High-Resolution Ion Mobility Separations of Isomeric Glycoforms with Variations on the Peptide and Glycan Levels

Analysis of N- and O-linked site-specific glycosylation by ion mobility mass spectrometry: State of the art and future directions

Glycosylation, the major post-translational modification of proteins, significantly increases the diversity of proteoforms. Glycans are involved in a variety of pivotal structural and functional roles of proteins, and changes in glycosylation are profoundly connected to the progression of numerous diseases. Mass spectrometry (MS) has emerged as the gold standard for glycan and glycopeptide analysis because of its high sensitivity and the wealth of fragmentation information that can be obtained. Various separation techniques have been employed to resolve glycan and glycopeptide isomers at the front end of the MS. However, differentiating structures of isobaric and isomeric glycopeptides constitutes a challenge in MS-based characterization. Many reports described the use of various ion mobility-mass spectrometry (IM-MS) techniques for glycomic analyses. Nevertheless, very few studies have focused on N- and O-linked site-specific glycopeptidomic analysis. Unlike glycomics, glycoproteomics presents a multitude of inherent challenges in microheterogeneity, which are further exacerbated by the lack of dedicated bioinformatics tools. In this review, we cover recent advances made towards the growing field of site-specific glycosylation analysis using IM-MS with a specific emphasis on the MS techniques and capabilities in resolving isomeric peptidoglycan structures. Furthermore, we discuss commonly used software that supports IM-MS data analysis of glycopeptides.

Mass Spectrometry Strategies for O-Glycoproteomics

Glycoproteomics has accelerated in recent decades owing to numerous innovations in the analytical workflow. In particular, new mass spectrometry strategies have contributed to inroads in O-glycoproteomics, a field that lags behind N-glycoproteomics due to several unique challenges associated with the complexity of O-glycosylation. This review will focus on progress in sample preparation, enrichment strategies, and MS/MS techniques for the identification and characterization of O-glycoproteins.

Isomeric Separation of α2,3/α2,6-Linked 2-Aminobenzamide (2AB)-Labeled Sialoglycopeptides by C18-LC-MS/MS

Determination of the relative expression levels of the α2,3/α2,6-sialic acid linkage isomers on glycoproteins is critical to the analysis of various human diseases such as cancer, inflammation, and viral infection. However, it remains a challenge to separate and differentiate site-specific linkage isomers at the glycopeptide level. Some derivatization methods on the carboxyl group of sialic acid have been developed to generate mass differences between linkage isomers. In this study, we utilized chemical derivatization that occurred on the vicinal diol of sialic acid to separate linkage isomers on a reverse-phase column using a relatively short time. 2-Aminobenzamide (2AB) labeling derivatization, including periodate oxidation and reductive amination, took only ∼3 h and achieved high labeling efficiency (>90%). Within a 66 min gradient, the sialic acid linkage isomers of 2AB-labeled glycopeptides from model glycoproteins can be efficiently resolved compared to native glycopeptides. Two different methods, neuraminidase digestion and higher-energy collision dissociation tandem mass spectrometry (HCD-MS2) fragmentation, were utilized to differentiate those isomeric peaks. By calculating the diagnostic oxonium ion ratio of Gal2ABNeuAc and 2ABNeuAc fragments, significant differences in chromatographic retention times and in mass spectral peak abundances were observed between linkage isomers. Their corresponding MS2 PCA plots also helped to elucidate the linkage information. This method was successfully applied to human blood serum. A total of 514 2AB-labeled glycopeptide structures, including 152 sets of isomers, were identified, proving the applicability of this method in linkage-specific structural characterization and relative quantification of sialic acid isomers.

