Genome-scale model reveals metabolic basis of biomass partitioning in a model diatom

TitleGenome-scale model reveals metabolic basis of biomass partitioning in a model diatom
Publication TypeJournal Article
Year of Publication2016
AuthorsLevering J., Broddrick J., Dupont C.L, Peers G., Beeri K., Mayers J., Gallina A.A, Allen A.E, Palsson B.O, Zengler K.
JournalPlos One
Date Published2016/05
Type of ArticleArticle
ISBN Number1932-6203
Accession NumberWOS:000375677000062
Keywordsamino-acid; biochemical-composition; extracellular-matrix; functional-characterization; glycolytic pathway; marine diatoms; phaeodactylum-tricornutum; protein; signal peptides; thalassiosira-pseudonana

Diatoms are eukaryotic microalgae that contain genes from various sources, including bacteria and the secondary endosymbiotic host. Due to this unique combination of genes, diatoms are taxonomically and functionally distinct from other algae and vascular plants and confer novel metabolic capabilities. Based on the genome annotation, we performed a genome-scale metabolic network reconstruction for the marine diatom Phaeodactylum tricornutum. Due to their endosymbiotic origin, diatoms possess a complex chloroplast structure which complicates the prediction of subcellular protein localization. Based on previous work we implemented a pipeline that exploits a series of bioinformatics tools to predict protein localization. The manually curated reconstructed metabolic network iLB1027_lipid accounts for 1,027 genes associated with 4,456 reactions and 2,172 metabolites distributed across six compartments. To constrain the genome-scale model, we determined the organism specific biomass composition in terms of lipids, carbohydrates, and proteins using Fourier transform infrared spectrometry. Our simulations indicate the presence of a yet unknown glutamine-ornithine shunt that could be used to transfer reducing equivalents generated by photosynthesis to the mitochondria. The model reflects the known biochemical composition of P. tricornutum in defined culture conditions and enables metabolic engineering strategies to improve the use of P. tricornutum for biotechnological applications.

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