Development of synthetic molecular circuits for the control of cell systems

Synthetic biology is a young field of applicative research aiming to design and build up artificial biological devices, useful for human applications. How synthetic biology emerged in past years and how the development of the Registry of Standard Biological Parts aimed to introduce one practical starting solution to apply the basics of engineering to molecular biology is presented in chapter 1 in the thesis The same chapter recalls how biological parts can make up a genetic program, the molecular cloning tecnique useful for this purpose, and an overview of the mathematical modeling adopted to describe gene circuit behavior. Although the design of gene circuits has become feasible the increasing complexity of gene networks asks for a rational approach to design gene circuits. A bottom-up approach was proposed, suggesting that the behavior of a complicated system can be predicted from the features of its parts. The option to use modular parts in large-scale networks will be facilitated by a detailed and shared characterization of their functional properties. Such a prediction, requires well-characterized mathematical models of the parts and of how they behave when assembled together. In chapter 2, the feasibility of the bottom-up approach in the design of a synthetic program in Escherichia coli bacterial cells is described. The rational design of gene networks is however far from being established. The synthetic biology approach can used the mathematical formalism to identify biological information not assessable with experimental measurements. In this context, chapter 3 describes the design of a synthetic sensor for identifying molecules of interest inside eukaryotic cells. The Registry of Standard parts collects standard and modular biological parts. To spread the use of BioBricks the iGEM competition was started. The ICM Laboratory, where Francesca Ceroni completed her Ph.D, partecipated with teams of students and Chapter 4 summarizes the projects developed.

Pervasive Sensing in Future Networks

Pervasive Sensing is a recent research trend that aims at providing widespread computing and sensing capabilities to enable the creation of smart environments that can sense, process, and act by considering input coming from both people and devices. The capabilities necessary for Pervasive Sensing are nowadays available on a plethora of devices, from embedded devices to PCs and smartphones. The wide availability of new devices and the large amount of data they can access enable a wide range of novel services in different areas, spanning from simple data collection systems to socially-aware collaborative filtering. However, the strong heterogeneity and unreliability of devices and sensors poses significant challenges. So far, existing works on Pervasive Sensing have focused only on limited portions of the whole stack of available devices and data that they can use, to propose and develop mainly vertical solutions. The push from academia and industry for this kind of services shows that time is mature for a more general support framework for Pervasive Sensing solutions able to enhance frail architectures, promote a well balanced usage of resources on different devices, and enable the widest possible access to sensed data, while ensuring a minimal energy consumption on battery-operated devices. This thesis focuses on pervasive sensing systems to extract design guidelines as foundation of a comprehensive reference model for multi-tier Pervasive Sensing applications. The validity of the proposed model is tested in five different scenarios that present peculiar and different requirements, and different hardware and sensors. The ease of mapping from the proposed logical model to the real implementations and the positive performance result campaigns prove the quality of the proposed approach and offer a reliable reference model, together with a direction for the design and deployment of future Pervasive Sensing applications.

Molecular and functional characterization of the chemotactic genes in the PCBs-degrader Pseudomonas pseudoalcaligenes KF707

Although bacteria represent the simplest form of life on Earth, they have a great impact on all living beings. For example the degrader bacterium Pseudomonas pseudoalcaligenes KF707 is used in bioremediation procedures for the recovery of polluted sites. Indeed, KF707 strain is know for its ability to degrade biphenyl and polychlorinated biphenyls - to which is chemotactically attracted - and to tolerate the oxydative stress due to toxic metal oxyanions such as tellurite and selenite. Moreover, in bioremediation processes, target compounds can be easily accessible to KF707 through biofilm formation. All these considerations suggest that KF707 is such a unique microorganism and this Thesis work has been focused on determining the molecular nature of some of the peculiar physiological traits of this strain. The genome project provided a large set of informations: putative genes involved in the degradation of aromatic and toxic compounds and associated to stress response were identified. Notably, multiple chemotactic operons and cheA genes were also found. Deleted mutants in the cheA genes were constructed and their role in motility, chemotaxis and biofilm formation were assessed and compared to those previously attributed to a cheA1 gene in a KF707 mutant constructed by a mini-Tn5 transposon insertion and which was impaired in motility and biofilm development. The results of this present Thesis work, taken together, were interpreted to suggest that in Pseudomonas pseudoalcaligenes KF707 strain, multiple factors are involved in these networks and they might play different roles depending on the environmental conditions. The ability of KF707 strain to produce signal molecules possibly involved in cell-to-cell communication, was also investigated: lack of a lux-like QS system - which is conversely widely present in Gram negative bacteria – keeps open the question about the actual molecular nature of KF707 quorum sensing mechanism.

Molecular strategies for genetic diversity analysis and development of markers linked to resistance traits in apple

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.