Resolving D-Amino Acid Containing Peptides Using Ion Mobility-Mass Spectrometry: Challenges and Recent Developments

Peptides and proteins having D-amino acids in their sequences are now believed to be widespread among different living organisms. Their significance is attributed to the diverse functions of these molecules, such as having a certain pathological implication or enhancing biological activity. Indeed, some peptide molecules with D-amino acids in their structure have already found their way to clinical use such as the antibacterial gramicidin and the antidiabetic nateglinide. Ion mobility mass spectrometry (IM-MS) added an additional dimension of separation as it depends on ions mobility in the space, which is dependent on their shapes, and the shape depends on the orientation of atoms. Thus, D-amino acids containing peptides (DAACPs) will have different mobility and collision cross-section values than those with L-amino acids. Eventually, this will lead to baseline separation of the two peptides. Additionally, ion mobility can precisely locate the position of D-amino acids by analyzing the difference in the arrival times of the fragment ions. The importance of DAACPs, as well as the difficulties in discovering them, were addressed in this review. Similarly, we emphasized how recent developments in IM-MS have improved their detection and analysis. Consequently, the LC-IM-MS/MS platform appears to be promising in isomeric mixture analysis.

An identification method to distinguish monomeric sugar isomers on glycopeptides

A one-step protocol for the automated flow synthesis of protected glycosylated amino acids is described using pumps with open-source controls in overall yields of 21-50%. The resulting glycosylated amino acids could be used directly in solid-phase peptide synthesis (SPPS) protocols to quickly produce glycopeptide standards. Access to a variety of stereoisomers of the sugar enabled the development of an LC-MS/MS protocol that can distinguish between peptides modified with carbohydrates having the same exact mass. This method could definitively identify fucose in an O-glycosylation site on the transmembrane protein, Notch1.

General Method to Obtain Collision Cross-Section Values in Multipass High-Resolution Cyclic Ion Mobility Separations

In recent years, ion mobility spectrometry-mass spectrometry (IMS-MS) has advanced the field of omics-based research, especially with the development of high-resolution platforms; however, these separations have generally been qualitative in nature. The rotationally averaged ion neutral collision cross section (CCS) is one of the only quantitative metrics available for aiding in characterizing biomolecules in IMS-MS. However, determining the CCS of an ion for multipass IMS systems, such as in cyclic ion mobility-mass spectrometry (cIMS-MS) and structures for lossless ion manipulations, has been challenging due to the lack of methods available for calculating CCS when more than a single pass is required for separation as well as the laborious nature of requiring calibrants and unknown compounds to be subjected to identical number of passes, which may not be possible in certain instances because of peak splitting, high levels of diffusion, etc. Herein, we present a general method that uses average ion velocities for calculating CCS values in cIMS-MS-based separations. Initially, we developed calibration curves using common CCS calibrants [i.e., tetra-alkylammonium salts, polyalanine, and hexakis(fluoroalkoxy)phosphazines] at different traveling wave (TW) conditions and the calculated cIMS CCS values were within ∼1% error or less compared to previously established drift tube IMS CCS measurements. Since it has been established that glycans can split into their α/β anomers, we utilized this method for two glycan species, 2α-mannobiose and melibiose. Both glycans were analyzed at the same TW conditions as the calibrants, and we observed anomer splitting at pathlengths of 20 m for 2α-mannobiose and 40 m for melibiose and thus assigned two unique CCS values for each glycan, which is the first time this has ever been done. We have demonstrated that the use of average ion velocities is a robust approach for obtaining CCS values with good agreement to CCS measurements from the previous literature and anticipate that this methodology can be applied to any IMS-MS platform that utilizes multipass separations. Our future work aims to incorporate this methodology for the development of a high-resolution CCS database to aid in the characterization of human milk oligosaccharides.

