Heterogeneity of the GFP fitness landscape and data-driven protein design

  1. Louisa Gonzalez Somermeyer
  2. Aubin Fleiss
  3. Alexander S Mishin
  4. Nina G Bozhanova
  5. Anna A Igolkina
  6. Jens Meiler
  7. Maria-Elisenda Alaball Pujol
  8. Ekaterina V Putintseva
  9. Karen S Sarkisyan  Is a corresponding author
  10. Fyodor A Kondrashov  Is a corresponding author
  1. Institute of Science and Technology Austria, Austria
  2. MRC London Institute of Medical Sciences, United Kingdom
  3. Russian Academy of Sciences, Russian Federation
  4. Vanderbilt University, United States
  5. Austrian Academy of Sciences, Austria
  6. LabGenius, United Kingdom

Abstract

Studies of protein fitness landscapes reveal biophysical constraints guiding protein evolution and empower prediction of functional proteins. However, generalisation of these findings is limited due to scarceness of systematic data on fitness landscapes of proteins with a defined evolutionary relationship. We characterized the fitness peaks of four orthologous fluorescent proteins with a broad range of sequence divergence. While two of the four studied fitness peaks were sharp, the other two were considerably flatter, being almost entirely free of epistatic interactions. Mutationally robust proteins, characterized by a flat fitness peak, were not optimal templates for machine-learning-driven protein design - instead, predictions were more accurate for fragile proteins with epistatic landscapes. Our work paves insights for practical application of fitness landscape heterogeneity in protein engineering.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting file and are available on GitHub https://github.com/aequorea238/Orthologous_GFP_Fitness_Peaks

The following data sets were generated

Article and author information

Author details

  1. Louisa Gonzalez Somermeyer

    Institute of Science and Technology Austria, Klosterneuburg, Austria
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9139-5383
  2. Aubin Fleiss

    Synthetic Biology Group, MRC London Institute of Medical Sciences, London, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  3. Alexander S Mishin

    Department of Genetics and Postgenomic Technologies, Russian Academy of Sciences, Moscow, Russian Federation
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4935-7030
  4. Nina G Bozhanova

    Department of Chemistry, Vanderbilt University, Nashville, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2164-5698
  5. Anna A Igolkina

    Gregor Mendel Institute, Austrian Academy of Sciences, Vienna, Austria
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8851-9621
  6. Jens Meiler

    Department of Chemistry, Vanderbilt University, Nashville, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8945-193X
  7. Maria-Elisenda Alaball Pujol

    Synthetic Biology Group, MRC London Institute of Medical Sciences, London, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1868-2674
  8. Ekaterina V Putintseva

    LabGenius, London, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  9. Karen S Sarkisyan

    Synthetic Biology Group, MRC London Institute of Medical Sciences, London, United Kingdom
    For correspondence
    karen.s.sarkisyan@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
  10. Fyodor A Kondrashov

    Institute of Science and Technology Austria, Klosterneuburg, Austria
    For correspondence
    fyodor.kondrashov@oist.jp
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8243-4694

Funding

European Research Council (771209-CharFL)

  • Fyodor A Kondrashov

MRC London Institute of Medical Sciences (UKRI MC-A658-5QEA0)

  • Karen S Sarkisyan

President's Grant (МК-5405.2021.1.4)

  • Karen S Sarkisyan

Marie Skłodowska-Curie Fellowship (898203)

  • Aubin Fleiss

Russian Science Foundation (19-74-10102)

  • Alexander S Mishin

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Daniel J Kliebenstein, University of California, Davis, United States

Version history

  1. Received: November 25, 2021
  2. Preprint posted: December 9, 2021 (view preprint)
  3. Accepted: March 25, 2022
  4. Accepted Manuscript published: May 5, 2022 (version 1)
  5. Accepted Manuscript updated: May 6, 2022 (version 2)
  6. Version of Record published: May 19, 2022 (version 3)

Copyright

© 2022, Gonzalez Somermeyer et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Louisa Gonzalez Somermeyer
  2. Aubin Fleiss
  3. Alexander S Mishin
  4. Nina G Bozhanova
  5. Anna A Igolkina
  6. Jens Meiler
  7. Maria-Elisenda Alaball Pujol
  8. Ekaterina V Putintseva
  9. Karen S Sarkisyan
  10. Fyodor A Kondrashov
(2022)
Heterogeneity of the GFP fitness landscape and data-driven protein design
eLife 11:e75842.
https://doi.org/10.7554/eLife.75842

Share this article

https://doi.org/10.7554/eLife.75842

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