Understanding Plant Nitrogen Metabolism through Metabolomics and Computational Approaches
A comprehensive understanding of plant metabolism could provide a direct mechanism for improving nitrogen use efficiency (NUE) in crops. One of the major barriers to achieving this outcome is our poor understanding of the complex metabolic networks, physiological factors, and signaling mechanisms th...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2016-10-01
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| Series: | Plants |
| Subjects: | |
| Online Access: | http://www.mdpi.com/2223-7747/5/4/39 |
| _version_ | 1798026955952488448 |
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| author | Perrin H. Beatty Matthias S. Klein Jeffrey J. Fischer Ian A. Lewis Douglas G. Muench Allen G. Good |
| author_facet | Perrin H. Beatty Matthias S. Klein Jeffrey J. Fischer Ian A. Lewis Douglas G. Muench Allen G. Good |
| author_sort | Perrin H. Beatty |
| collection | DOAJ |
| description | A comprehensive understanding of plant metabolism could provide a direct mechanism for improving nitrogen use efficiency (NUE) in crops. One of the major barriers to achieving this outcome is our poor understanding of the complex metabolic networks, physiological factors, and signaling mechanisms that affect NUE in agricultural settings. However, an exciting collection of computational and experimental approaches has begun to elucidate whole-plant nitrogen usage and provides an avenue for connecting nitrogen-related phenotypes to genes. Herein, we describe how metabolomics, computational models of metabolism, and flux balance analysis have been harnessed to advance our understanding of plant nitrogen metabolism. We introduce a model describing the complex flow of nitrogen through crops in a real-world agricultural setting and describe how experimental metabolomics data, such as isotope labeling rates and analyses of nutrient uptake, can be used to refine these models. In summary, the metabolomics/computational approach offers an exciting mechanism for understanding NUE that may ultimately lead to more effective crop management and engineered plants with higher yields. |
| first_indexed | 2024-04-11T18:43:42Z |
| format | Article |
| id | doaj.art-00ab598f8d81494982bf986065e1fef7 |
| institution | Directory Open Access Journal |
| issn | 2223-7747 |
| language | English |
| last_indexed | 2024-04-11T18:43:42Z |
| publishDate | 2016-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Plants |
| spelling | doaj.art-00ab598f8d81494982bf986065e1fef72022-12-22T04:08:53ZengMDPI AGPlants2223-77472016-10-01543910.3390/plants5040039plants5040039Understanding Plant Nitrogen Metabolism through Metabolomics and Computational ApproachesPerrin H. Beatty0Matthias S. Klein1Jeffrey J. Fischer2Ian A. Lewis3Douglas G. Muench4Allen G. Good5Department of Biological Sciences, University of Alberta, 85 Avenue NW, Edmonton, AB T6G 2E9, CanadaDepartment of Biological Sciences, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, CanadaDepartment of Biological Sciences, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, CanadaDepartment of Biological Sciences, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, CanadaDepartment of Biological Sciences, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, CanadaDepartment of Biological Sciences, University of Alberta, 85 Avenue NW, Edmonton, AB T6G 2E9, CanadaA comprehensive understanding of plant metabolism could provide a direct mechanism for improving nitrogen use efficiency (NUE) in crops. One of the major barriers to achieving this outcome is our poor understanding of the complex metabolic networks, physiological factors, and signaling mechanisms that affect NUE in agricultural settings. However, an exciting collection of computational and experimental approaches has begun to elucidate whole-plant nitrogen usage and provides an avenue for connecting nitrogen-related phenotypes to genes. Herein, we describe how metabolomics, computational models of metabolism, and flux balance analysis have been harnessed to advance our understanding of plant nitrogen metabolism. We introduce a model describing the complex flow of nitrogen through crops in a real-world agricultural setting and describe how experimental metabolomics data, such as isotope labeling rates and analyses of nutrient uptake, can be used to refine these models. In summary, the metabolomics/computational approach offers an exciting mechanism for understanding NUE that may ultimately lead to more effective crop management and engineered plants with higher yields.http://www.mdpi.com/2223-7747/5/4/39metabolomicsnitrogennitrogen use efficiency (NUE)transgenic cropsnitrogen uptake efficiency (NUpE)nitrogen utilization efficiency (NUtE)flux balance analysis (FBA)N boundarymass spectrometry (MS)nuclear magnetic resonance (NMR) |
| spellingShingle | Perrin H. Beatty Matthias S. Klein Jeffrey J. Fischer Ian A. Lewis Douglas G. Muench Allen G. Good Understanding Plant Nitrogen Metabolism through Metabolomics and Computational Approaches Plants metabolomics nitrogen nitrogen use efficiency (NUE) transgenic crops nitrogen uptake efficiency (NUpE) nitrogen utilization efficiency (NUtE) flux balance analysis (FBA) N boundary mass spectrometry (MS) nuclear magnetic resonance (NMR) |
| title | Understanding Plant Nitrogen Metabolism through Metabolomics and Computational Approaches |
| title_full | Understanding Plant Nitrogen Metabolism through Metabolomics and Computational Approaches |
| title_fullStr | Understanding Plant Nitrogen Metabolism through Metabolomics and Computational Approaches |
| title_full_unstemmed | Understanding Plant Nitrogen Metabolism through Metabolomics and Computational Approaches |
| title_short | Understanding Plant Nitrogen Metabolism through Metabolomics and Computational Approaches |
| title_sort | understanding plant nitrogen metabolism through metabolomics and computational approaches |
| topic | metabolomics nitrogen nitrogen use efficiency (NUE) transgenic crops nitrogen uptake efficiency (NUpE) nitrogen utilization efficiency (NUtE) flux balance analysis (FBA) N boundary mass spectrometry (MS) nuclear magnetic resonance (NMR) |
| url | http://www.mdpi.com/2223-7747/5/4/39 |
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