I'm Alessandro Filisetti and presently I work in the exciting world of research, with the titanic aim to be a researcher [or something like that] in Italy. Although the rationality would suggest me to find my way out of Italy, our life is not only rationality, but also feelings and place where you like to live.
For this reason I decided to find my way here in Italy, trying to do my best for me and my family.
From 2007 to 2011 I was a Research Fellow at the European Centre for Living Technology in Venice (IT). I was a visiting student in 2004 at the Institute of Mathematical and Behavioural Sciences, University of California at Irvine, Irvine (CA). In 2009 I was awarded for the best student poster prize receiving an honourable mention (it is definitely not too much but it is something) at ECCS09 (European Conference on Complex Systems) and in 2010 I won the first prize at the "Best paper awards" at ECCS10. My main research area concerns the study and the characterization of the complex systems; presently I'm focusing on the complex systems biology and in particular I'm studying the synchronization phenomena in theoretical models of protocell and the emergence of autocatalytic sets of molecules in theoretical models of catalytic reaction networks composed of random polymers.
Abstract: Autocatalytic cycles are rather common in biological systems and they might have played a major role in the transition from non-living to living systems. Several theoretical models have been proposed to address the experimentalists during the investigation of this issue and most of them describe a phase transition depending upon the level of heterogeneity of the chemical soup. Nevertheless, it is well known that reproducing the emergence of autocatalytic sets in wet laboratories is a hard task. Understanding the rationale at the basis of such a mismatch between theoretical predictions and experimental observations is therefore of fundamental importance. We here introduce a novel stochastic model of catalytic reaction networks, in order to investigate the emergence of autocatalytic cycles, sensibly considering the importance of noise, of small-number effects and the possible growth of the number of different elements in the system. Furthermore, the introduction of a temporal threshold that defines how long a specific reaction is kept in the reaction graph allows to univocally define cycles also within an asynchronous framework. The foremost analyses have been focused on the study of the variation of the composition of the incoming flux. It was possible to show that the activity of the system is enhanced, with particular regard to the emergence of autocatalytic sets, if a larger number of different elements is present in the incoming flux, while the specific length of the species seems to entail minor effects on the overall dynamics.
Abstract: This work aims to consider simplified models of protocells in order to describe their general behaviors. The advantage of the modelling approach is that the early protocells of life-forms on Earth are not reproduced in the present time. However, the problem is considered as a right track to understand the origin of life as well as to work with more objective synthesis of new drugs.
Abstract: In this paper, we study general protocell models aiming to understand the synchronization phenomenon of genetic material and container productions, a necessary condition to ensure sustainable growth in protocells and eventually leading to Darwinian evolution when applied to a population of protocells. Synchronization has been proved to be an emergent property in many relevant protocell models in the class of the so-called surface reaction models, assuming both linear- and non-linear dynamics for the involved chemical reactions. We here extend this analysis by introducing and studying a new class of models where the relevant chemical reactions are assumed to occur inside the protocell, in contrast with the former model where the reaction site was the external surface. While in our previous studies, the replicators were assumed to compete for resources, without any direct interaction among them, we here improve both models by allowing linear interaction between replicators: catalysis and/or inhibition. Extending some techniques previously introduced, we are able to give a quite general analytical answer about the synchronization phenomenon in this more general context. We also report on results of numerical simulations to support the theory, where applicable, and allow the investigation of cases which are not amenable to analytical calculations.
Abstract: Although autocatalytic networks are common in nature, it is very difficult to reproduce them in laboratory. Since there are several models in literature describing a phase transition to an autocatalytic set once that a certain degree of heterogeneity in the composition of the system is reached, it is interesting to understand why it is so difficult to observe such a phenomenon in the laboratory. For this reason, we here present a model designed for the study of that systems taking into account the stochastic nature of the dynamics of interacting molecules. In particular, the analysis is focused on the emergence of autocatalytic sets in accordance with different residence times and influx compositions.
Abstract: The present work extends our previous studies which had considered synchronization in the classes of so-called "Surface Reaction Models" SRM and "Internal Reaction Models" IRM when linear kinetics were assumed for the relevant chemical reactions. Let us show here that similar results have been obtained also for the "Non linear Reaction Models", both SMRs and IRMs, hence the synchronization phenomenon seems to be very robust with respect to the chosen architecture once linear and non linear kinetics are considered.
Also the case where the genetic material kinetic is chaotic has been taken into account and the result is that the coupling between genetic material and container kinetics seems to be able to rule the chaos leading to synchronization.
Abstract: The transition from non living to living matter is a key issue in the study on the origin and evolution of life. Although there are different theoretical scenarios, it is widely accepted that the first life forms were simple protocells endowed with some capabilities of self-assembly, self-reproduction, self-maintenance and self-repair. Protocells also hold the promise to be the basis of a new kind of living technology.
The thesis is divided in two (related but relatively independent) parts. In the first part different models of protocells, describing the coupled growth of the lipid container and of the self-replicating molecules, are investigated. The models differ in the nature of the interactions between the molecules and in the hypotheses about the phase (lipidic or aqueous) where the key processes take place. In particular we focus on the synchronization between the processes of growth and division of the container and that of the increase in number of the self-replicating molecules, which is necessary for a viable growth of a population of protocells and therefore also represents a prerequisite for darwinian evolution to take place. We show that such a synchronization phenomenon spontaneously emerges, without being assumed a priori, under fairly general assumptions.
In the second part the emergence of the autocatalytic cycles, necessary for a continuous growth of the self-replicating molecules in a protocell, is analyzed.\\
Although autocatalytic networks are common in biology, it is very difficult to obtain them in laboratory. Since there are several models in the literature describing a phase transition to an autocatalytic set once that a certain degree of heterogeneity in the composition of the system is reached, it is interesting to understand why it is so difficult to observe such a phenomenon in the laboratory. For this reason, we present here a model designed for the study of that problem. While this model is based on previous studies by Kauffman and others, it is original in that a stochastic dynamics is introduced and analyzed, and stochastic effects may be particularly important when some kinds of molecules are present in very small numbers. It is shown that this is indeed the case for a wide range of parameter values.
We also analyze the influence of the influx composition on the emergence of autocatalytic sets, showing that a minimum variety is necessary for their achievement and providing quantitative estimates.
Finally, further developments in order to add new elements of plausibility to the system are presented.
