UMI-linked consensus sequencing enables phylogenetic analysis of directed evolution.
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Zurek, P. J., Knyphausen, P., Neufeld, K., Pushpanath, A., & Hollfelder, F. (2020). UMI-linked consensus sequencing enables phylogenetic analysis of directed evolution.. Nature communications, 11 (1), 6023. https://doi.org/10.1038/s41467-020-19687-9
The success of protein evolution campaigns is strongly dependent on the sequence context in which mutations are introduced, stemming from pervasive non-additive interactions between a protein’s amino acids (‘intra-gene epistasis’). Our limited understanding of such epistasis hinders the correct prediction of the functional contributions and adaptive potential of mutations. Here we present a straightforward unique molecular identifier (UMI)-linked consensus sequencing workflow (UMIC-seq) that simplifies mapping of evolutionary trajectories from full-length sequences. Attaching UMIs to gene variants allows accurate consensus generation for closely related genes with nanopore sequences. We exemplify the utility of this approach by reconstructing the artificial phylogeny emerging in three rounds of directed evolution of an amine dehydrogenase biocatalyst via ultrahigh throughput droplet screening. Uniquely, we are able to identify lineages and their founding variant, as well as non-additive interactions between mutations within a full gene showing sign epistasis. Access to deep and accurate long reads will facilitate prediction of key beneficial mutations and adaptive potential based on in silico analysis of large sequence datasets.
Recombinant Proteins, Cloning, Molecular, Directed Molecular Evolution, Protein Engineering, Computational Biology, Phylogeny, Epistasis, Genetic, Mutagenesis, Consensus Sequence, Mutation, Gene Library, Software, Oxidoreductases Acting on CH-NH Group Donors, Biocatalysis, Enzyme Assays, High-Throughput Screening Assays, High-Throughput Nucleotide Sequencing, Datasets as Topic
European Commission Horizon 2020 (H2020) Marie Sk?odowska-Curie actions (722610)
European Commission Horizon 2020 (H2020) ERC (695664)
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External DOI: https://doi.org/10.1038/s41467-020-19687-9
This record's URL: https://www.repository.cam.ac.uk/handle/1810/311590
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