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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
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    1. 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.
    2. 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.
    3. 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.
    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.
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