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A systematic simulation of the effect of salicylic acid on sphingolipid metabolism.

Shi C, Yin J, Liu Z, Wu JX, Zhao Q, Ren J, Yao N - Front Plant Sci (2015)

Bottom Line: This model predicts significant changes in fluxes of certain sphingolipid species after SA treatment, changes that likely trigger downstream physiological and phenotypic effects.The results show that both SA and BTH affect sphingolipid metabolism, altering the concentrations of certain species and also changing the optimal flux distribution and turnover rate of sphingolipids.Our strategy allows us to estimate sphingolipid fluxes on a short time scale and gives us a systemic view of the effect of SA on sphingolipid homeostasis.

View Article: PubMed Central - PubMed

Affiliation: State Key Laboratory of Biocontrol, Guangdong Key Laboratory of Plant Resources, Department of Biological Science and Technology, School of Life Sciences, Sun Yat-sen University Guangzhou, China.

ABSTRACT
The phytohormone salicylic acid (SA) affects plant development and defense responses. Recent studies revealed that SA also participates in the regulation of sphingolipid metabolism, but the details of this regulation remain to beexplored. Here, we use in silico Flux Balance Analysis (FBA) with published microarray data to construct a whole-cell simulation model, including 23 pathways, 259 reactions, and 172 metabolites, to predict the alterations in flux of major sphingolipid species after treatment with exogenous SA. This model predicts significant changes in fluxes of certain sphingolipid species after SA treatment, changes that likely trigger downstream physiological and phenotypic effects. To validate the simulation, we used (15)N-labeled metabolic turnover analysis to measure sphingolipid contents and turnover rate in Arabidopsis thaliana seedlings treated with SA or the SA analog benzothiadiazole (BTH). The results show that both SA and BTH affect sphingolipid metabolism, altering the concentrations of certain species and also changing the optimal flux distribution and turnover rate of sphingolipids. Our strategy allows us to estimate sphingolipid fluxes on a short time scale and gives us a systemic view of the effect of SA on sphingolipid homeostasis.

No MeSH data available.


Simulated flux distribution of selected sphingolipid species. The untreated plants (black) and in silico SA (light gray) and BTH-treated plants (gray) were taken from the flux balance model. The effects of exogenous SA and BTH were simulated by changing the target flux bound proportional to its related gene expression alteration identified by published microarray data (Wang et al., 2006; van Leeuwen et al., 2007). LC, long-chain (≤C18); VLC: very-long-chain (>C18).
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Figure 2: Simulated flux distribution of selected sphingolipid species. The untreated plants (black) and in silico SA (light gray) and BTH-treated plants (gray) were taken from the flux balance model. The effects of exogenous SA and BTH were simulated by changing the target flux bound proportional to its related gene expression alteration identified by published microarray data (Wang et al., 2006; van Leeuwen et al., 2007). LC, long-chain (≤C18); VLC: very-long-chain (>C18).

Mentions: indicate significant up and down, respectively (P < 0.05, FDR < 0.05 in multiple covariance analysis) of incorporation rate compared to untreated plants. The bold numbers are in disagreement with simulation data shown in Figure 2.


A systematic simulation of the effect of salicylic acid on sphingolipid metabolism.

Shi C, Yin J, Liu Z, Wu JX, Zhao Q, Ren J, Yao N - Front Plant Sci (2015)

Simulated flux distribution of selected sphingolipid species. The untreated plants (black) and in silico SA (light gray) and BTH-treated plants (gray) were taken from the flux balance model. The effects of exogenous SA and BTH were simulated by changing the target flux bound proportional to its related gene expression alteration identified by published microarray data (Wang et al., 2006; van Leeuwen et al., 2007). LC, long-chain (≤C18); VLC: very-long-chain (>C18).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4373270&req=5

Figure 2: Simulated flux distribution of selected sphingolipid species. The untreated plants (black) and in silico SA (light gray) and BTH-treated plants (gray) were taken from the flux balance model. The effects of exogenous SA and BTH were simulated by changing the target flux bound proportional to its related gene expression alteration identified by published microarray data (Wang et al., 2006; van Leeuwen et al., 2007). LC, long-chain (≤C18); VLC: very-long-chain (>C18).
Mentions: indicate significant up and down, respectively (P < 0.05, FDR < 0.05 in multiple covariance analysis) of incorporation rate compared to untreated plants. The bold numbers are in disagreement with simulation data shown in Figure 2.

Bottom Line: This model predicts significant changes in fluxes of certain sphingolipid species after SA treatment, changes that likely trigger downstream physiological and phenotypic effects.The results show that both SA and BTH affect sphingolipid metabolism, altering the concentrations of certain species and also changing the optimal flux distribution and turnover rate of sphingolipids.Our strategy allows us to estimate sphingolipid fluxes on a short time scale and gives us a systemic view of the effect of SA on sphingolipid homeostasis.

View Article: PubMed Central - PubMed

Affiliation: State Key Laboratory of Biocontrol, Guangdong Key Laboratory of Plant Resources, Department of Biological Science and Technology, School of Life Sciences, Sun Yat-sen University Guangzhou, China.

ABSTRACT
The phytohormone salicylic acid (SA) affects plant development and defense responses. Recent studies revealed that SA also participates in the regulation of sphingolipid metabolism, but the details of this regulation remain to beexplored. Here, we use in silico Flux Balance Analysis (FBA) with published microarray data to construct a whole-cell simulation model, including 23 pathways, 259 reactions, and 172 metabolites, to predict the alterations in flux of major sphingolipid species after treatment with exogenous SA. This model predicts significant changes in fluxes of certain sphingolipid species after SA treatment, changes that likely trigger downstream physiological and phenotypic effects. To validate the simulation, we used (15)N-labeled metabolic turnover analysis to measure sphingolipid contents and turnover rate in Arabidopsis thaliana seedlings treated with SA or the SA analog benzothiadiazole (BTH). The results show that both SA and BTH affect sphingolipid metabolism, altering the concentrations of certain species and also changing the optimal flux distribution and turnover rate of sphingolipids. Our strategy allows us to estimate sphingolipid fluxes on a short time scale and gives us a systemic view of the effect of SA on sphingolipid homeostasis.

No MeSH data available.