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A computational analysis of stoichiometric constraints and trade-offs in cyanobacterial biofuel production.

Knoop H, Steuer R - Front Bioeng Biotechnol (2015)

Bottom Line: Applied to the synthesis of ethanol, ethylene, and propane, these in silico transition experiments point to bottlenecks and potential modification targets in cyanobacterial metabolism.Our analysis reveals incompatibilities between biotechnological product synthesis and native host metabolism, such as shifts in ATP/NADPH demand and the requirement to reintegrate metabolic by-products.Similar strategies can be employed for a large class of cyanobacterial products to identify potential stoichiometric bottlenecks.

View Article: PubMed Central - PubMed

Affiliation: Institut für Theoretische Biologie, Humboldt-Universität zu Berlin , Berlin , Germany.

ABSTRACT
Cyanobacteria are a promising biological chassis for the synthesis of renewable fuels and chemical bulk commodities. Significant efforts have been devoted to improve the yields of cyanobacterial products. However, while the introduction and heterologous expression of product-forming pathways is often feasible, the interactions and incompatibilities of product synthesis with the host metabolism are still insufficiently understood. In this work, we investigate the stoichiometric properties and trade-offs that underlie cyanobacterial product formation using a computational reconstruction of cyanobacterial metabolism. First, we evaluate the synthesis requirements of a selection of cyanobacterial products of potential biotechnological interest. Second, the large-scale metabolic reconstruction allows us to perform in silico experiments that mimic and predict the metabolic changes that must occur in the transition from a growth-only phenotype to a production-only phenotype. Applied to the synthesis of ethanol, ethylene, and propane, these in silico transition experiments point to bottlenecks and potential modification targets in cyanobacterial metabolism. Our analysis reveals incompatibilities between biotechnological product synthesis and native host metabolism, such as shifts in ATP/NADPH demand and the requirement to reintegrate metabolic by-products. Similar strategies can be employed for a large class of cyanobacterial products to identify potential stoichiometric bottlenecks.

No MeSH data available.


Metabolic transitions from cellular growth to product formation. We are interested in computationally predicted flux changes during the transition from growth-only phenotype to a production-only phenotype. We distinguish 5 different cases. (A) A given reaction flux is only active for product synthesis and attains a zero value for WT growth; (B) a reaction flux attains a non-zero value for growth, but increases for product synthesis; (C) a reaction flux is only active during growth and attains a zero value for product synthesis, (D) the predicted reaction flux for growth is larger than the flux required for product synthesis, (E) the reaction flux changes sign during the transition for a growth phenotype to a production phenotype. We note that predicted flux solutions are not unique. The shaded areas indicate regions of computationally equivalent solutions (flux variability).
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Figure 4: Metabolic transitions from cellular growth to product formation. We are interested in computationally predicted flux changes during the transition from growth-only phenotype to a production-only phenotype. We distinguish 5 different cases. (A) A given reaction flux is only active for product synthesis and attains a zero value for WT growth; (B) a reaction flux attains a non-zero value for growth, but increases for product synthesis; (C) a reaction flux is only active during growth and attains a zero value for product synthesis, (D) the predicted reaction flux for growth is larger than the flux required for product synthesis, (E) the reaction flux changes sign during the transition for a growth phenotype to a production phenotype. We note that predicted flux solutions are not unique. The shaded areas indicate regions of computationally equivalent solutions (flux variability).

Mentions: Our approach is further illustrated in Figure 4. The following scenarios can be distinguished: first, we expect that the majority of reaction fluxes decrease during the transition to product synthesis. The synthesis of any individual compound typically requires far fewer active reactions than the synthesis of biomass, whose formation involves the formation of a broad range of cellular compounds. Reactions that only participate in biomass synthesis but are not required for the synthesis of the desired product will eventually reach zero flux in the in silico transition experiment. Second, there may be reactions that carry lower, but still non-zero, flux in the production-only phenotype, as compared to wildtype growth. That is, flux through these reactions is required for product synthesis, but, given a fixed light intensity, this flux is significantly lower than the value required for cellular growth. These reactions are potential candidates for down-regulation, as their enzymatic capacities in the native host organism are likely to be adapted to a wildtype growth, hence exceeds the capacity required for product synthesis. Third, in addition to reactions with decreased flux, we also expect a number of reaction fluxes to increase during the transition toward synthesis of a desired product. In particular, the synthesis reactions itself, which are often heterologously expressed and therefore do not carry any flux in the WT. Of particular interest, however, are those reaction fluxes that increase their value during product synthesis, but are not itself part of the core synthesis pathway. These reactions constitute potential bottlenecks, as their enzymatic capacities may not be sufficient to support the increased flux necessary for product synthesis. As will be shown below, these reactions fluxes are typically associated with the recycling and reintegration of by-products and the adaptation of co-factor usage for product synthesis. Finally, in a few cases, fluxes may also reverse direction during the transition from a growth-only to a product-only phenotype. Table 2 provides a summary of the number of these different cases encountered in the transition experiments for the 12 bioproducts considered here. We note that the analysis of metabolic transitions toward fuel synthesis is complicated by the fact that the computationally predicted fluxes are usually not unique. Rather, several feasible and functionally equivalent flux solutions may exist. We therefore must take flux variability into account. Unless otherwise noted, all flux changes are reported in terms of median flux.


