HILIC/MS quantitation of low-abundant phospholipids and sphingolipids in human plasma and serum: Dysregulation in pancreatic cancer.

A new hydrophilic interaction liquid chromatography - mass spectrometry method is developed for low-abundant phospholipids and sphingolipids in human plasma and serum. The optimized method involves the Cogent Silica type C hydride column, the simple sample preparation by protein precipitation, and the removal of highly abundant lipid classes using the postcolumn valve directed to waste during two elution windows. The method allows a highly confident and sensitive identification of low-abundant lipid classes in human plasma (246 lipid species from 24 lipid subclasses) based on mass accuracy and retention dependencies in both polarity modes. The method is validated for quantitation using two internal standards (if available) for each lipid class and applied to human plasma and serum samples obtained from patients with pancreatic ductal adenocarcinoma (PDAC), healthy controls, and NIST SRM 1950. Multivariate data analysis followed by various statistical projection methods is used to determine the most dysregulated lipids. Significant downregulation is observed for lysophospholipids with fatty acyl composition 16:0, 18:0, 18:1, and 18:2. Distinct trends are observed for phosphatidylethanolamines (PE) in relation to the bonding type of fatty acyls, where most PE with acyl bonds are upregulated, while ether/plasmenyl PE are downregulated. For the sphingolipid category, sphingolipids with very long N-acyl chains are downregulated, while sphingolipids with shorter N-acyl chains were upregulated in PDAC. These changes are consistently observed for various classes of sphingolipids, ranging from ceramides to glycosphingolipids, indicating a possible metabolic disorder in ceramide biosynthesis caused by PDAC.

Altered plasma membrane abundance of the sulfatide-binding protein NF155 links glycosphingolipid imbalances to demyelination.

Myelin is a multilayered membrane that tightly wraps neuronal axons, enabling efficient, high-speed signal propagation. The axon and myelin sheath form tight contacts, mediated by specific plasma membrane proteins and lipids, and disruption of these contacts causes devastating demyelinating diseases. Using two cell-based models of demyelinating sphingolipidoses, we demonstrate that altered lipid metabolism changes the abundance of specific plasma membrane proteins. These altered membrane proteins have known roles in cell adhesion and signaling, with several implicated in neurological diseases. The cell surface abundance of the adhesion molecule neurofascin (NFASC), a protein critical for the maintenance of myelin-axon contacts, changes following disruption to sphingolipid metabolism. This provides a direct molecular link between altered lipid abundance and myelin stability. We show that the NFASC isoform NF155, but not NF186, interacts directly and specifically with the sphingolipid sulfatide via multiple binding sites and that this interaction requires the full-length extracellular domain of NF155. We demonstrate that NF155 adopts an S-shaped conformation and preferentially binds sulfatide-containing membranes in cis, with important implications for protein arrangement in the tight axon-myelin space. Our work links glycosphingolipid imbalances to disturbance of membrane protein abundance and demonstrates how this may be driven by direct protein-lipid interactions, providing a mechanistic framework to understand the pathogenesis of galactosphingolipidoses.

Comprehensive characterization of complex glycosphingolipids in human pancreatic cancer tissues.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most common causes of cancer-related deaths worldwide, accounting for 90% of primary pancreatic tumors with an average 5-year survival rate of less than 10%. PDAC exhibits aggressive biology, which, together with late detection, results in most PDAC patients presenting with unresectable, locally advanced, or metastatic disease. In-depth lipid profiling and screening of potential biomarkers currently appear to be a promising approach for early detection of PDAC or other cancers. Here, we isolated and characterized complex glycosphingolipids (GSL) from normal and tumor pancreatic tissues of patients with PDAC using a combination of TLC, chemical staining, carbohydrate-recognized ligand-binding assay, and LC/ESI-MS2. The major neutral GSL identified were GSL with the terminal blood groups A, B, H, Lea, Leb, Lex, Ley, P1, and PX2 determinants together with globo- (Gb3 and Gb4) and neolacto-series GSL (nLc4 and nLc6). We also revealed that the neutral GSL profiles and their relative amounts differ between normal and tumor tissues. Additionally, the normal and tumor pancreatic tissues differ in type 1/2 core chains. Sulfatides and GM3 gangliosides were the predominant acidic GSL along with the minor sialyl-nLc4/nLc6 and sialyl-Lea/Lex. The comprehensive analysis of GSL in human PDAC tissues extends the GSL coverage and provides an important platform for further studies of GSL alterations; therefore, it could contribute to the development of new biomarkers and therapeutic approaches.

