Abstract
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.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$32.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$259.00 per year
only $21.58 per issue
Buy this article
- Purchase on SpringerLink
- Instant access to the full article PDF.
USD 39.95
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
Data availability
Illumina sequencing data were deposited to the Sequence Read Archive under Bioproject PRJNA1140560.
Code availability
Software used to analyze the data is available as a Python package (https://github.com/dbikard/dgrec). Jupyter notebooks showing the analyses of the manuscript are also available (https://gitlab.pasteur.fr/dbikard/dgrec_analysis).
References
Packer, M. S. & Liu, D. R. Methods for the directed evolution of proteins. Nat. Rev. Genet. 16, 379–394 (2015).
Lynch, M. Evolution of the mutation rate. Trends Genet. 26, 345–352 (2010).
Morrison, M. S., Podracky, C. J. & Liu, D. R. The developing toolkit of continuous directed evolution. Nat. Chem. Biol. 16, 610–619 (2020).
Molina, R. S. et al. In vivo hypermutation and continuous evolution. Nat. Rev. Methods Primers 2, 36 (2022).
Ravikumar, A., Arzumanyan, G. A., Obadi, M. K. A., Javanpour, A. A. & Liu, C. C. Scalable, continuous evolution of genes at mutation rates above genomic error thresholds. Cell 175, 1946–1957 (2018).
Tian, R. et al. Engineered bacterial orthogonal DNA replication system for continuous evolution. Nat. Chem. Biol. 19, 1504–1512 (2023).
Tian, R. et al. Establishing a synthetic orthogonal replication system enables accelerated evolution in E. coli. Science 383, 421–426 (2024).
Halperin, S. O. et al. CRISPR-guided DNA polymerases enable diversification of all nucleotides in a tunable window. Nature 560, 248–252 (2018).
Hurtado, J. E. et al. Nickase fidelity drives EvolvR-mediated diversification in mammalian cells. Nat. Commun. 16, 3723 (2025).
Moore, C. L., Papa, L. J. III & Shoulders, M. D. A processive protein chimera introduces mutations across defined DNA regions in vivo. J. Am. Chem. Soc. 140, 11560–11564 (2018).
Janeway, C. A., Jr, Travers, P., Walport, M. & Shlomchik, M. J. The Generation of Diversity in Immunoglobulins 5th edn (Garland Science, 2001).
Liu, M. et al. Reverse transcriptase-mediated tropism switching in Bordetella bacteriophage. Science 295, 2091–2094 (2002).
Doulatov, S. et al. Tropism switching in Bordetella bacteriophage defines a family of diversity-generating retroelements. Nature 431, 476–481 (2004).
Paul, B. G. et al. Retroelement-guided protein diversification abounds in vast lineages of Bacteria and Archaea. Nat. Microbiol. 2, 1–7 (2017).
Roux, S. et al. Ecology and molecular targets of hypermutation in the global microbiome. Nat. Commun. 12, 3076 (2021).
Macadangdang, B. R. et al. Targeted protein evolution in the gut microbiome by diversity-generating retroelements. Science 390, eadv2111 (2025).
Wu, L. et al. Diversity-generating retroelements: natural variation, classification and evolution inferred from a large-scale genomic survey. Nucleic Acids Res. 46, 11–24 (2018).
Dai, W. et al. Three-dimensional structure of tropism-switching Bordetella bacteriophage. Proc. Natl Acad. Sci. USA 107, 4347–4352 (2010).
Guo, H. et al. Target site recognition by a diversity-generating retroelement. PLoS Genet. 7, e1002414 (2011).
Handa, S. et al. Template-assisted synthesis of adenine-mutagenized cDNA by a retroelement protein complex. Nucleic Acids Res. 46, 9711–9725 (2018).
McMahon, S. A. et al. The C-type lectin fold as an evolutionary solution for massive sequence variation. Nat. Struct. Mol. Biol. 12, 886–892 (2005).
Handa, S. et al. RNA control of reverse transcription in a diversity-generating retroelement. Nature 638, 1122–1129 (2025).
Macadangdang, B. R., Makanani, S. K. & Miller, J. F. Accelerated Evolution by Diversity-Generating Retroelements. Annu Rev Microbiol. 76, 389–411 (2022).
Handa, S., Paul, B. G., Miller, J. F., Valentine, D. L. & Ghosh, P. Conservation of the C-type lectin fold for accommodating massive sequence variation in archaeal diversity-generating retroelements. BMC Struct. Biol. 16, 13 (2016).