Critical considerations in N-glycoproteomics

N-Glycoproteomics, the system-wide study of glycans asparagine-linked to protein carriers, holds a unique and still largely untapped potential to provide deep insights into the complexity and dynamics of the heterogeneous N-glycoproteome. Despite the advent of innovative analytical and informatics tools aiding the analysis, N-glycoproteomics remains challenging and consequently largely restricted to specialised laboratories. Aiming to stimulate discussions of method harmonisation, data standardisation and reporting guidelines to make N-glycoproteomics more reproducible and accessible to the community, we here discuss critical considerations related to the design and execution of N-glycoproteomics experiments and highlight good practices in N-glycopeptide data collection, analysis, interpretation and sharing. Giving the rapid maturation and, expectedly, a wide-spread implementation of N-glycoproteomics capabilities across the community in future years, this piece aims to point out common pitfalls, to encourage good data sharing and documentation practices, and to highlight practical solutions and strategies to enhance the insight into the N-glycoproteome.

MS-based glycomics and glycoproteomics methods enabling isomeric characterization

Glycosylation is one of the most significant and abundant posttranslational modifications in mammalian cells. It mediates a wide range of biofunctions, including cell adhesion, cell communication, immune cell trafficking, and protein stability. Also, aberrant glycosylation has been associated with various diseases such as diabetes, Alzheimer's disease, inflammation, immune deficiencies, congenital disorders, and cancers. The alterations in the distributions of glycan and glycopeptide isomers are involved in the development and progression of several human diseases. However, the microheterogeneity of glycosylation brings a great challenge to glycomic and glycoproteomic analysis, including the characterization of isomers. Over several decades, different methods and approaches have been developed to facilitate the characterization of glycan and glycopeptide isomers. Mass spectrometry (MS) has been a powerful tool utilized for glycomic and glycoproteomic isomeric analysis due to its high sensitivity and rich structural information using different fragmentation techniques. However, a comprehensive characterization of glycan and glycopeptide isomers remains a challenge when utilizing MS alone. Therefore, various separation methods, including liquid chromatography, capillary electrophoresis, and ion mobility, were developed to resolve glycan and glycopeptide isomers before MS. These separation techniques were coupled to MS for a better identification and quantitation of glycan and glycopeptide isomers. Additionally, bioinformatic tools are essential for the automated processing of glycan and glycopeptide isomeric data to facilitate isomeric studies in biological cohorts. Here in this review, we discuss commonly employed MS-based techniques, separation hyphenated MS methods, and software, facilitating the separation, identification, and quantitation of glycan and glycopeptide isomers.

Glycoproteomic Analyses of Influenza A Viruses Using timsTOF Pro MS

N-Linked glycosylation in hemagglutinin and neuraminidase glycoproteins of influenza viruses affects antigenic and receptor binding properties, and precise analyses of site-specific glycoforms in these proteins are critical in understanding the antigenic and immunogenic properties of influenza viruses. In this study, we developed a glycoproteomic approach by using a timsTOF Pro mass spectrometer (MS) to determine the abundance and heterogeneity of site-specific glycosylation for influenza glycoproteins. Compared with a Q Exactive HF MS, the timsTOF Pro MS method without the hydrophilic interaction liquid chromatography column enrichment achieved similar glycopeptide coverage and quantities but was more effective in identifying low-abundance glycopeptides. We quantified the distributions of intact site-specific glycopeptides in hemagglutinin of A/chicken/Wuxi/0405005/2013 (H7N9) and A/mute swan/Rhode Island/A00325125/2008 (H7N3). Results showed that hemagglutinin for both viruses had complex N-glycans at N22, N38, N240, and N483 but only high-mannose glycans at N411 and, however, that the type and quantities of glycans were distinct between these viruses. Collisional cross section (CCS) provided by the ion mobility spectrometry from the timsTOF Pro MS data differentiated sialylation linkages of the glycopeptides. In summary, timsTOF Pro MS method can quantify intact site-specific glycans for influenza glycoproteins without enrichment and thus facilitate influenza vaccine development and production.

