Heat and water stress induce unique transcriptional signatures of heat-shock proteins and transcription factors in grapevine

Grapevine is an extremely important crop worldwide.In southern Europe, post-flowering phases of the growth cycle can occur under high temperatures, excessive light, and drought conditions at soil and/or atmospheric level. In this study, we subjected greenhouse grown grapevine, variety Aragonez, to two individual abiotic stresses, water deficit stress(WDS), and heat stress (HS). The adaptation of plants to stress is a complex response triggered by cascades of molecular net works involved in stress perception, signal transduction, and the expression of specific stress-related genes and metabolites. Approaches such as array-based transcript profiling allow assessing the expression of thousands of genes in control and stress tissues. Using microarrays, we analyzed the leaf transcriptomic profile of the grapevine plants. Photosynthesis measurements verified that the plants were significantly affected by the stresses applied. Leaf gene expression was obtained using a high-throughput transcriptomic grapevine array, the 23K custom-made Affymetrix Vitis GeneChip. We identified 1,594 genes as differentially expressed between control and treatments and grouped them into ten major functional categories using MapMan software. The transcriptome of Aragonez was more significantly affected by HS when compared with WDS. The number of genes coding for heat-shock proteins and transcription factors expressed solely in response to HS suggesting their expression as unique signatures of HS. However, across-talk between the response pathways to both stresses was observed at the level of AP2/ERF transcription factors.

Antibiotic resistance in the gut microbiota

Antibiotic resistance is an increasing threat to our ability to treat infectious diseases. Thus, understanding the effects of antibiotics on the gut microbiota, as well as the potential for such populations to act as a reservoir for resistance genes, is imperative. This thesis set out to investigate the gut microbiota of antibiotic treated infants compared to untreated controls using high-throughput DNA sequencing. The results demonstrated the significant effects of antibiotic treatment, resulting in increased proportions of Proteobacteria and decreased proportions of Bifidobacterium. The species diversity of bifidobacteria was also reduced. This thesis also highlights the ability of the human gut microbiota to act as an antibiotic resistance reservoir. Using metagenomic DNA extracted from faecal samples from adult males, PCR was employed to demonstrate the prevalence and diversity of aminoglycoside and β-lactam resistance genes in the adult gut microbiota and highlighted the merits of the approach adopted. Using infant faecal samples, we constructed and screened a second fosmid metagenomic bank for the same families of resistance genes and demonstrated that the infant gut microbiota is also a reservoir for resistance genes. Using in silico analysis we highlighted the existence of putative aminoglycoside and β-lactam resistance determinants within the genomes of Bifidobacterium species. In the case of the β- lactamases, these appear to be mis-annotated. However, through homologous recombination-mediated insertional inactivation, we have demonstrated that the putative aminoglycoside resistance proteins do contribute to resistance. In additional studies, we investigated the effects of short bowel syndrome on infant gut microbiota, the immune system and bile acid metabolism. We also sequenced the microbiota of the human vermiform appendix, highlighting its complexity. Finally, this thesis demonstrated the strain specific nature of 2 different probiotic CLA-producing Bifidobacterium breve on the murine gut microbiota.

Development of a novel molecular tool for the rapid assessment of the biodiversity changes of benthic nematodes assemblages. Mares Conference Marine Ecosystems Helath and conservation

The molecular profiling system was developed using directed terminal-restriction fragment length polymorphism (dT-RFLP) to characterize soil nematode assemblages by relative abundance of feeding guilds and validation by comparison to traditional morphological method. The good performance of these molecular tools applied to soil nematodes assemblages create an opportunity to develop a novel approach for rapid assessment of the biodiversity changes of benthic nematodes assemblages of marine and estuarine sediments. The main aim of this research is to combine morphological and molecular analysis of estuarine nematodes assemblages, to establish a tool for fast assessment of the biodiversity changes within habitat recovery of Zostera noltii seagrass beds; and validate the dT-RFLP as a high-throughput tool to assess the system recovery. It was also proposed to develop a database of sequences related to individuals identified at species level to develop a new taxonomic reference system. A molecular phylogenetic analysis of the estuarine nematodes has being performed. After morphological identification, barcoding of 18S rDNA are being determined for each nematode species and the results have shown a good degree of concordance between traditional morphology-based identification and DNA sequences. The digest strategy developed for soil nematodes is not suitable for marine nematodes. Then five samples were cloned and sequenced and the sequence data was used to design a new dT-RFLP strategy to adapt this tool to marine assemblages. Several solutions were presented by DRAT and tested empirically to select the solution that cuts most efficiently, separating the different clusters. The results of quantitative PCR showed differences in nematode density between two sampling stations according the abundance of the nematode density obtained by the traditional methods. These results suggest that qPCR could be a robust tool for enumeration of nematode abundance, saving time.

