Data underlying research on Engineering of molybdenum-cofactor-dependent nitrate assimilation in Yarrowia lipolytica

doi: 10.4121/14230238.v1
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/14230238
Datacite citation style:
Jean-Marc Daran; Perli, Thomas (2021): Data underlying research on Engineering of molybdenum-cofactor-dependent nitrate assimilation in Yarrowia lipolytica. Version 1. 4TU.ResearchData. dataset.
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Engineering a new metabolic function in a microbial host can be limited by the availability of the relevant co-factor. For instance, in Yarrowia lipolytica, the expression of a functional nitrate reductase is precluded by the absence of molybdenum cofactor (Moco) biosynthesis. In this study, we demonstrated that the Ogataea parapolymorpha Moco biosynthesis pathway associated with the expression of a high affinity molybdate transporter could lead to the synthesis of Moco in Y. lipolytica. This was achieved by coupling Moco biosynthesis to the Moco-dependent nitrate assimilation pathway of the same donor, O. parapolymorpha. In addition to 11 heterologous genes, fast growth on nitrate required adaptive laboratory evolution which, resulted in up to 100-fold increase in nitrate reductase activity and in up to 4-fold increase in growth rate. Genome sequencing of evolved isolates revealed the presence of a limited number of non-synonymous mutations or small insertions/deletions in annotated coding sequences. This study that builds up on a previous work establishing Moco synthesis in S. cerevisiae demonstrated that the Moco pathway could be successfully transferred in very distant yeasts and, potentially, to any other genera, which would enable the expression of new enzyme families and expand the nutrient range used by industrial yeasts.

  • 2021-03-18 first online, published, posted
  • Predictive and Accelerated Metabolic Engineering Network (grant code 722287) [more info...] European Commission
TU Delft, Faculty Applied Sciences, Department of Biotechnology


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