1,720,989 research outputs found
The Stochastic Evolution of a Protocell: The Gillespie Algorithm in a Dynamically Varying Volume
Full text linkWe propose an improvement of the Gillespie algorithm allowing us to study the time evolution of an ensemble of chemical reactions occurring in a varying volume, whose growth is directly related to the amount of some specific molecules, belonging to the reactions set. This allows us to study the stochastic evolution of a protocell, whose volume increases because of the production of container molecules. Several protocell models are considered and compared with the deterministic models
Synchronization phenomena in protocell models
No full textAlmost all life forms known today, are composed by cells, fundamental constituting units able to self–replicate and evolve through changes in genetic information; it is generally believed that this was not the case when first life–forms emerged on Earth almost 4 billion years ago. These protocells were much simpler, probably exhibiting only few simplified functionalities, that required a primitive embodiment structure, a protometabolism and a rudimentary genetics, so to guarantee that offsprings were similar to their parents. Artificial protocells have not yet been reproduced and intense research programs are being established aiming at developing reference models to capture the essence of the first protocells appeared on earth and enableto monitor their subsequent evolution. The interest for these researches is motivated either by the quest to understand which are the minimal requirements for a life form to exist and evolve, or by the search for indications about the way in which primitive life might have developed on earth. Moreover besides from their interest for the origin–of–life problem, protocells may be of practical interest in applications: obtain populations ofprotocells that grow and reproduce, specialized for useful tasks, like drug synthesis and reduce pollution.Because protocells didn’t yet exist, in order to study how they can develop researchers have considered simplified models able to capture general behaviors, without carefully adding complicating details
The growth of populations of protocells
No full textmodels of synchronization in populations of protocell
Parameter sensitivity analysis of stochastic models: Application to catalytic reaction networks
No full textA general numerical methodology for parametric sensitivity analysis is proposed, which allows to determine the parameters exerting the greatest influence on the output of a stochastic computational model, especially when the knowledge about the actual value of a parameter is insufficient. An application of the procedure is performed on a model of protocell, in order to detect the kinetic rates mainly affecting the capability of a catalytic reaction network enclosed in a semi-permeable membrane to retain material from its environment and to generate a variety of molecular species within its boundaries. It is shown that the former capability is scarcely sensitive to variations in the model parameters, whereas a kinetic rate responsible for profound modifications of the latter can be identified and it depends on the specific reaction network. A faster uptaking of limited resources from the environment may have represented a significant advantage from an evolutionary point of view and this result is a first indication in order to decipher which kind of structures are more suitable to achieve a viable evolution
Non linear protocell models: Syncronisation and Chaos
No full textAbstract We consider generic protocells models allowing linear and non-linear kineticsfor the main involved chemical reactions.We are interested in understanding if and howthe protocell division and the metabolism do synchronize to give rise to sustainableevolution of the protocell
SUFFICIENT CONDITIONS FOR EMERGENT SYNCHRONIZATION IN PROTOCELL MODELS
Full text linkIn this paper, we study general protocell models aiming to understand the synchronizationphenomenon of genetic material and container productions, a necessary condition to ensure sustainablegrowth in protocells and eventually leading to Darwinian evolution when applied to a population ofprotocells.Synchronization has been proved to be an emergent property in many relevant protocell models inthe class of the so-called surface reaction models, assuming both linear- and non-linear dynamics forthe involved chemical reactions. We here extend this analysis by introducing and studying a new classof models where the relevant chemical reactions are assumed to occur inside the protocell, in contrastwith 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 linearinteraction between replicators: catalysis and/or inhibition. Extending some techniques previouslyintroduced, we are able to give a quite general analytical answer about the synchronizationphenomenon in this more general context. We also report on results of numerical simulations tosupport the theory, where applicable, and allow the investigation of cases which are not amenable toanalytical calculations
SYNCHRONIZATION PHENOMENA IN PROTOCELL MODELS
Full text linkA protocell comprises at least one kind of“container”(typically an amphiphile) and one kind of replicator molecule. There are therefore two kinds of reactions whichare crucial for the working of the protocell, which will be called here keyreactions: those which synthesize the container molecules and those whichsynthesize the replicators.The two key reactions may take place at different rates. However, toachieve sustained protocell growth and avoiding death by dilution it isnecessary that the two are proceed at equal rate, a condi-tion referred to as synchronization. With our models we are able to prove that synchronization is an emergent property in contrast to earlier models, like the well–knownChemoton where synchronization was achieved by ad hoc hypothesesconcerning the form of kinetic equations.We consider here several protocells models both linear and non–linear inreplicators kinetic (the overall model is definitely non–linear because of thedivision event), moreover some models posses only autoreplicator moleculeswithout interaction between them while other models has either catalyticor inhibitory interaction between replicators
Dynamical criticality: overview and open questions
Full text linkSystems that exhibit complex behaviours are often found in a particular dynamical condition, poised between order and disorder. This observation is at the core of the so-called criticality hypothesis, which states that systems in a dynamical regime between order and disorder attain the highest level of computational capabilities and achieve an optimal trade-off between robustness and flexibility. Recent results in cellular and evolutionary biology, neuroscience and computer science have revitalised the interest in the criticality hypothesis, emphasising its role as a viable candidate general law in adaptive complex systems. This paper provides an overview of the works on dynamical criticality that are - to the best of our knowledge - particularly relevant for the criticality hypothesis. The authors review the main contributions concerning dynamics and information processing at the edge of chaos, and illustrate the main achievements in the study of critical dynamics in biological systems. Finally, the authors discuss open questions and propose an agenda for future work
Synchronization phenomena in non linear protocell model
No full textIn this paper we study general protocell models aiming to un-derstand the synchronization phenomenon of genetic material and containerproductions, a necessary condition to ensure sustainable growth in protocellsand eventually leading to Darwinian evolution when applied to a populationof protocells.Synchronization has been proved to be an emergent property in many rel-evant protocell models in the class of the so–called Surface Reaction Models,assuming both linear and nonlinear dynamics for the involved chemical reac-tions
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