Scene Mapping and Understanding by Robotic Vision

The first mechanical Automaton concept was found in a Chinese text written in the 3rd century BC, while Computer Vision was born in the late 1960s. Therefore, visual perception applied to machines (i.e. the Machine Vision) is a young and exciting alliance. When robots came in, the new field of Robotic Vision was born, and these terms began to be erroneously interchanged. In short, we can say that Machine Vision is an engineering domain, which concern the industrial use of Vision. The Robotic Vision, instead, is a research field that tries to incorporate robotics aspects in computer vision algorithms. Visual Servoing, for example, is one of the problems that cannot be solved by computer vision only. Accordingly, a large part of this work deals with boosting popular Computer Vision techniques by exploiting robotics: e.g. the use of kinematics to localize a vision sensor, mounted as the robot end-effector. The remainder of this work is dedicated to the counterparty, i.e. the use of computer vision to solve real robotic problems like grasping objects or navigate avoiding obstacles. Will be presented a brief survey about mapping data structures most widely used in robotics along with SkiMap, a novel sparse data structure created both for robotic mapping and as a general purpose 3D spatial index. Thus, several approaches to implement Object Detection and Manipulation, by exploiting the aforementioned mapping strategies, will be proposed, along with a completely new Machine Teaching facility in order to simply the training procedure of modern Deep Learning networks.

A preclinical study of spinal cord injury focused on cellular and molecular modifications as potential targets for innovative therapies

Spinal Cord Injury (SCI) is a devastating condition for human and animal health. In SCI particularly, neurons, oligodendrocytes precursor cells, and mature oligodendrocytes are highly vulnerable to the toxic microenvironment after the lesion and susceptible to the elevated levels of noxious stimuli. Thus the regenerative response of the organism in case of SCI is significantly reduced, and only little spontaneous amelioration is observed in lesioned patients during the early phases. This work mainly focuses on studying and characterizing the modification induced by the SCI in a preclinical animal model. We investigated the ECM composition in the spinal cord segments surrounding the primary lesion site at a gene expression level. We found Timp1 and CD44 as a crucial hub in the secondary cascade of SCI in both spinal cord segments surrounding the lesion site. Interestingly, a temporal and anatomical difference in gene expression, indicating a complex regulation of ECM genes after SCI that could be used as a tool for regenerative medicine. We also investigated the modification in synaptic plasticity-related gene expression in spinal and supraspinal areas involved in motor control. We confirmed the anatomical and temporal difference in gene expression in spinal cord tissue. This analysis suggests that a molecular mapping of the lesion-induced modification could be a useful tool for regenerative medicine. In the last part, we evaluated the efficacy of an implantable biopolymer loaded with an anti-inflammatory drug and a pro-myelinating agent on the acute phase of SCI in our preclinical model. We found a consistent reduction of the inflammatory state in the spinal lesion site and the cord's surrounding segments. Moreover, we found increased preservation of the spinal cord tissue with a related upregulation of neuronal and oligodendroglial markers after lesion. Our treatment showed effective ameliorating functional outcome and reducing the lesion extension in the chronic phase.

Simulation of photoinduced processes in organic chromophores: mapping photochemically relevant states for accurate dynamics

The simulation of ultrafast photoinduced processes is a fundamental step towards the understanding of the underlying molecular mechanism and interpretation/prediction of experimental data. Performing a computer simulation of a complex photoinduced process is only possible introducing some approximations but, in order to obtain reliable results, the need to reduce the complexity must balance with the accuracy of the model, which should include all the relevant degrees of freedom and a quantitatively correct description of the electronic states involved in the process. This work presents new computational protocols and strategies for the parameterisation of accurate models for photochemical/photophysical processes based on state-of-the-art multiconfigurational wavefunction-based methods. The required ingredients for a dynamics simulation include potential energy surfaces (PESs) as well as electronic state couplings, which must be mapped across the wide range of geometries visited during the wavepacket/trajectory propagation. The developed procedures allow to obtain solid and extended databases reducing as much as possible the computational cost, thanks to, e.g., specific tuning of the level of theory for different PES regions and/or direct calculation of only the needed components of vectorial quantities (like gradients or nonadiabatic couplings). The presented approaches were applied to three case studies (azobenzene, pyrene, visual rhodopsin), all requiring an accurate parameterisation but for different reasons. The resulting models and simulations allowed to elucidate the mechanism and time scale of the internal conversion, reproducing or even predicting new transient experiments. The general applicability of the developed protocols to systems with different peculiarities and the possibility to parameterise different types of dynamics on an equal footing (classical vs purely quantum) prove that the developed procedures are flexible enough to be tailored for each specific system, and pave the way for exact quantum dynamics with multiple degrees of freedom.

