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. 2020 Sep 11;8(9):1396.
doi: 10.3390/microorganisms8091396.

A Genome-Scale Metabolic Model of Thalassiosira pseudonana CCMP 1335 for a Systems-Level Understanding of Its Metabolism and Biotechnological Potential

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A Genome-Scale Metabolic Model of Thalassiosira pseudonana CCMP 1335 for a Systems-Level Understanding of Its Metabolism and Biotechnological Potential

Ahmad Ahmad et al. Microorganisms. .

Abstract

Thalassiosira pseudonana is a transformable and biotechnologically promising model diatom with an ability to synthesise nutraceuticals such as fucoxanthin and store a significant amount of polyglucans and lipids including omega-3 fatty acids. While it was the first diatom to be sequenced, a systems-level analysis of its metabolism has not been done yet. This work presents first comprehensive, compartmentalized, and functional genome-scale metabolic model of the marine diatom Thalassiosira pseudonana CCMP 1335, which we have termed iThaps987. The model includes 987 genes, 2477 reactions, and 2456 metabolites. Comparison with the model of another diatom Phaeodactylum tricornutum revealed presence of 183 unique enzymes (belonging primarily to amino acid, carbohydrate, and lipid metabolism) in iThaps987. Model simulations showed a typical C3-type photosynthetic carbon fixation and suggested a preference of violaxanthin-diadinoxanthin pathway over violaxanthin-neoxanthin pathway for the production of fucoxanthin. Linear electron flow was found be active and cyclic electron flow was inactive under normal phototrophic conditions (unlike green algae and plants), validating the model predictions with previous reports. Investigation of the model for the potential of Thalassiosira pseudonana CCMP 1335 to produce other industrially useful compounds suggest iso-butanol as a foreign compound that can be synthesized by a single-gene addition. This work provides novel insights about the metabolism and potential of the organism and will be helpful to further investigate its metabolism and devise metabolic engineering strategies for the production of various compounds.

Keywords: diatom; flux analysis; fucoxanthin; heterologous products; photosynthesis.

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Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection; analyses; or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Figures

Figure 1
Figure 1
Comparison of two diatom GEMs. (a) A Venn diagram showing common and unique enzymes in iThaps987 and iLB1025 models. (b) Distribution of unique enzymes iThaps987 in various main pathway categories. (c) Distribution of unique enzymes in sub-pathways of main pathway categories. The color coding follows the colors used for the corresponding pathway in (b).
Figure 1
Figure 1
Comparison of two diatom GEMs. (a) A Venn diagram showing common and unique enzymes in iThaps987 and iLB1025 models. (b) Distribution of unique enzymes iThaps987 in various main pathway categories. (c) Distribution of unique enzymes in sub-pathways of main pathway categories. The color coding follows the colors used for the corresponding pathway in (b).
Figure 2
Figure 2
Flux-map showing flux distributions under Si-rich/Si-limited condition. Chloroplast are shown in green color while mitochondria are shown in red. Photosynthesis, lipid, and fucoxanthin synthesis occurs in chloroplast while the TCA cycle and part of the urea cycle occurs in mitochondria. Other major pathways are located in cytosol. The flux through pathways was simulated by fixing the measured growth rate and using the minimization of total flux as the objective function.
Figure 3
Figure 3
Effect Si+ transport variation on biomass and chrysolaminarin production. For these simulations, the Si+-transport was varied from zero to the value obtained under Si+ replete condition (0.05 mmol/(gDCW.h) and the fluxes through biomass and chrysolaminarin biosynthesis reactions are presented.
Figure 4
Figure 4
Simulated effect of variation of maintenance ATP (ATPM) values on metabolism. (a) Effect of ATPM values on the ratio of mitochondrial and plastidial ATP synthesis. The flux through ATPM reaction was varied and the effect on plastidial and mitochondrial ATP synthesis reactions was simulated. (b) Effect of ATPM values on flux through different reactions of the model, iThaps987. PSI: Photosystem-I, PSII: photosystem-II, Photon_tx: Photon transport, Plastidial_ATP_Synthase: Plastdial ATP synthesis reaction, Mitochondrial_ATP_Synthase: Mitochondrial ATP synthesis reaction, OAA_MAL_Chlo_tx: Malate–oxaloacetate shuttle_chloroplast_transport, OAA_MAL_Mito_tx: Malate–oxaloacetate shuttle_ mitochondria_transport. (c): The figure shows the fluxes under low (1.5 mmol/(gDW.h)) and high (7.5 mmol/(gDW.h)) ATP maintenance values. The values written in green were obtained from simulations performed under normal wild-type conditions while the values written in red were obtained from simulations performed by knocking out the transporter for mitochondrial malate–oxaloacetate shuttle. LEF: Linear Electron Flow, CEF: Cyclic Electron Flow, PSI: Photo-system I, PSII: Photo-system II, PQ: Plastoquinone, PC: Plastocyanin, Fdxn: Ferredoxin.
Figure 4
Figure 4
Simulated effect of variation of maintenance ATP (ATPM) values on metabolism. (a) Effect of ATPM values on the ratio of mitochondrial and plastidial ATP synthesis. The flux through ATPM reaction was varied and the effect on plastidial and mitochondrial ATP synthesis reactions was simulated. (b) Effect of ATPM values on flux through different reactions of the model, iThaps987. PSI: Photosystem-I, PSII: photosystem-II, Photon_tx: Photon transport, Plastidial_ATP_Synthase: Plastdial ATP synthesis reaction, Mitochondrial_ATP_Synthase: Mitochondrial ATP synthesis reaction, OAA_MAL_Chlo_tx: Malate–oxaloacetate shuttle_chloroplast_transport, OAA_MAL_Mito_tx: Malate–oxaloacetate shuttle_ mitochondria_transport. (c): The figure shows the fluxes under low (1.5 mmol/(gDW.h)) and high (7.5 mmol/(gDW.h)) ATP maintenance values. The values written in green were obtained from simulations performed under normal wild-type conditions while the values written in red were obtained from simulations performed by knocking out the transporter for mitochondrial malate–oxaloacetate shuttle. LEF: Linear Electron Flow, CEF: Cyclic Electron Flow, PSI: Photo-system I, PSII: Photo-system II, PQ: Plastoquinone, PC: Plastocyanin, Fdxn: Ferredoxin.
Figure 5
Figure 5
Distribution of total and essential reactions of the model across various subsystems.

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