Robust and high-throughput lipidomic quantitation of human blood samples using flow injection analysis with tandem mass spectrometry for clinical use.

Direct infusion of lipid extracts into the ion source of a mass spectrometer is a well-established method for lipid analysis. In most cases, nanofluidic devices are used for sample introduction. However, flow injection analysis (FIA) based on sample infusion from a chromatographic pump can offer a simple alternative to shotgun-based approaches. Here, we describe important modification of a method based on FIA and tandem mass spectrometry (MS/MS). We focus on minimizing contamination of the FIA/MS both to render the lipidomic platform more robust and to increase its capacity and applicability for long-sequence measurements required in clinical applications. Robust validation of the developed method confirms its suitability for lipid quantitation in human plasma analysis. Measurements of standard human plasma reference material (NIST SRM 1950) and a set of plasma samples collected from kidney cancer patients and from healthy volunteers yielded highly similar results between FIA-MS/MS and ultra-high-performance supercritical fluid chromatography (UHPSFC)/MS, thereby demonstrating that all modifications have practically no effect on the statistical output. Newly modified FIA-MS/MS allows for the quantitation of 141 lipid species in plasma (11 major lipid classes) within 5.7 min. Finally, we tested the method in a clinical laboratory of the General University Hospital in Prague. In the clinical setting, the method capacity reached 257 samples/day. We also show similar performance of the classification models trained based on the results obtained in clinical settings and the analytical laboratory at the University of Pardubice. Together, these findings demonstrate the high potential of the modified FIA-MS/MS for application in clinical laboratories to measure plasma and serum lipid profiles.

Altered Plasma, Urine, and Tissue Profiles of Sulfatides and Sphingomyelins in Patients with Renal Cell Carcinoma.

PURPOSE: RCC, the most common type of kidney cancer, is associated with high mortality. A non-invasive diagnostic test remains unavailable due to the lack of RCC-specific biomarkers in body fluids. We have previously described a significantly altered profile of sulfatides in RCC tumor tissues, motivating us to investigate whether these alterations are reflected in collectible body fluids and whether they can enable RCC detection. METHODS: We collected and further analyzed 143 plasma, 100 urine, and 154 tissue samples from 155 kidney cancer patients, together with 207 plasma and 70 urine samples from 214 healthy controls. RESULTS: For the first time, we show elevated concentrations of lactosylsulfatides and decreased levels of sulfatides with hydroxylated fatty acyls in body fluids of RCC patients compared to controls. These alterations are emphasized in patients with the advanced tumor stage. Classification models are able to distinguish between controls and patients with RCC. In the case of all plasma samples, the AUC for the testing set was 0.903 (0.844-0.954), while for urine samples it was 0.867 (0.763-0.953). The models are able to efficiently detect patients with early- and late-stage RCC based on plasma samples as well. The test set sensitivities were 80.6% and 90%, and AUC values were 0.899 (0.832-0.952) and 0.981 (0.956-0.998), respectively. CONCLUSION: Similar trends in body fluids and tissues indicate that RCC influences lipid metabolism, and highlight the potential of the studied lipids for minimally-invasive cancer detection, including patients with early tumor stages, as demonstrated by the predictive ability of the applied classification models.

Liquid chromatography at the University of Pardubice: A tribute to Professor Pavel Jandera.

