High-Throughput Profiling of Metabolic Phenotypes Using High-Resolution GC-MS.

Autor:	Wase N; Department of Biochemistry and Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, NE, USA.; Biomolecular Analysis Facility, University of Virginia School of Medicine, Charlottesville, VA, USA., Abshire N; Department of Biochemistry and Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, NE, USA., Obata T; Department of Biochemistry and Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, NE, USA. tobata2@unl.edu.
Jazyk:	angličtina
Zdroj:	Methods in molecular biology (Clifton, N.J.) [Methods Mol Biol] 2022; Vol. 2539, pp. 235-260.
DOI:	10.1007/978-1-0716-2537-8_19
Abstrakt:	Metabolite profiling provides insights into the metabolic signatures, which themselves are considered as phonotypes closely related to the agronomic and phenotypic traits such as yield, nutritional values, stress resistance, and nutrient use efficiency. GC-MS is a sensitive and high-throughput analytical platform and has been proved to be a vital tool for the analysis of primary metabolism to provide an overview of cellular and organismal metabolic status. The potential of GC-MS metabolite profiling as a tool for detecting metabolic changes in plants grown in a high-throughput plant phenotyping platform was explored. In this chapter, we describe an integrated workflow of semi-targeted GC-high-resolution (HR)-time-of-flight (TOF)-MS metabolomics with both the analytical and computational steps, focusing mainly on the sample preparation, GC-HR-TOF-MS analysis part, and data analysis for plant phenotyping efforts. (© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)
Databáze:	MEDLINE
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