Farzadfard, F. & Lu, T. K. Genomically encoded analog memory with precise in vivo DNA writing in living cell populations. Science 346, 1256272 (2014).
Simon, A. J., Morrow, B. R. & Ellington, A. D. Retroelement-based genome editing and evolution. ACS Synth. Biol. 7, 2600–2611 (2018).
Schubert, M. G. et al. High-throughput functional variant screens via in vivo production of single-stranded DNA. Proc. Natl Acad. Sci. USA 118, e2018181118 (2021).
González-Delgado, A., Lopez, S. C., Rojas-Montero, M., Fishman, C. B. & Shipman, S. L. Simultaneous multi-site editing of individual genomes using retron arrays. Nat Chem Biol. 20, 1482–1492 (2024).
Fishman, C. B. et al. Continuous multiplexed phage genome editing using recombitrons. Nat Biotechnol. 43, 1299–1310 (2025).
Lopez, S. C., Crawford, K. D., Lear, S. K., Bhattarai-Kline, S. & Shipman, S. L. Precise genome editing across kingdoms of life using retron-derived DNA. Nat Chem Biol. 18, 199–206 (2022).
Wannier, T. M. et al. Improved bacterial recombineering by parallelized protein discovery. Proc. Natl Acad. Sci. USA 117, 13689–13698 (2020).
Naorem, S. S. et al. DGR mutagenic transposition occurs via hypermutagenic reverse transcription primed by nicked template RNA. Proc. Natl Acad. Sci. USA 114, E10187–E10195 (2017).
Kou, R. et al. Benefits and challenges with applying unique molecular identifiers in next generation sequencing to detect low frequency mutations. PLoS One 11, e0146638 (2016).
Handa, S., Reyna, A., Wiryaman, T. & Ghosh, P. Determinants of adenine-mutagenesis in diversity-generating retroelements. Nucleic Acids Res. 49, 1033–1045 (2021).
Wannier, T. M. et al. Recombineering and MAGE. Nat. Rev. Methods Primers 1, 7 (2021).
Fishman, C. B. et al. Continuous multiplexed phage genome editing using recombitrons. Nat. Biotechnol. 43, 1299–1310 (2025).
Lorenz, R. et al. ViennaRNA Package 2.0. Algorithms Mol. Biol. 6, 26 (2011).
Brockhurst, M. A., Koskella, B. & Zhang, Q. G. Bacteria–phage antagonistic coevolution and the implications for phage therapy. In Bacteriophages (eds Harper, D. R., Abedon, S. T., Burrowes, B. H. & McConville, M.L.) (Springer, 2017).
Borin, J. M. et al. Rapid bacteria–phage coevolution drives the emergence of multiscale networks. Science 382, 674–678 (2023).
Meyer, J. R. et al. Repeatability and contingency in the evolution of a key innovation in phage lambda. Science 335, 428–432 (2012).
Andrews, B. & Fields, S. Balance between promiscuity and specificity in phage λ host range. ISME J. 15, 2195–2205 (2021).
Ge, X. & Wang, J. Structural mechanism of bacteriophage lambda tail’s interaction with the bacterial receptor. Nat. Commun. 15, 4185 (2024).
Salema, V. et al. Selection of single domain antibodies from immune libraries displayed on the surface of E. coli cells with two β-domains of opposite topologies. PLoS ONE 8, e75126 (2013).
Salema, V. & Fernández, L. Á Escherichia coli surface display for the selection of nanobodies. Microb. Biotechnol. 10, 1468–1484 (2017).
Casasnovas, J. M. et al. Nanobodies protecting from lethal SARS-CoV-2 infection target receptor binding epitopes preserved in virus variants other than Omicron. Front. Immunol. 13, 863831 (2022).
Lopez, S. C., Crawford, K. D., Lear, S. K., Bhattarai-Kline, S. & Shipman, S. L. Precise genome editing across kingdoms of life using retron-derived DNA. Nat. Chem. Biol. 18, 199–206 (2022).
González-Delgado, A., Lopez, S. C., Rojas-Montero, M., Fishman, C. B. & Shipman, S. L. Simultaneous multi-site editing of individual genomes using retron arrays. Nat. Chem. Biol. 20, 1482–1492 (2024).
Ni, Y. et al. Reducing competition between msd and genomic DNA improves retron editing efficiency. EMBO Rep. 25, 5316–5330 (2024).
Esvelt, K. M., Carlson, J. C. & Liu, D. R. A system for the continuous directed evolution of biomolecules. Nature 472, 499–503 (2011).
