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UMI-linked consensus sequencing enables phylogenetic analysis of directed evolution.

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Knyphausen, Philipp 
Neufeld, Katharina 
Pushpanath, Ahir 
Hollfelder, Florian  ORCID logo


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 based on full-length sequences. Attaching UMIs to gene variants allows accurate consensus generation for closely related genes with nanopore sequencing. 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.



Biocatalysis, Cloning, Molecular, Computational Biology, Consensus Sequence, Datasets as Topic, Directed Molecular Evolution, Enzyme Assays, Epistasis, Genetic, Gene Library, High-Throughput Nucleotide Sequencing, High-Throughput Screening Assays, Mutagenesis, Mutation, Oxidoreductases Acting on CH-NH Group Donors, Phylogeny, Protein Engineering, Recombinant Proteins, Software

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Nat Commun

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Springer Science and Business Media LLC


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European Commission Horizon 2020 (H2020) Marie Sk?odowska-Curie actions (722610)
European Commission Horizon 2020 (H2020) ERC (695664)
Eu H2020