Differential Isotope Labeling by Permethylation and Reversed-Phase Liquid Chromatography-Mass Spectrometry for Relative Quantification of Intact Neutral Glycolipids in Mammalian Cells

Unraveling the complexity of glycosphingolipidome: the key role of mass spectrometry in the structural analysis of glycosphingolipids

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.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2019-2020

This review is the tenth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2020. Also included are papers that describe methods appropriate to analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. The review is basically divided into three sections: (1) general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, quantification and the use of arrays. (2) Applications to various structural types such as oligo- and polysaccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals, and (3) other areas such as medicine, industrial processes and glycan synthesis where MALDI is extensively used. Much of the material relating to applications is presented in tabular form. The reported work shows increasing use of incorporation of new techniques such as ion mobility and the enormous impact that MALDI imaging is having. MALDI, although invented nearly 40 years ago is still an ideal technique for carbohydrate analysis and advancements in the technique and range of applications show little sign of diminishing.

Segment Scan Mass Spectral Acquisition for Increasing the Metabolite Detectability in Chemical Isotope Labeling Liquid Chromatography-Mass Spectrometry Metabolome Analysis

We report a segmented spectrum scan method using Orbitrap MS in chemical isotope labeling (CIL) liquid chromatography-mass spectrometry (LC-MS) for improving the metabolite detection efficiency. In this method, the full m/z range is divided into multiple segments with the scanning of each segment to produce multiple narrow-range spectra during the LC data acquisition. These segmented spectra are separately processed to extract the peak pair information with each peak pair arising from a differentially labeled metabolite in the analysis of a mixture of ¹³C and ¹²C reagent-labeled samples. The sublists of peak pairs are merged to form the final peak pair list from the LC-MS run. Various experimental conditions, including automatic gain control (AGC) values, mass resolutions, segment m/z widths, number of segments, and total data acquisition time in the LC run, were examined to arrive at an optimal setting in the segment scan for increasing the number of detectable metabolites while maintaining the same analysis time as in the full scan. The optimal method used a segment width of 120 m/z with 60k resolution for a 16 min CIL LC-MS run. Using dansyl-labeled human urine samples as an example, we demonstrated that this method could detect 5867 peak pairs or metabolites (not features), compared to 3765 peak pairs detectable in a full scan, representing a 56% gain. Out of 5867 peak pairs, 5575 (95.0%) could be identified or mass-matched. The relative quantification accuracy was slightly reduced (81% peak pairs were within ±25% of the expected peak ratio of 1.0 in full, compared to 87% in the full scan) due to the inclusion of more low-abundance peak pairs in the segment scan. The peak ratio measurement precision was not significantly affected by the segment scan. We also showed the increase of the peak pair number detectable from 3843 in the full scan to 7273 (89% gain) using the Orbitrap operated at 120k resolution with a 60 m/z segment width when multiple repeat sample injections were used. Thus, segment scan Orbitrap MS is an enabling method for detecting coeluting metabolites in CIL LC-MS for increasing the metabolomic coverage.

Mass Spectrometry-Based Techniques to Elucidate the Sugar Code

Cells encode information in the sequence of biopolymers, such as nucleic acids, proteins, and glycans. Although glycans are essential to all living organisms, surprisingly little is known about the "sugar code" and the biological roles of these molecules. The reason glycobiology lags behind its counterparts dealing with nucleic acids and proteins lies in the complexity of carbohydrate structures, which renders their analysis extremely challenging. Building blocks that may differ only in the configuration of a single stereocenter, combined with the vast possibilities to connect monosaccharide units, lead to an immense variety of isomers, which poses a formidable challenge to conventional mass spectrometry. In recent years, however, a combination of innovative ion activation methods, commercialization of ion mobility-mass spectrometry, progress in gas-phase ion spectroscopy, and advances in computational chemistry have led to a revolution in mass spectrometry-based glycan analysis. The present review focuses on the above techniques that expanded the traditional glycomics toolkit and provided spectacular insight into the structure of these fascinating biomolecules. To emphasize the specific challenges associated with them, major classes of mammalian glycans are discussed in separate sections. By doing so, we aim to put the spotlight on the most important element of glycobiology: the glycans themselves.

