211 research outputs found
A stochastic model of catalytic reaction networks in protocells
Protocells are supposed to have played a key role in the self-organizing
processes leading to the emergence of life. Existing models either (i) describe
protocell architecture and dynamics, given the existence of sets of
collectively self-replicating molecules for granted, or (ii) describe the
emergence of the aforementioned sets from an ensemble of random molecules in a
simple experimental setting (e.g. a closed system or a steady-state flow
reactor) that does not properly describe a protocell. In this paper we present
a model that goes beyond these limitations by describing the dynamics of sets
of replicating molecules within a lipid vesicle. We adopt the simplest possible
protocell architecture, by considering a semi-permeable membrane that selects
the molecular types that are allowed to enter or exit the protocell and by
assuming that the reactions take place in the aqueous phase in the internal
compartment. As a first approximation, we ignore the protocell growth and
division dynamics. The behavior of catalytic reaction networks is then
simulated by means of a stochastic model that accounts for the creation and the
extinction of species and reactions. While this is not yet an exhaustive
protocell model, it already provides clues regarding some processes that are
relevant for understanding the conditions that can enable a population of
protocells to undergo evolution and selection.Comment: 20 pages, 5 figure
A model of protocell based on the introduction of a semi-permeable membrane in a stochastic model of catalytic reaction networks
In this work we introduce some preliminary analyses on the role of a
semi-permeable membrane in the dynamics of a stochastic model of catalytic
reaction sets (CRSs) of molecules. The results of the simulations performed on
ensembles of randomly generated reaction schemes highlight remarkable
differences between this very simple protocell description model and the
classical case of the continuous stirred-tank reactor (CSTR). In particular, in
the CSTR case, distinct simulations with the same reaction scheme reach the
same dynamical equilibrium, whereas, in the protocell case, simulations with
identical reaction schemes can reach very different dynamical states, despite
starting from the same initial conditions.Comment: In Proceedings Wivace 2013, arXiv:1309.712
On RAF Sets and Autocatalytic Cycles in Random Reaction Networks
The emergence of autocatalytic sets of molecules seems to have played an
important role in the origin of life context. Although the possibility to
reproduce this emergence in laboratory has received considerable attention,
this is still far from being achieved. In order to unravel some key properties
enabling the emergence of structures potentially able to sustain their own
existence and growth, in this work we investigate the probability to observe
them in ensembles of random catalytic reaction networks characterized by
different structural properties. From the point of view of network topology, an
autocatalytic set have been defined either in term of strongly connected
components (SCCs) or as reflexively autocatalytic and food-generated sets
(RAFs). We observe that the average level of catalysis differently affects the
probability to observe a SCC or a RAF, highlighting the existence of a region
where the former can be observed, whereas the latter cannot. This parameter
also affects the composition of the RAF, which can be further characterized
into linear structures, autocatalysis or SCCs. Interestingly, we show that the
different network topology (uniform as opposed to power-law catalysis systems)
does not have a significantly divergent impact on SCCs and RAFs appearance,
whereas the proportion between cleavages and condensations seems instead to
play a role. A major factor that limits the probability of RAF appearance and
that may explain some of the difficulties encountered in laboratory seems to be
the presence of molecules which can accumulate without being substrate or
catalyst of any reaction.Comment: pp 113-12
Recursiveness, Switching, and Fluctuations in a Replicating Catalytic Network
A protocell model consisting of mutually catalyzing molecules is studied in
order to investigate how chemical compositions are transferred recursively
through cell divisions under replication errors. Depending on the path rate,
the numbers of molecules and species, three phases are found: fast switching
state without recursive production, recursive production, and itinerancy
between the above two states. The number distributions of the molecules in the
recursive states are shown to be log-normal except for those species that form
a core hypercycle, and are explained with the help of a heuristic argument.Comment: 4 pages (with 7 figures (6 color)), submitted to PR
Multistable protocells can aid the evolution of prebiotic autocatalytic sets
We present a simple mathematical model that captures the evolutionary
capabilities of a prebiotic compartment or protocell. In the model the
protocell contains an autocatalytic set whose chemical dynamics is coupled to
the growth-division dynamics of the compartment. Bistability in the dynamics of
the autocatalytic set results in a protocell that can exist with two distinct
growth rates. Stochasticity in chemical reactions plays the role of mutations
and causes transitions from one growth regime to another. We show that the
system exhibits `natural selection', where a `mutant' protocell in which the
autocatalytic set is active arises by chance in a population of inactive
protocells, and then takes over the population because of its higher growth
rate or `fitness'. The work integrates three levels of dynamics: intracellular
chemical, single protocell, and population (or ecosystem) of protocells..Comment: 28 pages, 12 figures, includes Supplementary Materia
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