Development of molecular approaches to assess the diversity and abundance of marine nematodes assemblages for assessment of Good Environmental Status of the estuarine and marine ecosystems

In Europe, the concerns with the status of marine ecosystems have increased, and the Marine Directive has as main goal the achievement of Good Environmental Status (GES) of EU marine waters by 2020. Molecular tools are seen as promising and emerging approaches to improve ecosystem monitoring, and have led ecology into a new era, representing perhaps the most source of innovation in marine monitoring techniques. Benthic nematodes are considered ideal organisms to be used as biological indicator of natural and anthropogenic disturbances in aquatic ecosystems underpinning monitoring programmes on the ecological quality of marine ecosystems, very useful to assess the GES of the marine environment. dT-RFLP (directed Terminal-Restriction Fragment Length Polymorphism) allows to assess the diversity of nematode communities, but also allows studying the functioning of the ecosystem, and combined with relative real-time PCR (qPCR), provides a high-throughput semi-quantitative characterization of nematode communities. These characteristics make the two molecular tools good descriptors for the good environmental status assessment. The main aim of this study is to develop and optimize the dT-RFLP and qPCR in Mira estuary (SW coast, Portugal). A molecular phylogenetic analysis of marine and estuarine nematodes is being performed combining morphological and molecular analysis to evaluate the diversity of free-living marine nematodes in Mira estuary. After morphological identification, barcoding of 18S rDNA and COI genes are being determined for each nematode species morphologically identified. So far we generated 40 new sequences belonging to 32 different genus and 17 families, and the study has shown a good degree of concordance between traditional morphology-based identification and DNA sequences. These results will improve the assessment of marine nematode diversity and contribute to a more robust nematode taxonomy. The DNA sequences are being used to develop the dT-RFLP with the ability to easily process large sample numbers (hundreds and thousands), rather than typical of classical taxonomic or low throughput molecular analyses. A preliminary study showed that the digest enzymes used in dT-RFLP for terrestrial assemblages separated poorly the marine nematodes at taxonomic level for functional group analysis. A new digest combination was designed using the software tool DRAT (Directed Terminal Restriction Analysis Tool) to distinguished marine nematode taxa. Several solutions were provided by DRAT and tested empirically to select the solution that cuts most efficiently. A combination of three enzymes and a single digest showed to be the best solution to separate the different clusters. Parallel to this, another tool is being developed to estimate the population size (qPCR). An improvement in qPCR estimation of gene copy number using an artificial reference is being performed for marine nematodes communities to quantify the abundance. Once developed, it is proposed to validate both methodologies by determining the spatial and temporal variability of benthic nematodes assemblages across different environments. The application of these high-throughput molecular approaches for benthic nematodes will improve sample throughput and their implementation more efficient and faster as indicator of ecological status of marine ecosystems.

Dissecting the Heat-Stress Tolerance QTLome in Durum Wheat

Heat stress negatively affects wheat performance during its entire cycle, particularly during the reproductive stage. In view of the climate change and the prediction of a continued increase in temperature in the new future, it is urgent to concentrate efforts to discover novel genetic sources able to improve the resilience of wheat to heat stress. In this direction, this study addressed two different experiments in durum wheat to identify novel QTLs suitable to be applied in marker-assisted selection for heat tolerance. Chlorophyll fluorescence (ChlF) is a valuable indicator of plant response to environmental changes allowing a detailed assessment of PSII activity in view of its non-invasive measurement and high-throughput phenotyping. In the first study (Chapter 2), the Light-Induced Fluorescence Transient (LIFT) method was used to access ChlF data to map QTLs for ChlF-related traits during the vegetative growth stage in durum wheat under heat stress condition. Our results provide evidence that LIFT consistently measures ChlF at the level of high-throughput phenotyping combined with high accuracy which is required for Genome-Wide Association Study (GWAS) aimed at identifying genomic regions affecting PSII activity. The 50 QTLs identified for ChlF-related traits under heat stress mostly clustered into five chromosomes hotspots unrelated to phenology, a feature that makes these QTLs a valuable asset for marker-assisted breeding programs across different latitudes. In the second study (Chapter 3), a set of 183 accessions suitable for GWAS, was exposed to optimal and high temperature during two crop seasons under field conditions. Important agronomic traits were evaluated in order to identify valuable QTLs for GY and its components. The GWAS analysis identified several QTLs in the single years as well as in the joint analysis. From the total QTLs identified, 13 QTL clusters can be highlighted to be affecting heat tolerance across different years and/or different traits.

