The first multi-tissue genome-scale metabolic model of a woody plant highlights suberin biosynthesis pathways in Quercus suber

PLoS Comput Biol. 2023 Sep 20;19(9):e1011499. doi: 10.1371/journal.pcbi.1011499. eCollection 2023 Sep.

Abstract

Over the last decade, genome-scale metabolic models have been increasingly used to study plant metabolic behaviour at the tissue and multi-tissue level under different environmental conditions. Quercus suber, also known as the cork oak tree, is one of the most important forest communities of the Mediterranean/Iberian region. In this work, we present the genome-scale metabolic model of the Q. suber (iEC7871). The metabolic model comprises 7871 genes, 6231 reactions, and 6481 metabolites across eight compartments. Transcriptomics data was integrated into the model to obtain tissue-specific models for the leaf, inner bark, and phellogen, with specific biomass compositions. The tissue-specific models were merged into a diel multi-tissue metabolic model to predict interactions among the three tissues at the light and dark phases. The metabolic models were also used to analyse the pathways associated with the synthesis of suberin monomers, namely the acyl-lipids, phenylpropanoids, isoprenoids, and flavonoids production. The models developed in this work provide a systematic overview of the metabolism of Q. suber, including its secondary metabolism pathways and cork formation.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Lipids
  • Quercus* / genetics
  • Quercus* / metabolism
  • Secondary Metabolism
  • Wood / genetics

Substances

  • suberin
  • Lipids

Grants and funding

The authors would like to acknowledge project 22231/01/SAICT/2016: “Biodata.pt – Infraestrutura Portuguesa de Dados Biológicos”, supported by Lisboa Portugal Regional Operational Programme (Lisboa2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF) that supported HD and DL. The authors would also like to acknowledge the Portuguese Foundation for Science and Technology (FCT) for the Strategic Funding FCT 2020-2023 (PEst UIDB/04469/2020). EC acknowledges FCT for the scholarship (DFA/BD/8076/2020). IC was funded by DL 57/2016/CP1351/CT0003. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.