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.

Mitochondrial Genomics: structure, inheritance and phylogenetic utility of the Mitochondrial genome in Bivalvia and Insecta

This PhD Thesis is the result of my research activity in the last three years. My main research interest was centered on the evolution of mitochondrial genome (mtDNA), and on its usefulness as a phylogeographic and phylogenetic marker at different taxonomic levels in different taxa of Metazoa. From a methodological standpoint, my main effort was dedicated to the sequencing of complete mitochondrial genomes, and the approach to whole-genome sequencing was based on the application of Long-PCR and shotgun sequences. Moreover, this research project is a part of a bigger sequencing project of mtDNAs in many different Metazoans’ taxa, and I mostly dedicated myself to sequence and analyze mtDNAs in selected taxa of bivalves and hexapods (Insecta). Sequences of bivalve mtDNAs are particularly limited, and my study contributed to extend the sampling. Moreover, I used the bivalve Musculista senhousia as model taxon to investigate the molecular mechanisms and the evolutionary significance of their aberrant mode of mitochondrial inheritance (Doubly Uniparental Inheritance, see below). In Insects, I focused my attention on the Genus Bacillus (Insecta Phasmida). A detailed phylogenetic analysis was performed in order to assess phylogenetic relationships within the genus, and to investigate the placement of Phasmida in the phylogenetic tree of Insecta. The main goal of this part of my study was to add to the taxonomic coverage of sequenced mtDNAs in basal insects, which were only partially analyzed.

Functional Genomics and Cell Biology of the Dolphin (Tursiops runcatus): Establishment of Novel Molecular Tools to Study Marine Mammals in Changing Environments

The dolphin (Tursiops truncatus) is a mammal that is adapted to life in a totally aquatic environment. Despite the popularity and even iconic status of the dolphin, our knowledge of its physiology, its unique adaptations and the effects on it of environmental stressors are limited. One approach to improve this limited understanding is the implementation of established cellular and molecular methods to provide sensitive and insightful information for dolphin biology. We initiated our studies with the analysis of wild dolphin peripheral blood leukocytes, which have the potential to be informative of the animal’s global immune status. Transcriptomic profiles from almost 200 individual samples were analyzed using a newly developed species-specific microarray to assess its value as a prognostic and diagnostic tool. Functional genomics analyses were informative of stress-induced gene expression profiles and also of geographical location specific transcriptomic signatures, determined by the interaction of genetic, disease and environmental factors. We have developed quantitative metrics to unambiguously characterize the phenotypic properties of dolphin cells in culture. These quantitative metrics can provide identifiable characteristics and baseline data which will enable identification of changes in the cells due to time in culture. We have also developed a novel protocol to isolate primary cultures from cryopreserved tissue of stranded marine mammals, establishing a tissue (and cell) biorepository, a new approach that can provide a solution to the limited availability of samples. The work presented represents the development and application of tools for the study of the biology, health and physiology of the dolphin, and establishes their relevance for future studies of the impact on the dolphin of environmental infection and stress.

Metaheuristics for Search Problems in Genomics - New Algorithms and Applications

In this thesis we made the first steps towards the systematic application of a methodology for automatically building formal models of complex biological systems. Such a methodology could be useful also to design artificial systems possessing desirable properties such as robustness and evolvability. The approach we follow in this thesis is to manipulate formal models by means of adaptive search methods called metaheuristics. In the first part of the thesis we develop state-of-the-art hybrid metaheuristic algorithms to tackle two important problems in genomics, namely, the Haplotype Inference by parsimony and the Founder Sequence Reconstruction Problem. We compare our algorithms with other effective techniques in the literature, we show strength and limitations of our approaches to various problem formulations and, finally, we propose further enhancements that could possibly improve the performance of our algorithms and widen their applicability. In the second part, we concentrate on Boolean network (BN) models of gene regulatory networks (GRNs). We detail our automatic design methodology and apply it to four use cases which correspond to different design criteria and address some limitations of GRN modeling by BNs. Finally, we tackle the Density Classification Problem with the aim of showing the learning capabilities of BNs. Experimental evaluation of this methodology shows its efficacy in producing network that meet our design criteria. Our results, coherently to what has been found in other works, also suggest that networks manipulated by a search process exhibit a mixture of characteristics typical of different dynamical regimes.

Ecological genetics and conservation genomics of wolf (Canis lupus)

In the present work, we apply both traditional and Next Generation Sequencing (NGS) tools to investigate some of the most important adaptive traits of wolves (Canis lupus). In the first part, we analyze the variability of three Major Histocompatibility Complex (MHC) class II genes in the Italian wolf population, also studying their possible role in mating choice and their influence on fitness traits. In the second section, as part of a larger canid genome project, we will exploit NGS data to investigate the transcript-level differences between the wolf and the dog genome that can be correlated to domestication.

Trascriptome analysis and functional genomics of Neisseria meningitidis in human blood

Neisseria meningitidis (Nm) is the major cause of septicemia and meningococcal meningitis. During the course of infection, it must adapt to different host environments as a crucial factor for survival. Despite the severity of meningococcal sepsis, little is known about how Nm adapts to permit survival and growth in human blood. A previous time-course transcriptome analysis, using an ex vivo model of human whole blood infection, showed that Nm alters the expression of nearly 30% of ORFs of the genome: major dynamic changes were observed in the expression of transcriptional regulators, transport and binding proteins, energy metabolism, and surface-exposed virulence factors. Starting from these data, mutagenesis studies of a subset of up-regulated genes were performed and the mutants were tested for the ability to survive in human whole blood; Nm mutant strains lacking the genes encoding NMB1483, NalP, Mip, NspA, Fur, TbpB, and LctP were sensitive to killing by human blood. Then, the analysis was extended to the whole Nm transcriptome in human blood, using a customized 60-mer oligonucleotide tiling microarray. The application of specifically developed software combined with this new tiling array allowed the identification of different types of regulated transcripts: small intergenic RNAs, antisense RNAs, 5’ and 3’ untranslated regions and operons. The expression of these RNA molecules was confirmed by 5’-3’RACE protocol and specific RT-PCR. Here we describe the complete transcriptome of Nm during incubation in human blood; we were able to identify new proteins important for survival in human blood and also to identify additional roles of previously known virulence factors in aiding survival in blood. In addition the tiling array analysis demonstrated that Nm expresses a set of new transcripts, not previously identified, and suggests the presence of a circuit of regulatory RNA elements used by Nm to adapt to proliferate in human blood.