Non-Equilibrium Atmospheric Plasma As A Novel Route To Nanomaterial Synthesis And Processing For Biomedical Applications

Since last century, the rising interest of value-added and advanced functional materials has spurred a ceaseless development in terms of industrial processes and applications. Among the emerging technologies, thanks to their unique features and versatility in terms of supported processes, non-equilibrium plasma discharges appear as a key solvent-free, high-throughput and cost-efficient technique. Nevertheless, applied research studies are needed with the aim of addressing plasma potentialities optimizing devices and processes for future industrial applications. In this framework, the aim of this dissertation is to report on the activities carried out and the results achieved concerning the development and optimization of plasma techniques for nanomaterial synthesis and processing to be applied in the biomedical field. In the first section, the design and investigation of a plasma assisted process for the production of silver (Ag) nanostructured multilayer coatings exhibiting anti-biofilm and anti-clot properties is described. With the aim on enabling in-situ and on-demand deposition of Ag nanoparticles (NPs), the optimization of a continuous in-flight aerosol process for particle synthesis is reported. The stability and promising biological performances of deposited coatings spurred further investigation through in-vitro and in-vivo tests which results are reported and discussed. With the aim of addressing the unanswered questions and tuning NPs functionalities, the second section concerns the study of silver containing droplet conversion in a flow-through plasma reactor. The presented results, obtained combining different analysis techniques, support a formation mechanism based on droplet to particle conversion driven by plasma induced precursor reduction. Finally, the third section deals with the development of a simulative and experimental approach used to investigate the in-situ droplet evaporation inside the plasma discharge addressing the main contributions to liquid evaporation in the perspective of process industrial scale up.

Computational resources for structural and metagenomic characterization of functions in bacteria and bacterial communities. Antimicrobial resistance, pathways for xenobiotic degradation and relationship between gut microbiome and ageing.

Prokaryotic organisms are one of the most successful forms of life, they are present in all known ecosystems. The deluge diversity of bacteria reflects their ability to colonise every environment. Also, human beings host trillions of microorganisms in their body districts, including skin, mucosae, and gut. This symbiosis is active for all other terrestrial and marine animals, as well as plants. With the term holobiont we refer, with a single word, to the systems including both the host and its symbiotic microbial species. The coevolution of bacteria within their ecological niches reflects the adaptation of both host and guest species, and it is shaped by complex interactions that are pivotal for determining the host state. Nowadays, thanks to the current sequencing technologies, Next Generation Sequencing, we have unprecedented tools for investigating the bacterial life by studying the prokaryotic genome sequences. NGS revolution has been sustained by the advancements in computational performance, in terms of speed, storage capacity, algorithm development and hardware costs decreasing following the Moore’s Law. Bioinformaticians and computational biologists design and implement ad hoc tools able to analyse high-throughput data and extract valuable biological information. Metagenomics requires the integration of life and computational sciences and it is uncovering the deluge diversity of the bacterial world. The present thesis work focuses mainly on the analysis of prokaryotic genomes under different aspects. Being supervised by two groups at the University of Bologna, the Biocomputing group and the group of Microbial Ecology of Health, I investigated three different topics: i) antimicrobial resistance, particularly with respect to missense point mutations involved in the resistant phenotype, ii) bacterial mechanisms involved in xenobiotic degradation via the computational analysis of metagenomic samples, and iii) the variation of the human gut microbiota through ageing, in elderly and longevous individuals.

