Accessing unexplored regions of sequence space in directed enzyme evolution via insertion/deletion mutagenesis

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Emond, Stephane 
Kay, Emily 
Heames, Brennan 
Devenish, Sean 

Insertions and deletions (InDels) are frequently observed in natural protein evolution, yet their potential remains untapped in laboratory evolution. Here we introduce a transposon mutagenesis approach (TRIAD) to generate libraries of random variants with short in-frame InDels, and screen TRIAD libraries to evolve a promiscuous arylesterase activity in a phosphotriesterase. The evolution exhibits features that are distinct from previous point mutagenesis campaigns: while the average activity of TRIAD variants is more deleterious, a larger proportion has successfully adapted for the new activity, and different functional profiles emerge: (i) both strong and weak trade-off between original vs promiscuous activity are observed; (ii) trade-off is more severe (20- to 35-fold increased kcat/KM in arylesterase with 60-400-fold decreases in the original phosphotriesterase activity) and (iii) improvements show up in kcat rather than just in KM, suggesting novel adaptive solutions. These distinct features make TRIAD an alternative to widely used point mutagenesis, providing access to functional innovations and traversing unexplored fitness landscape regions.

Evolution, Molecular, Humans, INDEL Mutation, Mutagenesis, Phosphoric Triester Hydrolases, Synthetic Biology
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Nature Communications
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Springer Nature
Biotechnology and Biological Sciences Research Council (BB/L002469/1)
Biotechnology and Biological Sciences Research Council (BB/M011194/1)
Engineering and Physical Sciences Research Council (EP/P020259/1)
BBSRC (1644161)
Biotechnology and Biological Sciences Research Council (1644161)
We would like to thank Christopher Kitching for assistance with analysis scripts and Charlotte Miton for helpful comments on the paper. S.E., N.T. and S.D. held EU Marie Curie FP7 fellowships, F.H. is an H2020 ERC Advanced Investigator [695669]. This work was supported by the Biotechnology and Biological Sciences Research Council through a research grant [BB/L002469/1] and a studentship to M.P. [BB/M011194/1]. We acknowledge support from the Cambridge Service for Data Driven Discovery (CSD3) operated by the University of Cambridge Research Computing Service (, provided by Dell EMC and Intel using Tier-2 funding from the Engineering and Physical Sciences Research Council (capital grant EP/P020259/1), and DiRAC funding from the Science and Technology Facilities Council (