Pavel Jandera was a world-leading analytical chemist who devoted his entire professional life to research in the field of high-performance liquid chromatography. During his scientific career, he worked at the Department of Analytical Chemistry at the University of Pardubice, Czech Republic. His greatest contribution to the field of liquid chromatography was the introduction of a comprehensive theory of liquid chromatography with programmed elution conditions. He was also involved in the research of gradient elution techniques in preparative chromatography, modeling of retention and selectivity in various phase systems, preparation of organic monolithic microcolumns, and, last but not least, in the development of theory and practical applications of two-dimensional liquid chromatography, mainly in the comprehensive form. In this review article, we have tried to capture the highlights of his scientific career and provide the readers with a detailed overview of Pavel Jandera's contribution to the evolution of separation sciences.

Clinical lipidomics - A community-driven roadmap to translate research into clinical applications.

Lipid metabolites, beyond triglycerides and cholesterol, have been shown to have vast potential for applications in clinical applications, with substantial societal and economical value. To successfully evolve from the current research-grade methods to assays suitable for routine clinical applications, a harmonization - if not standardization - of these mass spectrometry-based workflows is necessary. Input on clinical needs and technological capabilities must be obtained from all relevant stakeholders, including wet lab scientists, informaticians and data scientists, manufacturers, and medical professionals. In order to build bridges between this diverse group of professionals, the International Lipidomics Society and its Clinical Lipidomics Interest Group were created. This opinion article is intended to provide an overview of international efforts to tackle the issues of workflow harmonization, and to serve as an open invitation for others to join this growing community.

Ultrahigh-performance supercritical fluid chromatography - mass spectrometry for the qualitative analysis of metabolites covering a large polarity range.

The applicability of ultrahigh-performance supercritical fluid chromatography coupled with mass spectrometry (UHPSFC/MS) for the qualitative analysis of metabolites with a wide polarity range (log P: -3.89-18.95) was evaluated using a representative set of 78 standards belonging to nucleosides, biogenic amines, carbohydrates, amino acids, and lipids. The effects of the gradient shape and the percentage of water (1, 2, and 5%) were investigated on the Viridis BEH column. The screening of eight stationary phases was performed for columns with different interaction sites, such as hydrogen bonding, hydrophobic, π-π, or anionic exchange type interactions. The highest number of compounds (67) of the set studied was detected on the Torus Diol column, which provided a resolution parameter of 39. The DEA column had the second best performance with 58 detected standards and the resolution parameter of 54. The overall performance of other parameters, such as selectivity, peak height, peak area, retention time stability, asymmetry factor, and mass accuracy, led to the selection of the Diol column for the final method. The comparison of additives showed that ammonium acetate gave a superior sensitivity over ammonium formate. Moreover, the influence of the ion source on the ionization efficiency was studied by employing atmospheric pressure chemical ionization (APCI) and electrospray ionization (ESI). The results proved the complementarity of both ionization techniques, but also the superior ionization capacity of the ESI source in the negative ion mode, for which 53% of the analytes were detected compared to only 7% for the APCI source. Finally, optimized analytical conditions were applied to the analysis of a pooled human plasma sample. 44 compounds from the preselected set were detected in human plasma using ESI-UHPSFC/MS in MSE mode considering both ionization modes.

Lipidomic profiling of human serum enables detection of pancreatic cancer.

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.

Retention dependences support highly confident identification of lipid species in human plasma by reversed-phase UHPLC/MS.

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.

Lipidomic and metabolomic analysis reveals changes in biochemical pathways for non-small cell lung cancer tissues.

Lung cancer represents one of the leading worldwide causes of cancer death, but the pathobiochemistry of this disease is still not fully understood. Here we characterize the lipidomic and metabolomic profiles of the tumor and surrounding normal tissues for 23 patients with non-small cell lung cancer. In total, 500 molecular species were identified and quantified by a combination of the lipidomic shotgun tandem mass spectrometry (MS/MS) analysis and the targeted metabolomic approach using liquid chromatography (LC) - MS/MS. The statistical evaluation includes multivariate and univariate methods with the emphasis on paired statistical approaches. Our research revealed significant changes in several biochemical pathways related to the central carbon metabolism, acylcarnitines, dipeptides as well as the disruption in the lipid metabolism observed mainly for glycerophospholipids, sphingolipids, and cholesteryl esters.

