Ultra performance liquid chromatography – mass spectrometry studies of formalin‐induced alterations of human brain lipidome

The development of ‘omics’ sciences offers new opportunities for the study of neurodegenerative diseases but increases at the same time the sample demand on brain banks that collect and store valuable human post‐mortem tissue. Our study aims to evaluate in lipidomics the potential of formalin‐fixed tissue compared with the cryopreservation method, considered as the gold standard for biochemical research. Two complementary liquid chromatography/mass spectrometry analytical platforms were used on the basis of hybrid quadrupole time‐of‐flight and triple quadrupole mass spectrometers. Untargeted fingerprinting, semitargeted profiling of specific lipid classes and targeted monitoring of lipid species were performed in formalin‐fixed and cryopreserved samples to provide detailed information at the molecular level on the formalin‐induced alterations of the brain tissue. In vitro incubations of lipid standards were also performed to further describe the degradation processes induced by formaldehyde. Phospholipid compounds were found to be extensively hydrolysed, whilst the sphingolipid ones were preserved. N‐methylation and N‐formylation of amine‐containing phospholipids have also been evidenced. These findings show that the potential detrimental effect of formalin on the analytes of interest must be taken into account when analysing formalin‐fixed samples. Copyright © 2014 John Wiley & Sons, Ltd.     

Temperature‐programmed capillary high‐performance liquid chromatography with atmospheric pressure chemical ionization mass spectrometry for analysis of fatty acid methyl esters

A new capillary high‐performance liquid chromatography method with atmospheric pressure chemical ionization mass spectrometry was developed for the analysis of fatty acid methyl esters and long‐chain alcohols. The chromatographic separation was achieved using a Zorbax SB‐C18 HPLC column (0.3 × 150 mm, 3.5 μm) with a mobile phase composed of acetonitrile and formic acid and delivered isocratically at a flow rate of 10 μL/min. The column temperature was programmed simply, using a common column oven. Good reproducibility of the temperature profile and retention times were achieved. The temperature programming during the isocratic high‐performance liquid chromatography run had a similar effect as a solvent gradient; it reduced retention times of later eluting analytes and improved their detection limits. Two atmospheric pressure chemical ionization sources of the mass spectrometry detector were compared: an enclosed conventional ion source and an in‐house made ion source with a glass microchip nebulizer. The enclosed source provided better detectability of saturated fatty acid methyl esters and made it possible to determine the double bond positions using acetonitrile‐related adducts, while the open chip‐based source provided better analytical figures of merit for unsaturated fatty acid methyl esters. Temperature‐programmed capillary high‐performance liquid chromatography is a promising method for analyzing neutral lipids in lipidomics and other applications.     

Ultraperformance convergence chromatography‐high resolution tandem mass spectrometry for lipid biomarker profiling and identification

Lipids represent biologically ubiquitous and highly dynamic molecules in terms of abundance and structural diversity. Whereas the potential for lipids to inform on disease/injury is promising, their unique characteristics make detection and identification of lipids from biological samples analytically demanding. We report the use of ultraperformance convergence chromatography (UPC²), a variant of supercritical fluid chromatography, coupled to high‐resolution, data‐independent tandem mass spectrometry for characterization of total lipid extracts from mouse lung tissue. The UPC² platform resulted in lipid class separation and when combined with orthogonal column chemistries yielded chromatographic separation of intra‐class species based on acyl chain hydrophobicity. Moreover, the combined approach of using UPC² with orthogonal column chemistries, accurate mass measurements, time‐aligned low‐ and high‐collision energy total ion chromatograms, and positive and negative ion mode product ion spectra correlation allowed for confident lipid identification. Of great interest was the identification of differentially expressed ceramides that were elevated 24 h post whole thorax lung irradiation. The identification of lipids that were elevated 24 h post‐irradiation signifies a unique opportunity to investigate early mechanisms of action prior to the onset of clinical symptoms in the whole thorax lung irradiation mouse model.     

Targeted Metabolomics for Biomarker Discovery

Metabolomics is a truly interdisciplinary field of science, which combines analytical chemistry, platform technology, mass spectrometry, and NMR spectroscopy with sophisticated data analysis. Applied to biomarker discovery, it includes aspects of pathobiochemistry, systems biology/medicine, and molecular diagnostics and requires bioinformatics and multivariate statistics. While successfully established in the screening of inborn errors in neonates, metabolomics is now widely used in the characterization and diagnostic research of an ever increasing number of diseases. In this Review we highlight important technical prerequisites as well as recent developments in metabolomics and metabolomics data analysis with special emphasis on their utility in biomarker identification and qualification, as well as targeted metabolomics by employing high‐throughput mass spectrometry.     

