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Exploiting Models of Molecular Evolution to Efficiently Direct Protein Engineering

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Abstract

Directed evolution and protein engineering approaches used to generate novel or enhanced biomolecular function often use the evolutionary sequence diversity of protein homologs to rationally guide library design. To fully capture this sequence diversity, however, libraries containing millions of variants are often necessary. Screening libraries of this size is often undesirable due to inaccuracies of high-throughput assays, costs, and time constraints. The ability to effectively cull sequence diversity while still generating the functional diversity within a library thus holds considerable value. This is particularly relevant when high-throughput assays are not amenable to select/screen for certain biomolecular properties. Here, we summarize our recent attempts to develop an evolution-guided approach, Reconstructing Evolutionary Adaptive Paths (REAP), for directed evolution and protein engineering that exploits phylogenetic and sequence analyses to identify amino acid substitutions that are likely to alter or enhance function of a protein. To demonstrate the utility of this technique, we highlight our previous work with DNA polymerases in which a REAP-designed small library was used to identify a DNA polymerase capable of accepting non-standard nucleosides. We anticipate that the REAP approach will be used in the future to facilitate the engineering of biopolymers with expanded functions and will thus have a significant impact on the developing field of ‘evolutionary synthetic biology’.

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Acknowledgments

This work was supported by a National Institutes of Health grant to EAG. MFC was supported by an NIH NRSA award and in part by the Emory University Fellowship in Research and Science Teaching (FIRST) program’s NIH/NIGMS IRACDA grant number K12 GM000680-11. This work was also supported by the National Aeronautics and Space Administration’s Exobiology and Astrobiology Programs.

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Authors and Affiliations

  1. School of Biology, Georgia Institute of Technology, Atlanta, GA, 30332, USA

    Megan F. Cole & Eric A. Gaucher

  2. School of Chemistry and Parker H. Petit Institute for Bioengineering and Biosciences, Georgia Institute of Technology, 310 Ferst Dr., Atlanta, GA, 30332, USA

    Eric A. Gaucher

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  1. Megan F. Cole
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  2. Eric A. Gaucher
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Correspondence to Eric A. Gaucher.

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Cole, M.F., Gaucher, E.A. Exploiting Models of Molecular Evolution to Efficiently Direct Protein Engineering. J Mol Evol 72, 193–203 (2011). https://doi.org/10.1007/s00239-010-9415-2

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