Photoactive nanodevices for potential biological applications

Biological systems are complex and highly organized architectures governed by noncovalent interactions, which are responsible for molecular recognition, self-assembly, self-organization, adaptation and evolution processes. These systems provided the inspiration for the development of supramolecular chemistry, that aimed at the design of artificial multicomponent molecular assemblies, namely supramolecular systems, properly designed to perform different operations: each constituting unit performs a single act, whereas the entire supramolecular system is able to execute a more complex function, resulting from the cooperation of the constituting components. Supramolecular chemistry deals with the development of molecular systems able to mimic naturally occurring events, for example complexation and self-assembly through the establishment of noncovalent interactions. Moreover, the application of external stimuli, such as light, allows to perform these operations in a time- and space-controlled manner. These systems can interact with biological systems and, thus, can be applied for bioimaging, therapeutic and drug delivery purposes. In this work the study of biocompatible supramolecular species able to interact with light is presented. The first part deals with the photophysical, photochemical and electrochemical characterization of water-soluble blue emitting triazoloquinolinium and triazolopyridinium salts. Moreover, their interaction with DNA has been explored, in the perspective of developing water-soluble systems for bioimaging applications. In the second part, the effect exerted by the presence of azobenzene-bearing supramolecular species in liposomes, inserted both in the phospholipid bilayer and in the in the aqueous core of vesicles has been studied, in order to develop systems able to deliver small molecules and ions in a photocontrolled manner. Moreover, the versatility of azobenzene and its broad range of applications have been highlighted, since conjugated oligoazobenzene derivatives proved not to be adequate to be inserted in the phospholipid bilayer of liposomes, but their electrochemical properties made them interesting candidates as electron acceptor materials for photovoltaic applications.

Relationships between airborne pollen allergens and environmental factors.

This thesis is a collection of scientific papers resulting from my research activity during the PhD course in Earth, Life, and Environmental Sciences. The main subject of the thesis is the capability of pollen to trigger a hypersensitive reaction in different environmental conditions, and the need to better characterise such allergenicity in order to measure it. This topic is discussed from different perspectives, using ecological, morphological, and molecular approaches. The thesis starts by summarising the importance of green infrastructures in the cities, from economical and conservational perspectives. It then focalises on the lesser-known ecosystem disservices urban vegetation can provide, and in particular on pollen allergy, exploring its causes and illustrating possible ways to monitor, foresee, and mitigate the allergenic risk. The possibility to monitor the allergenicity of urban green areas is then examined in depth, with an original research paper that proposes a method standardisation for existing allergenicity indices (Specific Allergenic Index and Urban Green Zones Allergenicty Index), and compares the indices results to evaluate their effectiveness. At the end of the thesis, pollen allergenicity is also approached from a molecular perspective, by investigating pollen allergens release mechanisms in the context of pollen hydration and germination. In particular, in an unpublished original research paper, the nature of allergen-carrying extracellular nanovesicles (pollensomes) released by pollen is extensively studied on a non-allergenic pollen model, to understand their biological role and thus the environmental conditions that trigger their release. Moreover, the last paper reported in the thesis demonstrates the secretion of a potential pollen allergen, a low-molecular weight cyclophilin, during pollen germination under stressful conditions. The thesis concludes with a brief description of other scientific activities carried on during the PhD, that still need more scientific corroboration to be published.

Machine learning tools for protein annotation: the cases of transmembrane β-barrel and myristoylated proteins

Biology is now a “Big Data Science” thanks to technological advancements allowing the characterization of the whole macromolecular content of a cell or a collection of cells. This opens interesting perspectives, but only a small portion of this data may be experimentally characterized. From this derives the demand of accurate and efficient computational tools for automatic annotation of biological molecules. This is even more true when dealing with membrane proteins, on which my research project is focused leading to the development of two machine learning-based methods: BetAware-Deep and SVMyr. BetAware-Deep is a tool for the detection and topology prediction of transmembrane beta-barrel proteins found in Gram-negative bacteria. These proteins are involved in many biological processes and primary candidates as drug targets. BetAware-Deep exploits the combination of a deep learning framework (bidirectional long short-term memory) and a probabilistic graphical model (grammatical-restrained hidden conditional random field). Moreover, it introduced a modified formulation of the hydrophobic moment, designed to include the evolutionary information. BetAware-Deep outperformed all the available methods in topology prediction and reported high scores in the detection task. Glycine myristoylation in Eukaryotes is the binding of a myristic acid on an N-terminal glycine. SVMyr is a fast method based on support vector machines designed to predict this modification in dataset of proteomic scale. It uses as input octapeptides and exploits computational scores derived from experimental examples and mean physicochemical features. SVMyr outperformed all the available methods for co-translational myristoylation prediction. In addition, it allows (as a unique feature) the prediction of post-translational myristoylation. Both the tools here described are designed having in mind best practices for the development of machine learning-based tools outlined by the bioinformatics community. Moreover, they are made available via user-friendly web servers. All this make them valuable tools for filling the gap between sequential and annotated data.

