IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v15y2024i1d10.1038_s41467-024-52816-2.html
   My bibliography  Save this article

Minimisation of metabolic networks defines a new functional class of genes

Author

Listed:
  • Giorgio Jansen

    (University of Cambridge
    University of Catania)

  • Tanda Qi

    (University of Manchester)

  • Vito Latora

    (Queen Mary University of London
    University of Catania)

  • Grigoris D. Amoutzias

    (University of Thessaly)

  • Daniela Delneri

    (University of Manchester)

  • Stephen G. Oliver

    (University of Cambridge)

  • Giuseppe Nicosia

    (University of Cambridge
    University of Catania)

Abstract

Construction of minimal metabolic networks (MMNs) contributes both to our understanding of the origins of metabolism and to the efficiency of biotechnological processes by preventing the diversion of flux away from product formation. We have designed MMNs using a novel in silico synthetic biology pipeline that removes genes encoding enzymes and transporters from genome-scale metabolic models. The resulting minimal gene-set still ensures both viability and high growth rates. The composition of these MMNs has defined a new functional class of genes termed Network Efficiency Determinants (NEDs). These genes, whilst not essential, are very rarely eliminated in constructing an MMN, suggesting that it is difficult for metabolism to be re-routed to obviate the need for such genes. Moreover, the removal of NED genes from an MMN significantly reduces its global efficiency. Bioinformatic analyses of the NED genes have revealed that not only do these genes have more genetic interactions than the bulk of metabolic genes but their protein products also show more protein-protein interactions. In yeast, NED genes are predominantly single-copy and are highly conserved across evolutionarily distant organisms. These features confirm the importance of the NED genes to the metabolic network, including why they are so rarely excluded during minimisation.

