Literature DB >> 26165453

Primordial evolvability: Impasses and challenges.

Vera Vasas1, Chrisantha Fernando2, András Szilágyi3, István Zachár4, Mauro Santos5, Eörs Szathmáry6.   

Abstract

While it is generally agreed that some kind of replicating non-living compounds were the precursors of life, there is much debate over their possible chemical nature. Metabolism-first approaches propose that mutually catalytic sets of simple organic molecules could be capable of self-replication and rudimentary chemical evolution. In particular, the graded autocatalysis replication domain (GARD) model, depicting assemblies of amphiphilic molecules, has received considerable interest. The system propagates compositional information across generations and is suggested to be a target of natural selection. However, evolutionary simulations indicate that the system lacks selectability (i.e. selection has negligible effect on the equilibrium concentrations). We elaborate on the lessons learnt from the example of the GARD model and, more widely, on the issue of evolvability, and discuss the implications for similar metabolism-first scenarios. We found that simple incorporation-type chemistry based on non-covalent bonds, as assumed in GARD, is unlikely to result in alternative autocatalytic cycles when catalytic interactions are randomly distributed. An even more serious problem stems from the lognormal distribution of catalytic factors, causing inherent kinetic instability of such loops, due to the dominance of efficiently catalyzed components that fail to return catalytic aid. Accordingly, the dynamics of the GARD model is dominated by strongly catalytic, but not auto-catalytic, molecules. Without effective autocatalysis, stable hereditary propagation is not possible. Many repetitions and different scaling of the model come to no rescue. Despite all attempts to show the contrary, the GARD model is not evolvable, in contrast to reflexively autocatalytic networks, complemented by rare uncatalyzed reactions and compartmentation. The latter networks, resting on the creation and breakage of chemical bonds, can generate novel ('mutant') autocatalytic loops from a given set of environmentally available compounds. Real chemical reactions that make or break covalent bonds, rather than mere incorporation of components, are necessary for open-ended evolvability. The issue of whether or not several concrete chemical systems (rather than singular curiosities) could realize reflexively autocatalytic macromolecular networks will ultimately determine the relevance of metabolism-first approaches to the origin of life, as stepping stones towards true open-endedness that requires the combination of rich combinatorial chemistry controlled by information stored in template replicators.
Copyright © 2015 Elsevier Ltd. All rights reserved.

Keywords:  Autocatalysis; Catalytic reaction networks; Chemical evolution; Collectively autocatalytic sets; Evolvability; GARD model; Metabolism-first theories; Origin of life

Mesh:

Year:  2015        PMID: 26165453     DOI: 10.1016/j.jtbi.2015.06.047

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  7 in total

1.  Foldamer hypothesis for the growth and sequence differentiation of prebiotic polymers.

Authors:  Elizaveta Guseva; Ronald N Zuckermann; Ken A Dill
Journal:  Proc Natl Acad Sci U S A       Date:  2017-08-22       Impact factor: 11.205

Review 2.  Systems protobiology: origin of life in lipid catalytic networks.

Authors:  Doron Lancet; Raphael Zidovetzki; Omer Markovitch
Journal:  J R Soc Interface       Date:  2018-07       Impact factor: 4.118

Review 3.  Ecology and Evolution in the RNA World Dynamics and Stability of Prebiotic Replicator Systems.

Authors:  András Szilágyi; István Zachar; István Scheuring; Ádám Kun; Balázs Könnyű; Tamás Czárán
Journal:  Life (Basel)       Date:  2017-11-27

4.  Predicting species emergence in simulated complex pre-biotic networks.

Authors:  Omer Markovitch; Natalio Krasnogor
Journal:  PLoS One       Date:  2018-02-15       Impact factor: 3.240

5.  Multilevel selection as Bayesian inference, major transitions in individuality as structure learning.

Authors:  Dániel Czégel; István Zachar; Eörs Szathmáry
Journal:  R Soc Open Sci       Date:  2019-08-28       Impact factor: 2.963

Review 6.  Is pre-Darwinian evolution plausible?

Authors:  Marc Tessera
Journal:  Biol Direct       Date:  2018-09-21       Impact factor: 4.540

7.  Mathematical modeling reveals spontaneous emergence of self-replication in chemical reaction systems.

Authors:  Yu Liu; David J T Sumpter
Journal:  J Biol Chem       Date:  2018-10-03       Impact factor: 5.157

  7 in total

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