Literature DB >> 34162839

The adaptive landscape of a metallo-enzyme is shaped by environment-dependent epistasis.

Dave W Anderson1,2, Florian Baier3, Gloria Yang3, Nobuhiko Tokuriki4.   

Abstract

Enzymes can evolve new catalytic activity when environmental changes present them with novel substrates. Despite this seemingly straightforward relationship, factors other than the direct catalytic target can also impact adaptation. Here, we characterize the catalytic activity of a recently evolved bacterial methyl-parathion hydrolase for all possible combinations of the five functionally relevant mutations under eight different laboratory conditions (in which an alternative divalent metal is supplemented). The resultant adaptive landscapes across this historical evolutionary transition vary in terms of both the number of "fitness peaks" as well as the genotype(s) at which they are found as a result of genotype-by-environment interactions and environment-dependent epistasis. This suggests that adaptive landscapes may be fluid and molecular adaptation is highly contingent not only on obvious factors (such as catalytic targets), but also on less obvious secondary environmental factors that can direct it towards distinct outcomes.

Entities:  

Year:  2021        PMID: 34162839     DOI: 10.1038/s41467-021-23943-x

Source DB:  PubMed          Journal:  Nat Commun        ISSN: 2041-1723            Impact factor:   14.919


  51 in total

1.  How mutational epistasis impairs predictability in protein evolution and design.

Authors:  Charlotte M Miton; Nobuhiko Tokuriki
Journal:  Protein Sci       Date:  2016-01-22       Impact factor: 6.725

2.  Molecular signatures of selection on reproductive character displacement of flower color in Phlox drummondii.

Authors:  Robin Hopkins; Donald A Levin; Mark D Rausher
Journal:  Evolution       Date:  2011-10-05       Impact factor: 3.694

3.  Darwinian evolution can follow only very few mutational paths to fitter proteins.

Authors:  Daniel M Weinreich; Nigel F Delaney; Mark A Depristo; Daniel L Hartl
Journal:  Science       Date:  2006-04-07       Impact factor: 47.728

4.  Quantitative Description of a Protein Fitness Landscape Based on Molecular Features.

Authors:  María-Rocío Meini; Pablo E Tomatis; Daniel M Weinreich; Alejandro J Vila
Journal:  Mol Biol Evol       Date:  2015-03-12       Impact factor: 16.240

5.  Visualizing fitness landscapes.

Authors:  David M McCandlish
Journal:  Evolution       Date:  2011-03-01       Impact factor: 3.694

6.  Intramolecular epistasis and the evolution of a new enzymatic function.

Authors:  Sajid Noor; Matthew C Taylor; Robyn J Russell; Lars S Jermiin; Colin J Jackson; John G Oakeshott; Colin Scott
Journal:  PLoS One       Date:  2012-06-29       Impact factor: 3.240

7.  Stepwise acquisition of pyrimethamine resistance in the malaria parasite.

Authors:  Elena R Lozovsky; Thanat Chookajorn; Kyle M Brown; Mallika Imwong; Philip J Shaw; Sumalee Kamchonwongpaisan; Daniel E Neafsey; Daniel M Weinreich; Daniel L Hartl
Journal:  Proc Natl Acad Sci U S A       Date:  2009-07-08       Impact factor: 11.205

8.  Higher-order epistasis shapes the fitness landscape of a xenobiotic-degrading enzyme.

Authors:  Gloria Yang; Dave W Anderson; Florian Baier; Elias Dohmen; Nansook Hong; Paul D Carr; Shina Caroline Lynn Kamerlin; Colin J Jackson; Erich Bornberg-Bauer; Nobuhiko Tokuriki
Journal:  Nat Chem Biol       Date:  2019-10-21       Impact factor: 15.040

9.  Quantitative exploration of the catalytic landscape separating divergent plant sesquiterpene synthases.

Authors:  Paul E O'Maille; Arthur Malone; Nikki Dellas; B Andes Hess; Lidia Smentek; Iseult Sheehan; Bryan T Greenhagen; Joe Chappell; Gerard Manning; Joseph P Noel
Journal:  Nat Chem Biol       Date:  2008-09-07       Impact factor: 15.040

10.  Long-term experimental evolution in Escherichia coli. XI. Rejection of non-transitive interactions as cause of declining rate of adaptation.

Authors:  J Arjan G M de Visser; Richard E Lenski
Journal:  BMC Evol Biol       Date:  2002-10-30       Impact factor: 3.260

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