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Stochastic simulations of minimal cells: the Ribocell model
BACKGROUND: Over the last two decades, lipid compartments (liposomes, lipid-coated droplets) have been extensively used as in vitro "minimal" cell models. In particular, simple and complex biomolecular reactions have been carried out inside these self-assembled micro- and nano-sized compar...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2012
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3303737/ https://www.ncbi.nlm.nih.gov/pubmed/22536956 http://dx.doi.org/10.1186/1471-2105-13-S4-S10 |
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author | Mavelli, Fabio |
author_facet | Mavelli, Fabio |
author_sort | Mavelli, Fabio |
collection | PubMed |
description | BACKGROUND: Over the last two decades, lipid compartments (liposomes, lipid-coated droplets) have been extensively used as in vitro "minimal" cell models. In particular, simple and complex biomolecular reactions have been carried out inside these self-assembled micro- and nano-sized compartments, leading to the synthesis of RNA and functional proteins inside liposomes. Despite this experimental progress, a detailed physical understanding of the underlying dynamics is missing. In particular, the combination of solute compartmentalization, reactivity and stochastic effects has not yet been clarified. A combination of experimental and computational approaches can reveal interesting mechanisms governing the behavior of micro compartmentalized systems, in particular by highlighting the intrinsic stochastic diversity within a population of "synthetic cells". METHODS: In this context, we have developed a computational platform called ENVIRONMENT suitable for studying the stochastic time evolution of reacting lipid compartments. This software - which implements a Gillespie Algorithm - is an improvement over a previous program that simulated the stochastic time evolution of homogeneous, fixed-volume, chemically reacting systems, extending it to more general conditions in which a collection of similar such systems interact and change over the course of time. In particular, our approach is focused on elucidating the role of randomness in the time behavior of chemically reacting lipid compartments, such as micelles, vesicles or micro emulsions, in regimes where random fluctuations due to the stochastic nature of reacting events can lead an open system towards unexpected time evolutions. RESULTS: This paper analyses the so-called Ribocell (RNA-based cell) model. It consists in a hypothetical minimal cell based on a self-replicating minimum RNA genome coupled with a self-reproducing lipid vesicle compartment. This model assumes the existence of two ribozymes, one able to catalyze the conversion of molecular precursors into lipids and the second able to replicate RNA strands. The aim of this contribution is to explore the feasibility of this hypothetical minimal cell. By deterministic kinetic analysis, the best external conditions to observe synchronization between genome self-replication and vesicle membrane reproduction are determined, while its robustness to random fluctuations is investigated using stochastic simulations, and then discussed. |
format | Online Article Text |
id | pubmed-3303737 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-33037372012-03-15 Stochastic simulations of minimal cells: the Ribocell model Mavelli, Fabio BMC Bioinformatics Research BACKGROUND: Over the last two decades, lipid compartments (liposomes, lipid-coated droplets) have been extensively used as in vitro "minimal" cell models. In particular, simple and complex biomolecular reactions have been carried out inside these self-assembled micro- and nano-sized compartments, leading to the synthesis of RNA and functional proteins inside liposomes. Despite this experimental progress, a detailed physical understanding of the underlying dynamics is missing. In particular, the combination of solute compartmentalization, reactivity and stochastic effects has not yet been clarified. A combination of experimental and computational approaches can reveal interesting mechanisms governing the behavior of micro compartmentalized systems, in particular by highlighting the intrinsic stochastic diversity within a population of "synthetic cells". METHODS: In this context, we have developed a computational platform called ENVIRONMENT suitable for studying the stochastic time evolution of reacting lipid compartments. This software - which implements a Gillespie Algorithm - is an improvement over a previous program that simulated the stochastic time evolution of homogeneous, fixed-volume, chemically reacting systems, extending it to more general conditions in which a collection of similar such systems interact and change over the course of time. In particular, our approach is focused on elucidating the role of randomness in the time behavior of chemically reacting lipid compartments, such as micelles, vesicles or micro emulsions, in regimes where random fluctuations due to the stochastic nature of reacting events can lead an open system towards unexpected time evolutions. RESULTS: This paper analyses the so-called Ribocell (RNA-based cell) model. It consists in a hypothetical minimal cell based on a self-replicating minimum RNA genome coupled with a self-reproducing lipid vesicle compartment. This model assumes the existence of two ribozymes, one able to catalyze the conversion of molecular precursors into lipids and the second able to replicate RNA strands. The aim of this contribution is to explore the feasibility of this hypothetical minimal cell. By deterministic kinetic analysis, the best external conditions to observe synchronization between genome self-replication and vesicle membrane reproduction are determined, while its robustness to random fluctuations is investigated using stochastic simulations, and then discussed. BioMed Central 2012-03-28 /pmc/articles/PMC3303737/ /pubmed/22536956 http://dx.doi.org/10.1186/1471-2105-13-S4-S10 Text en Copyright ©2012 Mavelli licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Mavelli, Fabio Stochastic simulations of minimal cells: the Ribocell model |
title | Stochastic simulations of minimal cells: the Ribocell model |
title_full | Stochastic simulations of minimal cells: the Ribocell model |
title_fullStr | Stochastic simulations of minimal cells: the Ribocell model |
title_full_unstemmed | Stochastic simulations of minimal cells: the Ribocell model |
title_short | Stochastic simulations of minimal cells: the Ribocell model |
title_sort | stochastic simulations of minimal cells: the ribocell model |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3303737/ https://www.ncbi.nlm.nih.gov/pubmed/22536956 http://dx.doi.org/10.1186/1471-2105-13-S4-S10 |
work_keys_str_mv | AT mavellifabio stochasticsimulationsofminimalcellstheribocellmodel |