3 suggested the possible presence of isopeptide bond or some other post-translational modification in the protein.However, this observation needs further investigation. Differential Scanning Fluorimetry study reveals that calcium play role in protein folding and provides stability to SdrE. At the end we have demonstrated that SdrE is immunogenic against clinical strain of S. aureus in murine abscess model. In the second part, I characterized a protein, annotated as epidermin leader peptide processing serine protease (EpiP), as a novel S. aureus vaccine candidate. The crystal structure of the rEpiP was solved at 2.05 Å resolution by x-ray crystallography . The structure showed that rEpiP was cleaved somewhere between residues 95 and 100 and cleavage occurs through an autocatalytic intra-molecular mechanism. In addition, the protein expressed by S. aureus cells also appeared to undergo a similar processing event. To determine if the protein acts as a serine protease, we mutated the catalytic serine 393 residue to alanine, generating rEpiP-S393A and solved its crystal structure at a resolution of 1.95 Å. rEpiP-S393A was impaired in its protease activity, as expected. Protective efficacy of rEpiP and the non-cleaving mutant protein was comparable, implying that the two forms are interchangeable for vaccination purposes.

Development and applications of hollow fiber flow field-flow fractionation in the bioanalytical field. Studies of aggregation phenomena in complex protein samples

Recent advances in the fast growing area of therapeutic/diagnostic proteins and antibodies - novel and highly specific drugs - as well as the progress in the field of functional proteomics regarding the correlation between the aggregation of damaged proteins and (immuno) senescence or aging-related pathologies, underline the need for adequate analytical methods for the detection, separation, characterization and quantification of protein aggregates, regardless of the their origin or formation mechanism. Hollow fiber flow field-flow fractionation (HF5), the miniaturized version of FlowFFF and integral part of the Eclipse DUALTEC FFF separation system, was the focus of this research; this flow-based separation technique proved to be uniquely suited for the hydrodynamic size-based separation of proteins and protein aggregates in a very broad size and molecular weight (MW) range, often present at trace levels. HF5 has shown to be (a) highly selective in terms of protein diffusion coefficients, (b) versatile in terms of bio-compatible carrier solution choice, (c) able to preserve the biophysical properties/molecular conformation of the proteins/protein aggregates and (d) able to discriminate between different types of protein aggregates. Thanks to the miniaturization advantages and the online coupling with highly sensitive detection techniques (UV/Vis, intrinsic fluorescence and multi-angle light scattering), HF5 had very low detection/quantification limits for protein aggregates. Compared to size-exclusion chromatography (SEC), HF5 demonstrated superior selectivity and potential as orthogonal analytical method in the extended characterization assays, often required by therapeutic protein formulations. In addition, the developed HF5 methods have proven to be rapid, highly selective, sensitive and repeatable. HF5 was ideally suitable as first dimension of separation of aging-related protein aggregates from whole cell lysates (proteome pre-fractionation method) and, by HF5-(UV)-MALS online coupling, important biophysical information on the fractionated proteins and protein aggregates was gathered: size (rms radius and hydrodynamic radius), absolute MW and conformation.

Genomic and proteomic approaches in pig meat quality research field

Pig meat and carcass quality is a complex concept determined by environmental and genetic factors concurring to the phenotypic variation in qualitative characteristics of meat (fat content, tenderness, juiciness, flavor,etc). This thesis shows the results of different investigations to study and to analyze pig meat and carcass quality focusing mainly on genomic; moreover proteomic approach has been also used. The aim was to analyze data from association studies between genes considered as candidate and meat and carcass quality in different pig breeds. The approach was used to detect new SNP in genes functionally associated to the studied traits and to confirm as candidate other genes already known. Five polymorphisms (one new SNP in Calponin 1 gene and four additional polymorphism already known in other genes) were considered on chromosome 2 (SSC2). Calponin 1 (CNN1) was associated to the studied traits and furthermore the results reported confirmed the data already known for Lactate dehydrogenase A (LDHA), Low density lipoprotein receptor (LDLR), Myogenic differentiation 1 (MYOD1) e Ubiquitin-like 5 (UBL5), in Italian Large White pigs. Using an in silico search it was possible to detect on SSC2 a new SNP of Deoxyhypusine synthase (DHPS) gene partially overlapping with WD repeat domain 83 (WDR83) gene and significant for the meat pH variation in Italian Large White (ILW) pigs. Perilipin 1 (PLIN1) mapping on chromosome 7 and Perilipin 2 (PLIN2) mapping on chromosome 1 were studied and the results obtained in Duroc breed have shown significant associations with carcass traits. Moreover a study of protein composition of porcine LD muscle, indicated an effect of temperature treatment of carcass, on proteins of the sarcoplasmic fraction and in particular on PGM1 phosphorylation. Future studies on pig meat quality should be based on the integration of different experimental approaches (genomics, proteomics, transcriptomics, etc).