Suggested Citation

  • Giorgio Jansen & Tanda Qi & Vito Latora & Grigoris D. Amoutzias & Daniela Delneri & Stephen G. Oliver & Giuseppe Nicosia, 2024. "Minimisation of metabolic networks defines a new functional class of genes," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-52816-2
    DOI: 10.1038/s41467-024-52816-2
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-024-52816-2
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-024-52816-2?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. H. Jeong & S. P. Mason & A.-L. Barabási & Z. N. Oltvai, 2001. "Lethality and centrality in protein networks," Nature, Nature, vol. 411(6833), pages 41-42, May.
    2. Nevan J. Krogan & Gerard Cagney & Haiyuan Yu & Gouqing Zhong & Xinghua Guo & Alexandr Ignatchenko & Joyce Li & Shuye Pu & Nira Datta & Aaron P. Tikuisis & Thanuja Punna & José M. Peregrín-Alvarez & Mi, 2006. "Global landscape of protein complexes in the yeast Saccharomyces cerevisiae," Nature, Nature, vol. 440(7084), pages 637-643, March.
    3. Hongzhong Lu & Feiran Li & Benjamín J. Sánchez & Zhengming Zhu & Gang Li & Iván Domenzain & Simonas Marcišauskas & Petre Mihail Anton & Dimitra Lappa & Christian Lieven & Moritz Emanuel Beber & Nikola, 2019. "A consensus S. cerevisiae metabolic model Yeast8 and its ecosystem for comprehensively probing cellular metabolism," Nature Communications, Nature, vol. 10(1), pages 1-13, December.
    4. Bernard Dujon & David Sherman & Gilles Fischer & Pascal Durrens & Serge Casaregola & Ingrid Lafontaine & Jacky de Montigny & Christian Marck & Cécile Neuvéglise & Emmanuel Talla & Nicolas Goffard & Li, 2004. "Genome evolution in yeasts," Nature, Nature, vol. 430(6995), pages 35-44, July.
    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. Wilhelm, Thomas & Hollunder, Jens, 2007. "Information theoretic description of networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 385(1), pages 385-396.
    2. Laurienti, Paul J. & Joyce, Karen E. & Telesford, Qawi K. & Burdette, Jonathan H. & Hayasaka, Satoru, 2011. "Universal fractal scaling of self-organized networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(20), pages 3608-3613.
    3. Chung-Yen Yu & Yung-Ting Chuang & Hsi-Peng Kuan, 2017. "Understanding Faculty Collaboration and Productivity: A Case Study," Asian Social Science, Canadian Center of Science and Education, vol. 13(3), pages 1-1, March.
    4. Pei Wang & Shunjie Chen & Sijia Yang, 2022. "Recent Advances on Penalized Regression Models for Biological Data," Mathematics, MDPI, vol. 10(19), pages 1-24, October.
    5. Jordán, Ferenc, 2022. "The network perspective: Vertical connections linking organizational levels," Ecological Modelling, Elsevier, vol. 473(C).
    6. P.B., Divya & Lekha, Divya Sindhu & Johnson, T.P. & Balakrishnan, Kannan, 2022. "Vulnerability of link-weighted complex networks in central attacks and fallback strategy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 590(C).
    7. Nadadoor Venkat R. & Ben-Zvi Amos & Shah Sirish L., 2011. "Inferring Gene Networks using Robust Statistical Techniques," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 10(1), pages 1-30, May.
    8. Hassan Badrane & Shaoji Cheng & Christopher L. Dupont & Binghua Hao & Eileen Driscoll & Kristin Morder & Guojun Liu & Anthony Newbrough & Giuseppe Fleres & Drishti Kaul & Josh L. Espinoza & Cornelius , 2023. "Genotypic diversity and unrecognized antifungal resistance among populations of Candida glabrata from positive blood cultures," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    9. Yameng Xu & Xinglong Wang & Chenyang Zhang & Xuan Zhou & Xianhao Xu & Luyao Han & Xueqin Lv & Yanfeng Liu & Song Liu & Jianghua Li & Guocheng Du & Jian Chen & Rodrigo Ledesma-Amaro & Long Liu, 2022. "De novo biosynthesis of rubusoside and rebaudiosides in engineered yeasts," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    10. Mustafa C. Camur & Thomas Sharkey & Chrysafis Vogiatzis, 2022. "The Star Degree Centrality Problem: A Decomposition Approach," INFORMS Journal on Computing, INFORMS, vol. 34(1), pages 93-112, January.
    11. Ramesh Ummanni & Frederike Mundt & Heike Pospisil & Simone Venz & Christian Scharf & Christine Barett & Maria Fälth & Jens Köllermann & Reinhard Walther & Thorsten Schlomm & Guido Sauter & Carsten Bok, 2011. "Identification of Clinically Relevant Protein Targets in Prostate Cancer with 2D-DIGE Coupled Mass Spectrometry and Systems Biology Network Platform," PLOS ONE, Public Library of Science, vol. 6(2), pages 1-14, February.
    12. Peter Langfelder & Paul S Mischel & Steve Horvath, 2013. "When Is Hub Gene Selection Better than Standard Meta-Analysis?," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-16, April.
    13. Kim, Jongkwang & Wilhelm, Thomas, 2008. "What is a complex graph?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(11), pages 2637-2652.
    14. Erica W. Carter & Orlene Guerra Peraza & Nian Wang, 2023. "The protein interactome of the citrus Huanglongbing pathogen Candidatus Liberibacter asiaticus," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    15. Feiran Li & Yu Chen & Qi Qi & Yanyan Wang & Le Yuan & Mingtao Huang & Ibrahim E. Elsemman & Amir Feizi & Eduard J. Kerkhoven & Jens Nielsen, 2022. "Improving recombinant protein production by yeast through genome-scale modeling using proteome constraints," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    16. Iván Domenzain & Benjamín Sánchez & Mihail Anton & Eduard J. Kerkhoven & Aarón Millán-Oropeza & Céline Henry & Verena Siewers & John P. Morrissey & Nikolaus Sonnenschein & Jens Nielsen, 2022. "Reconstruction of a catalogue of genome-scale metabolic models with enzymatic constraints using GECKO 2.0," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    17. Dong, Chen & Xu, Guiqiong & Meng, Lei & Yang, Pingle, 2022. "CPR-TOPSIS: A novel algorithm for finding influential nodes in complex networks based on communication probability and relative entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    18. Jiawei Luo & Yi Qi, 2015. "Identification of Essential Proteins Based on a New Combination of Local Interaction Density and Protein Complexes," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-27, June.
    19. Xia Cao & Chuanyun Li & Wei Chen & Jinqiu Li & Chaoran Lin, 2020. "Research on the invulnerability and optimization of the technical cooperation innovation network based on the patent perspective—A case study of new energy vehicles," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-19, September.
    20. Jie Zhao & Xiujuan Lei & Fang-Xiang Wu, 2017. "Predicting Protein Complexes in Weighted Dynamic PPI Networks Based on ICSC," Complexity, Hindawi, vol. 2017, pages 1-11, August.

    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:15:y:2024:i:1:d:10.1038_s41467-024-52816-2. 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.