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Genome-scale metabolic model of Rhodococcus jostii RHA1 (iMT1174) to study the accumulation of storage compounds during nitrogen-limited condition.

Tajparast M, Frigon D - BMC Syst Biol (2015)

Bottom Line: Seven objective functions used with flux balance analysis (FBA) were compared for their capacity to predict the mixture of storage compounds accumulated after the sudden onset of N-limitation.Finally, it was found that the quantitative predictions of the storage mixture during N-limited storage accumulation were fairly sensitive to the biomass composition, as expected.PHA turned out to be the main storage pool of the mixture in R. jostii RHA1.

View Article: PubMed Central - PubMed

Affiliation: Microbial Community Engineering Laboratory, Department of Civil Engineering and Applied Mechanics, McGill University, 817 Sherbrooke Street West, Montreal, QC, H3A 0C3, Canada. mohammad.tajparast@mail.mcgill.ca.

ABSTRACT

Background: Rhodococcus jostii RHA1 growing on different substrates is capable of accumulating simultaneously three types of carbon storage compounds: glycogen, polyhydroxyalkanoates (PHA), and triacylglycerols (TAG). Under nitrogen-limited (N-limited) condition, the level of storage increases as is commonly observed for other bacteria. The proportion of each storage compound changes with substrate, but it remains unclear what modelling approach should be adopted to predict the relative composition of the mixture of the storage compounds. We analyzed the growth of R. jostii RHA1 under N-limited conditions using a genome-scale metabolic modelling approach to determine which global metabolic objective function could be used for the prediction.

Results: The R. jostii RHA1 model (iMT1174) produced during this study contains 1,243 balanced metabolites, 1,935 unique reactions, and 1,174 open reading frames (ORFs). Seven objective functions used with flux balance analysis (FBA) were compared for their capacity to predict the mixture of storage compounds accumulated after the sudden onset of N-limitation. Predictive abilities were determined using a Bayesian approach. Experimental data on storage accumulation mixture (glycogen, polyhydroxyalkanoates, and triacylglycerols) were obtained for batch cultures grown on glucose or acetate. The best FBA simulation results were obtained using a novel objective function for the N-limited condition which combined the maximization of the storage fluxes and the minimization of metabolic adjustments (MOMA) with the preceding non-limited conditions (max storage + environmental MOMA). The FBA solutions for the non-limited growth conditions were simply constrained by the objective function of growth rate maximization. Measurement of central metabolic fluxes by (13)C-labelling experiments of amino acids further supported the application of the environmental MOMA principle in the context of changing environment. Finally, it was found that the quantitative predictions of the storage mixture during N-limited storage accumulation were fairly sensitive to the biomass composition, as expected.

Conclusions: The genome-scale metabolic model analysis of R. jostii RHA1 cultures suggested that the intracellular reaction flux profile immediately after the onset of N-limited condition are impacted by the values of the same fluxes during the period of non-limited growth. PHA turned out to be the main storage pool of the mixture in R. jostii RHA1.

No MeSH data available.


Related in: MedlinePlus

Measured and calculated storage yields of three different storage compounds glycogen, PHA and TAG on glucose (a–f) and acetate (g–l). a measured storage yields on glucose, along with the error bars, b maximization of the storage fluxes+environmental MOMA on glucose, c environmental MOMA on glucose, d maximization of the storage fluxes on glucose, e minimization of the metabolic fluxes on glucose, f minimization and maximization of ATP production, and minimization of NADH production on glucose, g measured storage yield on acetate, along with the error bars, h maximization of the storage fluxes+environmental MOMA on acetate, i environmental MOMA on acetate, j maximization of the storage fluxes on acetate, k minimization of the metabolic fluxes on acetate, l minimization and maximization of ATP production, and minimization of NADH production on acetate. Note that the storage yields were identical for minimization and maximization of ATP production and minimization of NADH production; therefore, they were grouped in one graph
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Fig5: Measured and calculated storage yields of three different storage compounds glycogen, PHA and TAG on glucose (a–f) and acetate (g–l). a measured storage yields on glucose, along with the error bars, b maximization of the storage fluxes+environmental MOMA on glucose, c environmental MOMA on glucose, d maximization of the storage fluxes on glucose, e minimization of the metabolic fluxes on glucose, f minimization and maximization of ATP production, and minimization of NADH production on glucose, g measured storage yield on acetate, along with the error bars, h maximization of the storage fluxes+environmental MOMA on acetate, i environmental MOMA on acetate, j maximization of the storage fluxes on acetate, k minimization of the metabolic fluxes on acetate, l minimization and maximization of ATP production, and minimization of NADH production on acetate. Note that the storage yields were identical for minimization and maximization of ATP production and minimization of NADH production; therefore, they were grouped in one graph

Mentions: For the seven objective functions compared, two patterns of storage accumulation were simulated during the period of N-limitation and carbon excess; most of the objective functions simulated a single storage compound accumulation, while objective functions based on the environmental MOMA (environmental MOMA alone and maxStorage+environmental MOMA) predicted the accumulation of a mixture of storage compounds (Fig. 5b,c,h,i).Fig. 5


Genome-scale metabolic model of Rhodococcus jostii RHA1 (iMT1174) to study the accumulation of storage compounds during nitrogen-limited condition.

