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Dynamics of the Heat Stress Response of Ceramides with Different Fatty-Acyl Chain Lengths in Baker's Yeast.

Chen PW, Fonseca LL, Hannun YA, Voit EO - PLoS Comput. Biol. (2015)

Bottom Line: The article demonstrates that computational modeling has the capacity to convert metabolic snapshots, taken sequentially over time, into a description of cellular, dynamic strategies.The specific application is a detailed analysis of a set of actions with which Saccharomyces cerevisiae responds to heat stress.The details of the sphingolipid responses to heat stress are important, because they guide some of the longer-term alterations in gene expression, with which the cells adapt to the increased temperature.

View Article: PubMed Central - PubMed

Affiliation: Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America; The George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America.

ABSTRACT
The article demonstrates that computational modeling has the capacity to convert metabolic snapshots, taken sequentially over time, into a description of cellular, dynamic strategies. The specific application is a detailed analysis of a set of actions with which Saccharomyces cerevisiae responds to heat stress. Using time dependent metabolic concentration data, we use a combination of mathematical modeling, reverse engineering, and optimization to infer dynamic changes in enzyme activities within the sphingolipid pathway. The details of the sphingolipid responses to heat stress are important, because they guide some of the longer-term alterations in gene expression, with which the cells adapt to the increased temperature. The analysis indicates that all enzyme activities in the system are affected and that the shapes of the time trends in activities depend on the fatty-acyl CoA chain lengths of the different ceramide species in the system.

No MeSH data available.


Related in: MedlinePlus

Details of the procedures of flux estimation and enzyme activity estimation.
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pcbi.1004373.g011: Details of the procedures of flux estimation and enzyme activity estimation.

Mentions: Details of the two core components of our approach, namely the estimation of dynamic fluxes and of enzyme activities, are shown in the flowchart of Fig 11. The first task, as shown in the upper panel of Fig 11, consists of checking the mass balances within the system and to construct the stoichiometric matrix that describes the production and degradation rates of the dependent metabolites. Because the system has considerably more fluxes than metabolites, we are faced with a highly underdetermined system. We are dealing with this situation by solving the system in 30 pieces, starting from the initial steady state to time 1, from time 1 to time 2, all the way to the end of the heat stress experiment (30th minute). The following describes in more detail a customized optimization strategy with which we determine the flux distribution in each time point.


Dynamics of the Heat Stress Response of Ceramides with Different Fatty-Acyl Chain Lengths in Baker's Yeast.

Chen PW, Fonseca LL, Hannun YA, Voit EO - PLoS Comput. Biol. (2015)

Details of the procedures of flux estimation and enzyme activity estimation.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4524633&req=5

pcbi.1004373.g011: Details of the procedures of flux estimation and enzyme activity estimation.
Mentions: Details of the two core components of our approach, namely the estimation of dynamic fluxes and of enzyme activities, are shown in the flowchart of Fig 11. The first task, as shown in the upper panel of Fig 11, consists of checking the mass balances within the system and to construct the stoichiometric matrix that describes the production and degradation rates of the dependent metabolites. Because the system has considerably more fluxes than metabolites, we are faced with a highly underdetermined system. We are dealing with this situation by solving the system in 30 pieces, starting from the initial steady state to time 1, from time 1 to time 2, all the way to the end of the heat stress experiment (30th minute). The following describes in more detail a customized optimization strategy with which we determine the flux distribution in each time point.

Bottom Line: The article demonstrates that computational modeling has the capacity to convert metabolic snapshots, taken sequentially over time, into a description of cellular, dynamic strategies.The specific application is a detailed analysis of a set of actions with which Saccharomyces cerevisiae responds to heat stress.The details of the sphingolipid responses to heat stress are important, because they guide some of the longer-term alterations in gene expression, with which the cells adapt to the increased temperature.

View Article: PubMed Central - PubMed

Affiliation: Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America; The George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America.

ABSTRACT
The article demonstrates that computational modeling has the capacity to convert metabolic snapshots, taken sequentially over time, into a description of cellular, dynamic strategies. The specific application is a detailed analysis of a set of actions with which Saccharomyces cerevisiae responds to heat stress. Using time dependent metabolic concentration data, we use a combination of mathematical modeling, reverse engineering, and optimization to infer dynamic changes in enzyme activities within the sphingolipid pathway. The details of the sphingolipid responses to heat stress are important, because they guide some of the longer-term alterations in gene expression, with which the cells adapt to the increased temperature. The analysis indicates that all enzyme activities in the system are affected and that the shapes of the time trends in activities depend on the fatty-acyl CoA chain lengths of the different ceramide species in the system.

No MeSH data available.


Related in: MedlinePlus