Multidimensional separation and analysis of alpha-1-acid glycoprotein N-glycopeptides using high-field asymmetric waveform ion mobility spectrometry (FAIMS) and nano-liquid chromatography tandem mass spectrometry

Bottom-up nLC-MS/MS-based glycoprotein mass spectrometry workflows rely on the generation of a mixture of non-glycosylated and glycosylated peptides via proteolysis of glycoproteins. Such methods are challenged by suppression of hydrophilic glycopeptide ions by more abundant, hydrophobic, and readily ionizable non-glycosylated peptides. Commercially available high-field asymmetric waveform ion mobility spectrometry (FAIMS) devices have recently been introduced and present a potential benefit for glycoproteomic workflows by enabling orthogonal separation of non-glycosylated peptides and glycopeptides following chromatographic separation, and prior to MS/MS analysis. However, knowledge is lacking regarding optimal FAIMS conditions for glycopeptide analyses. Here, we document optimal FAIMS compensation voltages for the transmission and analysis of human alpha-1-acid glycoprotein (AGP) tryptic N-glycopeptide ions. Further, we evaluate the effect of FAIMS on AGP glycopeptide assignment confidence by comparing the number of assigned glycopeptides at different confidence levels using a standard nLC-MS/MS method or an otherwise identical method employing FAIMS. Optimized methods will potentiate glycoproteomic analyses by increasing the number of unique glycopeptide identifications and the confidence of glycopeptide assignments. Data are available via ProteomeXchange with identifier PXD036667. Analysis of alpha-1-acid glycoprotein (AGP) tryptic digests via nLC-FAIMS-MS/MS (top) led to the establishment of ideal FAIMS voltages for the analysis of AGP N-glycopeptides (bottom), suggesting that FAIMS can improve the depth of glycoproteome characterization. Pairs of CV magnitudes are shown along the x-axis.

MS-based glycomics: An analytical tool to assess nervous system diseases

Neurological diseases affect millions of peopleochemistryorldwide and are continuously increasing due to the globe's aging population. Such diseases affect the nervous system and are characterized by a progressive decline in brain function and progressive cognitive impairment, decreasing the quality of life for those with the disease as well as for their families and loved ones. The increased burden of nervous system diseases demands a deeper insight into the biomolecular mechanisms at work during disease development in order to improve clinical diagnosis and drug design. Recently, evidence has related glycosylation to nervous system diseases. Glycosylation is a vital post-translational modification that mediates many biological functions, and aberrant glycosylation has been associated with a variety of diseases. Thus, the investigation of glycosylation in neurological diseases could provide novel biomarkers and information for disease pathology. During the last decades, many techniques have been developed for facilitation of reliable and efficient glycomic analysis. Among these, mass spectrometry (MS) is considered the most powerful tool for glycan analysis due to its high resolution, high sensitivity, and the ability to acquire adequate structural information for glycan identification. Along with MS, a variety of approaches and strategies are employed to enhance the MS-based identification and quantitation of glycans in neurological samples. Here, we review the advanced glycomic tools used in nervous system disease studies, including separation techniques prior to MS, fragmentation techniques in MS, and corresponding strategies. The glycan markers in common clinical nervous system diseases discovered by utilizing such MS-based glycomic tools are also summarized and discussed.

Methods to improve quantitative glycoprotein coverage from bottom-up LC-MS data

Advances in mass spectrometry instrumentation, methods development, and bioinformatics have greatly improved the ease and accuracy of site-specific, quantitative glycoproteomics analysis. Data-dependent acquisition is the most popular method for identification and quantification of glycopeptides; however, complete coverage of glycosylation site glycoforms remains elusive with this method. Targeted acquisition methods improve the precision and accuracy of quantification, but at the cost of throughput and discoverability. Data-independent acquisition (DIA) holds great promise for more complete and highly quantitative site-specific glycoproteomics analysis, while maintaining the ability to discover novel glycopeptides without prior knowledge. We review additional features that can be used to increase selectivity and coverage to the DIA workflow: retention time modeling, which would simplify the interpretation of complex tandem mass spectra, and ion mobility separation, which would maximize the sampling of all precursors at a giving chromatographic retention time. The instrumentation and bioinformatics to incorporate these features into glycoproteomics analysis exist. These improvements in quantitative, site-specific analysis will enable researchers to assess glycosylation similarity in related biological systems, answering new questions about the interplay between glycosylation state and biological function.

