Modeling and simulation of a synthetic genetic circuit that implements a multicelled behavior in a growing microcolony of E. coli

Synthetic Biology is a relatively new discipline, born at the beginning of the New Millennium, that brings the typical engineering approach (abstraction, modularity and standardization) to biotechnology. These principles aim to tame the extreme complexity of the various components and aid the construction of artificial biological systems with specific functions, usually by means of synthetic genetic circuits implemented in bacteria or simple eukaryotes like yeast. The cell becomes a programmable machine and its low-level programming language is made of strings of DNA. This work was performed in collaboration with researchers of the Department of Electrical Engineering of the University of Washington in Seattle and also with a student of the Corso di Laurea Magistrale in Ingegneria Biomedica at the University of Bologna: Marilisa Cortesi. During the collaboration I contributed to a Synthetic Biology project already started in the Klavins Laboratory. In particular, I modeled and subsequently simulated a synthetic genetic circuit that was ideated for the implementation of a multicelled behavior in a growing bacterial microcolony. In the first chapter the foundations of molecular biology are introduced: structure of the nucleic acids, transcription, translation and methods to regulate gene expression. An introduction to Synthetic Biology completes the section. In the second chapter is described the synthetic genetic circuit that was conceived to make spontaneously emerge, from an isogenic microcolony of bacteria, two different groups of cells, termed leaders and followers. The circuit exploits the intrinsic stochasticity of gene expression and intercellular communication via small molecules to break the symmetry in the phenotype of the microcolony. The four modules of the circuit (coin flipper, sender, receiver and follower) and their interactions are then illustrated. In the third chapter is derived the mathematical representation of the various components of the circuit and the several simplifying assumptions are made explicit. Transcription and translation are modeled as a single step and gene expression is function of the intracellular concentration of the various transcription factors that act on the different promoters of the circuit. A list of the various parameters and a justification for their value closes the chapter. In the fourth chapter are described the main characteristics of the gro simulation environment, developed by the Self Organizing Systems Laboratory of the University of Washington. Then, a sensitivity analysis performed to pinpoint the desirable characteristics of the various genetic components is detailed. The sensitivity analysis makes use of a cost function that is based on the fraction of cells in each one of the different possible states at the end of the simulation and the wanted outcome. Thanks to a particular kind of scatter plot, the parameters are ranked. Starting from an initial condition in which all the parameters assume their nominal value, the ranking suggest which parameter to tune in order to reach the goal. Obtaining a microcolony in which almost all the cells are in the follower state and only a few in the leader state seems to be the most difficult task. A small number of leader cells struggle to produce enough signal to turn the rest of the microcolony in the follower state. It is possible to obtain a microcolony in which the majority of cells are followers by increasing as much as possible the production of signal. Reaching the goal of a microcolony that is split in half between leaders and followers is comparatively easy. The best strategy seems to be increasing slightly the production of the enzyme. To end up with a majority of leaders, instead, it is advisable to increase the basal expression of the coin flipper module. At the end of the chapter, a possible future application of the leader election circuit, the spontaneous formation of spatial patterns in a microcolony, is modeled with the finite state machine formalism. The gro simulations provide insights into the genetic components that are needed to implement the behavior. In particular, since both the examples of pattern formation rely on a local version of Leader Election, a short-range communication system is essential. Moreover, new synthetic components that allow to reliably downregulate the growth rate in specific cells without side effects need to be developed. In the appendix are listed the gro code utilized to simulate the model of the circuit, a script in the Python programming language that was used to split the simulations on a Linux cluster and the Matlab code developed to analyze the data.

Teos-based consolidants for stone conservation: evaluation of the effects and testing by x-ray imaging

Natural stones have been widely used in the construction field since antiquity. Building materials undergo decay processes due to mechanical,chemical, physical and biological causes that can act together. Therefore an interdisciplinary approach is required in order to understand the interaction between the stone and the surrounding environment. Utilization of buildings, inadequate restoration activities and in general anthropogenic weathering factors may contribute to this degradation process. For this reasons, in the last few decades new technologies and techniques have been developed and introduced in the restoration field. Consolidants are largely used in restoration and conservation of cultural heritage in order to improve the internal cohesion and to reduce the weathering rate of building materials. It is important to define the penetration depth of a consolidant for determining its efficacy. Impregnation mainly depends on the microstructure of the stone (i.e. porosity) and on the properties of the product itself. Throughout this study, tetraethoxysilane (TEOS) applied on globigerina limestone samples has been chosen as object of investigation. After hydrolysis and condensation, TEOS deposits silica gel inside the pores, improving the cohesion of the grains. X-ray computed tomography has been used to characterize the internal structure of the limestone samples,treated and untreated with a TEOS-based consolidant. The aim of this work is to investigate the penetration depth and the distribution of the TEOS inside the porosity, using both traditional approaches and advanced X-ray tomographic techniques, the latter allowing the internal visualization in three dimensions of the materials. Fluid transport properties and porosity have been studied both at macroscopic scale, by means of capillary uptake tests and radiography, and at microscopic scale,investigated with X-ray Tomographic Microscopy (XTM). This allows identifying changes in the porosity, by comparison of the images before and after the treatment, and locating the consolidant inside the stone. Tests were initially run at University of Bologna, where characterization of the stone was carried out. Then the research continued in Switzerland: X-ray tomography and radiography were performed at Empa, Swiss Federal Laboratories for Materials Science and Technology, while XTM measurements with synchrotron radiation were run at Paul Scherrer Institute in Villigen.

Pressure Swing Adsorption on Carbon Molecular Sieves for Nitrogen Production: Modelling and Simulation with Aspen Adsorption

L’azoto è uno dei prodotti principali dell’industria chimica, utilizzato principalmente per assicurare un sicuro stoccaggio di composti infiammabili. Generatori con sistemi PSA sono spesso più economici della tradizionale distillazione criogenica. I processi PSA utilizzano una colonna a letto fisso, riempita con materiale adsorbente, che adsorbe selettivamente un componente da una miscela gassosa. L’ossigeno diffonde molto più velocemente dell'azoto nei pori di setacci molecolari carboniosi. Oltre ad un ottimo materiale adsorbente, anche il design è fondamentale per la performance di un processo PSA. La fase di adsorbimento è seguita da una fase di desorbimento. Il materiale adsorbente può essere quindi riutilizzato nel ciclo seguente. L’assenza di un simulatore di processo ha reso necessario l’uso di dati sperimentali per sviluppare nuovi processi. Un tale approccio è molto costoso e lungo. Una modellazione e simulazione matematica, che consideri tutti i fenomeni di trasporto, è richiesta per una migliore comprensione dell'adsorbente sia per l'ottimizzazione del processo. La dinamica della colonna richiede la soluzione di insiemi di PDE distribuite nel tempo e nello spazio. Questo lavoro è stato svolto presso l'Università di Scienze Applicate - Münster, Germania. Argomento di questa tesi è la modellazione e simulazione di un impianto PSA per la produzione di azoto con il simulatore di processo Aspen Adsorption con l’obiettivo di permettere in futuro ottimizzazioni di processo affidabili, attendibili ed economiche basate su computazioni numeriche. E' discussa l’ottimizzazione di parametri, dati cinetici, termodinamici e di equilibrio. Il modello è affidabile, rigoroso e risponde adeguatamente a diverse condizioni al contorno. Tuttavia non è ancora pienamente soddisfacente poiché manca una rappresentazione adeguata della cinetica ovvero dei fenomeni di trasporto di materia. La messa a punto del software permetterà in futuro di indagare velocemente nuove possibilità di operazione.