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- Title
UMI-linked consensus sequencing enables phylogenetic analysis of directed evolution.
- Authors
Zurek, Paul Jannis; Knyphausen, Philipp; Neufeld, Katharina; Pushpanath, Ahir; Hollfelder, Florian
- Abstract
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. The success of protein evolution is dependent on the sequence context mutations are introduced into. Here the authors present UMIC-seq that allows consensus generation for closely related genes by using unique molecular identifiers linked to gene variants.
- Subjects
FORECASTING; PROTEIN-protein interactions; AMINO acids; ENZYMES
- Publication
Nature Communications, 2020, Vol 11, Issue 1, pN.PAG
- ISSN
2041-1723
- Publication type
Article
- DOI
10.1038/s41467-020-19687-9