Analysis of the compartmentalized metabolome – a validation of the non-aqueous fractionation technique
| العنوان: | Analysis of the compartmentalized metabolome – a validation of the non-aqueous fractionation technique |
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| المؤلفون: | Sebastian Klie, Dirk Steinhauser, Leonard Krall, Patrick Giavalisco, Lothar Willmitzer, Stephan Krueger, Ulf-Ingo Flügge |
| المصدر: | Frontiers in Plant Science, Vol 2 (2011) Frontiers in plant science |
| بيانات النشر: | Frontiers Media SA, 2011. |
| سنة النشر: | 2011 |
| مصطلحات موضوعية: | least-squares algorithms, analysis workflow, Metabolite, subcellular metabolomics, Context (language use), Plant Science, Fractionation, computational simulations, lcsh:Plant culture, Biology, computer.software_genre, chemistry.chemical_compound, Metabolome, lcsh:SB1-1110, Computational analysis, visualization, Original Research, Experimental data, Robustness (evolution), BestFit tool, chemistry, Data mining, Biological system, computer, Derived Data, least squares algorithms |
| الوصف: | With the development of high throughput metabolic technologies, a plethora of primary and secondary compounds have been detected in the plant cell. However, there are still major gaps in our understanding of the plant metabolome. This is especially true with regards to the compartmental localization of these identified metabolites.Non-aqueous fractionation (NAF) is a powerful technique for the determination of subcellular metabolite distributions in eukaryotic cells, and it has become the method of choice to analyze the distribution of a large number of metabolites concurrently. However, the NAF technique produces a continuous gradient of metabolite distributions, not discrete assignments. Resolution of these distributions requires computational analyses based on marker metabolites to resolve compartmental localizations.In this article we focus on expanding the computational analysis of data derived from non-aqueous fractionation. Along with an experimental workflow, we describe the critical steps in NAF experiments and how computational approaches can aid in assessing the quality and robustness of the derived data. For this, we have developed and provide a new version (v1.2) of the BestFit command line tool for calculation and evaluation of subcellular metabolite distributions. Furthermore, using both simulated and experimental data we show the influence on estimated subcellular distributions by modulating important parameters, such as the number of fractions taken or which marker metabolite is selected. Finally, we discuss caveats and benefits of non-aqueous fractionation analysis in the context of the compartmentalized metabolome. |
| تدمد: | 1664-462X |
| الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::38ee4fb0e0c767e58368b02f8ed09086Test https://doi.org/10.3389/fpls.2011.00055Test |
| حقوق: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....38ee4fb0e0c767e58368b02f8ed09086 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 1664462X |
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