Abstract
The so-called Ribocell (ribozymes-based cell) is a theoretical cellular model that has been proposed some years ago as a possible minimal cell prototype. It consists in a self-replicating minimum RNA genome coupled with a self-reproducing lipid vesicle compartment. This model assumes the existence of two hypothetical ribozymes one able to catalyze the conversion of molecular precursors into lipids and the second one able to replicate RNA strands. Therefore, in an environment rich both of lipid precursors and activated nucleotides, the ribocell can self-reproduce if the genome self-replication and the compartment self-reproduction mechanisms are somehow synchronized. The aim of this contribution is to explore the feasibility of this model with in silico simulations using kinetic parameters available in literature.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
Of course a cell can also die for not optimal external conditions.
- 2.
The underlying assumption of the deterministic approach is that all vesicles have the same time behavior in average.
- 3.
The system state density probability ℘(x, t) is defined so that the product ℘(x, t)dt gives the probability to find the system in the state x at the time interval [t, t + dt].
- 4.
References
Ao P (2005) Metabolic network modelling: including stochastic effects. Comput Chem Engin 29:2297–2303
Chen IA, Roberts RW, Szostak JW (2004) The emergence of competition between model protocells. Science 305:1474–1476
Christensen U (2007) Thermodynamic and kinetic characterization of duplex formation between 2’-O, 4’-C-Methylene-modified Oligoribonucleotides. DNA RNA Biosci Rep 27:327–333
Gillespie DT (1976) A general method for numerically simulating the stochastic time evolution of coupled chemical reactions. J Comput Phys 22:403–434
Gillespie DT (1977) Exact stochastic simulation of coupled chemical reactions. J Phys Chem 81:2340–2361
Gillespie DT (1992) Markov processes: an introduction for physical scientists. Academic Press, San Diego
Gillespie DT (2007) Stochastic simulation of chemical kinetics. Annu Rev Phys Chem 58:35–55
Gillespie DT (2009) Deterministic limit of the stochastic chemical kinetics. J Phys Chem 113:1640–1644
Lecca P (2007) Simulating the cellular passive transport of glucose using a time-dependent extension of Gillespie algorithm for stochastic pi-calculus. Int J Data Mim Bioinf 1:315–336
Li H, Cao Y, Petzold LR, Gillespie DT (2008) Algorithms and software for stochastic simulation of biochemical reacting systems. Biotechnol Prog 24:56–61
Lincoln TA, Joyce GF (2009) Self-sustained replication of an RNA enzyme. Science 323:1229–1232
Lu T, Volfson D, Tsimring L, Hasty J (2004) Cellular growth and division in the Gillespie algorithm. Syst Biol 1:121–128
Luisi PL (1998) About various definitions of life. Orig Life Evol Biosph 28:613–622
Luisi PL (2003) Autopoiesis: a review and a reappraisal. Naturwissensch 90:49–59
Mansy SS, Szostak JW (2008) Thermostability of model protocell membranes. PNAS 105:13351–13355
Mansy SS, Schrum JP et al (2008) Template directed synthesis of a genetic polymer in a model protocell. Nature 454:122–126
Mavelli F, Lerario M, Ruiz-Mirazo K (2008) ‘Environment’: a stochastic simulation platform to study protocell dynamics. In: Arabnia HR et al (eds) BIO-COMP’08 proceedings, vol II. CSREA Press, New York
Mavelli F, Piotto S (2006) Stochastic simulations of homogeneous chemically reacting systems. J Mol Struct 771:55–64
Mavelli F, Ruiz-Mirazo K (2007) Stochastic simulations of minimal self-reproducing cellular systems. Phil Trans Royal Soc B 362:1789–1802
Mavelli F, Ruiz-Mirazo K (2010) Environment: a computational platform to stochastically simulate self-replicating reacting vesicles. Phys Biol 7:036002
Mavelli F, Stano P (2010) Kinetic models for autopoietic chemical systems: role of fluctuations in homeostatic regime. Phys Biol 7:16010
McAdams HH, Arkin AP (1997) Stochastic mechanisms in gene expression. Proc Natl Acad Sci U S A 94:814–819
McQuarry DA (1975) Probability theory and stochastic processes. In: Henderson D (ed) Physical chemistry, an advanced treatise XIB. Academic Press, New York
Ruiz-Mirazo K, Mavelli F (2007) Simulation model for functionalized vesicles: lipid-peptide integration in minimal protocells. In: Almeida F (ed) Advances in artificial life. Springer, Berlin
Ruiz-Mirazo K, Mavelli F (2008) On the way towards basic autonomous systems: stochastic simulations of minimal lipid-peptide cells. Biosystems 91:374–387
Sacerdote MG, Szostak JW (2005) Semipermeable lipid bilayers exhibit diastereo-selectivity favoring ribose. PNAS 102:6004–6008
Samoilov M, Plyasunov S, Arkin AP (2005) Stochastic amplification and signaling in enzymatic futile cycles through noise-induced bistability with oscillations. Proc Natl Acad Sci USA 102:2310–2315
Stage-Zimmermann TK, Uhlenbeck OC (1998) Hammerhead ribozyme kinetics. RNA 4:875–889
Szostak JW, Bartel DP and Luisi PL (2001) Synthesizing life. Nature 409:387–390.
Tsoi PY, Yang M (2002) Surface plasmon resonance study of human polymerase β binding to DNA. Biochem J 361:317–325
Van Kampen NG (1981) Stochastic processes in physics and chemistry. Elsevier, Amsterdam
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer Netherlands
About this chapter
Cite this chapter
Mavelli, F. (2011). Theoretical Approaches to Ribocell Modeling. In: Luisi, P., Stano, P. (eds) The Minimal Cell. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-9944-0_14
Download citation
DOI: https://doi.org/10.1007/978-90-481-9944-0_14
Published:
Publisher Name: Springer, Dordrecht
Print ISBN: 978-90-481-9943-3
Online ISBN: 978-90-481-9944-0
eBook Packages: Biomedical and Life SciencesBiomedical and Life Sciences (R0)