IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v13y2022i1d10.1038_s41467-022-32538-z.html
   My bibliography  Save this article

Experimental exploration of a ribozyme neutral network using evolutionary algorithm and deep learning

Author

Listed:
  • Rachapun Rotrattanadumrong

    (Okinawa Institute of Science and Technology Graduate University)

  • Yohei Yokobayashi

    (Okinawa Institute of Science and Technology Graduate University)

Abstract

A neutral network connects all genotypes with equivalent phenotypes in a fitness landscape and plays an important role in the mutational robustness and evolvability of biomolecules. In contrast to earlier theoretical works, evidence of large neutral networks has been lacking in recent experimental studies of fitness landscapes. This suggests that evolution could be constrained globally. Here, we demonstrate that a deep learning-guided evolutionary algorithm can efficiently identify neutral genotypes within the sequence space of an RNA ligase ribozyme. Furthermore, we measure the activities of all 216 variants connecting two active ribozymes that differ by 16 mutations and analyze mutational interactions (epistasis) up to the 16th order. We discover an extensive network of neutral paths linking the two genotypes and reveal that these paths might be predicted using only information from lower-order interactions. Our experimental evaluation of over 120,000 ribozyme sequences provides important empirical evidence that neutral networks can increase the accessibility and predictability of the fitness landscape.

Suggested Citation

  • Rachapun Rotrattanadumrong & Yohei Yokobayashi, 2022. "Experimental exploration of a ribozyme neutral network using evolutionary algorithm and deep learning," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-32538-z
    DOI: 10.1038/s41467-022-32538-z
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-022-32538-z
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-022-32538-z?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Johan O. L. Andreasson & Andrew Savinov & Steven M. Block & William J. Greenleaf, 2020. "Comprehensive sequence-to-function mapping of cofactor-dependent RNA catalysis in the glmS ribozyme," Nature Communications, Nature, vol. 11(1), pages 1-11, December.
    2. Simeon D. Castle & Claire S. Grierson & Thomas E. Gorochowski, 2021. "Towards an engineering theory of evolution," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
    3. Nilesh Vaidya & Michael L. Manapat & Irene A. Chen & Ramon Xulvi-Brunet & Eric J. Hayden & Niles Lehman, 2012. "Spontaneous network formation among cooperative RNA replicators," Nature, Nature, vol. 491(7422), pages 72-77, November.
    4. Amirali Aghazadeh & Hunter Nisonoff & Orhan Ocal & David H. Brookes & Yijie Huang & O. Ozan Koyluoglu & Jennifer Listgarten & Kannan Ramchandran, 2021. "Epistatic Net allows the sparse spectral regularization of deep neural networks for inferring fitness functions," Nature Communications, Nature, vol. 12(1), pages 1-10, December.
    5. Júlia Domingo & Guillaume Diss & Ben Lehner, 2018. "Pairwise and higher-order genetic interactions during the evolution of a tRNA," Nature, Nature, vol. 558(7708), pages 117-121, June.
    6. Frank J. Poelwijk & Michael Socolich & Rama Ranganathan, 2019. "Learning the pattern of epistasis linking genotype and phenotype in a protein," Nature Communications, Nature, vol. 10(1), pages 1-11, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Andreas Wagner, 2023. "Evolvability-enhancing mutations in the fitness landscapes of an RNA and a protein," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    2. Solip Park & Fran Supek & Ben Lehner, 2021. "Higher order genetic interactions switch cancer genes from two-hit to one-hit drivers," Nature Communications, Nature, vol. 12(1), pages 1-10, December.
    3. Jonathan Yaacov Weinstein & Carlos Martí-Gómez & Rosalie Lipsh-Sokolik & Shlomo Yakir Hoch & Demian Liebermann & Reinat Nevo & Haim Weissman & Ekaterina Petrovich-Kopitman & David Margulies & Dmitry I, 2023. "Designed active-site library reveals thousands of functional GFP variants," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    4. Simeon D. Castle & Michiel Stock & Thomas E. Gorochowski, 2024. "Engineering is evolution: a perspective on design processes to engineer biology," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    5. Federica Luppino & Ivan A. Adzhubei & Christopher A. Cassa & Agnes Toth-Petroczy, 2023. "DeMAG predicts the effects of variants in clinically actionable genes by integrating structural and evolutionary epistatic features," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    6. David C. Marciano & Chen Wang & Teng-Kuei Hsu & Thomas Bourquard & Benu Atri & Ralf B. Nehring & Nicholas S. Abel & Elizabeth A. Bowling & Taylor J. Chen & Pamela D. Lurie & Panagiotis Katsonis & Susa, 2022. "Evolutionary action of mutations reveals antimicrobial resistance genes in Escherichia coli," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    7. Duncan Ingram & Guy-Bart Stan, 2023. "Modelling genetic stability in engineered cell populations," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    8. Friedrich, Thomas & Köpper, Wilhelm, 2013. "Schumpeter´s Gale: Mixing and compartmentalization in Economics and Biology," MPRA Paper 45405, University Library of Munich, Germany.
    9. Andras Gyorgy, 2023. "Competition and evolutionary selection among core regulatory motifs in gene expression control," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    10. Vincent Ouazan-Reboul & Jaime Agudo-Canalejo & Ramin Golestanian, 2023. "Self-organization of primitive metabolic cycles due to non-reciprocal interactions," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    11. Remkes A. Scheele & Laurens H. Lindenburg & Maya Petek & Markus Schober & Kevin N. Dalby & Florian Hollfelder, 2022. "Droplet-based screening of phosphate transfer catalysis reveals how epistasis shapes MAP kinase interactions with substrates," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    12. Nicolae Sapoval & Amirali Aghazadeh & Michael G. Nute & Dinler A. Antunes & Advait Balaji & Richard Baraniuk & C. J. Barberan & Ruth Dannenfelser & Chen Dun & Mohammadamin Edrisi & R. A. Leo Elworth &, 2022. "Current progress and open challenges for applying deep learning across the biosciences," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    13. Ryo Mizuuchi & Taro Furubayashi & Norikazu Ichihashi, 2022. "Evolutionary transition from a single RNA replicator to a multiple replicator network," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    14. Karol Buda & Charlotte M. Miton & Nobuhiko Tokuriki, 2023. "Pervasive epistasis exposes intramolecular networks in adaptive enzyme evolution," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    15. Brian M. Petersen & Monica B. Kirby & Karson M. Chrispens & Olivia M. Irvin & Isabell K. Strawn & Cyrus M. Haas & Alexis M. Walker & Zachary T. Baumer & Sophia A. Ulmer & Edgardo Ayala & Emily R. Rhod, 2024. "An integrated technology for quantitative wide mutational scanning of human antibody Fab libraries," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    16. David Ding & Ada Y. Shaw & Sam Sinai & Nathan Rollins & Noam Prywes & David F. Savage & Michael T. Laub & Debora S. Marks, 2024. "Protein design using structure-based residue preferences," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    17. Takahiro Nemoto & Tommaso Ocari & Arthur Planul & Muge Tekinsoy & Emilia A. Zin & Deniz Dalkara & Ulisse Ferrari, 2023. "ACIDES: on-line monitoring of forward genetic screens for protein engineering," Nature Communications, Nature, vol. 14(1), pages 1-11, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-32538-z. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.