Miller, S. M., Wang, T. & Liu, D. R. Phage-assisted continuous and non-continuous evolution. Nat. Protoc. 15, 4101–4127 (2020).
Filsinger, G. T. et al. A diverse single-stranded DNA-annealing protein library enables efficient genome editing across bacterial phyla. Proc. Natl Acad. Sci. USA 122, e2414342122 (2025).
St-Pierre, F. et al. One-step cloning and chromosomal integration of DNA. ACS Synth. Biol. 2, 537–541 (2013).
Thomason, L. C., Costantino, N. & Court, D. L. E. coli genome manipulation by P1 transduction. Curr. Protoc. Mol. Biol. Chapter 1, 1.17.1–1.17.8 (2007).
Gibson, D. G. et al. Enzymatic assembly of DNA molecules up to several hundred kilobases. Nat. Methods 6, 343–345 (2009).
Engler, C., Gruetzner, R., Kandzia, R. & Marillonnet, S. Golden Gate shuffling: a one-pot DNA shuffling method based on type IIs restriction enzymes. PLoS One 4, e5553 (2009).
Hartley, J. L., Temple, G. F. & Brasch, M. A. DNA cloning using in vitro site-specific recombination. Genome Res. 10, 1788–1795 (2000).
Jakočiūnė, D. & Moodley, A. A rapid bacteriophage DNA extraction method. Methods Protoc. 1, 27 (2018).
Anzalone, A. V. et al. Programmable deletion, replacement, integration and inversion of large DNA sequences with twin prime editing. Nat. Biotechnol. 40, 731–740 (2022).
Clement, K., Farouni, R., Bauer, D. E. & Pinello, L. AmpUMI: design and analysis of unique molecular identifiers for deep amplicon sequencing. Bioinformatics 34, i202–i210 (2018).
Clement, K. et al. CRISPResso2 provides accurate and rapid genome editing sequence analysis. Nat. Biotechnol. 37, 224–226 (2019).
Acknowledgements
We thank L. Cerdan and L.-A. Fernandez for providing VHH-1.29 and the pNeae vector, H. Mouquet, C. Planchais and P. Rosenbaum for providing the SARS-CoV-2 RBDs and expertise on antibody engineering, T. Rose for guidance on the immunotube panning experiments, P. Lafaye and G. Ayme for their expertise on nanobody selection, P. England for the BLI experiments and S. Volant and E. Jacquemet for the help in setting up a TR functionality model. This study was funded by the European Research Council (101044479), Agence Nationale de la Recherche (ANR-10-LABX-62-IBEID) and Ecole Doctorale Complexité du Vivant, Sorbonne Université (Contrat doctoral 4481/2022) to P.R, the Ecole Doctorale Frontières de l’Innovation en Recherche et Education funded by the Bettencourt Schueller foundation and the Ecole Universitaire de Recherche Interdisciplinaire de Paris graduate program (ANR-17-EURE-0012) and Fondation pour la Recherche Médicale (ECO202206015569) to E.L.R. and the National Science Foundation (2509382) to S.L.S.
Author information
Authors and Affiliations
Contributions
R.L., conceptualization, methodology, investigation, writing, visualization and supervision. P.R., conceptualization, methodology, investigation, writing, software and visualization. E.L.R., conceptualization, methodology, investigation, writing and visualization. D.W., methodology and investigation. L.R., methodology, investigation and software. C.F., methodology and investigation. A.M., methodology and investigation. W.R., methodology and investigation. L.W., methodology and investigation. I.N., methodology and investigation. P.V., investigation. N.B., methodology and investigation. K.M.C.M., investigation. A.B., investigation. T.C., investigation. O.S., methodology and investigation. N.W., methodology and supervision. L.R., methodology and investigation. R.M., methodology, supervision and project administration. S.C., methodology and supervision. S.L.S., methodology and supervision. D.B., conceptualization, methodology, writing, software, visualization, supervision, project administration and funding acquisition.
Corresponding authors
Ethics declarations
Competing interests
The following patent applications related to this work have been filed by Institut Pasteur with D.B., R.L. and W.R. as inventors: EP4294922A1 and WO2024038003A1. The remaining authors declare no competing interests.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data
Extended Data Fig. 1 Mutation rate per base per generation for the different nucleotides.
Dot plot representing mutation rate per base per generation of each base type inside and outside the targeted region (VR), with an active or a catalytically dead bRT. Statistical significance was calculated by a two-sided student test with unequal variance (ns = p > 0.05; * = p < 0.05; ** = p < 0.01). A, T, G, C bases are respectively n = 9, 25, 18, 15 inside the VR, and n = 13, 14, 8, 11 outside the VR, points are shown only when at least one mutation is observed at the position.
