Network-level architecture and the evolutionary potential of underground metabolism

Richard A. Notebaart*, Balázs Szappanos, Bálint Kintses, Ferenc Pál, Ádám Györkei, Balázs Bogos, Viktória Lázár, Réka Spohn, Bálint Csörgö, Allon Wagner, Eytan Ruppin, Csaba Pál, Balázs Papp

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

92 Scopus citations


A central unresolved issue in evolutionary biology is how metabolic innovations emerge. Low-level enzymatic side activities are frequent and can potentially be recruited for new biochemical functions. However, the role of such underground reactions in adaptation toward novel environments has remained largely unknown and out of reach of computational predictions, not least because these issues demand analyses at the level of the entire metabolic network. Here, we provide a comprehensive computational model of the underground metabolism in Escherichia coli. Most underground reactions are not isolated and 45% of them can be fully wired into the existing network and form novel pathways that produce key precursors for cell growth. This observation allowed us to conduct an integrated genome-wide in silico and experimental survey to characterize the evolutionary potential of E. coli to adapt to hundreds of nutrient conditions. We revealed that underground reactions allow growth in new environments when their activity is increased. We estimate that at least ~20% of the underground reactions that can be connected to the existing network confer a fitness advantage under specific environments. Moreover, our results demonstrate that the genetic basis of evolutionary adaptations via underground metabolism is computationally predictable. The approach used here has potential for various application areas from bioengineering to medical genetics.

Original languageEnglish
Pages (from-to)11762-11767
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Issue number32
StatePublished - 12 Aug 2014


  • Enzyme promiscuity
  • Evolutionary innovation
  • Molecular evolution
  • Network evolution
  • Phenotype microarray


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