Cited by 13Origins and Evolution of LifeDNA and Biological ComputingRNA and protein synthesis mechanisms

Two Different Template Replicators Coexisting in the Same Protocell: Stochastic Simulation of an Extended Chemoton Model

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Zachar, István, Fedor, Anna, Szathmáry, Eörs·2011·PLoS ONE

Abstract

The simulation of complex biochemical systems, consisting of intertwined subsystems, is a challenging task in computational biology. The complex biochemical organization of the cell is effectively modeled by the minimal cell model called chemoton, proposed by Gánti. Since the chemoton is a system consisting of a large but fixed number of interacting molecular species, it can effectively be implemented in a process algebra-based language such as the BlenX programming language. The stochastic model behaves comparably to previous continuous deterministic models of the chemoton. Additionally to the well-known chemoton, we also implemented an extended version with two competing template cycles. The new insight from our study is that the coupling of reactions in the chemoton ensures that these templates coexist providing an alternative solution to Eigen's paradox. Our technical innovation involves the introduction of a two-state switch to control cell growth and division, thus providing an example for hybrid methods in BlenX. Further developments to the BlenX language are suggested in the Appendix.

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  • A stochastic implementation of the chemoton model, approximating the SCM, proves that two different competing template replicators can coexist in a protocell.

    “A stochastic implementation of the chemoton model (approximating the SCM) proves that two different competing template replicators can coexist in a protocell [103].”

    From Ecology and Evolution in the RNA World Dynamics and Stability of Prebiotic Replicator Systems (2017) · cites this paper as [103]

    The Introduction and Results and Discussion > Conclusions report a stochastic chemoton implementation in which two competing templates coexist through coupled chemical reactions. The Introduction describes the stochastic corrector model (SCM) as a different solution based on competition between reproducing compartments; it does not characterize this implementation as an approximation of the SCM. No page numbers are available in our copy. (LLM, conf=0.84)

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Research works printed but not linked: 11

  1. [4]Gánti T 2003 The Principles of Life Oxford, USA Oxford University Press
  2. [7]Ciocchetta F 2008 The BlenX language with biological transactions. Priami C 114 152 Transactions on Computational Systems Biology IX Lecture Notes in Computer Science
  3. [8]Livi CM Jordán F Lecca P Okey TA 2011 Identifying key species in ecosystems with stochastic sensitivity analysis. Ecological Modelling in press
  4. [9]Gillespie DT 1977 Exact stochastic simulation of coupled chemical reactions. The Journal of Physical Chemistry 81 2340 2361
  5. [11]Eigen M 1971 Self-organization of matter and the evolution of biological macromolecules. Naturwissenschaften 58 465 523 4942363
  6. [12]Eigen M Schuster P 1978 The Hypercycle. A Principle of Natural Self-Organization. Part C: The Realistic Hypercycle. Naturwissenschaften 65 341 369 593400
  7. [14]Fernando C di Paolo E 2004 The chemoton: A model for the origin of long RNA templates. Pollack J Bedau M Husbands P T I Watson R Cambridge, MA MIT Press 1 8
  8. [15]Mavelli F Ruiz-Mirazo K 2007 Stochastic simulations of minimal self-reproducing cellular systems. Philosophical Transactions of the Royal Society B: Biological Sciences 362 1789 1802 PMC2515193 17510021
  9. [18]Fernando C Kiedrowski GV Szathmáry E 2007 A stochastic model of nonenzymatic nucleic acid replication: “Elongators” sequester replicators. Journal of Molecular Evolution 64 572 585 17437149
  10. [20]Munteanu A Solé RV 2006 Phenotypic diversity and chaos in a minimal cell model. Journal of Theoretical Biology 240 434 442 16330052
  11. [21]Segbroeck SV Nowe A Lenaerts T 2009 Stochastic Simulation of the Chemoton. Artificial Life 15 213 226 19199383

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Authors
Zachar, I., Fedor, A., & Szathmáry, E.
Affiliations
Eötvös Loránd University (HU)
Corresponding author
Fedor, Anna
Venue
PLoS ONE
Published
2011-07-19
Volume
6
Issue
7
Pages
e21380
ISSN
1932-6203 (ISSN-L)
OpenAlex
W2050543969
Cited by
13
References
1
Citations by year
2026: 1 · 2025: 1 · 2022: 2 · 2020: 1 · 2017: 3 · 2016: 1 · 2015: 1 · 2014: 1 · 2012: 2
FWCI
0.51
Type
journal article
Language
en
Open access
Locations
  • PLoS ONE (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Repository of the Academy's Library (Library of the Hungarian Academy of Sciences) (acceptedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • ELTE Digital Institutional Repository (EDIT) (Eötvös Loránd University) (submittedVersion, other-oa)
Funders
  • European Commission (225167, 2007–2013, FP7 2007-2013, FP7/2007)
  • Hungarian Scientific Research Fund (NAP 2005/KCKHA005)
  • Nemzeti Kutatási és Technológiai Hivatal (KCKHA005, NAP 2005/KCKHA005)
Topics
  • Physical Sciences › Physics and Astronomy › Astronomy and Astrophysics › Origins and Evolution of Life
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › DNA and Biological Computing
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
Keywords
chemoton, protocells, stochastic simulation, process algebra, hybrid simulation, cell growth and division, minimal cell model, origin of life
MeSH terms
Computer Simulation, Models, Biological, Programming Languages, Stochastic Processes, Artificial Cells

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