Extended Data Fig. 2 Amplicon sequencing characterization of DGRec components.
Amplicon sequencing of the sacB chromosomal gene locus targeted by the TR-AM009, using the UMI correction procedure as in Fig. 1. The plot area was restricted to the targeted region (VR). All tested combinations are shown with 2 biological replicates. All panels have the TR-AM009 expressed from the pRL021 DGRec backbone, except for ΔCspRecT and MutL* where it is expressed from the pRL038 backbone. Yellow ticks on the X-axis indicate adenine positions from the TR.
Extended Data Fig. 3 bRT variants with altered error rates.
A) DGRec mutagenesis on sacB performed by pRL021_TR-AM009 accompanied by pRL014 (wild type RT), pRL037 (bRT with I181N mutation) or pRL036 (bRT with R74A mutation). Mutagenesis was below the detection level for the R74A variant and was significantly reduced for the I181N variant. B) Closer view on wild type versus I181N variant mutagenesis profile, showing how the bias in the incorporation of nucleotides at adenines is altered.
Extended Data Fig. 4 Position of the DGR RNA, and dual targeting within cells.
A) Plasmid maps of pRL038 and pRL021, two compatible DGRec plasmids containing each a dgrRNA locus. CmR: chloramphenicol resistance gene; KanR: kanamycin resistance gene. Plasmid maps created with BioRender.com. B) Biological duplicates of cells expressing the DGR RNA with TR-AM009 either on the pRL038 or the pRL021 backbone. C) Dual targeting with a distinct DGR RNA placed on the two plasmids in the same cells.
Extended Data Fig. 5 Self-targeting of the DGR RNA in the DGRec system.
A) schematic representation of dgrRNA chromosomal VR targeting (1) versus self-targeting (2). B) Amplicon sequencing after 48 h mutagenesis with TR-AM009, compared at two positions in the same culture: around the targeted VR inside sacB in the chromosome, and around the TR on the DGR RNA inside the plasmid.
Extended Data Fig. 6 Effect of base -5 to base +5 on the bRT biases.
Ternary scatter plots of the rate of A to T mutations (bottom axis), A to C mutations (right axis), A to G mutations (left axis) depending on the base -5 up to +5. Each point represents the barycenter of the distribution for a given base. The contour indicates the convex hull enclosing 75% of the data points (nA=984).
Extended Data Fig. 7 Amino acid mutation table of the bRT.
Frequency at which different amino acids are reached by bRT mutagenesis depending on the starting codon. Red dots highlight the amino acid encoded by the starting codon.
Extended Data Fig. 8 Position of DGRec mutations for TR of different sizes.
TR cloned from fragmented E. coli DNA were assayed in a self-mutagenesis assay. The fraction of DGRec mutants that carry a mutation at each adenine position is reported. The grey box highlights a region for which no sequencing data was obtained.
Extended Data Fig. 9 Distributions of adenine mutations.
A) Example of the genotype with the highest count of adenine mutagenized (24) from the high-throughput library of 378 model-selected TRs. Adenines mutagenized are colored in red, Adenines not mutagenized are colored in green. B) Example of the genotype with the highest percentage of adenine mutagenized (90%) from the high-throughput library of 378 model selected TRs. Adenines mutagenized are colored in red, Adenines not mutagenized are colored in green. Thymine mutagenized are colored in blue. C to F) Respectively, distribution of the maximum count, maximum percentage, average count and average percentage of mutagenized adenines in mutagenized genotypes for a given TR (n = 378 TRs).
Extended Data Fig. 10 Plasmid maps of all the DGRec backbone plasmids used in this study.
CmR: chloramphenicol resistance gene; KanR: kanamycin resistance gene. In the DGRec 2 plasmid systems, pRL014 or pRL038 are used in combination with pRL021, while in the single-plasmid system, pPR150 alone is needed. Figure created with BioRender.com.
Supplementary information
Supplementary Information (download PDF )
Supplementary Methods, Figures 1–22 and Tables 1–6.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Rochette, P., Lopez-Rodriguez, E., Wen, D.J. et al. Diversity-generating retroelements for programmable targeted hypermutagenesis. Nat Biotechnol (2026). https://doi.org/10.1038/s41587-026-03078-4
Received:
Accepted:
Published:
Version of record:
DOI: https://doi.org/10.1038/s41587-026-03078-4
