Prediction and characterization of enzymatic activities guided by sequence similarity and genome neighborhood networks

  1. Suwen Zhao
  2. Ayano Sakai
  3. Xinshuai Zhang
  4. Matthew W Vetting
  5. Ritesh Kumar
  6. Brandan Hillerich
  7. Brian San Francisco
  8. Jose Solbiati
  9. Adam Steves
  10. Shoshana Brown
  11. Eyal Akiva
  12. Alan Barber
  13. Ronald D Seidel
  14. Patricia C Babbitt
  15. Steven C Almo
  16. John A Gerlt  Is a corresponding author
  17. Matthew P Jacobson
  1. University of California, San Francisco, United States
  2. University of Illinois at Urbana-Champaign, United States
  3. Albert Einstein College of Medicine, United States

Abstract

Metabolic pathways in eubacteria and archaea often are encoded by operons and/or gene clusters (genome neighborhoods) that provide important clues for assignment of both enzyme functions and metabolic pathways. We describe a bioinformatic approach (genome neighborhood network; GNN) that enables large scale prediction of the in vitro enzymatic activities and in vivo physiological functions (metabolic pathways) of uncharacterized enzymes in protein families. We demonstrate the utility of the GNN approach by predicting in vitro activities and in vivo functions in the proline racemase superfamily (PRS; InterPro IPR008794). The predictions were verified by measuring in vitro activities for 51 proteins in 12 families in the PRS that represent ~85% of the sequences; in vitro activities of pathway enzymes, carbon/nitrogen source phenotypes, and/or transcriptomic studies confirmed the predicted pathways. The synergistic use of sequence similarity networks3 and GNNs will facilitate the discovery of the components of novel, uncharacterized metabolic pathways in sequenced genomes.

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Author details

  1. Suwen Zhao

    University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Ayano Sakai

    University of Illinois at Urbana-Champaign, Urbana, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Xinshuai Zhang

    University of Illinois at Urbana-Champaign, Urbana, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Matthew W Vetting

    Albert Einstein College of Medicine, Bronx, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Ritesh Kumar

    University of Illinois at Urbana-Champaign, Urbana, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Brandan Hillerich

    Albert Einstein College of Medicine, Bronx, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Brian San Francisco

    University of Illinois at Urbana-Champaign, Urbana, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. Jose Solbiati

    University of Illinois at Urbana-Champaign, Urbana, United States
    Competing interests
    The authors declare that no competing interests exist.
  9. Adam Steves

    University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  10. Shoshana Brown

    University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  11. Eyal Akiva

    University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  12. Alan Barber

    University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  13. Ronald D Seidel

    Albert Einstein College of Medicine, Bronx, United States
    Competing interests
    The authors declare that no competing interests exist.
  14. Patricia C Babbitt

    University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  15. Steven C Almo

    Albert Einstein College of Medicine, Bronx, United States
    Competing interests
    The authors declare that no competing interests exist.
  16. John A Gerlt

    University of Illinois at Urbana-Champaign, Urbana, United States
    For correspondence
    j-gerlt@illinois.edu
    Competing interests
    The authors declare that no competing interests exist.
  17. Matthew P Jacobson

    University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.

Reviewing Editor

  1. Jon Clardy, Harvard Medical School, United States

Version history

  1. Received: May 5, 2014
  2. Accepted: June 26, 2014
  3. Accepted Manuscript published: June 30, 2014 (version 1)
  4. Version of Record published: July 30, 2014 (version 2)

Copyright

© 2014, Zhao 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. Suwen Zhao
  2. Ayano Sakai
  3. Xinshuai Zhang
  4. Matthew W Vetting
  5. Ritesh Kumar
  6. Brandan Hillerich
  7. Brian San Francisco
  8. Jose Solbiati
  9. Adam Steves
  10. Shoshana Brown
  11. Eyal Akiva
  12. Alan Barber
  13. Ronald D Seidel
  14. Patricia C Babbitt
  15. Steven C Almo
  16. John A Gerlt
  17. Matthew P Jacobson
(2014)
Prediction and characterization of enzymatic activities guided by sequence similarity and genome neighborhood networks
eLife 3:e03275.
https://doi.org/10.7554/eLife.03275

Share this article

https://doi.org/10.7554/eLife.03275

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