An extraction method for intracellular metabolite profiling should ideally be able to recover the broadest possible range of metabolites present in a sample. However, the development of such methods is hampered by the diversity of the physico-chemical properties of metabolites as well as by the specific characteristics of samples and cells. In this study, we report the optimization of an UPLC-MS method for the metabolite analysis of platelet samples. The optimal analytical protocol was determined by testing seven different extraction methods as well as by employing two different LC-MS methods, in which the metabolites were separated by using hydrophilic interaction liquid chromatography (HILIC) and reversed phase liquid chromatography (RPLC). The optimal conditions were selected using the coverage of the platelets' metabolome, the response of the identified metabolites, the reproducibility of the analytical method, and the time of the analysis as main evaluation criteria. Our results show that methanol-water (7:3) extraction coupled with HILIC-MS method provides the best compromise, allowing identification of 107 metabolites in a platelet cell extract sample, 91% of them with a RSD% lower than 20. A higher number of metabolites could be detected when analyzing the platelet samples with two different LC-MS methods or when using complementary extraction methods in parallel. © 2012 Elsevier B.V

Paglia, G., Magnusdottir, M., Thorlacius, S., Sigurjonsson, O., Gudmundsson, S., Palsson, B., et al. (2012). Intracellular metabolite profiling of platelets: Evaluation of extraction processes and chromatographic strategies. JOURNAL OF CHROMATOGRAPHY. B, 898, 111-120 [10.1016/j.jchromb.2012.04.026].

Intracellular metabolite profiling of platelets: Evaluation of extraction processes and chromatographic strategies

Paglia G.
Primo
;
2012

Abstract

An extraction method for intracellular metabolite profiling should ideally be able to recover the broadest possible range of metabolites present in a sample. However, the development of such methods is hampered by the diversity of the physico-chemical properties of metabolites as well as by the specific characteristics of samples and cells. In this study, we report the optimization of an UPLC-MS method for the metabolite analysis of platelet samples. The optimal analytical protocol was determined by testing seven different extraction methods as well as by employing two different LC-MS methods, in which the metabolites were separated by using hydrophilic interaction liquid chromatography (HILIC) and reversed phase liquid chromatography (RPLC). The optimal conditions were selected using the coverage of the platelets' metabolome, the response of the identified metabolites, the reproducibility of the analytical method, and the time of the analysis as main evaluation criteria. Our results show that methanol-water (7:3) extraction coupled with HILIC-MS method provides the best compromise, allowing identification of 107 metabolites in a platelet cell extract sample, 91% of them with a RSD% lower than 20. A higher number of metabolites could be detected when analyzing the platelet samples with two different LC-MS methods or when using complementary extraction methods in parallel. © 2012 Elsevier B.V
Articolo in rivista - Articolo scientifico
Extraction; HILIC; Metabolomics; Platelets; Reversed phase liquid chromatography; UPLC-MS
English
2012
898
111
120
none
Paglia, G., Magnusdottir, M., Thorlacius, S., Sigurjonsson, O., Gudmundsson, S., Palsson, B., et al. (2012). Intracellular metabolite profiling of platelets: Evaluation of extraction processes and chromatographic strategies. JOURNAL OF CHROMATOGRAPHY. B, 898, 111-120 [10.1016/j.jchromb.2012.04.026].
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/244097
Citazioni
  • Scopus 45
  • ???jsp.display-item.citation.isi??? 43
Social impact