Tajparast M, Frigon D - BMC Syst Biol (2015)

Measured and calculated storage yields of three different storage compounds glycogen, PHA and TAG on glucose (a–f) and acetate (g–l). a measured storage yields on glucose, along with the error bars, b maximization of the storage fluxes+environmental MOMA on glucose, c environmental MOMA on glucose, d maximization of the storage fluxes on glucose, e minimization of the metabolic fluxes on glucose, f minimization and maximization of ATP production, and minimization of NADH production on glucose, g measured storage yield on acetate, along with the error bars, h maximization of the storage fluxes+environmental MOMA on acetate, i environmental MOMA on acetate, j maximization of the storage fluxes on acetate, k minimization of the metabolic fluxes on acetate, l minimization and maximization of ATP production, and minimization of NADH production on acetate. Note that the storage yields were identical for minimization and maximization of ATP production and minimization of NADH production; therefore, they were grouped in one graph
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4528721&req=5

Fig5: Measured and calculated storage yields of three different storage compounds glycogen, PHA and TAG on glucose (a–f) and acetate (g–l). a measured storage yields on glucose, along with the error bars, b maximization of the storage fluxes+environmental MOMA on glucose, c environmental MOMA on glucose, d maximization of the storage fluxes on glucose, e minimization of the metabolic fluxes on glucose, f minimization and maximization of ATP production, and minimization of NADH production on glucose, g measured storage yield on acetate, along with the error bars, h maximization of the storage fluxes+environmental MOMA on acetate, i environmental MOMA on acetate, j maximization of the storage fluxes on acetate, k minimization of the metabolic fluxes on acetate, l minimization and maximization of ATP production, and minimization of NADH production on acetate. Note that the storage yields were identical for minimization and maximization of ATP production and minimization of NADH production; therefore, they were grouped in one graph
Mentions: For the seven objective functions compared, two patterns of storage accumulation were simulated during the period of N-limitation and carbon excess; most of the objective functions simulated a single storage compound accumulation, while objective functions based on the environmental MOMA (environmental MOMA alone and maxStorage+environmental MOMA) predicted the accumulation of a mixture of storage compounds (Fig. 5b,c,h,i).Fig. 5

Bottom Line: Seven objective functions used with flux balance analysis (FBA) were compared for their capacity to predict the mixture of storage compounds accumulated after the sudden onset of N-limitation.Finally, it was found that the quantitative predictions of the storage mixture during N-limited storage accumulation were fairly sensitive to the biomass composition, as expected.PHA turned out to be the main storage pool of the mixture in R. jostii RHA1.

View Article: PubMed Central - PubMed

Affiliation: Microbial Community Engineering Laboratory, Department of Civil Engineering and Applied Mechanics, McGill University, 817 Sherbrooke Street West, Montreal, QC, H3A 0C3, Canada. mohammad.tajparast@mail.mcgill.ca.

ABSTRACT

Background: Rhodococcus jostii RHA1 growing on different substrates is capable of accumulating simultaneously three types of carbon storage compounds: glycogen, polyhydroxyalkanoates (PHA), and triacylglycerols (TAG). Under nitrogen-limited (N-limited) condition, the level of storage increases as is commonly observed for other bacteria. The proportion of each storage compound changes with substrate, but it remains unclear what modelling approach should be adopted to predict the relative composition of the mixture of the storage compounds. We analyzed the growth of R. jostii RHA1 under N-limited conditions using a genome-scale metabolic modelling approach to determine which global metabolic objective function could be used for the prediction.

Results: The R. jostii RHA1 model (iMT1174) produced during this study contains 1,243 balanced metabolites, 1,935 unique reactions, and 1,174 open reading frames (ORFs). Seven objective functions used with flux balance analysis (FBA) were compared for their capacity to predict the mixture of storage compounds accumulated after the sudden onset of N-limitation. Predictive abilities were determined using a Bayesian approach. Experimental data on storage accumulation mixture (glycogen, polyhydroxyalkanoates, and triacylglycerols) were obtained for batch cultures grown on glucose or acetate. The best FBA simulation results were obtained using a novel objective function for the N-limited condition which combined the maximization of the storage fluxes and the minimization of metabolic adjustments (MOMA) with the preceding non-limited conditions (max storage + environmental MOMA). The FBA solutions for the non-limited growth conditions were simply constrained by the objective function of growth rate maximization. Measurement of central metabolic fluxes by (13)C-labelling experiments of amino acids further supported the application of the environmental MOMA principle in the context of changing environment. Finally, it was found that the quantitative predictions of the storage mixture during N-limited storage accumulation were fairly sensitive to the biomass composition, as expected.

Conclusions: The genome-scale metabolic model analysis of R. jostii RHA1 cultures suggested that the intracellular reaction flux profile immediately after the onset of N-limited condition are impacted by the values of the same fluxes during the period of non-limited growth. PHA turned out to be the main storage pool of the mixture in R. jostii RHA1.

No MeSH data available.


Related in: MedlinePlus