Literature DB >> 32353078

Evolutionary innovation using EDGE, a system for localized elevated mutagenesis.

Xiao Yi1, Romas Kazlauskas1,2, Michael Travisano1,3.   

Abstract

Mutations arising across the whole genome can hinder the emergence of evolutionary innovation required for adaptation because many mutations are deleterious. This trade-off is overcome by elevated mutagenesis to localized loci. Examples include phase variation and diversity-generating retroelements. However, these mechanisms are rare in nature; and all have narrow mutational spectra limiting evolutionary innovation. Here, we engineer a platform of Experimental Designed Genic Evolution (EDGE) to study the potential for evolutionary novelty at a single locus. Experimental evolution with EDGE shows that bacterial resistance to a novel antibiotic readily evolves, provided that elevated mutagenesis is focused on a relevant gene. A model is proposed to account for the cost and benefit of such single loci to adaptation in a changing environment and explains their high mutation rates, limited innovation, and the rarity of localized mutagenesis in nature. Overall, our results suggest that localized mutation systems can facilitate continuing adaptive evolution without necessarily restricting the spectrum of mutations. EDGE has utility in dissecting the complex process of adaptation with its localized, efficient evolution.

Entities:  

Year:  2020        PMID: 32353078     DOI: 10.1371/journal.pone.0232330

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


  2 in total

1.  Analysis of lineage-specific protein family variability in prokaryotes combined with evolutionary reconstructions.

Authors:  Svetlana Karamycheva; Yuri I Wolf; Erez Persi; Eugene V Koonin; Kira S Makarova
Journal:  Biol Direct       Date:  2022-08-30       Impact factor: 7.173

2.  Plasmid hypermutation using a targeted artificial DNA replisome.

Authors:  Xiao Yi; Joleen Khey; Romas J Kazlauskas; Michael Travisano
Journal:  Sci Adv       Date:  2021-07-16       Impact factor: 14.136

  2 in total

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