Most cited article - PubMed ID 29543437
Lipidomic Analysis
Reversed-phase ultrahigh-performance liquid chromatography-mass spectrometry (RP-UHPLC/MS) method is optimized for the quantitation of a large number of lipid species in biological samples, primarily in human plasma and serum. The method uses a C18 bridged ethylene hybrid (BEH) column (150 × 2.1 mm; 1.7 μm) for the separation of lipids from 23 subclasses with a total run time of 25 min. Lipid species separation allows the resolution of isobaric and isomeric lipid forms. A triple quadrupole mass spectrometer is used for targeted lipidomic analysis using multiple reaction monitoring (MRM) in the positive ion mode. Data are evaluated by Skyline software, and the concentrations of analytes are determined using internal standards per each individual lipid class.
- Keywords
- High-throughput lipidomics, Mass spectrometry, Plasma, Quantitation, Reversed-phase, Serum, Ultrahigh-performance liquid chromatography,
- MeSH
- Chromatography, Reverse-Phase * methods MeSH
- Mass Spectrometry methods MeSH
- Liquid Chromatography-Mass Spectrometry MeSH
- Humans MeSH
- Lipidomics * methods MeSH
- Lipids * analysis MeSH
- High-Throughput Screening Assays methods MeSH
- Software MeSH
- Tandem Mass Spectrometry methods MeSH
- Chromatography, High Pressure Liquid methods MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Names of Substances
- Lipids * MeSH
Mass spectrometry-based lipidomics and metabolomics generate extensive data sets that, along with metadata such as clinical parameters, require specific data exploration skills to identify and visualize statistically significant trends and biologically relevant differences. Besides tailored methods developed by individual labs, a solid core of freely accessible tools exists for exploratory data analysis and visualization, which we have compiled here, including preparation of descriptive statistics, annotated box plots, hypothesis testing, volcano plots, lipid maps and fatty acyl chain plots, unsupervised and supervised dimensionality reduction, dendrograms, and heat maps. This review is intended for those who would like to develop their skills in data analysis and visualization using freely available R or Python solutions. Beginners are guided through a selection of R and Python libraries for producing publication-ready graphics without being overwhelmed by the code complexity. This manuscript, along with associated GitBook code repository containing step-by-step instructions, offers readers a comprehensive guide, encouraging the application of R and Python for robust and reproducible chemometric analysis of omics data.
- MeSH
- Mass Spectrometry MeSH
- Humans MeSH
- Lipidomics * methods MeSH
- Metabolomics * methods MeSH
- Programming Languages MeSH
- Software * MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Review MeSH
Chemical derivatization involves the reaction of an analyte with a derivatization agent to modify its structure, improving the peak shape, chromatographic performance, structural analysis, ionization efficiency, and sensitivity. A novel derivatization method using 3-(chlorosulfonyl)benzoic acid is developed for the determination of monoacylglycerols, diacylglycerols, free sterols, and tocopherols using the reversed-phase ultra-high-performance liquid chromatography-tandem mass spectrometry (RP-UHPLC/MS/MS) method in the negative ion mode. The chromatographic and mass spectrometric properties of derivatized lipids are investigated by using 29 lipid standards spanning four lipid classes. The derivatization process is optimized using pooled plasma spiked by 9 internal standards, achieving an optimal yield with a reaction time of 40 min at 60 °C. The stability of the derivatives is confirmed, with short-term stability maintained for 10 h at 4 °C and long-term stability preserved for 5 days at -80 °C. The repeatability and reproducibility are verified by one/two operator(s), which underscores the simplicity and robustness of the method, and calibration curves with high linear regression coefficients illustrate the accuracy of the method. The derivatization approach, which combines RP-UHPLC/MS/MS and the use of specific fragmentation patterns, significantly reduces limits of detection, reaching 15-25 pmol/mL for free sterols in plasma. The optimized method is applied to the analysis of human plasma, leading to the identification of 92 lipid species in the targeted lipid classes. This represents a substantial improvement in sensitivity and detection capabilities compared to those of previously reported methods.
