Fig 1.
Metabolic network reconstruction workflow.
In step one we obtained a draft reconstruction based on P. tricornutum’s genome annotation and reference reconstructions. This draft reconstruction was manually curated using several resources such as an improved genome annotation, subcellular localization predictions and external databases. All reactions were elementally and charge balanced, QC/QA was performed and a biomass objective function was defined before transforming the reconstruction into a computational model. In an iterative process, the in silico predictions are compared with experimental observations to validate and improve the metabolic model.
Fig 2.
Reconstruction characteristics iLB1027_lipid.
(A) Reactions per subsystem. Most reactions are involved in lipid metabolism. Our FTIR measurements underline the fact that the lipids make up the highest fraction of biomass. Due to the presence of multiple compartments and the fact that many pathways are split among compartments, many reactions are attributed to intracellular transport. The modeling subsystem contains ATP maintenance, biomass, demand, sink, and exchange reactions. (B) Percent reactions and metabolites per compartment. Most reactions and metabolites are present in the cytosol, followed by chloroplast and mitochondria in the case of reactions and mitochondria and chloroplast for metabolites. Peroxisome, extracellular space, and thylakoid contain less than 5% and 8% of all reactions and metabolites in the reconstruction, respectively.
Fig 3.
Subcellular localization prediction pipeline.
Schematic representation of the implemented subcellular localization prediction pipeline for Phaeodactylum tricornutum adapted from previous work [57]. Subcellular compartments are given in ellipses and bioinformatics programs are displayed in rectangles. Our added steps are highlighted in gray. The ER retention signal is (K/D)-(D/E)-E-L in the protein C-terminal region. A protein is categorized as peroxisomal if the signal (S/A/C)-(K/R/H)-(L/M) or S-S-L is found in the C-terminal region.
Table 1.
Validation of the in silico subcellular localization prediction pipeline.
Fig 4.
FTIR spectrum and culture data.
A typical FTIR spectrum for Phaeodactylum tricornutum is shown in (A). Peaks corresponding to lipids, proteins and carbohydrates are highlighted (see Table A in S1 File for specific wavelengths). Panel (B) shows the growth curve and photosynthetic efficiency of the culture used for model calibrations and the biomass objective function. The decline in Fv/Fm indicates the onset of nitrogen starvation (n = 1). Percent dry weight of the cells in terms of carbohydrates, lipids, and proteins according to FTIR spectra and the calibrated linear model (n = 5, error bars represent five independent FTIR scans) is displayed in (C).
Table 2.
Characteristics of available models for Phaeodactylum tricornutum.
Fig 5.
Genes in reconstruction over predicted genes in genome against genome size for selected eukaryotic metabolic reconstructions.
The three reconstructions with the highest ratio of genes in reconstruction per genes in genome are highlighted. bna572+ has a comparable ratio as iLB1025 and iLB1027_lipid, iTO977 has a higher ratio. Compared to iTO977 and bna572+, iLB1025 and iLB1027_lipid contain more reactions. The number of reactions in the respective reconstructions is used to scale the circle diameters. Note the discontinuous x-axis. Abbreviations: AraGEM: Arabidopsis thaliana [73]; bna572+: Brassica napus [74]; AlgaGEM: Chlamydomonas reinhardtii [75]; iRC1080: Chlamydomonas reinhardtii [39]; iRS1563: Zea mays [76]; iLB1025 and iLB1027_lipid: Phaeodactylum tricornutum, this study; iTO977: Saccharomyces cerevisiae Sc288 [77]; Recon2: Homo sapiens [78]; iMM1415: Mus musculus [79].
Fig 6.
Light-dependent carbon partitioning.
(A) Simulations indicated as photon uptake exceeds carbon uptake, excess redox potential is stored in triacylglycerol. The saturation of carbon uptake is shown in black. (B) Percent of carbon fixed in TAG against percent of metabolite flow through NADHOR (vNADHOR; EC 1.6.5.3,1.6.99.3) over metabolite flow through PSI (vPSI; EC 1.97.1.2) at a super-saturating photon uptake of 22 mM. According to our simulations TAG accumulation is inversely proportional to energetic coupling. TAG accumulation is prohibited when at least 35% of photosynthetically fixed electrons are redirected to the mitochondria.
Table 3.
Photosynthetic electron flow constraints as determined by Bailleul et al. [83].
Fig 7.
Chloroplastic ornithine cycle as revealed by the model.
Metabolic network usage of a chloroplastic ornithine cycle is shown under a saturating photon constraint of 16 mM allowing maximum carbon uptake. Minor reactants and products are omitted for visual clarity (i.e., water, protons and phosphate). Metabolite and reaction abbreviation suffixes indicate cellular compartment; c, cytosol; h, chloroplast; m, mitochondria. Reversible reactions are indicated by arrowheads at both ends. The filled arrowhead indicates the direction in which the reaction is running, i.e. from substrate (open arrowhead) to product (filled arrowhead). Abbreviations used: ACOAT, acetylornithine transaminase; AGK, acetylglutamate kinase; AGPR, N-acetyl-δ-glutamyl-phosphate reductase; GACT, glutamate N-acetyltransferase; GLNA, glutamine synthase; GLTS, glutamate synthase (ferredoxin dependent); GLUDH2, glutamine dehydrogenase (NAD dependent); GLUSA, glutamate semialdehyde degradation (spontaneous); OAT, ornithine aminotransferase; P5CDH, 1-pyrroline-5-carboxylate dehydrogenase; acorn, N-acetylornithine; acglu, N-acetyl-L-glutamate; acg5p, N-acetyl-L-glutamate 5-phosphate; acg5sa, N-Acetyl-L-glutamate 5-semialdehyde; adp, ADP; akg, α-ketoglutarate; atp, ATP; fdxox, ferredoxin (oxidized); fdxrd, ferredoxin (reduced); gln__L, L-glutamine; glu__L, L-glutamate; glu5sa, L-glutamate 5-semialdehyde; nad, NAD+; nadh, NADH; nadp, NADP+; nadph, NADPH; nh4, ammonium ion; orn, ornithine; 1pyr5c, (S)-1-Pyrroline-5-carboxylate.