TY - JOUR
T1 - The evolutionary dynamics of metabolic protocells
AU - Pechuan, Ximo
AU - Puzio, Raymond
AU - Bergman, Aviv
N1 - Funding Information:
Funding for AB was provided by NIH R01-CA164468-01 https://www.nih.gov/ and NIH R01-DA033788 https://www.nih.gov. Funding for RP and XP was provided by the EON seed grant from the ELSI Origins http://eon.elsi.jp/eon-seed-grants-now-available/Network project. Funding for XP was provided by Fulbright Spain https://fulbright.es/ and Fundacion Ramon Areces http://www.fundacionareces.es/fundacionareces/. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The authors would like to thank Cameron Smith, Daniel Biro and Maryl Lambros for their helpful comments.
Publisher Copyright:
© 2018 Pechuan et al. http://creativecommons.org/licenses/by/4.0/.
PY - 2018/7
Y1 - 2018/7
N2 - Protocell multilevel selection models have been proposed to study the evolutionary dynamics of vesicles encapsulating a set of replicating, competing and mutating sequences. The frequency of the different sequence types determines protocell survival through a fitness function. One of the defining features of these models is the genetic load generated when the protocell divides and its sequences are assorted between the offspring vesicles. However, these stochastic assortment effects disappear when the redundancy of each sequence type is sufficiently high. The fitness dependence of the vesicle with its sequence content is usually defined without considering a realistic account on how the lower level dynamics would specify the protocell fitness. Here, we present a protocell model with a fitness function determined by the output flux of a simple metabolic network with the aim of understanding how the evolution of both kinetic and topological features of metabolism would have been constrained by the particularities of the protocell evolutionary dynamics. In our model, the sequences inside the vesicle are both the carriers of information and Michaelis-Menten catalysts exhibiting saturation. We found that the saturation of the catalysts controlling the metabolic fluxes, achievable by modifying the kinetic or stoichiometric parameters, provides a mechanism to ameliorate the assortment load by increasing the redundancy of the catalytic sequences required to achieve the maximum flux. Regarding the network architecture, we conclude that combinations of parallel network motifs and bimolecular catalysts are a robust way to increase the complexity of the metabolism enclosed by the protocell.
AB - Protocell multilevel selection models have been proposed to study the evolutionary dynamics of vesicles encapsulating a set of replicating, competing and mutating sequences. The frequency of the different sequence types determines protocell survival through a fitness function. One of the defining features of these models is the genetic load generated when the protocell divides and its sequences are assorted between the offspring vesicles. However, these stochastic assortment effects disappear when the redundancy of each sequence type is sufficiently high. The fitness dependence of the vesicle with its sequence content is usually defined without considering a realistic account on how the lower level dynamics would specify the protocell fitness. Here, we present a protocell model with a fitness function determined by the output flux of a simple metabolic network with the aim of understanding how the evolution of both kinetic and topological features of metabolism would have been constrained by the particularities of the protocell evolutionary dynamics. In our model, the sequences inside the vesicle are both the carriers of information and Michaelis-Menten catalysts exhibiting saturation. We found that the saturation of the catalysts controlling the metabolic fluxes, achievable by modifying the kinetic or stoichiometric parameters, provides a mechanism to ameliorate the assortment load by increasing the redundancy of the catalytic sequences required to achieve the maximum flux. Regarding the network architecture, we conclude that combinations of parallel network motifs and bimolecular catalysts are a robust way to increase the complexity of the metabolism enclosed by the protocell.
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U2 - 10.1371/journal.pcbi.1006265
DO - 10.1371/journal.pcbi.1006265
M3 - Article
C2 - 30028838
AN - SCOPUS:85050972388
SN - 1553-734X
VL - 14
JO - PLoS Computational Biology
JF - PLoS Computational Biology
IS - 7
M1 - e1006265
ER -