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Analyses of Arabidopsis ecotypes reveal metabolic diversity to convert D-amino acids

Overview of attention for article published in SpringerPlus, October 2013
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Title
Analyses of Arabidopsis ecotypes reveal metabolic diversity to convert D-amino acids
Published in
SpringerPlus, October 2013
DOI 10.1186/2193-1801-2-559
Pubmed ID
Authors

Dirk Gördes, Grit Koch, Kerstin Thurow, Üner Kolukisaoglu

Abstract

For a long time D-enantiomers of proteinogenic L-amino acids were assumed to be physiologically irrelevant for plants. But there is growing evidence that D-amino acids (D-AAs) also fulfil important physiological functions in these organisms. However, the knowledge about the metabolic fate of D-AAs in plants is still scarce and more information about it is needed. To close this gap we established an optimized protocol for the processing and analysis of D- and L-AAs from large numbers of Arabidopsis lines. This included the application of 18 different D-AAs to seedlings, the extraction of free amino acids from the samples and the determination of 16 L-AAs and their corresponding D-enantiomers. To validate our approach we searched for genetic accessions with aberrant amino acid metabolism. Therefore we applied D-AAs on 17 ecotypes of Arabidopsis thaliana and analysed their free amino acid contents. These analyses confirmed the suitability of the system for the analysis of large sets of plant samples with enhanced velocity and improved accuracy. Furthermore, the resulting data led to the definition of standard amino acid profiles in response to D-AAs of Arabidopsis seedlings. Within these analyses the ecotype Landsberg erecta was found with aberrant metabolic patterns like drastically reduced capabilities to convert different D-AAs to D-alanine and D-glutamate. The presented experimental setup and results of this study offer starting points to dissect the metabolic pathway of D-AAs in plants.

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Mendeley readers

The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 22%
Student > Bachelor 4 17%
Researcher 3 13%
Student > Master 3 13%
Professor > Associate Professor 2 9%
Other 3 13%
Unknown 3 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 10 43%
Biochemistry, Genetics and Molecular Biology 5 22%
Engineering 3 13%
Computer Science 1 4%
Linguistics 1 4%
Other 0 0%
Unknown 3 13%