Development of thermochemiluminescence-based sensitive probes: synthesis, optimization, and characterization of c2- and c7-substituted acridine-containing 1,2-dioxetanes

After initial efforts in the late 1980s, the interest in thermochemiluminescence (TCL) as an effective detection technique has gradually faded due to some drawbacks, such as the high temperatures required to trigger the light emission and the relatively low intensities, which determined a poor sensitivity. Recent advances made with the adoption of variably functionalized 1,2-dioxetanes as innovative luminophores, have proved to be a promising approach for the development of reagentless and ultrasensitive detection methods exploitable in biosensors by using TCL compounds as labels, as either single molecules or included in modified nanoparticles. In this PhD Thesis, a novel class of N-substituted acridine-containing 1,2-dioxetanes was designed, synthesized, and characterized as universal TCL probes endowed with optimal emission-triggering temperatures and higher detectability particularly useful in bioanalytical assays. The different decorations introduced by the insertion of both electron donating (EDGs) and electron withdrawing groups (EWGs) at the 2- and 7-positions of acridine fluorophore was found to profoundly affect the photophysical properties and the activation parameters of the final 1,2-dioxetane products. Challenges in the synthesis of 1,2-dioxetanes were tackled with the recourse to continuous flow photochemistry to achieve the target parent compound in high yields, short reaction time, and easy scalability. Computational studies were also carried out to predict the olefins reactivity in the crucial photooxygenation reaction as well as the final products stability. The preliminary application of TCL prototype molecule has been performed in HaCaT cell lines showing the ability of these molecules to be detected in real biological samples and cell-based assays. Finally, attempts on the characterization of 1,2-dioxetanes in different environments (solid state, optical glue and nanosystems) and the development of bioconjugated TCL probes will be also presented and discussed.

Beyond pollinator reward: steps forward and knowledge gaps on the role of floral nectar in plant-animal interactions.

The work done within the framework of my PhD project has been carried out between November 2019 and January 2023 at the Department of Biological, Geological and Environmental Sciences of the University of Bologna, under the supervision of Prof. Marta Galloni and PhD Gherardo Bogo. A period of three months was spent at the Natural History Museum of Rijeka, under the supervision of Prof. Boštjan Surina. The main aim of the thesis was to investigate further the so-called pollinator manipulation hypothesis, which states that when a floral visitor gets in contact with a specific nectar chemistry, the latter affects its behavior of visit on flowers, with potential repercussions on the plant reproductive fitness. To the purpose, the topic was tackled by means of three main approaches: field studies, laboratory assessments, and bibliographic reviews. This research project contributes to two main aspects. First, when insects encounter nectar-like concentrations of a plethora of secondary metabolites in their food-environment, various aspects of their behavior relevant to flower visitation can be affected. In addition, the results I gained confirm that the combination of field studies and laboratory assessments allows to get more realistic pictures of a given phenomenon than the single approaches. Second, reviewing the existent literature in the field of nectar ecology has highlighted how crucial is to establish the origin of nectar biogenic amines to either confirm or reject the multiple speculations made on the role of nectar microbes in shaping plant-animal interactions.

Toxic cyanobacteria in water intended for drinking purpose: improvement of cells and toxins’ analyses and of treatments for their removal

