Time-scale separation and stochasticity conspire to impact phenotypic dynamics in the canonical and inverted Bacillus subtilis core genetic regulation circuits
Lijie Hao, Zhuoqin Yang, Marc Turcotte
Time-scale separation and stochasticity conspire to impact phenotypic dynamics in the canonical and inverted Bacillus subtilis core genetic regulation circuits
Background: In this work, we study two seemingly unrelated aspects of core genetic nonlinear dynamical control of the competence phenotype in Bacillus subtilis, a common Gram-positive bacterium living in the soil.
Methods: We focus on hitherto unchartered aspects of the dynamics by exploring the effect of time-scale separation between transcription and translation and, as well, the effect of intrinsic molecular stochasticity. We consider these aspects of regulatory control as two possible evolutionary handles.
Results: Hence, using theory and computations, we study how the onset of oscillations breaks the excitability-based competence phenotype in two topologically close evolutionary-competing circuits: the canonical “wild-type” regulation circuit selected by Evolution and the corresponding indirect-feedback inverted circuit that failed to be selected by Evolution, as was shown elsewhere, due to dynamical reasons.
Conclusions: Relying on in-silico perturbation of the living state, we show that the canonical core genetic regulation of excitability-based competence is more robust against switching to phenotype-breaking oscillations than the inverted feedback organism. We show how this is due to time-scale separation and stochasticity.
Bacillus subtilis / competence / gene regulation / deterministic dynamics / stochastic dynamics
[1] |
Eldar, A. and Elowitz, M. B. (2010) Functional roles for noise in genetic circuits. Nature, 467, 167–173
CrossRef
Pubmed
Google scholar
|
[2] |
Cağatay, T., Turcotte, M., Elowitz, M. B., Garcia-Ojalvo, J. and Süel, G. M. (2009) Architecture-dependent noise discriminates functionally analogous differentiation circuits. Cell, 139, 512–522
CrossRef
Pubmed
Google scholar
|
[3] |
SchultzD., Ben Jacob E., OnuchicJ. N. and WolynesP. G. (2007) Molecular level stochastic model for competence cycles in Bacillus subtilis. Proc. Natl. Acad. Sci. USA., 104, 17582–17587
CrossRef
Pubmed
Google scholar
|
[4] |
TurcotteM., Garcia-Ojalvo J. and SüelG. M. (2008) A genetic timer through noise-induced stabilization of an unstable state. Proc. Natl. Acad. Sci. USA, 105, 15732–15737.
CrossRef
Pubmed
Google scholar
|
[5] |
SüelG. M., Garcia-Ojalvo J., LibermanL. M. and ElowitzM. B. (2006) An excitable gene regulatory circuit induces transient cellular differentiation. Nature, 440, 545–550.
CrossRef
Pubmed
Google scholar
|
[6] |
SüelG. M., Kulkarni R. P., DworkinJ., Garcia-OjalvoJ. and ElowitzM. B. (2007) Tunability and noise dependence in differentiation dynamics. Science, 315, 1716–1719.
CrossRef
Pubmed
Google scholar
|
[7] |
DubnauD. (1999) DNA uptake in bacteria. Annu. Rev. Microbiol., 53, 217–244.
CrossRef
Pubmed
Google scholar
|
[8] |
GrossmanA. D. (1995) Genetic networks controlling the initiation of sporulation and the development of genetic competence in Bacillus subtilis. Annu. Rev. Genet., 29, 477–508.
CrossRef
Pubmed
Google scholar
|
[9] |
DubnauD. (1991) Genetic competence in Bacillus subtilis. Microbiol. Rev ., 55,395
|
[10] |
DubnauD. (1991) The regulation of genetic competence in Bacillus subtilis. Mol. Microbiol., 5, 11–18.
CrossRef
Pubmed
Google scholar
|
[11] |
MaW., Trusina A., El-SamadH., LimW. A. and TangC. (2009) Defining network topologies that can achieve biochemical adaptation. Cell, 138, 760–773.
CrossRef
Pubmed
Google scholar
|
[12] |
ZhangJ., Yuan Z., LiH. X. and ZhouT. (2010) Architecture-dependent robustness and bistability in a class of genetic circuits. Biophys. J., 99, 1034–1042.
CrossRef
Pubmed
Google scholar
|
[13] |
LevyE. D. (2010) A simple definition of structural regions in proteins and its use in analyzing interface evolution. J. Mol. Biol., 403, 660–670.
CrossRef
Pubmed
Google scholar
|
[14] |
KastritisP. L. and BonvinA. M. (2013) Molecular origins of binding affinity: seeking the Archimedean point. Curr. Opin. Struct. Biol., 23, 868–877.
CrossRef
Pubmed
Google scholar
|
[15] |
KastritisP. L., Rodrigues J. P. G. L., Folkers G. E., BoelensR. and BonvinA. M. J. J. (2014) Proteins feel more than they see: fine-tuning of binding affinity by properties of the non-interacting surface. J. Mol. Biol., 426, 2632–2652.
CrossRef
Pubmed
Google scholar
|
[16] |
RosanovaA., Colliva A., OsellaM. and CaselleM. (2017) Modelling the evolution of transcription factor binding preferences in complex eukaryotes. Sci. Rep., 7, 7596
CrossRef
Pubmed
Google scholar
|
[17] |
EchaveJ. and Wilke C. O. (2017) Biophysical models of protein evolution: understanding the patterns of evolutionary sequence divergence. Annu. Rev. Biophys., 46, 85–103.
CrossRef
Pubmed
Google scholar
|
[18] |
GillespieD. T. (1976) A general method for numerically simulating the stochastic time evolution of coupled chemical reactions. J. Comput. Phys., 22, 403–434.
CrossRef
Google scholar
|
[19] |
GillespieD. T. (1977) Exact stochastic simulation of coupled chemical reactions. J. Phys. Chem., 81, 2340–2361.
CrossRef
Google scholar
|
[20] |
GillespieD. T. (2001) Approximate accelerated stochastic simulation of chemically reacting systems. J. Chem. Phys., 115, 1716–1733.
CrossRef
Google scholar
|
[21] |
GillespieD. T. (1976) A general method for numerically simulating the stochastic time evolution of coupled chemical reactions. J. Comput. Phys., 22, 403–434.
CrossRef
Google scholar
|
[22] |
GillespieD. T. (1977) Exact stochastic simulation of coupled chemical reactions. J. Phys. Chem., 81, 2340–2361.
CrossRef
Google scholar
|
[23] |
GillespieD. T. (1991) Markov Processes: An Introduction for Physical Scientists. Manhattan: Academic Press
|
[24] |
GillespieD. T. (2007) Stochastic simulation of chemical kinetics. Annu. Rev. Phys. Chem., 58, 35–55.
CrossRef
Pubmed
Google scholar
|
[25] |
DoedelE. J. (1986) AUTO: software for continuation and bifurcation problems in ordinary differential equations. California Institute of Technology, 12, 791–802
|
[26] |
ErmentroutB. (2011) XPP-Aut
|
[27] |
ConradE. D. (2011) Oscill8
|
/
〈 | 〉 |