2016
DOI: 10.1007/s11306-016-1132-4
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Comprehensive optimization of LC–MS metabolomics methods using design of experiments (COLMeD)

Abstract: Introduction Both reverse-phase and HILIC chemistries are deployed for liquid-chromatography mass spectrometry (LC-MS) metabolomics analyses, however HILIC methods lag behind reverse-phase methods in reproducibility and versatility. Comprehensive metabolomics analysis is additionally complicated by the physiochemical diversity of metabolites and array of tunable analytical parameters. Objective Our aim was to rationally and efficiently design complementary HILIC-based polar metabolomics methods on multiple i… Show more

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Cited by 32 publications
(24 citation statements)
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“…Polar metabolites were then analyzed through UPLC-MS utilizing a method optimized through the COLMeD approach as described in (Rhoades and Weljie, 2016). The following procedure should be used as guidelines in acquiring data by individuals trained in using a mass spectrometer.…”
Section: Methodsmentioning
confidence: 99%
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“…Polar metabolites were then analyzed through UPLC-MS utilizing a method optimized through the COLMeD approach as described in (Rhoades and Weljie, 2016). The following procedure should be used as guidelines in acquiring data by individuals trained in using a mass spectrometer.…”
Section: Methodsmentioning
confidence: 99%
“…Although both NMR and MS are essential tools in metabolomics, mass spectrometry can analyze samples with greater sensitivity (Liu and Locasale, 2017). Within mass spectrometry, various approaches are available, however a rapid approach to profile the global metabolome is needed (Lv et al ., 2011; Rhoades and Weljie, 2016). Advancements in triple quadrupole mass spectrometers have made them well suited for ion-switching methods (scanning in both positive and negative ion modes within a single analysis) in addition to enabling reproducible and sensitive targeted profiling of numerous metabolites (Lv et al ., 2011; Gika et al ., 2012; Yuan et al ., 2012; Rhoades and Weljie, 2016).…”
Section: Introductionmentioning
confidence: 99%
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