Phage therapy: A software system for phage quantification and kinetic model inference.

One of the most serious problems of the modern medicine is the growing emergence of antibiotic resistance among pathogenic bacteria. In this circumstance, different and innovative approaches for treating infections caused by multidrug-resistant bacteria are imperatively required. Bacteriophage Therapy is one among the fascinating approaches to be taken into account. This consists of the use of bacteriophages, viruses that infect bacteria, in order to defeat specific bacterial pathogens. Phage therapy is not an innovative idea, indeed, it was widely used around the world in the 1930s and 1940s, in order to treat various infection diseases, and it is still used in Eastern Europe and the former Soviet Union. Nevertheless, Western scientists mostly lost interest in further use and study of phage therapy and abandoned it after the discovery and the spread of antibiotics. The advancement of scientific knowledge of the last years, together with the encouraging results from recent animal studies using phages to treat bacterial infections, and above all the urgent need for novel and effective antimicrobials, have given a prompt for additional rigorous researches in this field. In particular, in the laboratory of synthetic biology of the department of Life Sciences at the University of Warwick, a novel approach was adopted, starting from the original concept of phage therapy, in order to study a concrete alternative to antibiotics. The innovative idea of the project consists in the development of experimental methodologies, which allow to engineer a programmable synthetic phage system using a combination of directed evolution, automation and microfluidics. The main aim is to make “the therapeutics of tomorrow individualized, specific, and self-regulated” (Jaramillo, 2015). In this context, one of the most important key points is the Bacteriophage Quantification. Therefore, in this research work, a mathematical model describing complex dynamics occurring in biological systems involving continuous growth of bacteriophages, modulated by the performance of the host organisms, was implemented as algorithms into a working software using MATLAB. The developed program is able to predict different unknown concentrations of phages much faster than the classical overnight Plaque Assay. What is more, it gives a meaning and an explanation to the obtained data, making inference about the parameter set of the model, that are representative of the bacteriophage-host interaction.

Stochastic modeling of bacterial protein domains distribution to predict horizontal gene transfer

In questo elaborato, abbiamo tentato di modellizzare i processi che regolano la presenza dei domini proteici. I domini proteici studiati in questa tesi sono stati ottenuti dai genomi batterici disponibili nei data base pubblici (principalmente dal National Centre for Biotechnology Information: NCBI) tramite una procedura di simulazione computazionale. Ci siamo concentrati su organismi batterici in quanto in essi la presenza di geni trasmessi orizzontalmente, ossia che parte del materiale genetico non provenga dai genitori, e assodato che sia presente in una maggiore percentuale rispetto agli organismi più evoluti. Il modello usato si basa sui processi stocastici di nascita e morte, con l'aggiunta di un parametro di migrazione, usato anche nella descrizione dell'abbondanza relativa delle specie in ambito delle biodiversità ecologiche. Le relazioni tra i parametri, calcolati come migliori stime di una distribuzione binomiale negativa rinormalizzata e adattata agli istogrammi sperimentali, ci induce ad ipotizzare che le famiglie batteriche caratterizzate da un basso valore numerico del parametro di immigrazione abbiano contrastato questo deficit con un elevato valore del tasso di nascita. Al contrario, ipotizziamo che le famiglie con un tasso di nascita relativamente basso si siano adattate, e in conseguenza, mostrano un elevato valore del parametro di migrazione. Inoltre riteniamo che il parametro di migrazione sia direttamente proporzionale alla quantità di trasferimento genico orizzontale effettuato dalla famiglia batterica.