Design, realization, and characterization of complex reaction networks in dynamic mechanically interlocked molecules

The experimental projects discussed in this thesis are all related to the field of artificial molecular machines, specifically to systems composed of pseudorotaxane and rotaxane architectures. The characterization of the peculiar properties of these mechano-molecules is frequently associated with the analysis and elucidation of complex reaction networks; this latter aspect represents the main focus and central thread tying my thesis work. In each chapter, a specific project is described as summarized below: the focus of the first chapter is the realization and characterization of a prototype model of a photoactivated molecular transporter based on a pseudorotaxane architecture; in the second chapter is reported the design, synthesis, and characterization of a [2]rotaxane endowed with a dibenzylammonium station and a novel photochromic unit that acts as a recognition site for a DB24C8 crown ether macrocycle; in the last chapter is described the synthesis and characterization of a [3]rotaxane in which the relative number of rings and stations can be changed on command.

Mapping new non-genetic dependencies in malignant pleural mesothelioma

Malignant Pleural Mesothelioma (MPM) is a very aggressive cancer whose incidence is growing worldwide. MPM escapes the classical models of carcinogenesis and lacks a distinctive genetic fingerprint, keeping obscure the molecular events that lead to tumorigenesis. This severely impacts on the limited therapeutic options and on the lack of specific biomarkers, concurring to make MPM one of the deadliest cancers. Here we combined a functional genome-wide loss of function CRISPR/Cas9 screening with patients’ transcriptomic and clinical data, to identify genes essential for MPM progression. Besides, we explored the role of non-coding RNAs to MPM progression by analysing gene expression profiles and clinical data from the MESO-TCGA dataset. We identified TRIM28 and the lncRNA LINC00941 as new vulnerabilities of MPM, associated with disease aggressiveness and bad outcome of patients. TRIM28 is a multi-domain protein involved in many processes, including transcription regulation. We showed that TRIM28 silencing impairs MPM cells’ growth and clonogenicity by blocking cells in mitosis. RNA-seq profiling showed that TRIM28 loss abolished the expression of major mitotic players. Our data suggest that TRIM28 is part of the B-MYB/FOXM1-MuvB complex that specifically drives the activation of mitotic genes, keeping the time of mitosis. In parallel, we found LINC00941 as strongly associated with reduced survival probability in MPM patients. LINC00941 KD profoundly reduced MPM cells’ growth, migration and invasion. This is accompanied by changes in morphology, cytoskeleton organization and cell-cell adhesion properties. RNA-seq profiling showed that LINC00941 KD impacts crucial functions of MPM, including HIF1α signalling. Collectively these data provided new insights into MPM biology and demonstrated that the integration of functional screening with patients’ clinical data is a powerful tool to highlight new non-genetic cancer dependencies that associate to a bad outcome in vivo, paving the way to new MPM-oriented targeted strategies and prognostic tools to improve patients risk-based stratification.

Gwas analysis for the identification of molecular basis responsible for yield related traits and disease resistance in durum wheat

The PhD thesis was developed in the framework of Innovar H2020 project. This project aimed at using genomics, transcriptomics and phenotyping techniques to update varietal registration procedure used in Europe for Value of Cultivation and Use (VCU) and Distinctiness Uniformity and Stability (DUS) protocols. The phenotypic and genotypic diversity of a durum wheat panel were assessed for different agronomic traits, connected with wheat development, disease resistance and spike fertility. A panel of 253 durum wheat varieties was characterized for VCU and DUS traits and genotyped with Illumina 90K SNP Chip array (Wang et al., 2014). GWAS analysis was performed, detecting strong QTLs confirmed also by literature review. Candidate genes were identified for each trait and molecular markers will be developed to be used for marker assisted selection in breeding programs. As for disease resistance, the panel was evaluated for resistance to Soil-Borne-Cereal-Mosaic-Virus (SBCMV). A major QTL, sbm2, was detected on chromosome 2B responsible for durum wheat resistance (Maccaferri et al., 2011). The sbm2 interval was explored by fine mapping on segregant population using KASP markers and by RNASeq analysis, detecting candidate genes involved in plant-pathogen reaction. As regards yield related traits, detailed analysis was performed on the GNI-2A QTL (Milner et al., 2016), responsible for increased number spike fertility. Fine mapping analysis was performed on durum panel identifying hox2 a strong candidate gene, codifying for transcription factor protein. The gene is paralogue of GNI-1 (Sakuma et al., 2019), and it has a 4 kbp deletion responsible for increased number of florets per spikelet. To conclude, the herein reported thesis shows a complete characterization of agronomic and disease resistance traits in modern durum wheat varieties. The results obtained will augment available information for each variety, identifying informative molecular markers for breeding purposes and QTLs/candidate genes responsible for different agronomic traits.