Wide-scale population genomics of Atlantic bluefin tuna (Thunnus thynnus) inferred by novel high-throughput technology

My PhD project was focused on Atlantic bluefin tuna, Thunnus thynnus, a fishery resource overexploited in the last decades. For a better management of stocks, it was necessary to improve scientific knowledge of this species and to develop novel tools to avoid collapse of this important commercial resource. To do this, we used new high throughput sequencing technologies, as Next Generation Sequencing (NGS), and markers linked to expressed genes, as SNPs (Single Nucleotide Polymorphisms). In this work we applied a combined approach: transcriptomic resources were used to build cDNA libreries from mRNA isolated by muscle, and genomic resources allowed to create a reference backbone for this species lacking of reference genome. All cDNA reads, obtained from mRNA, were mapped against this genome and, employing several bioinformatics tools and different restricted parameters, we achieved a set of contigs to detect SNPs. Once a final panel of 384 SNPs was developed, following the selection criteria, it was genotyped in 960 individuals of Atlantic bluefin tuna, including all size/age classes, from larvae to adults, collected from the entire range of the species. The analysis of obtained data was aimed to evaluate the genetic diversity and the population structure of Thunnus thynnus. We detect a low but significant signal of genetic differentiation among spawning samples, that can suggest the presence of three genetically separate reproduction areas. The adult samples resulted instead genetically undifferentiated between them and from the spawning populations, indicating a presence of panmictic population of adult bluefin tuna in the Mediterranean Sea, without different meta populations.

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.

Bioinformatic methods in applied genomic research

Here I will focus on three main topics that best address and include the projects I have been working in during my three year PhD period that I have spent in different research laboratories addressing both computationally and practically important problems all related to modern molecular genomics. The first topic is the use of livestock species (pigs) as a model of obesity, a complex human dysfunction. My efforts here concern the detection and annotation of Single Nucleotide Polymorphisms. I developed a pipeline for mining human and porcine sequences. Starting from a set of human genes related with obesity the platform returns a list of annotated porcine SNPs extracted from a new set of potential obesity-genes. 565 of these SNPs were analyzed on an Illumina chip to test the involvement in obesity on a population composed by more than 500 pigs. Results will be discussed. All the computational analysis and experiments were done in collaboration with the Biocomputing group and Dr.Luca Fontanesi, respectively, under the direction of prof. Rita Casadio at the Bologna University, Italy. The second topic concerns developing a methodology, based on Factor Analysis, to simultaneously mine information from different levels of biological organization. With specific test cases we develop models of the complexity of the mRNA-miRNA molecular interaction in brain tumors measured indirectly by microarray and quantitative PCR. This work was done under the supervision of Prof. Christine Nardini, at the “CAS-MPG Partner Institute for Computational Biology” of Shangai, China (co-founded by the Max Planck Society and the Chinese Academy of Sciences jointly) The third topic concerns the development of a new method to overcome the variety of PCR technologies routinely adopted to characterize unknown flanking DNA regions of a viral integration locus of the human genome after clinical gene therapy. This new method is entirely based on next generation sequencing and it reduces the time required to detect insertion sites, decreasing the complexity of the procedure. This work was done in collaboration with the group of Dr. Manfred Schmidt at the Nationales Centrum für Tumorerkrankungen (Heidelberg, Germany) supervised by Dr. Annette Deichmann and Dr. Ali Nowrouzi. Furthermore I add as an Appendix the description of a R package for gene network reconstruction that I helped to develop for scientific usage (http://www.bioconductor.org/help/bioc-views/release/bioc/html/BUS.html).

Transposable elements dynamics in taxa with different reproductive strategies or speciation rate

In recent years the advances in genomics allowed to understand the importance of Transposable Elements (TE) in the evolution of eukaryotic genomes. In this thesis I face two aspects of the TE impact on the in the animal kingdom. The first part is a comparison of the dynamics of the TE dynamics in three species of stick-insects of the Genus Bacillus. I produced three random genomic libraries of 200 Kbps for the three parental species of the taxon: a gonochoric population of Bacillus rossius (facultative parthenogenetic), Bacillus grandii (gonochoric) and Bacillus atticus (obligate parthenogenetic). The unisexual taxon Bacillus atticus does not shows dramatic differences in TE total content and activity with respect to Bacillus grandii and Bacillus rossius. This datum does not confirm the trend observed in other animal models in which unisexual taxa tend to repress the activity of TE to escape the extinction by accumulation of harmful mutations. In the second part I tried to add a contribute to the debate initiated in recent years about the possibility that a high TE content is linked to a high rate of speciation. I designed an evolutionary framework to establish the different rate of speciation among two or more taxa, then I compared TE dynamics considering the different rates of speciation. The species dataset comprises: 29 mammals, four birds, two fish and two insects. On the whole the majority of comparisons confirms the expected trend. In particular the amount of species analyzed in Mammalia allowed me to get a statistical support (p<0,05) of the fact that the TE activity of recently mobilized elements is positively related with the rate of speciation.

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).