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Resurrecting Enzymes by Ancestral Sequence Reconstruction

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Enzyme Engineering

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2397))

Abstract

Ancestral Sequence Reconstruction (ASR) allows one to infer the sequences of extinct proteins using the phylogeny of extant proteins. It consists of disclosing the evolutionary history—i.e., the phylogeny—of a protein family of interest and then inferring the sequences of its ancestors—i.e., the nodes in the phylogeny. Assisted by gene synthesis, the selected ancestors can be resurrected in the lab and experimentally characterized. The crucial step to succeed with ASR is starting from a reliable phylogeny. At the same time, it is of the utmost importance to have a clear idea on the evolutionary history of the family under study and the events that influenced it. This allows us to implement ASR with well-defined hypotheses and to apply the appropriate experimental methods. In the last years, ASR has become popular to test hypotheses about the origin of functionalities, changes in activities, understanding physicochemical properties of proteins, among others. In this context, the aim of this chapter is to present the ASR approach applied to the reconstruction of enzymes—i.e., proteins with catalytic roles. The spirit of this contribution is to provide a basic, hands-to-work guide for biochemists and biologists who are unfamiliar with molecular phylogenetics.

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Acknowledgments

I thank Georg K. A. Hochberg for the enlighten discussion and for the suggestions about the chapter structure and contents. I also thank Callum R. Nicoll and Martín A. Palazzolo for their careful critical reading of the manuscript and to Marco W. Fraaije and Maximiliano Juri Ayub for their comments. This work was supported by the European Union’s Horizon 2020 research and innovation program under grant agreement No 847675 and the ANPCyT (Argentina) PICT 2016-2839 to MLM. MLM is a member of the Researcher Career of CONICET, Argentina.

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Authors and Affiliations

  1. Molecular Enzymology group, University of Groningen, Groningen, The Netherlands

    Maria Laura Mascotti

  2. IMIBIO-SL CONICET, Facultad de Química Bioquímica y Farmacia, Universidad Nacional de San Luis, San Luis, Argentina

    Maria Laura Mascotti

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  1. Maria Laura Mascotti
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Correspondence to Maria Laura Mascotti .

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  1. Department of Biology and Biotechnology, University of Pavia, Pavia, Italy

    Francesca Magnani

  2. Department of Biology and Biotechnology, University of Pavia, Pavia, Italy

    Chiara Marabelli

  3. Department of Chemistry & Biochemistry, University of Bern, Bern, Switzerland

    Francesca Paradisi

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Mascotti, M.L. (2022). Resurrecting Enzymes by Ancestral Sequence Reconstruction. In: Magnani, F., Marabelli, C., Paradisi, F. (eds) Enzyme Engineering. Methods in Molecular Biology, vol 2397. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1826-4_7

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  • DOI: https://doi.org/10.1007/978-1-0716-1826-4_7

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-1825-7

  • Online ISBN: 978-1-0716-1826-4

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