Multidimensional chromatography offers enhanced chromatographic resolution and peak capacity, which are crucial for analyzing complex samples. This study presents a novel comprehensive online multidimensional chromatography method for the lipidomic analysis of biological samples, combining lipid class and lipid species separation approaches. The method combines optimized reversed-phase ultrahigh-performance liquid chromatography (RP-UHPLC) in the first dimension, utilizing a 150 mm long C18 column, with ultrahigh-performance supercritical fluid chromatography (UHPSFC) in the second dimension, using a 10 mm long silica column, both with sub-2 μm particles. A key advantage of employing UHPSFC in the second dimension is its ability to perform ultrafast analysis using gradient elution with a sampling time of 0.55 min. This approach offers a significant increase in the peak capacity. Compared to our routinely used 1D methods, the peak capacity of the 4D system is 10 times higher than RP-UHPLC and 18 times higher than UHPSFC. The entire chromatographic system is coupled with a high-resolution quadrupole-time-of-flight (QTOF) mass analyzer using electrospray ionization (ESI) in both full-scan and tandem mass spectrometry (MS/MS) and with positive- and negative-ion polarities, enabling the detailed characterization of the lipidome. The confident identification of lipid species is achieved through characteristic ions in both polarity modes, information from MS elevated energy (MSE) and fast data-dependent analysis scans, and mass accuracy below 5 ppm. This analytical method has been used to characterize the lipidomic profile of the total lipid extract from human plasma, which has led to the identification of 298 lipid species from 16 lipid subclasses.
- MeSH
- Humans MeSH
- Lipidomics * methods MeSH
- Lipids * analysis MeSH
- Chromatography, Supercritical Fluid methods MeSH
- Tandem Mass Spectrometry * methods MeSH
- Chromatography, High Pressure Liquid methods MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Names of Substances
- Lipids * MeSH
Glycosphingolipids (GSL) are a highly heterogeneous class of lipids representing the majority of the sphingolipid category. GSL are fundamental constituents of cellular membranes that have key roles in various biological processes, such as cellular signaling, recognition, and adhesion. Understanding the structural complexity of GSL is pivotal for unraveling their functional significance in a biological context, specifically their crucial role in the pathophysiology of various diseases. Mass spectrometry (MS) has emerged as a versatile and indispensable tool for the structural elucidation of GSL enabling a deeper understanding of their complex molecular structures and their key roles in cellular dynamics and patholophysiology. Here, we provide a thorough overview of MS techniques tailored for the analysis of GSL, emphasizing their utility in probing GSL intricate structures to advance our understanding of the functional relevance of GSL in health and disease. The application of tandem MS using diverse fragmentation techniques, including novel ion activation methodologies, in studying glycan sequences, linkage positions, and fatty acid composition is extensively discussed. Finally, we address current challenges, such as the detection of low-abundance species and the interpretation of complex spectra, and offer insights into potential solutions and future directions by improving MS instrumentation for enhanced sensitivity and resolution, developing novel ionization techniques, or integrating MS with other analytical approaches for comprehensive GSL characterization.
- Keywords
- Derivatization, Fragmentation, Glycosphingolipids, Liquid chromatography, Mass spectrometry, Structural elucidation,
- MeSH
- Glycosphingolipids * chemistry analysis MeSH
- Mass Spectrometry * methods MeSH
- Humans MeSH
- Tandem Mass Spectrometry methods MeSH
- Animals MeSH
- Check Tag
- Humans MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
- Review MeSH
- Names of Substances
- Glycosphingolipids * MeSH
Microflow liquid chromatography interfaced with mass spectrometry (μLC-MS/MS) is increasingly applied for high-throughput profiling of biological samples and has been proven to have an acceptable trade-off between sensitivity and reproducibility. However, lipidomics applications are scarce. We optimized a μLC-MS/MS system utilizing a 1 mm inner diameter × 100 mm column coupled to a triple quadrupole mass spectrometer to establish a sensitive, high-throughput, and robust single-shot lipidomics workflow. Compared to conventional lipidomics methods, we achieve a ∼4-fold increase in response, facilitating quantification of 351 lipid species from a single iPSC-derived cerebral organoid during a 15 min LC-MS analysis. Consecutively, we injected 303 samples over ∼75 h to prove the robustness and reproducibility of the microflow separation. As a proof of concept, μLC-MS/MS analysis of Alzheimer's disease patient-derived iPSC cerebral organoid reveals differential lipid metabolism depending on APOE phenotype (E3/3 vs E4/4). Microflow separation proves to be an environmentally friendly and cost-effective method as it reduces the consumption of harmful solvents. Also, the data demonstrate robust, in-depth, high-throughput performance to enable routine clinical or biomedical applications.
