Resolving Heparan Sulfate Oligosaccharide Positional Isomers Using Hydrophilic Interaction Liquid Chromatography-Cyclic Ion Mobility Mass Spectrometry

Sequencing Sialic Acid Positioning in Gangliosides by High-Resolution Cyclic Ion Mobility Separations Coupled with Multiple Collision-Induced Dissociation-Based Tandem Mass Spectrometry Strategies

Gangliosides, a diverse class of glycosphingolipids, are highly abundant in neural tissue and have been implicated in numerous aging-related diseases. Their characterization with methods such as liquid chromatography-tandem mass spectrometry is often precluded by their structural complexity, isomeric heterogeneity, and lack of commercially available authentic standards. In this work, we coupled high-resolution cyclic ion mobility spectrometry with multiple collision-induced dissociation-based tandem mass spectrometry strategies to sequence the sialic acid positions in various ganglioside isomers. Initially, as a proof-of-concept demonstration, we were able to characterize the sialic acid positions in several GD1 and GT1 species. From there, we extended our approach to identify the location of N-glycolylneuraminic acid (NeuGc) residues in previously uncharacterized GD1 and GQ1 isomers. Our results highlight the potential of this presented methodology for the de novo characterization of gangliosides within complex biological matrices without the need for authentic standards.

Recent advances in high-resolution traveling wave-based ion mobility separations coupled to mass spectrometry

Recently, ion mobility spectrometry-mass spectrometry (IMS-MS) has become more readily incorporated into various omics-based workflows. These growing applications are due to developments in instrumentation within the last decade that have enabled higher-resolution ion mobility separations. Two such platforms are the cyclic (cIMS) and structures for lossless ion manipulations (SLIM), both of which use traveling wave ion mobility spectrometry (TWIMS). High-resolution separations achieved with these techniques stem from the drastically increased pathlengths, on the order of 10 s of meters to >1 km, in both cIMS-MS and SLIM IMS-MS, respectively. Herein, we highlight recent developments and advances, for the period 2019-2023, in high-resolution traveling wave-based IMS-MS through instrumentation, calibration strategies, hyphenated techniques, and applications. Specifically, we will discuss applications including CCS calculations in multipass IMS-MS separations, coupling of IMS-MS with chromatography, imaging, and cryogenic infrared spectroscopy, and isomeric separations of glycans, lipids, and other small metabolites.

Insights into the selectivity of polar stationary phases based on quantitative retention mechanism assessment in hydrophilic interaction chromatography

Hydrophilic interaction chromatography (HILIC) offers different selectivity than reversed-phase liquid chromatography (RPLC). However, our knowledge of the driving force for selectivity is limited and there is a need for a better understanding of the selectivity in HILIC. Quantitative assessment of retention mechanisms makes it possible to investigate selectivity based on understanding the underlying retention mechanisms. In this study, selected model compounds from the Ikegami selectivity tests were evaluated on different polar stationary phases. The study results revealed significant insights into the selectivity in HILIC. First, hydroxy and methylene selectivity is driven by hydrophilic partitioning; but surface adsorption for 2-deoxyuridine or 5-methyluridine reduces the selectivity factor. Furthermore, the retention of 2-deoxyuridine or 5-methyluridine by surface adsorption in combination with the phase ratio explain the difference in hydroxy or methylene selectivity observed among different stationary phases. Investigations on xanthine positional isomers (1-methylxanthine/3-methylxanthine, theophylline/theobromine) indicate that isomeric selectivity is controlled by surface adsorption; however, hydrophilic partitioning may contribute to resolution by enhancing overall retention. In addition, two pairs of nucleoside isomers (adenosine/vidarabine, 2'-deoxy and 3'-deoxyguanosine) provide an example that isomeric selectivity can also be controlled by hydrophilic partitioning if their partitioning coefficients are significantly different in HILIC. Although more data is needed, the current study provides a mechanistic based understanding of the selectivity in HILIC and potentially a new way to design selectivity tests.

Mass spectrometry-based methods to characterize highly heterogeneous biopharmaceuticals, vaccines, and nonbiological complex drugs at the intact-mass level

The intact-mass MS measurements are becoming increasingly popular in characterization of a range of biopolymers, especially those of interest to biopharmaceutical industry. However, as the complexity of protein therapeutics and other macromolecular medicines increases, the new challenges arise, one of which is the high levels of structural heterogeneity that are frequently exhibited by such products. The very notion of the molecular mass measurement loses its clear and intuitive meaning when applied to an extremely heterogenous system that cannot be characterized by a unique mass, but instead requires that a mass distribution be considered. Furthermore, convoluted mass distributions frequently give rise to unresolved ionic signal in mass spectra, from which little-to-none meaningful information can be extracted using standard approaches that work well for homogeneous systems. However, a range of technological advances made in the last decade, such as the hyphenation of intact-mass MS measurements with front-end separations, better integration of ion mobility in MS workflows, development of an impressive arsenal of gas-phase ion chemistry tools to supplement MS methods, as well as the revival of the charge detection MS and its triumphant entry into the field of bioanalysis already made impressive contributions towards addressing the structural heterogeneity challenge. An overview of these techniques is accompanied by critical analysis of the strengths and weaknesses of different approaches, and a brief overview of their applications to specific classes of biopharmaceutical products, vaccines, and nonbiological complex drugs.

Collision Cross Section Prediction Based on Machine Learning

Ion mobility-mass spectrometry (IM-MS) is a powerful separation technique providing an additional dimension of separation to support the enhanced separation and characterization of complex components from the tissue metabolome and medicinal herbs. The integration of machine learning (ML) with IM-MS can overcome the barrier to the lack of reference standards, promoting the creation of a large number of proprietary collision cross section (CCS) databases, which help to achieve the rapid, comprehensive, and accurate characterization of the contained chemical components. In this review, advances in CCS prediction using ML in the past 2 decades are summarized. The advantages of ion mobility-mass spectrometers and the commercially available ion mobility technologies with different principles (e.g., time dispersive, confinement and selective release, and space dispersive) are introduced and compared. The general procedures involved in CCS prediction based on ML (acquisition and optimization of the independent and dependent variables, model construction and evaluation, etc.) are highlighted. In addition, quantum chemistry, molecular dynamics, and CCS theoretical calculations are also described. Finally, the applications of CCS prediction in metabolomics, natural products, foods, and the other research fields are reflected.

Glycosaminoglycans: What Remains To Be Deciphered?

Glycosaminoglycans (GAGs) are complex polysaccharides exhibiting a vast structural diversity and fulfilling various functions mediated by thousands of interactions in the extracellular matrix, at the cell surface, and within the cells where they have been detected in the nucleus. It is known that the chemical groups attached to GAGs and GAG conformations comprise "glycocodes" that are not yet fully deciphered. The molecular context also matters for GAG structures and functions, and the influence of the structure and functions of the proteoglycan core proteins on sulfated GAGs and vice versa warrants further investigation. The lack of dedicated bioinformatic tools for mining GAG data sets contributes to a partial characterization of the structural and functional landscape and interactions of GAGs. These pending issues will benefit from the development of new approaches reviewed here, namely (i) the synthesis of GAG oligosaccharides to build large and diverse GAG libraries, (ii) GAG analysis and sequencing by mass spectrometry (e.g., ion mobility-mass spectrometry), gas-phase infrared spectroscopy, recognition tunnelling nanopores, and molecular modeling to identify bioactive GAG sequences, biophysical methods to investigate binding interfaces, and to expand our knowledge and understanding of glycocodes governing GAG molecular recognition, and (iii) artificial intelligence for in-depth investigation of GAGomic data sets and their integration with proteomics.