The use of genome-scale metabolic network reconstruction to predict fluxes and equilibrium composition of N-fixing versus C-fixing cells in a diazotrophic cyanobacterium, Trichodesmium erythraeum

This file contains the list of dead end reactions generated by the study, not including exchange reactions. This means all reactions which include a metabolite that cannot be otherwise resolved (through reaction to another compound) is included. Dead ends are ignorant to photoautotroph or diazotroph because of the similar genetic background. (XLSX 50 kb

Multiscale Multiobjective Systems Analysis (MiMoSA): an advanced metabolic modeling framework for complex systems

In natural environments, cells live in complex communities and experience a high degree of heterogeneity internally and in the environment. Even in &lsquo;ideal&rsquo; laboratory environments, cells can experience a high degree of heterogeneity in their environments. Unfortunately, most of the metabolic modeling approaches that are currently used assume ideal conditions and that each cell is identical, limiting their application to pure cultures in well-mixed vessels. Here we describe our development of Multiscale Multiobjective Systems Analysis (MiMoSA), a metabolic modeling approach that can track individual cells in both space and time, track the diffusion of nutrients and light and the interaction of cells with each other and the environment. As a proof-of concept study, we used MiMoSA to model the growth of Trichodesmium erythraeum, a filamentous diazotrophic cyanobacterium which has cells with two distinct metabolic modes. The use of MiMoSA significantly improves our ability to predictively model metabolic changes and phenotype in more complex cell cultures. </div

Flux balance analysis of primary metabolism in Chlamydomonas reinhardtii

Background Photosynthetic organisms convert atmospheric carbon dioxide into numerous metabolites along the pathways to make new biomass. Aquatic photosynthetic organisms, which fix almost half of global inorganic carbon, have great potential: as a carbon dioxide fixation method, for the economical production of chemicals, or as a source for lipids and starch which can then be converted to biofuels. To harness this potential through metabolic engineering and to maximize production, a more thorough understanding of photosynthetic metabolism must first be achieved. A model algal species, C. reinhardtii, was chosen and the metabolic network reconstructed. Intracellular fluxes were then calculated using flux balance analysis (FBA). Results The metabolic network of primary metabolism for a green alga, C. reinhardtii, was reconstructed using genomic and biochemical information. The reconstructed network accounts for the intracellular localization of enzymes to three compartments and includes 484 metabolic reactions and 458 intracellular metabolites. Based on BLAST searches, one newly annotated enzyme (fructose-1,6-bisphosphatase) was added to the Chlamydomonas reinhardtii database. FBA was used to predict metabolic fluxes under three growth conditions, autotrophic, heterotrophic and mixotrophic growth. Biomass yields ranged from 28.9 g per mole C for autotrophic growth to 15 g per mole C for heterotrophic growth. Conclusion The flux balance analysis model of central and intermediary metabolism in C. reinhardtii is the first such model for algae and the first model to include three metabolically active compartments. In addition to providing estimates of intracellular fluxes, metabolic reconstruction and modelling efforts also provide a comprehensive method for annotation of genome databases. As a result of our reconstruction, one new enzyme was annotated in the database and several others were found to be missing; implying new pathways or non-conserved enzymes. The use of FBA to estimate intracellular fluxes also provides flux values that can be used as a starting point for rational engineering of C. reinhardtii. From these initial estimates, it is clear that aerobic heterotrophic growth on acetate has a low yield on carbon, while mixotrophically and autotrophically grown cells are significantly more carbon efficient

Stoichiometric modeling of photoautotrophic metabolism

Photosynthetic organisms are capable of producing a wide array of important organic compounds from freely available light and carbon dioxide. Roughly half of the annual rate of biological carbon fixation (105 petagrams) is performed by algae and other marine organisms. These organisms represent a large untapped potential for the production of proteins, secondary metabolites, organic acids, starch, lipids, etc. which can be converted into feed, specialty and bulk chemicals as well as biofuels. The main advantages of using algae for production of renewable feedstocks and fuels instead of terrestrial plants are that they have faster growth rates, they can be grown on non-arable land and they do not compete with food/feed supplies. In order to harness the potential of marine organisms to produce industrially relevant compounds at high levels, a basic understanding of cellular metabolism is required. We present the first metabolic network reconstruction and flux balance analysis of the model green alga, Chlamydomonas reinhardtii. The reconstructed network includes all pathways in primary metabolism (glycolysis, tricarboxylic acid cycle, reductive and oxidative pentose phosphate pathway) and the synthesis of amino acids, chlorophyll, starch, nucleotides and lipids. In total the network accounts for 484 enzymes, 729 reactions and 458 metabolites which are localized into three intracellular compartments (cytosol, mitochondria and chloroplast). Intracellular fluxes were estimated using flux balance analysis for optimal growth in three growth regimes: autotrophy, heterotrophy and mixotrophy and compared. Autotrophic fluxes were also compared to FBA results for Synechocystis, a cyanobacterium. Flux balance analysis was also used to compare fluxes and efficiencies of the five known carbon dioxide fixation pathways (Calvin Cycle, reductive TCA cycle, reductive acetyl-CoA pathway, 3-hydroxypropionate/malyl-CoA cycle and 3-hydroxypropionate/4-hydroxybutyrate cycle). Three of the pathways occur in photoautotrophic organisms, two in chemotrophic (hydrogen-utlizing) organisms. In contrast to light energy, hydrogen is not freely available; therefore the production of hydrogen from light is included in the overall energy demand calculation. This allows an even basis of comparison because all organisms are then using light as their primary energy source. Carbon fluxes, overall energy demand and efficiencies for each pathway are calculated and presented

Comparison of TCA cycle fluxes calculated by flux balance analysis with metabolic flux analysis.

<p>(A) FBA fluxes with maximum biomass as the objective function. (B) ¹³C-MFA calculated fluxes. (C) FBA fluxes with maximum ATP production as the objective function. The thickness of the arrow in panels A-C depicts the amount of flux through the reaction.</p

Fluxes calculated by ¹³C metabolic flux analysis for Case B (cytosolic citrate synthase and no plastidic gluconeogenesis).

<p>The fluxes are normalized to uptake rate of acetate on a basis of 10. The 90% confidence intervals for the fluxes are also reported in the supplementary materials (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0177292#pone.0177292.s010" target="_blank">S7 Table</a>).</p

Simplified diagram depicting the different network cases studied.

<p>(A) The ‘base case’ in which the network only includes cytosolic gluconeogenesis. (B) This case, based on case A, also includes cytosolic citrate synthase, which was included based on genomic and proteomic evidence. (C) This case is case B with the addition of plastidic gluconeogensis. (D) No cytosolic gluconeogenesis was included, but cytosolic citrate synthase and plastidic gluconeogenesis are included. (E) Only plastidic gluconeogenesis is included. The table in the bottom right hand corner gives the residuals (calculated by F-statistic) and degrees of freedom for each case. Additional information about statistical significance is provided in supplemental info.</p

Schematic of the overall modeling strategy.

<p>All the cases were evaluated independently and were evaluated by including dilution due to existing unlabeled biomass and unlabeled CO₂ from air. The case that gave the best statistical fit was selected as the final flux map for heterotrophic growth on acetate.</p