脂质组学及其分析方法

脂质组学的研究属于生命科学的范畴,与人类的健康密切相关。目前,脂质组学已成为代谢组学最重要的分支之一,且是一个非常活跃的研究领域,尤其在研究疾病方面的重要性已经引起了科学界的广泛关注。该文简要介绍了脂质组学的研究内容,重点评述了脂质组学分析方法,包括样品处理、轮廓分析、目标分析、成像分析以及数据处理。最后提出了脂质组学分析技术和方法的展望。     

Multivariate statistical identification of human bladder carcinomas using ambient ionization imaging mass spectrometry

Diagnosis of human bladder cancer in untreated tissue sections is achieved by using imaging data from desorption electrospray ionization mass spectrometry (DESI-MS) combined with multivariate statistical analysis. We use the distinctive DESI-MS glycerophospholipid (GP) mass spectral profiles to visually characterize and formally classify twenty pairs (40 tissue samples) of human cancerous and adjacent normal bladder tissue samples. The individual ion images derived from the acquired profiles correlate with standard histological hematoxylin and eosin (H&E)-stained serial sections. The profiles allow us to classify the disease status of the tissue samples with high accuracy as judged by reference histological data. To achieve this, the data from the twenty pairs were divided into a training set and a validation set. Spectra from the tumor and normal regions of each of the tissue sections in the training set were used for orthogonal projection to latent structures (O-PLS) treated partial least-square discriminate analysis (PLS-DA). This predictive model was then validated by using the validation set and showed a 5% error rate for classification and a misclassification rate of 12%. It was also used to create synthetic images of the tissue sections showing pixel-by-pixel disease classification of the tissue and these data agreed well with the independent classification that uses histological data by a certified pathologist. This represents the first application of multivariate statistical methods for classification by ambient ionization although these methods have been applied previously to other MS imaging methods. The results are encouraging in terms of the development of a method that could be utilized in a clinical setting through visualization and diagnosis of intact tissue.     

High-throughput lipidomics analysis to discover lipid biomarkers and profiles as potential targets for evaluating efficacy of Kai-Xin-San against APP/PS1 transgenic mice based on UPLC–Q/TOF–MS

Lipid metabolism has a significant function in the central nervous system and Alzheimer's disease (AD) is an age-related senile disease characterized by central nerve degeneration. The pathological development of AD is closely related to lipid metabolism disorders. To reveal the influence of Kai-Xin-San (KXS) on lipid metabolism in APP/PSI transgenic mice and potential therapeutic targets for treating AD, brain tissue samples were collected and analyzed by high-throughput lipidomics based on UPLC–Q/TOF-MS. The collected raw data were processed by multivariate data analysis to discover the potential biomarkers and lipid metabolic profiles. Compared with the control wild-type mouse group, nine potential lipid biomarkers were found in the AD model group, of which seven were up-regulated and two were down-regulated. Orally administrated KXS can reverse the changes in these potential biomarkers. Compared with the model group, a total of six differential metabolites showed a recovery trend and may be potential targets for KXS to treat AD. This study showed that high-throughput lipidomics can be used to discover the perturbed pathways and lipid biomarkers as potential targets to reveal the therapeutic effects of KXS.     

Mass‐spectrometry‐based lipidomics

Lipids, which have a core function in energy storage, signalling and biofilm structures, play important roles in a variety of cellular processes because of the great diversity of their structural and physiochemical properties. Lipidomics is the large‐scale profiling and quantification of biogenic lipid molecules, the comprehensive study of their pathways and the interpretation of their physiological significance based on analytical chemistry and statistical analysis. Lipidomics will not only provide insight into the physiological functions of lipid molecules but will also provide an approach to discovering important biomarkers for diagnosis or treatment of human diseases. Mass‐spectrometry‐based analytical techniques are currently the most widely used and most effective tools for lipid profiling and quantification. In this review, the field of mass‐spectrometry‐based lipidomics was discussed. Recent progress in all essential steps in lipidomics was carefully discussed in this review, including lipid extraction strategies, separation techniques and mass‐spectrometry‐based analytical and quantitative methods in lipidomics. We also focused on novel resolution strategies for difficult problems in determining C=C bond positions in lipidomics. Finally, new technologies that were developed in recent years including single‐cell lipidomics, flux‐based lipidomics and multiomics technologies were also reviewed.     

Shotgun lipidomics on a LTQ Orbitrap mass spectrometer by successive switching between acquisition polarity modes

Top–down shotgun lipidomics relies on direct infusion of total lipid extracts into a high‐resolution tandem mass spectrometer and implies that individual lipids are recognized by their accurately determined m/z. Lipid ionization efficiency and detection specificity strongly depend on the acquisition polarity, and therefore it is beneficial to analyze lipid mixtures in both positive and negative modes. Hybrid LTQ Orbitrap mass spectrometers are widely applied in top–down lipidomics; however, rapid polarity switching was previously unfeasible because of the severe and immediate degradation of mass accuracy. Here, we report on a method to rapidly acquire high‐resolution spectra in both polarity modes with sub‐ppm mass accuracy and demonstrate that it not only simplifies and accelerates shotgun lipidomics analyses but also improves the lipidome coverage because more lipid classes and more individual species within each class are recognized. In this way, shotgun analysis of total lipid extracts of human blood plasma enabled to quantify 222 species from 15 major lipid classes within 7 min acquisition cycle. Copyright © 2012 John Wiley & Sons, Ltd.     

基于衍生化技术的甘油磷脂分析方法研究进展

磷脂是所有生物细胞膜的主要成分,在许多生命活动过程中具有重要的功能。但由于生物样本中的磷脂种类繁多,含量极低,存在基质抑制效应,且结构中缺少易电离的官能团,从而导致对磷脂的定性和定量分析较困难。利用化学衍生化技术对其进行结构修饰可以提高离子化效率、改善色谱分离度且提高质谱(MS)检测的灵敏度和选择性。MS与衍生化方法结合已被广泛用于蛋白组学、糖组学、代谢物等的分析。近年来,这一策略逐渐被应用于脂质组学的分析研究。该文综述了国内外近10年基于衍生化技术的甘油磷脂分析方法及其应用研究进展,以激发衍生化技术在脂质组学分析中的应用潜能。