Tumor heterogeneity in Esophageal Adenocarcinoma: a genomic approach

INTRODUCTION: Esophageal adenocarcinoma (EAC) is a severe malignancy in terms of prognosis and mortality rate. Because its great genetic heterogeneity, disputes regarding classification, prevention and treatments are still unsolved. AIM: We investigated intra- and inter-EAC heterogeneity by defining EAC’s somatic mutational profile and the role of candidate microRNAs, to correlate the molecular profile of tumors to clinical outcomes and to identify biomarkers for classification. METHODS: 38 EAC cases were analyzed via high-throughput cell sorting technology combined with targeted sequencing and whole genome low-pass sequencing. Targeted sequencing of further 169 cases was performed to widen the study. miR221 and miR483-3p expression was profiled via qPCR in 112 EACs and correlation with clinical outcomes was investigated. RESULTS: 35/38 EACs carried at least one somatic mutation absent in stromal cells. TP53 was found mutated in 73.7% of cases. Selective sorting revealed tumor subclones with different mutational loads and copy number alterations, confirming the high intra-tumor heterogeneity of EAC. Mutations were in most cases at homozygous state, and we identified alterations that were missed with the whole-tumor analysis. Mutations in HNF1A gene, not previously associated with EAC, were identified in both cohorts. Higher expression of miR483-3p and miR221 was associated with poorer cancer specific survival (P=0.0293 and P=0.0059), and recurrence in the Lauren intestinal subtype (P=0.0459 and P=0.0002). Median expression levels of miRNAs were higher in patients with advanced tumor stages. The loss of SMAD4 immunoreactivity was significantly associated with poorer cancer specific survival and recurrence (P=0.0452; P=0.022 respectively). CONCLUSION: Combining selective sorting technology and next generation sequencing allowed to better define EAC inter- and intra-tumor heterogeneity. We identified HNF1A as a new mutated gene associated to EAC that could be involved in tumor progression and promising biomarkers such as SMAD4, miR221 and miR483-3p to identify patients at higher risk for more aggressive tumors.

Whole Exome Sequencing widens the genetic landscape of Hereditary Optic Neuropathies

Hereditary optic neuropathies (HON) are a genetic cause of visual impairment characterized by degeneration of retinal ganglion cells. The majority of HON are caused by pathogenic variants in mtDNA genes and in gene OPA1. However, several other genes can cause optic atrophy and can only be identified by high throughput genetic analysis. Whole Exome Sequencing (WES) is becoming the primary choice in rare disease molecular diagnosis, being both cost effective and informative. We performed WES on a cohort of 106 cases, of which 74 isolated ON patients (ON) and 32 syndromic ON patients (sON). The total diagnostic yield amounts to 27%, slightly higher for syndromic ON (31%) than for isolated ON (26%). The majority of genes found are related to mitochondrial function and already reported for harbouring HON pathogenic variants: ACO2, AFG3L2, C19orf12, DNAJC30, FDXR, MECR, MTFMT, NDUFAF2, NDUFB11, NDUFV2, OPA1, PDSS1, SDHA, SSBP1, and WFS1. Among these OPA1, ACO2, and WFS1 were confirmed as the most relevant genetic causes of ON. Moreover, several genes were identified, especially in sON patients, with direct impairment of non-mitochondrial molecular pathways: from autophagy and ubiquitin system (LYST, SNF8, WDR45, UCHL1), to neural cells development and function (KIF1A, GFAP, EPHB2, CACNA1A, CACNA1F), but also vitamin metabolism (SLC52A2, BTD), cilia structure (USH2A), and nuclear pore shuttling (NUTF2). Functional validation on yeast model was performed for pathogenic variants detected in MECR, MTFMT, SDHA, and UCHL1 genes. For SDHA and UCHL1 also muscle biopsy and fibroblast cell lines from patients were analysed, pointing to possible pathogenic mechanisms that will be investigated in further studies. In conclusion, WES proved to be an efficient tool when applied to our ON cohort, for both common disease-genes identification and novel genes discovery. It is therefore recommended to consider WES in ON molecular diagnostic pipeline, as for other rare genetic diseases.

Applications of network-based approaches in drug research

Recent research trends in computer-aided drug design have shown an increasing interest towards the implementation of advanced approaches able to deal with large amount of data. This demand arose from the awareness of the complexity of biological systems and from the availability of data provided by high-throughput technologies. As a consequence, drug research has embraced this paradigm shift exploiting approaches such as that based on networks. Indeed, the process of drug discovery can benefit from the implementation of network-based methods at different steps from target identification to drug repurposing. From this broad range of opportunities, this thesis is focused on three main topics: (i) chemical space networks (CSNs), which are designed to represent and characterize bioactive compound data sets; (ii) drug-target interactions (DTIs) prediction through a network-based algorithm that predicts missing links; (iii) COVID-19 drug research which was explored implementing COVIDrugNet, a network-based tool for COVID-19 related drugs. The main highlight emerged from this thesis is that network-based approaches can be considered useful methodologies to tackle different issues in drug research. In detail, CSNs are valuable coordinate-free, graphically accessible representations of structure-activity relationships of bioactive compounds data sets especially for medium-large libraries of molecules. DTIs prediction through the random walk with restart algorithm on heterogeneous networks can be a helpful method for target identification. COVIDrugNet is an example of the usefulness of network-based approaches for studying drugs related to a specific condition, i.e., COVID-19, and the same ‘systems-based’ approaches can be used for other diseases. To conclude, network-based tools are proving to be suitable in many applications in drug research and provide the opportunity to model and analyze diverse drug-related data sets, even large ones, also integrating different multi-domain information.

