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<p>Diversity-generating retroelements (DGRs) are natural systems that accelerate the evolution of diverse bacterial functions through targeted hypermutation. We establish a method using DGRs coupled to recombineering (DGRec), which enables the diversification of any sequence of interest in <i>Escherichia</i> <i>coli</i>. Detailed characterization of reverse transcriptase sequence biases demonstrates how it maximizes the exploration of the sequence space while avoiding nonsense mutations. By leveraging the high error rate of the DGR reverse transcriptase at adenines, DGRec can efficiently diversify user-defined sequence windows of 50–200 bp. Mutations can be focused at specific positions, with rates reaching up to 1.38 × 10<sup>−2</sup> per base per generation, allowing up to 24 mutations to accumulate within a single target sequence after 48 h. We apply DGRec to phage λ host-range engineering, to the evolution of dCas9 variants and to accelerated evolution of specific nanobodies through a bacterial display setup. Lastly, we establish the feasibility of DGR-mediated mutagenesis in yeast by adapting a recombination and selection strategy previously developed for retrons.</p>

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Diversity-generating retroelements for programmable targeted hypermutagenesis

  • 期刊论文

  • 发表日期：

    2026年4月16日

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  • Paul Rochette,
  • Elena Lopez-Rodriguez,
  • David J. Wen,
  • Léo Régnier,
  • Catherine Fan,
  • Anna Maikova,
  • William Rostain,
  • Linhan Wang,
  • Imran Nooraddin,
  • Amandine Maire,
  • Paul Vittot,
  • Nathan Barrabes,
  • Karol Melissa Cerdas-Mejías,
  • Auguste Bouvier,
  • Thea Chrysostomou,
  • Orso Subrini,
  • Nicolas Wolff,
  • Rémi Monasson,
  • Simona Cocco,
  • Seth L. Shipman,
  • Raphael Laurenceau,
  • David Bikard

摘要

Diversity-generating retroelements (DGRs) are natural systems that accelerate the evolution of diverse bacterial functions through targeted hypermutation. We establish a method using DGRs coupled to recombineering (DGRec), which enables the diversification of any sequence of interest in Escherichia coli. Detailed characterization of reverse transcriptase sequence biases demonstrates how it maximizes the exploration of the sequence space while avoiding nonsense mutations. By leveraging the high error rate of the DGR reverse transcriptase at adenines, DGRec can efficiently diversify user-defined sequence windows of 50–200 bp. Mutations can be focused at specific positions, with rates reaching up to 1.38 × 10−2 per base per generation, allowing up to 24 mutations to accumulate within a single target sequence after 48 h. We apply DGRec to phage λ host-range engineering, to the evolution of dCas9 variants and to accelerated evolution of specific nanobodies through a bacterial display setup. Lastly, we establish the feasibility of DGR-mediated mutagenesis in yeast by adapting a recombination and selection strategy previously developed for retrons.