@article{CordobaTongBurgosetal.2023,
  author    = {C{\´o}rdoba, Sandra Correa and Tong, Hao and Burgos, Asdrubal and Zhu, Feng and Alseekh, Saleh and Fernie, Alisdair R. and Nikoloski, Zoran},
  title     = {Identification of gene function based on models capturing natural variability of Arabidopsis thaliana lipid metabolism},
  series = {Nature Communications},
  volume    = {14},
  journal   = {Nature Communications},
  number    = {1},
  publisher = {Springer Nature},
  address   = {London},
  issn      = {2041-1723},
  doi       = {10.1038/s41467-023-40644-9},
  pages     = {12},
  year      = {2023},
  abstract  = {The use of automated tools to reconstruct lipid metabolic pathways is not warranted in plants. Here, the authors construct Plant Lipid Module for Arabidopsis rosette using constraint-based modeling, demonstrate its integration in other plant metabolic models, and use it to dissect the genetic architecture of lipid metabolism. Lipids play fundamental roles in regulating agronomically important traits. Advances in plant lipid metabolism have until recently largely been based on reductionist approaches, although modulation of its components can have system-wide effects. However, existing models of plant lipid metabolism provide lumped representations, hindering detailed study of component modulation. Here, we present the Plant Lipid Module (PLM) which provides a mechanistic description of lipid metabolism in the Arabidopsis thaliana rosette. We demonstrate that the PLM can be readily integrated in models of A. thaliana Col-0 metabolism, yielding accurate predictions (83\%) of single lethal knock-outs and 75\% concordance between measured transcript and predicted flux changes under extended darkness. Genome-wide associations with fluxes obtained by integrating the PLM in diel condition- and accession-specific models identify up to 65 candidate genes modulating A. thaliana lipid metabolism. Using mutant lines, we validate up to 40\% of the candidates, paving the way for identification of metabolic gene function based on models capturing natural variability in metabolism.},
  language  = {en}
}
@article{ArendZimmerXuetal.2023,
  author    = {Arend, Marius and Zimmer, David and Xu, Rudan and Sommer, Frederik and M{\"u}hlhaus, Timo and Nikoloski, Zoran},
  title     = {Proteomics and constraint-based modelling reveal enzyme kinetic properties of Chlamydomonas reinhardtii on a genome scale},
  series = {Nature Communications},
  volume    = {14},
  journal   = {Nature Communications},
  number    = {1},
  publisher = {Springer Nature},
  address   = {London},
  issn      = {2041-1723},
  doi       = {10.1038/s41467-023-40498-1},
  pages     = {9},
  year      = {2023},
  abstract  = {Metabolic engineering of microalgae offers a promising solution for sustainable biofuel production, and rational design of engineering strategies can be improved by employing metabolic models that integrate enzyme turnover numbers. However, the coverage of turnover numbers for Chlamydomonas reinhardtii, a model eukaryotic microalga accessible to metabolic engineering, is 17-fold smaller compared to the heterotrophic cell factory Saccharomyces cerevisiae. Here we generate quantitative protein abundance data of Chlamydomonas covering 2337 to 3708 proteins in various growth conditions to estimate in vivo maximum apparent turnover numbers. Using constrained-based modeling we provide proxies for in vivo turnover numbers of 568 reactions, representing a 10-fold increase over the in vitro data for Chlamydomonas. Integration of the in vivo estimates instead of in vitro values in a metabolic model of Chlamydomonas improved the accuracy of enzyme usage predictions. Our results help in extending the knowledge on uncharacterized enzymes and improve biotechnological applications of Chlamydomonas.},
  language  = {en}
}
@article{PandeyYuOmranianetal.2019,
  author    = {Pandey, Prashant K. and Yu, Jing and Omranian, Nooshin and Alseekh, Saleh and Vaid, Neha and Fernie, Alisdair R. and Nikoloski, Zoran and Laitinen, Roosa A. E.},
  title     = {Plasticity in metabolism underpins local responses to nitrogen in Arabidopsis thaliana populations},
  series = {Plant Direct},
  volume    = {3},
  journal   = {Plant Direct},
  number    = {11},
  publisher = {John Wiley \& sonst LTD},
  address   = {Chichester},
  issn      = {2475-4455},
  doi       = {10.1002/pld3.186},
  pages     = {6},
  year      = {2019},
  abstract  = {Nitrogen (N) is central for plant growth, and metabolic plasticity can provide a strategy to respond to changing N availability. We showed that two local A. thaliana populations exhibited differential plasticity in the compounds of photorespiratory and starch degradation pathways in response to three N conditions. Association of metabolite levels with growth-related and fitness traits indicated that controlled plasticity in these pathways could contribute to local adaptation and play a role in plant evolution.},
  language  = {en}
}