Development of advanced analytical methodologies for Alzheimer’s disease drug discovery

Advanced analytical methodologies were developed to characterize new potential active MTDLs on isolated targets involved in the first stages of Alzheimer’s disease (AD). In addition, the methods investigated drug-protein bindings and evaluated protein-protein interactions involved in the neurodegeneration. A high-throughput luminescent assay allowed the study of the first in class GSK-3β/ HDAC dual inhibitors towards the enzyme GSK-3β. The method was able to identify an innovative disease-modifying agent with an activity in the micromolar range both on GSK-3β, HDAC1 and HDAC6. Then, the same assay reliably and quickly selected true positive hit compounds among natural Amaryllidaceae alkaloids tested against GSK-3β. Hence, given the central role of the amyloid pathway in the multifactorial nature of AD, a multi-methodological approach based on mass spectrometry (MS), circular dichroism spectroscopy (CD) and ThT assay was applied to characterize the potential interaction of CO releasing molecules (CORMs) with Aβ1-42 peptide. The comprehensive method provided reliable information on the different steps of the fibrillation process and regarding CORMs mechanism of action. Therefore, the optimal CORM-3/Aβ1−42 ratio in terms of inhibitory effect was identified by mass spectrometry. CD analysis confirmed the stabilizing effect of CORM-3 on the Aβ1−42 peptide soluble form and the ThT Fluorescent Analysis ensured that the entire fibrillation process was delayed. Then the amyloid aggregation process was studied in view of a possible correlation with AD lipid brain alterations. Therefore, SH-SY5Y cells were treated with increasing concentration of Aß1-42 at different times and the samples were analysed by a RP-UHPLC system coupled with a high-resolution quadrupole TOF mass spectrometer in comprehensive data-independent SWATH acquisition mode. Each lipid class profiling in SH-SY5Y cells treated with Aß1-42 was compared to the one obtained from the untreated. The approach underlined some peculiar lipid alterations, suitable as biomarkers, that might be correlated to Aß1-42 different aggregation species.

Identification of outcome-oriented cut-offs for copy number alterations in multiple myeloma: predictive biomarkers with improved prognostic accuracy

Aim of the present study was to develop a statistical approach to define the best cut-off Copy number alterations (CNAs) calling from genomic data provided by high throughput experiments, able to predict a specific clinical end-point (early relapse, 18 months) in the context of Multiple Myeloma (MM). 743 newly diagnosed MM patients with SNPs array-derived genomic and clinical data were included in the study. CNAs were called both by a conventional (classic, CL) and an outcome-oriented (OO) method, and Progression Free Survival (PFS) hazard ratios of CNAs called by the two approaches were compared. The OO approach successfully identified patients at higher risk of relapse and the univariate survival analysis showed stronger prognostic effects for OO-defined high-risk alterations, as compared to that defined by CL approach, statistically significant for 12 CNAs. Overall, 155/743 patients relapsed within 18 months from the therapy start. A small number of OO-defined CNAs were significantly recurrent in early-relapsed patients (ER-CNAs) - amp1q, amp2p, del2p, del12p, del17p, del19p -. Two groups of patients were identified either carrying or not ≥1 ER-CNAs (249 vs. 494, respectively), the first one with significantly shorter PFS and overall survivals (OS) (PFS HR 2.15, p<0001; OS HR 2.37, p<0.0001). The risk of relapse defined by the presence of ≥1 ER-CNAs was independent from those conferred both by R-IIS 3 (HR=1.51; p=0.01) and by low quality (< stable disease) clinical response (HR=2.59 p=0.004). Notably, the type of induction therapy was not descriptive, suggesting that ER is strongly related to patients’ baseline genomic architecture. In conclusion, the OO- approach employed allowed to define CNAs-specific dynamic clonality cut-offs, improving the CNAs calls’ accuracy to identify MM patients with the highest probability to ER. As being outcome-dependent, the OO-approach is dynamic and might be adjusted according to the selected outcome variable of interest.

Pré-regulador retificador boost com controle digital por valores médios, para sistema de iluminação fluorescente multi-lâmpadas, utilizando dispositivo FPGA e VHDL

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Pré-regulador retificador entrelaçado (Interleaved) ZCS-FM boost, com controle digital através de dispositivo FPGA e linguagem VHDL

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)