Analysis of organic acids of tricarboxylic acid cycle in plants using GC-MS, and system modeling

Abstract Background Leaves of 15 plant species were collected from the catchment areas of the river Beas, Punjab, India, and analyzed for organic acids of tricarboxylic acid cycle, viz., citric acid (CA), succinic acid (SA), fumaric acid (FmA), and malic acid (MA). Methods Gas chromatography-mass sp...

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Main Authors: Vinod Kumar, Anket Sharma, Renu Bhardwaj, Ashwani Kumar Thukral
Format: Article
Language:English
Published: SpringerOpen 2017-10-01
Series:Journal of Analytical Science and Technology
Subjects:
Online Access:http://link.springer.com/article/10.1186/s40543-017-0129-6
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spelling doaj-f5277836bfad45b8b74c98aad11dc9702020-11-24T20:53:16ZengSpringerOpenJournal of Analytical Science and Technology2093-33712017-10-01811910.1186/s40543-017-0129-6Analysis of organic acids of tricarboxylic acid cycle in plants using GC-MS, and system modelingVinod Kumar0Anket Sharma1Renu Bhardwaj2Ashwani Kumar Thukral3Department of Botany, DAV UniversityDepartment of Botany, DAV UniversityDepartment of Botanical & Environmental Sciences, Guru Nanak Dev UniversityDepartment of Botanical & Environmental Sciences, Guru Nanak Dev UniversityAbstract Background Leaves of 15 plant species were collected from the catchment areas of the river Beas, Punjab, India, and analyzed for organic acids of tricarboxylic acid cycle, viz., citric acid (CA), succinic acid (SA), fumaric acid (FmA), and malic acid (MA). Methods Gas chromatography-mass spectrometry (GC-MS) was used to determine the content of organic acids in the leaves of plant species. Two microliters of plant sample was injected into the GC-MS, and the concentration of organic acids was quantified using standard curve. Results Average concentrations of these acids in the leaves of plants studied were 4.79, 0.98, 0.54, and 8.36 mg/g dw, respectively. The maximum contents of these acids were found in the leaves of Chenopodium album (CA = 6.42 mg/g dw), Argemone mexicana (SA = 1.27 and FmA = 0.73 mg/g dw), and Rumex dentatus (MA = 18.0 mg/g dw). Factor analysis revealed mainly two underlying factors for organic acids: Factor-1 having maximum loadings on SA and FmA and Factor-2 had maximum loadings on CA and MA. Multiple linear regression analysis of MA on other acids showed that CA and SA have positive regressions, whereas FmA has a negative regression on MA. In artificial neural network analysis, correlation between the target and output values of MA was found to be highly significant. System transfer coefficients were calculated from simulation graphs fitted to the mean values of different organic acids by using difference equations. Conclusions From the present study, it was found that citric acid has a maximum direct effect on the malic acid as compared to succinic and fumaric acids as revealed by path analysis. System modeling revealed that the rate of utilization of malic acid is about 9%. The present study describes a new system simulation technique in which a pathway comprising of linear transformation of biochemical constituents may be characterized in terms of its rate transfer coefficients.http://link.springer.com/article/10.1186/s40543-017-0129-6Krebs cycleCitric acidSuccinic acidFumaric acidMalic acidSimulation
collection DOAJ
language English
format Article
sources DOAJ
author Vinod Kumar
Anket Sharma
Renu Bhardwaj
Ashwani Kumar Thukral
spellingShingle Vinod Kumar
Anket Sharma
Renu Bhardwaj
Ashwani Kumar Thukral
Analysis of organic acids of tricarboxylic acid cycle in plants using GC-MS, and system modeling
Journal of Analytical Science and Technology
Krebs cycle
Citric acid
Succinic acid
Fumaric acid
Malic acid
Simulation
author_facet Vinod Kumar
Anket Sharma
Renu Bhardwaj
Ashwani Kumar Thukral
author_sort Vinod Kumar
title Analysis of organic acids of tricarboxylic acid cycle in plants using GC-MS, and system modeling
title_short Analysis of organic acids of tricarboxylic acid cycle in plants using GC-MS, and system modeling
title_full Analysis of organic acids of tricarboxylic acid cycle in plants using GC-MS, and system modeling
title_fullStr Analysis of organic acids of tricarboxylic acid cycle in plants using GC-MS, and system modeling
title_full_unstemmed Analysis of organic acids of tricarboxylic acid cycle in plants using GC-MS, and system modeling
title_sort analysis of organic acids of tricarboxylic acid cycle in plants using gc-ms, and system modeling
publisher SpringerOpen
series Journal of Analytical Science and Technology
issn 2093-3371
publishDate 2017-10-01
description Abstract Background Leaves of 15 plant species were collected from the catchment areas of the river Beas, Punjab, India, and analyzed for organic acids of tricarboxylic acid cycle, viz., citric acid (CA), succinic acid (SA), fumaric acid (FmA), and malic acid (MA). Methods Gas chromatography-mass spectrometry (GC-MS) was used to determine the content of organic acids in the leaves of plant species. Two microliters of plant sample was injected into the GC-MS, and the concentration of organic acids was quantified using standard curve. Results Average concentrations of these acids in the leaves of plants studied were 4.79, 0.98, 0.54, and 8.36 mg/g dw, respectively. The maximum contents of these acids were found in the leaves of Chenopodium album (CA = 6.42 mg/g dw), Argemone mexicana (SA = 1.27 and FmA = 0.73 mg/g dw), and Rumex dentatus (MA = 18.0 mg/g dw). Factor analysis revealed mainly two underlying factors for organic acids: Factor-1 having maximum loadings on SA and FmA and Factor-2 had maximum loadings on CA and MA. Multiple linear regression analysis of MA on other acids showed that CA and SA have positive regressions, whereas FmA has a negative regression on MA. In artificial neural network analysis, correlation between the target and output values of MA was found to be highly significant. System transfer coefficients were calculated from simulation graphs fitted to the mean values of different organic acids by using difference equations. Conclusions From the present study, it was found that citric acid has a maximum direct effect on the malic acid as compared to succinic and fumaric acids as revealed by path analysis. System modeling revealed that the rate of utilization of malic acid is about 9%. The present study describes a new system simulation technique in which a pathway comprising of linear transformation of biochemical constituents may be characterized in terms of its rate transfer coefficients.
topic Krebs cycle
Citric acid
Succinic acid
Fumaric acid
Malic acid
Simulation
url http://link.springer.com/article/10.1186/s40543-017-0129-6
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