Massive proliferations of cyanobacteria in freshwaters have recently increased, causing ecological and economic losses. Their ever-increasing presence in water sources destined to potabilization has become a major threat for public health, since several species can produce harmful toxins (cyanotoxin). Therefore, additional specific measures to improve management and treatment of drinking water(s) are required. The PhD thesis investigates toxic cyanobacteria in drinking waters with a special focus on Emilia-Romagna (Italy), throughout three separated chapters, each with different specific objectives. The first chapter aims at improving the fast monitoring of cyanobacteria in drinking water, which was investigated by testing different models of multi-wavelength spectrofluorometers. Inter-laboratories calibrations were conducted using mono-specific cultures and field samples, and both the feasibility and the technical limitations of such tools were illustrated. The second chapter evaluates the effectiveness of drinking water treatments in removing cyanobacterial cells and toxins. Two chlorinated oxidants (sodium hypochlorite and chlorine dioxide) already in use for pre-oxidation during water potabilization, were tested on cultures of the toxic cyanobacterium Microcystis aeruginosa posing a specific focus on toxin removal and revealing that pre-oxidation can cause the release of toxins and unknown metabolites. Innovative treatments based on non-thermal plasma were also tested, observing an effective and rapid inactivation of cyanobacterial cells. The third chapter presents a study on a cyanobacterium isolated from a drinking water reservoir of Emilia-Romagna and investigated by combining biological, chemical, and genomic methods. Although the strain did not produce any known cyanotoxin, high toxicity of water-extract was observed in bioassays and potential implications for drinking water were discussed. Overall, the PhD thesis offers new insights into toxic cyanobacteria management in drinking water, highlighting best practices for drinking water managers regarding their detection and removal. Additionally, the thesis provides new contributions to the understanding of the freshwater cyanobacteria community in the Emilia-Romagna region.

Green approach to Palladium Cross-Coupling reactions and development of new methodologies based on highly abundant metals

Transition metal catalyzed cross-coupling reactions represent among the most versatile and useful tools in organic synthesis for the carbon-carbon (C-C) bond formation and have a prominent role in both the academic and pharmaceutical segments. Among them, palladium catalyzed cross-coupling reactions are currently the most versatile. In this thesis, the applications, impact and development of green palladium cross-coupling reactions are discussed. Specifically, we discuss the translation of the Twelve Principles of Green Chemistry and their applications in pharmaceutical organometallic chemistry to stimulate the development of cost-effective and sustainable catalytic processes for the synthesis of active pharmaceutical ingredients (API). The Heck-Cassar-Sonogashira (HCS) and the Suzuki-Miyaura (SM) protocols, using HEP/H2O as green mixture and sulfonated phosphine ligands, allowed to recycle and recover the catalyst, always guaranteeing high yields and fast conversion under mild conditions, with aryl iodides, bromides, triflates and chlorides. No catalyst leakage or metal contamination of the final product were observed during the HCS and SM reactions, respecting the very low limits for metal impurities in medicines established by the International Conference of Harmonization Guidelines Q3D (ICH Q3D). In addition, a deep understanding of the reaction mechanism is very important if the final target is to develop efficient protocols that can be applied at industrial level. Experimental and theoretical studies pointed out the presence of two catalytic cycles depending on the counterion, shedding light on the role of base in catalyst reduction and acetylene coordination in the HCS coupling. Finally, the development of a cross-coupling reaction to form aryldifluoronitriles in the presence of copper is discussed, highlighting the importance of inserting fluorine atoms within biological structures and the use of readily available metals such as copper as an alternative to palladium.

Data surveillance for infectious diseases: models, complex networks and machine learning

In this thesis, we investigate the role of applied physics in epidemiological surveillance through the application of mathematical models, network science and machine learning. The spread of a communicable disease depends on many biological, social, and health factors. The large masses of data available make it possible, on the one hand, to monitor the evolution and spread of pathogenic organisms; on the other hand, to study the behavior of people, their opinions and habits. Presented here are three lines of research in which an attempt was made to solve real epidemiological problems through data analysis and the use of statistical and mathematical models. In Chapter 1, we applied language-inspired Deep Learning models to transform influenza protein sequences into vectors encoding their information content. We then attempted to reconstruct the antigenic properties of different viral strains using regression models and to identify the mutations responsible for vaccine escape. In Chapter 2, we constructed a compartmental model to describe the spread of a bacterium within a hospital ward. The model was informed and validated on time series of clinical measurements, and a sensitivity analysis was used to assess the impact of different control measures. Finally (Chapter 3) we reconstructed the network of retweets among COVID-19 themed Twitter users in the early months of the SARS-CoV-2 pandemic. By means of community detection algorithms and centrality measures, we characterized users’ attention shifts in the network, showing that scientific communities, initially the most retweeted, lost influence over time to national political communities. In the Conclusion, we highlighted the importance of the work done in light of the main contemporary challenges for epidemiological surveillance. In particular, we present reflections on the importance of nowcasting and forecasting, the relationship between data and scientific research, and the need to unite the different scales of epidemiological surveillance.