Normalization of Samples of Limited Amounts in Quantitative Metabolomics Using Liquid Chromatography Fluorescence Detection with Dansyl Labeling of Metabolites

Quantitative metabolomics requires the analysis of the same or a very similar amount of samples in order to accurately determine the concentration differences of individual metabolites in comparative samples. Ideally, the total amount or concentration of metabolites in each sample is measured to normalize all the analyzed samples. In this work, we describe a very sensitive method to measure a subclass of metabolites as a surrogate quantifier for normalization of samples with limited amounts. This method starts with low-volume dansyl labeling of all metabolites containing a primary/secondary amine or phenol group in a sample to produce a final solution of 21 μL. The dansyl-labeled metabolites generate fluorescence signals at 520 nm with photoexcitation at 250 nm. To remove the interference of dansyl hydroxyl products (Dns-OH) formed from the labeling reagents used, a fast-gradient liquid chromatography separation is used to elute Dns-OH using aqueous solution, followed by organic solvent elution to produce a chromatographic peak of labeled metabolites, giving a measurement throughput of 6 min per sample. The integrated fluorescence signals of the peak are found to be related to the injection amount of the dansyl-labeled metabolites. A calibration curve using mixtures of dansyl-labeled amino acids is used to determine the total concentration of labeled metabolites in a sample. This concentration is used for normalization of samples in the range from 2 to 120 μM in 21 μL with only 1 μL consumed for fluorescence quantification (i.e., 2-120 pmol). We demonstrate the application of this sensitive sample normalization method in comparative metabolome analysis of human cancer cells, MCF-7 cells, treated with and without resveratrol, using a starting material of as low as 500 cells.

Separation of Permethylated O-Glycans, Free Oligosaccharides, and Glycosphingolipid-Glycans Using Porous Graphitized Carbon (PGC) Column

Glycosylation is one of the most common and complex post-translational modifications of proteins. However, there are other carbohydrates such as free oligosaccharides and glycosphingolipids-glycans that are associated with important biological and clinical roles. To analyze these molecules using liquid chromatography coupled with mass spectrometry (LC-MS), the permethylation approach was utilized. Although permethylation is a commonly utilized glycan derivatization technique, separation of permethylated glycans released from glycosphingolipid (GSL) by LC-MS has never been previously demonstrated. Here, a nanoflow porous graphitized carbon (PGC) column coupled with a high-resolution mass spectrometer was used to achieve isomeric separation of these permethylated glycans. We demonstrate the separation of free reducing end and reduced end O-glycans, free oligosaccharides derived from human milk, and GSL glycans derived from the MDA-MB-231BR cancer cell line using PGC-LC-MS.

Recent advances in the mass spectrometric analysis of glycosphingolipidome - A review

Aberrant expression of glycosphingolipids has been implicated in a myriad of diseases, but our understanding of the strucural diversity, spatial distribution, and biological function of this class of biomolecules remains limited. These challenges partly stem from a lack of sensitive tools that can detect, identify, and quantify glycosphingolipids at the molecular level. Mass spectrometry has emerged as a powerful tool poised to address most of these challenges. Here, we review the recent developments in analytical glycosphingolipidomics with an emphasis on sample preparation, mass spectrometry and tandem mass spectrometry-based structural characterization, label-free and labeling-based quantification. We also discuss the nomenclature of glycosphingolipids, and emerging technologies like ion mobility spectrometry in differentiation of glycosphingolipid isomers. The intrinsic advantages and shortcomings of each method are carefully critiqued in line with an individual's research goals. Finally, future perspectives on analytical sphingolipidomics are stated, including a need for novel and more sensive methods in isomer separation, low abundance species detection, and profiling the spatial distribution of glycosphingolipid molecular species in cells and tissues using imaging mass spectrometry.

A high-throughput platform for detailed lipidomic analysis of a range of mouse and human tissues

Lipidomics is of increasing interest in studies of biological systems. However, high-throughput data collection and processing remains non-trivial, making assessment of phenotypes difficult. We describe a platform for surveying the lipid fraction for a range of tissues. These techniques are demonstrated on a set of seven different tissues (serum, brain, heart, kidney, adipose, liver, and vastus lateralis muscle) from post-weaning mouse dams that were either obese (> 12 g fat mass) or lean (<5 g fat mass). This showed that the lipid metabolism in some tissues is affected more by obesity than others. Analysis of human serum (healthy non-pregnant women and pregnant women at 28 weeks' gestation) showed that the abundance of several phospholipids differed between groups. Human placenta from mothers with high and low BMI showed that lean placentae contain less polyunsaturated lipid. This platform offers a way to map lipid metabolism with immediate application in metabolic research and elsewhere. Graphical abstract.