A computational analysis of stoichiometric constraints and trade-offs in cyanobacterial biofuel production.

Knoop H, Steuer R - Front Bioeng Biotechnol (2015)

Metabolic transitions from cellular growth to product formation. We are interested in computationally predicted flux changes during the transition from growth-only phenotype to a production-only phenotype. We distinguish 5 different cases. (A) A given reaction flux is only active for product synthesis and attains a zero value for WT growth; (B) a reaction flux attains a non-zero value for growth, but increases for product synthesis; (C) a reaction flux is only active during growth and attains a zero value for product synthesis, (D) the predicted reaction flux for growth is larger than the flux required for product synthesis, (E) the reaction flux changes sign during the transition for a growth phenotype to a production phenotype. We note that predicted flux solutions are not unique. The shaded areas indicate regions of computationally equivalent solutions (flux variability).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4403605&req=5

Figure 4: Metabolic transitions from cellular growth to product formation. We are interested in computationally predicted flux changes during the transition from growth-only phenotype to a production-only phenotype. We distinguish 5 different cases. (A) A given reaction flux is only active for product synthesis and attains a zero value for WT growth; (B) a reaction flux attains a non-zero value for growth, but increases for product synthesis; (C) a reaction flux is only active during growth and attains a zero value for product synthesis, (D) the predicted reaction flux for growth is larger than the flux required for product synthesis, (E) the reaction flux changes sign during the transition for a growth phenotype to a production phenotype. We note that predicted flux solutions are not unique. The shaded areas indicate regions of computationally equivalent solutions (flux variability).
Mentions: Our approach is further illustrated in Figure 4. The following scenarios can be distinguished: first, we expect that the majority of reaction fluxes decrease during the transition to product synthesis. The synthesis of any individual compound typically requires far fewer active reactions than the synthesis of biomass, whose formation involves the formation of a broad range of cellular compounds. Reactions that only participate in biomass synthesis but are not required for the synthesis of the desired product will eventually reach zero flux in the in silico transition experiment. Second, there may be reactions that carry lower, but still non-zero, flux in the production-only phenotype, as compared to wildtype growth. That is, flux through these reactions is required for product synthesis, but, given a fixed light intensity, this flux is significantly lower than the value required for cellular growth. These reactions are potential candidates for down-regulation, as their enzymatic capacities in the native host organism are likely to be adapted to a wildtype growth, hence exceeds the capacity required for product synthesis. Third, in addition to reactions with decreased flux, we also expect a number of reaction fluxes to increase during the transition toward synthesis of a desired product. In particular, the synthesis reactions itself, which are often heterologously expressed and therefore do not carry any flux in the WT. Of particular interest, however, are those reaction fluxes that increase their value during product synthesis, but are not itself part of the core synthesis pathway. These reactions constitute potential bottlenecks, as their enzymatic capacities may not be sufficient to support the increased flux necessary for product synthesis. As will be shown below, these reactions fluxes are typically associated with the recycling and reintegration of by-products and the adaptation of co-factor usage for product synthesis. Finally, in a few cases, fluxes may also reverse direction during the transition from a growth-only to a product-only phenotype. Table 2 provides a summary of the number of these different cases encountered in the transition experiments for the 12 bioproducts considered here. We note that the analysis of metabolic transitions toward fuel synthesis is complicated by the fact that the computationally predicted fluxes are usually not unique. Rather, several feasible and functionally equivalent flux solutions may exist. We therefore must take flux variability into account. Unless otherwise noted, all flux changes are reported in terms of median flux.

Bottom Line: Applied to the synthesis of ethanol, ethylene, and propane, these in silico transition experiments point to bottlenecks and potential modification targets in cyanobacterial metabolism.Our analysis reveals incompatibilities between biotechnological product synthesis and native host metabolism, such as shifts in ATP/NADPH demand and the requirement to reintegrate metabolic by-products.Similar strategies can be employed for a large class of cyanobacterial products to identify potential stoichiometric bottlenecks.

View Article: PubMed Central - PubMed

Affiliation: Institut für Theoretische Biologie, Humboldt-Universität zu Berlin , Berlin , Germany.

ABSTRACT
Cyanobacteria are a promising biological chassis for the synthesis of renewable fuels and chemical bulk commodities. Significant efforts have been devoted to improve the yields of cyanobacterial products. However, while the introduction and heterologous expression of product-forming pathways is often feasible, the interactions and incompatibilities of product synthesis with the host metabolism are still insufficiently understood. In this work, we investigate the stoichiometric properties and trade-offs that underlie cyanobacterial product formation using a computational reconstruction of cyanobacterial metabolism. First, we evaluate the synthesis requirements of a selection of cyanobacterial products of potential biotechnological interest. Second, the large-scale metabolic reconstruction allows us to perform in silico experiments that mimic and predict the metabolic changes that must occur in the transition from a growth-only phenotype to a production-only phenotype. Applied to the synthesis of ethanol, ethylene, and propane, these in silico transition experiments point to bottlenecks and potential modification targets in cyanobacterial metabolism. Our analysis reveals incompatibilities between biotechnological product synthesis and native host metabolism, such as shifts in ATP/NADPH demand and the requirement to reintegrate metabolic by-products. Similar strategies can be employed for a large class of cyanobacterial products to identify potential stoichiometric bottlenecks.

No MeSH data available.