Nanoliquid chromatography-mass spectrometry of oligosaccharides employing graphitized carbon chromatography on microchip with a high-accuracy mass analyzer

ABSTRACTLiquid chromatography-mass spectrometry (LC-MS) based lipidomics generate a large dataset, which requires high-performance data pre-processing tools for their interpretation such as XCMS, mzMine and Progenesis. These pre-processing tools rely heavily on accurate peak detection, which depends on setting the peak detection mass tolerance (PDMT) properly. The PDMT is usually set with a fixed value in either ppm or Da units. However, this fixed value may result in duplicates or missed peak detection. Therefore, we developed the dynamic binning method for accurate peak detection, which takes into account the peak broadening described by well-known physics laws of ion separation and set dynamically the value of PDMT as a function of m/z. Namely, in our method, the PDMT is proportional to for FTICR, to for Orbitrap, to m/z for Q-TOF and is a constant for Quadrupole mass analyzer, respectively. The dynamic binning method was implemented in XCMS [1,2] and the adopted source code is available in the Appendix. Our further goal was to compare the performance of different lipidomics pre-processing tools to find differential compounds. We have generated set samples with 43 lipids internal standards differentially spiked to aliquots of one human plasma lipid sample using Orbitrap LC-MS/MS. The performance of the various pipelines using aligned parameter sets was quantified by a quality score system which reflects the ability of a pre-processing pipeline to detect differential peaks spiked at various concentration levels. The quality score indicates that the dynamic binning method improves the performance of XCMS (maximum p-value 9.8·10−3 of two-sample Wilcoxon test). The modified XCMS software was further compared with mzMine and Progenesis. The results showed that modified XCMS and Progenesis had a similarly good performance in the aspect of finding differential compounds. In addition, Progenesis shows lower variability as indicated by lower CVs, followed by XCMS and mzMine. The lower variability of Progenesis improve the quantification, however, provide an incorrect quantification abundance order of spiked-in internal standards.

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Multiresidue Analysis of Pesticides in Vegetables and Fruits by Gas Chromatography/Mass Spectrometry after Gel Permeation Chromatography and Graphitized Carbon Column Cleanup

Journal of AOAC International ◽

10.1093/jaoac/87.4.1003 ◽

2004 ◽

Vol 87 (4) ◽

pp. 1003-1015 ◽

Cited By ~ 28

Author(s):

Eiji Ueno ◽

Harumi Oshima ◽

Isao Saito ◽

Hiroshi Matsumoto ◽

Yoshihiro Yoshimura ◽

...

Keyword(s):

Mass Spectrometry ◽

Gas Chromatography ◽

Sequential Analysis ◽

Gel Permeation Chromatography ◽

Gas Chromatography Mass Spectrometry ◽

Graphitized Carbon ◽

Chromatography Mass Spectrometry ◽

Relative Standard ◽

Fruit Samples ◽

Gel Permeation

Abstract A multiresidue method for pesticides that enables quantitative, sequential analysis of a large number of vegetable and fruit samples by gas chromatography/mass spectrometry has been developed. First, 89 important target compounds were selected for monitoring, and then the appropriate internal standards for these pesticides, 14 stable isotopically labeled pesticides (surrogates), were used. The sample was extracted with acetonitrile, and the extract was cleaned up by a salting-out step followed by redissolution in ethyl acetate. Coextractives were removed automatically by gel permeation chromatography with a graphitized carbon column, and then by use of a tandem silica-gel/PSA cartridge column. Recoveries of 82 of the 89 pesticides from fortified spinach, tomato, apple, and strawberry were within a range from 70 to 120%, and the relative standard deviation values of 80 of the 89 pesticides were <5%. The method was applied to 188 commercial vegetable and fruit samples to demonstrate its use in routine analysis.

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