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In Silico Predictions for Fucoxanthin Production by the Diatom Phaeodactylum Tricornutum

  • Claudia M. Bauer
  • Paulo Vilaça
  • Fernanda Ramlov
  • Eva Regina de Oliveira
  • Débora Q. Cabral
  • Caroline Schmitz
  • Rafaela Gordo Corrêa
  • Miguel Rocha
  • Marcelo Maraschin
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 803)

Abstract

Diatoms and brown seaweeds are the main producers of fucoxanthin, an oxy-carotenoid with important biological functions related to its antioxidative properties. The diatom Phaeodactylum tricornutum appears in this scenario as a good source for fucoxanthin production. Its whole genome sequence was published in 2008, and some genome-scale metabolic models are currently available. This work intends to make use of the two most recent genome-scale metabolic models published to predict ways to increase fucoxanthin production, using constraint-based modeling and flux balance analysis. One of the models was completed with 31 downstream reactions of the methylerythritol 4-phosphate plastidic (MEP) pathway. Simulations and optimizations were performed regarding inorganic carbon and nitrogen sources in the two models and comparisons were made between them. Biomass growth was predicted to increase in all sources tested, i.e., CO2, HCO3, NO3 and urea. However, the best results were obtained by combining CO2 plus HCO3 regarding inorganic carbon, and for urea as a nitrogen source, in both models tested. As a result of optimizations for fucoxanthin production, many of the knockout reactions brought on are involved in the metabolism of pyruvate, glutamine/glutamate and nitrogen assimilation.

Keywords

Fucoxanthin P. tricornutum Metabolic engineering Constraint-based modeling 

Notes

Acknowledgements

This work was supported by a grant from the National Council for Scientific and Technological Development (CNPq nº 490383/2013-0). The research fellowship from CNPq (grant nº 307099/2015-6) on behalf of M. Maraschin is acknowledged.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Claudia M. Bauer
    • 1
  • Paulo Vilaça
    • 2
  • Fernanda Ramlov
    • 1
  • Eva Regina de Oliveira
    • 1
  • Débora Q. Cabral
    • 1
  • Caroline Schmitz
    • 1
  • Rafaela Gordo Corrêa
    • 3
  • Miguel Rocha
    • 4
  • Marcelo Maraschin
    • 1
  1. 1.Plant Morphogenesis and Biochemistry LaboratoryFederal University of Santa CatarinaFlorianopolisBrazil
  2. 2.Silico Life Lda.BragaPortugal
  3. 3.Laboratory of PhycologyFederal University of Santa CatarinaFlorianopolisBrazil
  4. 4.Centre Biological Engineering, School of EngineeringUniversity of MinhoBragaPortugal

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