Recommendations for good practice in MS-based lipidomics.

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.

Multiomics of synaptic junctions reveals altered lipid metabolism and signaling following environmental enrichment.

Membrane lipids and their metabolism have key functions in neurotransmission. Here we provide a quantitative lipid inventory of mouse and rat synaptic junctions. To this end, we developed a multiomics extraction and analysis workflow to probe the interplay of proteins and lipids in synaptic signal transduction from the same sample. Based on this workflow, we generate hypotheses about novel mechanisms underlying complex changes in synaptic connectivity elicited by environmental stimuli. As a proof of principle, this approach reveals that in mice exposed to an enriched environment, reduced endocannabinoid synthesis and signaling is linked to increased surface expression of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) in a subset of Cannabinoid-receptor 1 positive synapses. This mechanism regulates synaptic strength in an input-specific manner. Thus, we establish a compartment-specific multiomics workflow that is suitable to extract information from complex lipid and protein networks involved in synaptic function and plasticity.

Plasma lipidomic profiles of kidney, breast and prostate cancer patients differ from healthy controls.

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.

Simple and Reproducible Derivatization with Benzoyl Chloride: Improvement of Sensitivity for Multiple Lipid Classes in RP-UHPLC/MS.

The chemical derivatization of multiple lipid classes was developed using benzoyl chloride as a nonhazardous derivatization agent at ambient conditions. The derivatization procedure was optimized with standards for 4 nonpolar and 8 polar lipid classes and measured by reversed-phase ultrahigh-performance liquid chromatography-tandem mass spectrometry. The derivatization and nonderivatization approaches were compared on the basis of the calibration curves of 22 internal standards from 12 lipid classes. The new method decreased the limit of detection 9-fold for monoacylglycerols (0.9-1.0 nmol/mL), 6.5-fold for sphingoid base (0.2 nmol/mL), and 3-fold for diacylglycerols (0.9 nmol/mL). The sensitivity expressed by the ratio of calibration slopes was increased 2- to 10-fold for almost all investigated lipid classes and even more than 100-fold for monoacylglycerols. Moreover, the benzoylation reaction produces a more stable derivative of cholesterol in comparison to the easily in-source fragmented nonderivatized form and enabled the detection of fatty acids in a positive ion mode, which does not require polarity switching as for the nonderivatized form. The intralaboratory comparison with an additional operator without previous derivatization experiences shows the simplicity, robustness, and reproducibility. The stability of the derivatives was determined by periodical measurements during a one month period and five freeze/thaw cycles. The fully optimized derivatization method was applied to human plasma, which allows the detection of 169 lipid species from 11 lipid classes using the high confidence level of identification in reversed-phase (RP)-ultra high performance liquid chromatography (UHPLC)/mass spectrometry (MS). Generally, we detected more lipid species for monoacylglycerols, diacylglycerols, and sphingoid bases in comparison with previously reported papers without the derivatization.

LipidQuant 1.0: automated data processing in lipid class separation-mass spectrometry quantitative workflows.

SUMMARY: We present the LipidQuant 1.0 tool for automated data processing workflows in lipidomic quantitation based on lipid class separation coupled with high-resolution mass spectrometry. Lipid class separation workflows, such as hydrophilic interaction liquid chromatography or supercritical fluid chromatography, should be preferred in lipidomic quantitation due to the coionization of lipid class internal standards with analytes from the same class. The individual steps in the LipidQuant workflow are explained, including lipid identification, quantitation, isotopic correction and reporting results. We show the application of LipidQuant data processing to a small cohort of human serum samples. AVAILABILITY AND IMPLEMENTATION: The LipidQuant 1.0 is freely available at Zenodo https://doi.org/10.5281/zenodo.5151201 and https://holcapek.upce.cz/lipidquant.php. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.