- MeSH
- Apolipoproteins E MeSH
- Chromatography, Liquid methods MeSH
- Phenotype MeSH
- Liquid Chromatography-Mass Spectrometry * MeSH
- Humans MeSH
- Lipidomics MeSH
- Reproducibility of Results MeSH
- Tandem Mass Spectrometry * methods MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Names of Substances
- Apolipoproteins E MeSH
Pancreatic cancer has the worst prognosis among all cancers. Cancer screening of body fluids may improve the survival time prognosis of patients, who are often diagnosed too late at an incurable stage. Several studies report the dysregulation of lipid metabolism in tumor cells, suggesting that changes in the blood lipidome may accompany tumor growth. Here we show that the comprehensive mass spectrometric determination of a wide range of serum lipids reveals statistically significant differences between pancreatic cancer patients and healthy controls, as visualized by multivariate data analysis. Three phases of biomarker discovery research (discovery, qualification, and verification) are applied for 830 samples in total, which shows the dysregulation of some very long chain sphingomyelins, ceramides, and (lyso)phosphatidylcholines. The sensitivity and specificity to diagnose pancreatic cancer are over 90%, which outperforms CA 19-9, especially at an early stage, and is comparable to established diagnostic imaging methods. Furthermore, selected lipid species indicate a potential as prognostic biomarkers.
- MeSH
- CA-19-9 Antigen blood MeSH
- Ceramides blood MeSH
- Humans MeSH
- Lipidomics methods MeSH
- Lysophosphatidylcholines blood MeSH
- Lipid Metabolism genetics MeSH
- Multivariate Analysis MeSH
- Biomarkers, Tumor blood genetics MeSH
- Pancreatic Neoplasms blood diagnosis mortality pathology MeSH
- Proportional Hazards Models MeSH
- Sensitivity and Specificity MeSH
- Sphingomyelins blood MeSH
- Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization MeSH
- Case-Control Studies MeSH
- Check Tag
- Humans MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Names of Substances
- CA-19-9 Antigen MeSH
- Ceramides MeSH
- Lysophosphatidylcholines MeSH
- Biomarkers, Tumor MeSH
- Sphingomyelins MeSH
Reversed-phase ultrahigh-performance liquid chromatography-mass spectrometry (RP-UHPLC/MS) method was developed with the aim to unambiguously identify a large number of lipid species from multiple lipid classes in human plasma. The optimized RP-UHPLC/MS method employed the C18 column with sub-2-μm particles with the total run time of 25 min. The chromatographic resolution was investigated with 42 standards from 18 lipid classes. The UHPLC system was coupled to high-resolution quadrupole-time-of-flight (QTOF) mass analyzer using electrospray ionization (ESI) measuring full-scan and tandem mass spectra (MS/MS) in positive- and negative-ion modes with high mass accuracy. Our identification approach was based on m/z values measured with mass accuracy within 5 ppm tolerance in the full-scan mode, characteristic fragment ions in MS/MS, and regularity in chromatographic retention dependences for individual lipid species, which provides the highest level of confidence for reported identifications of lipid species including regioisomeric and other isobaric forms. The graphs of dependences of retention times on the carbon number or on the number of double bond(s) in fatty acyl chains were constructed to support the identification of lipid species in homologous lipid series. Our list of identified lipid species is also compared with previous publications investigating human blood samples by various MS-based approaches. In total, we have reported more than 500 lipid species representing 26 polar and nonpolar lipid classes detected in NIST Standard reference material 1950 human plasma.
