Journal
JOURNAL OF CHROMATOGRAPHY A
Volume 1412, Issue -, Pages 43-51Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.chroma.2015.07.108
Keywords
Retention projection; Retention prediction; Liquid chromatography-mass spectrometry; Retention library; Retention database; Multi-laboratory study
Funding
- National Science Foundation Plant Genome Research Program [IOS-1238812, IOS-1400818]
- Division Of Integrative Organismal Systems
- Direct For Biological Sciences [1400818, 1238812] Funding Source: National Science Foundation
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Identification of small molecules by liquid chromatography-mass spectrometry (LC-MS) can be greatly improved if the chromatographic retention information is used along with mass spectral information to narrow down the lists of candidates. Linear retention indexing remains the standard for sharing retention data across labs, but it is unreliable because it cannot properly account for differences in the experimental conditions used by various labs, even when the differences are relatively small and unintentional. On the other hand, an approach called retention projection properly accounts for many intentional differences in experimental conditions, and when combined with a back-calculation methodology described recently, it also accounts for unintentional differences. In this study, the accuracy of this methodology is compared with linear retention indexing across eight different labs. When each lab ran a test mixture under a range of multi-segment gradients and flow rates they selected independently, retention projections averaged 22-fold more accurate for uncharged compounds because they properly accounted for these intentional differences, which were more pronounced in steep gradients. When each lab ran the test mixture under nominally the same conditions, which is the ideal situation to reproduce linear retention indices, retention projections still averaged 2-fold more accurate because they properly accounted for many unintentional differences between the LC systems. To the best of our knowledge, this is the most successful study to date aiming to calculate (or even just to reproduce) LC gradient retention across labs, and it is the only study in which retention was reliably calculated under various multi-segment gradients and flow rates chosen independently by labs. (C) 2015 Elsevier B.V. All rights reserved.
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