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Comprehensive analysis of lipids in biological systems by liquid chromatography-mass spectrometry.

ABSTRACT: Liquid chromatography-mass spectrometry (LC-MS)-based lipidomics has been a subject of dramatic developments over the past decade. This review focuses on state of the art in LC-MS-based lipidomics, covering all the steps of global lipidomic profiling. On the basis of review of 185 original papers and application notes, we can conclude that typical LC-MS-based lipidomics methods involve: (1) extraction using chloroform/MeOH or MTBE/MeOH protocols, both with addition of internal standards covering each lipid class; (2) separation of lipids using short microbore columns with sub-2-?m or 2.6-2.8-?m (fused-core) particle size with C18 or C8 sorbent with analysis time <30 min; (3) electrospray ionization in positive- and negative-ion modes with full spectra acquisition using high-resolution MS with capability to MS/MS. Phospholipids (phosphatidylcholines, phosphatidylethanolamines, phosphatidylinositols, phosphatidylserines, phosphatidylglycerols) followed by sphingomyelins, di- and tri-acylglycerols, and ceramides were the most frequently targeted lipid species.

SUBMITTER: Cajka T

PROVIDER: S-EPMC4187118 | biostudies-literature | 2014 Oct

REPOSITORIES: biostudies-literature

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Comprehensive analysis of lipids in biological systems by liquid chromatography-mass spectrometry.

Cajka Tomas T Fiehn Oliver O

Trends in analytical chemistry : TRAC 20141001

Liquid chromatography-mass spectrometry (LC-MS)-based lipidomics has been a subject of dramatic developments over the past decade. This review focuses on state of the art in LC-MS-based lipidomics, covering all the steps of global lipidomic profiling. On the basis of review of 185 original papers and application notes, we can conclude that typical LC-MS-based lipidomics methods involve: (1) extraction using chloroform/MeOH or MTBE/MeOH protocols, both with addition of internal standards covering ...[more]

PMID: 25309011

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Project description:BackgroundParkinson's disease (PD) is a prevalent neurological disease in the elderly with increasing morbidity and mortality. Despite enormous efforts, rapid and accurate diagnosis of PD is still compromised. Metabolomics defines the final readout of genome-environment interactions through the analysis of the entire metabolic profile in biological matrices. Recently, unbiased metabolic profiling of human sample has been initiated to identify novel PD metabolic biomarkers and dysfunctional metabolic pathways, however, it remains a challenge to define reliable biomarker(s) for clinical use.MethodsWe presented a comprehensive metabolic evaluation for identifying crucial metabolic disturbances in PD using liquid chromatography-high resolution mass spectrometry-based metabolomics approach. Plasma samples from 3 independent cohorts (n = 460, 223 PD, 169 healthy controls (HCs) and 68 PD-unrelated neurological disease controls) were collected for the characterization of metabolic changes resulted from PD, antiparkinsonian treatment and potential interferences of other diseases. Unbiased multivariate and univariate analyses were performed to determine the most promising metabolic signatures from all metabolomic datasets. Multiple linear regressions were applied to investigate the associations of metabolites with age, duration time and stage of PD. The combinational biomarker model established by binary logistic regression analysis was validated by 3 cohorts.ResultsA list of metabolites including amino acids, acylcarnitines, organic acids, steroids, amides, and lipids from human plasma of 3 cohorts were identified. Compared with HC, we observed significant reductions of fatty acids (FFAs) and caffeine metabolites, elevations of bile acids and microbiota-derived deleterious metabolites, and alterations in steroid hormones in drug-naïve PD. Additionally, we found that L-dopa treatment could affect plasma metabolome involved in phenylalanine and tyrosine metabolism and alleviate the elevations of bile acids in PD. Finally, a metabolite panel of 4 biomarker candidates, including FFA 10:0, FFA 12:0, indolelactic acid and phenylacetyl-glutamine was identified based on comprehensive discovery and validation workflow. This panel showed favorable discriminating power for PD.ConclusionsThis study may help improve our understanding of PD etiopathogenesis and facilitate target screening for therapeutic intervention. The metabolite panel identified in this study may provide novel approach for the clinical diagnosis of PD in the future.

Project description:Improvements in sample preparation, separation, and mass spectrometry continue to expand the coverage in LC-MS based lipidomics. While longer columns packed with smaller particles in theory give higher separation performance compared to shorter columns, the implementation of this technology above commercial limits has been sparse due to difficulties in packing long columns and successfully operating instruments at ultrahigh pressures. In this work, a liquid chromatograph that operates up to 35 kpsi was investigated for the separation and identification of lipid species from human plasma. Capillary columns between 15-50 cm long were packed with 1.7 µm BEH C18 particles and evaluated for their ability to separate lipid isomers and complex lipid extracts from human plasma. Putative lipid class identifications were assigned using accurate mass and relative retention time data of the eluting peaks. Our findings indicate that longer columns packed and operated at 35 kpsi outperform shorter columns packed and run at lower pressures in terms of peak capacity and numbers of features identified. Packing columns with relatively high concentration slurries (200 mg/mL) while sonicating the column resulted in 6-34% increase in peak capacity for 50 cm columns compared to lower slurry concentrations and no sonication. For a given analysis time, 50 cm long columns operated at 35 kpsi provided a 20-95% increase in chromatographic peak capacity compared with 15 cm columns operated at 15 kpsi. Analysis times up to 4 h were evaluated, generating peak capacities up to 410 ± 5 (n = 3, measured at 4σ) and identifying 480 ± 85 lipids (n = 2). Importantly, the results also show a correlation between the peak capacity and the number of lipids identified from a human plasma extract. This correlation indicates that ionization suppression is a limiting factor in obtaining sufficient signal for identification by mass spectrometry. The result also shows that the higher resolution obtained by shallow gradients overcomes possible signal reduction due to broader, more dilute peaks in long gradients for improving detection of lipids in LC-MS. Lastly, longer columns operated at shallow gradients allowed for the best separation of both regional and geometrical isomers. These results demonstrate a system that enables the advantages of using longer columns packed and run at ultrahigh pressure for improving lipid separations and lipidome coverage.

Dataset Information

Comprehensive analysis of lipids in biological systems by liquid chromatography-mass spectrometry.

Publications

Comprehensive analysis of lipids in biological systems by liquid chromatography-mass spectrometry.

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