High-Throughput Metabolomics: Isocratic and Gradient Mass Spectrometry-Based Methods.


Journal

Methods in molecular biology (Clifton, N.J.)
ISSN: 1940-6029
Titre abrégé: Methods Mol Biol
Pays: United States
ID NLM: 9214969

Informations de publication

Date de publication:
2019
Historique:
entrez: 24 5 2019
pubmed: 24 5 2019
medline: 27 11 2019
Statut: ppublish

Résumé

Metabolomics has emerged in the past decade as a highly attractive and impactful technique for phenotype-level profiling in diverse biological applications. Most recently, the dual developments of high-throughput analytical techniques along with dramatically increased sensitivity of high-resolution mass spectrometers have enabled the routine analysis of hundreds of unique samples per day. We have previously reported a robust 3 min isocratic metabolomics platform for the quantification of amino acids and the key pathways of central carbon and nitrogen metabolism. Building on this work, we describe here a 5 min reverse phase gradient followed by global, untargeted profiling of the hydrophilic metabolome. In addition to observing those metabolites measured in the 3 min run, the use of the longer gradient run here also allows for coverage of less polar compounds such as fatty acids and acylcarnitines, both key players in mitochondrial and lipid metabolism, without a significant sacrifice in throughput.

Identifiants

pubmed: 31119654
doi: 10.1007/978-1-4939-9236-2_2
doi:

Substances chimiques

Amino Acids 0
Fatty Acids 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

13-26

Auteurs

Travis Nemkov (T)

Department of Biochemistry and Molecular Genetics, University of Colorado Denver, Aurora, CO, USA.

Julie A Reisz (JA)

Department of Biochemistry and Molecular Genetics, University of Colorado Denver, Aurora, CO, USA.

Sarah Gehrke (S)

Department of Biochemistry and Molecular Genetics, University of Colorado Denver, Aurora, CO, USA.

Kirk C Hansen (KC)

Department of Biochemistry and Molecular Genetics, University of Colorado Denver, Aurora, CO, USA.

Angelo D'Alessandro (A)

Department of Biochemistry and Molecular Genetics, University of Colorado Denver, Aurora, CO, USA. angelo.dalessandro@ucdenver.edu.

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Classifications MeSH