Solid‐phase microextraction combined with comprehensive two‐dimensional gas chromatography for fatty acid profiling of cell wall phospholipids

Bogusz, Stanislau; Hantao, Leandro Wang; Braga, Soraia Cristina Gonzaga Neves; França, Valtenice de Cássia Rodrigues de Matos; Costa, Marcelo Fernandes; Hamer, Russell D.; Ventura, Dora Fix; Augusto, Fábio

doi:10.1002/jssc.201200256

Cited by 25 publications

(5 citation statements)

References 24 publications

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“…This method demonstrated about fourfold increased peak capacities . Bogusz et al described SPME combined with comprehensive 2D GC with flame ionization detection for fatty acid profiling of cell wall phospholipids . Profiling of fatty acids as biomarker for certain diseases have been reported.…”

Section: Introductionmentioning

confidence: 99%

Profiling of esterified fatty acids as biomarkers in the blood of dengue fever patients using a microliter‐scale extraction followed by gas chromatography and mass spectrometry

Khedr

Hegazy

Kamal

et al. 2014

J of Separation Science

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An improved gas chromatography with mass spectrometry procedure was developed to highlight the esterified fatty acids in 100 μL blood of dengue fever patients in the early febrile phase versus healthy volunteers. 24 adult patients and 24 healthy volunteers were included in this study. The recoveries of targeted esterified fatty acids content were in the range of 92.10-101.00% using methanol/dichloromethane (2:1, v/v) as the extraction solvent. An efficient chromatographic separation of targeted 17 esterified fatty acid methyl esters was obtained. The limits of detection and quantification were within the range of 16-131 and 53-430 ng/mL, respectively. The relative standard deviation of intraday and interday precision values ranged from 0.4 to 5.0%. The statistical data treatment showed a significant decrease of the content of four saturated fatty acids, C14:0, C15:0, C16:0, and C18:0 (P value < 0.05), and also showed a decrease of the content of eight unsaturated fatty acids, C16:1, C18:3n6, C18:2n6, C18:1n9, C20:3n3, C20:4n6, C20:2, and C22:6n3 (P value < 0.05) in dengue fever patients. Moreover, the amount of three omega-6 fatty acids including C18:3n6, C18:2n6, and C20:4n6 was dramatically decreased in the blood of dengue fever patients to a limit of 50 ± 10%.

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Section: Introductionmentioning

confidence: 99%

Profiling of esterified fatty acids as biomarkers in the blood of dengue fever patients using a microliter‐scale extraction followed by gas chromatography and mass spectrometry

Khedr

Hegazy

Kamal

et al. 2014

J of Separation Science

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show abstract

“…Smaller fatty acids in particular are suited for analysis via GC, and the FiehnLib library for example contains RI for various lipids. GC still sees use in lipidomics, and research improving on used methods is ongoing. − For separation based on liquid chromatography (LC), retention time prediction is less trivial due to the more complex interactions with the stationary phase. As a consequence, retention time prediction in LC is still an active research area.…”

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confidence: 99%

Retention Time Prediction Improves Identification in Nontargeted Lipidomics Approaches

et al. 2015

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Identification of lipids in nontargeted lipidomics based on liquid-chromatography coupled to mass spectrometry (LC-MS) is still a major issue. While both accurate mass and fragment spectra contain valuable information, retention time (tR) information can be used to augment this data. We present a retention time model based on machine learning approaches which enables an improved assignment of lipid structures and automated annotation of lipidomics data. In contrast to common approaches we used a complex mixture of 201 lipids originating from fat tissue instead of a standard mixture to train a support vector regression (SVR) model including molecular structural features. The cross-validated model achieves a correlation coefficient between predicted and experimental test sample retention times of r = 0.989. Combining our retention time model with identification via accurate mass search (AMS) of lipids against the comprehensive LIPID MAPS database, retention time filtering can significantly reduce the rate of false positives in complex data sets like adipose tissue extracts. In our case, filtering with retention time information removed more than half of the potential identifications, while retaining 95% of the correct identifications. Combination of high-precision retention time prediction and accurate mass can thus significantly narrow down the number of hypotheses to be assessed for lipid identification in complex lipid pattern like tissue profiles.

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“…11.1). Bogusz et al (2012) investigated the FA profile of the glycerophospholipid fraction from a buccal swab, after a basecatalyzed derivatization and a solid-phase microextraction (SPME) preconcentration.…”

Section: Fatty Acid Analysismentioning

confidence: 99%

Theory and Practice of UHPLC and UHPLC–MS

Guillarme

Veuthey

2017

Handbook of Advanced Chromatography /Mass Spectrometry Techniques

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Solid‐phase microextraction combined with comprehensive two‐dimensional gas chromatography for fatty acid profiling of cell wall phospholipids

Cited by 25 publications

References 24 publications

Profiling of esterified fatty acids as biomarkers in the blood of dengue fever patients using a microliter‐scale extraction followed by gas chromatography and mass spectrometry

Profiling of esterified fatty acids as biomarkers in the blood of dengue fever patients using a microliter‐scale extraction followed by gas chromatography and mass spectrometry

Retention Time Prediction Improves Identification in Nontargeted Lipidomics Approaches

Theory and Practice of UHPLC and UHPLC–MS

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