- Keywords
- Human plasma, Lipidomics, Lipids, Mass spectrometry, Retention behavior, Reversed-phase, Ultrahigh-performance liquid chromatography,
- MeSH
- Chromatography, Liquid methods MeSH
- Mass Spectrometry methods MeSH
- Humans MeSH
- Lipids blood chemistry MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Names of Substances
- Lipids MeSH
In the last 2 decades, lipidomics has become one of the fastest expanding scientific disciplines in biomedical research. With an increasing number of new research groups to the field, it is even more important to design guidelines for assuring high standards of data quality. The Lipidomics Standards Initiative is a community-based endeavor for the coordination of development of these best practice guidelines in lipidomics and is embedded within the International Lipidomics Society. It is the intention of this review to highlight the most quality-relevant aspects of the lipidomics workflow, including preanalytics, sample preparation, MS, and lipid species identification and quantitation. Furthermore, this review just does not only highlights examples of best practice but also sheds light on strengths, drawbacks, and pitfalls in the lipidomic analysis workflow. While this review is neither designed to be a step-by-step protocol by itself nor dedicated to a specific application of lipidomics, it should nevertheless provide the interested reader with links and original publications to obtain a comprehensive overview concerning the state-of-the-art practices in the field.
- Keywords
- LC-MS, MS, chromatography, ion mobility spectrometry, lipid identification, lipidomics, metabolomics, phospholipids, sphingolipids,
- MeSH
- Mass Spectrometry MeSH
- Humans MeSH
- Lipidomics * standards MeSH
- Lipids analysis MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Review MeSH
- Research Support, N.I.H., Extramural MeSH
- Names of Substances
- Lipids MeSH
Early detection of cancer is one of the unmet needs in clinical medicine. Peripheral blood analysis is a preferred method for efficient population screening, because blood collection is well embedded in clinical practice and minimally invasive for patients. Lipids are important biomolecules, and variations in lipid concentrations can reflect pathological disorders. Lipidomic profiling of human plasma by the coupling of ultrahigh-performance supercritical fluid chromatography and mass spectrometry is investigated with the aim to distinguish patients with breast, kidney, and prostate cancers from healthy controls. The mean sensitivity, specificity, and accuracy of the lipid profiling approach were 85%, 95%, and 92% for kidney cancer; 91%, 97%, and 94% for breast cancer; and 87%, 95%, and 92% for prostate cancer. No association of statistical models with tumor stage is observed. The statistically most significant lipid species for the differentiation of cancer types studied are CE 16:0, Cer 42:1, LPC 18:2, PC 36:2, PC 36:3, SM 32:1, and SM 41:1 These seven lipids represent a potential biomarker panel for kidney, breast, and prostate cancer screening, but a further verification step in a prospective study has to be performed to verify clinical utility.
- MeSH
- Early Detection of Cancer MeSH
- Adult MeSH
- Heparin chemistry MeSH
- Mass Spectrometry MeSH
- Kidney metabolism MeSH
- Middle Aged MeSH
- Humans MeSH
- Lipidomics * MeSH
- Lipids chemistry MeSH
- Young Adult MeSH
- Biomarkers, Tumor metabolism MeSH
- Prostatic Neoplasms metabolism MeSH
- Breast Neoplasms metabolism MeSH
- Area Under Curve MeSH
- Prospective Studies MeSH
- Prostate metabolism MeSH
- Breast metabolism MeSH
- Gene Expression Regulation, Neoplastic MeSH
- Reproducibility of Results MeSH
- Retrospective Studies MeSH
- ROC Curve MeSH
- Aged MeSH
- Models, Statistical MeSH
- Case-Control Studies MeSH
- Chromatography, Supercritical Fluid MeSH
- Check Tag
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Young Adult MeSH
- Male MeSH
- Aged MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Names of Substances
- Heparin MeSH
- Lipids MeSH
- Biomarkers, Tumor MeSH