Complementary proteome and glycoproteome access revealed through comparative analysis of reversed phase and porous graphitic carbon chromatography

Continual developments in instrumental and analytical techniques have aided in establishing rigorous connections between protein glycosylation and human illness. These illnesses, such as various forms of cancer, are often associated with poor prognoses, prompting the need for more comprehensive characterization of the glycoproteome. While innovative instrumental and computational strategies have largely benefited glycoproteomic analyses, less attention is given to benefits gained through alternative, optimized chromatographic techniques. Porous graphitic carbon (PGC) chromatography has gained considerable interest in glycomics research due to its mobile phase flexibility, increased retention of polar analytes, and improved structural elucidation at higher temperatures. PGC has yet to be systematically compared against or in tandem with standard reversed phase liquid chromatography (RPLC) in high-throughput bottom-up glycoproteomic experiments, leaving the potential benefits unexplored. Performing comparative analysis of single and biphasic separation regimes at a range of column temperatures illustrates complementary advantages for each method. PGC separation is shown to selectively retain shorter, more hydrophilic glycopeptide species, imparting higher average charge, and exhibiting greater microheterogeneity coverage for identified glycosites. Additionally, we demonstrate that liquid-phase separation of glycopeptide isomers may be achieved through both single and biphasic PGC separations, providing a means towards facile, multidimensional glycopeptide characterization. Beyond this, we demonstrate how utilization of multiple separation regimes and column temperatures can aid in profiling the glycoproteome in tumorigenic and aggressive prostate cancer cells. RAW MS proteomic and glycoproteomic datasets have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD024196 (10.6019/PXD024196) and PXD024195, respectively.

Current strategies for characterization of mucin-domain glycoproteins

Glycosylation, and especially O-linked glycosylation, remains a critical blind spot in the understanding of post-translational modifications. Due to their nature as proteins defined by a large density and abundance of O-glycosylation, mucins present extra challenges in the analysis of their structure and function. However, recent breakthroughs in multiple areas of research have rendered mucin-domain glycoproteins more accessible to current characterization techniques. In particular, the adaptation of mucinases to glycoproteomic workflows, the manipulation of cellular glycosylation pathways, and the advances in synthetic methods to more closely mimic mucin domains have introduced new and exciting avenues to study mucin glycoproteins. Here, we summarize recent developments in understanding the structure and biological function of mucin domains and their associated glycans, from glycoproteomic tools and visualization methods to synthetic glycopeptide mimetics.

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.

Measuring change in glycoprotein structure

Biosynthetic enzymes in the secretory pathway create distributions of glycans at each glycosite that elaborate the biophysical properties and biological functions of glycoproteins. Because the biosynthetic glycosylation reactions do not go to completion, each protein glycosite is heterogeneous with respect to glycosylation. This heterogeneity means that it is not sufficient to measure protein abundance in omics experiments. Rather, it is necessary to sample the distribution of glycosylation at each glycosite to quantify the changes that occur during biological processes. On the one hand, the use of data-dependent acquisition methods to sample glycopeptides is limited by the instrument duty cycle and the missing value problem. On the other, stepped window data-independent acquisition samples all precursors, but ion abundances are limited by duty cycle. Therefore, the ability to quantify accurately the flux in glycoprotein glycosylation that occurs during biological processes requires the exploitation of emerging mass spectrometry technologies capable of deep, comprehensive sampling and selective high confidence assignment of the complex glycopeptide mixtures. This review summarizes recent technical advances and mass spectral glycoproteomics analysis strategies and how these developments impact our ability to quantify the changes in glycosylation that occur during biological processes. We highlight specific improvements to glycopeptide characterization through activated electron dissociation, ion mobility trends and instrumentation, and efficient algorithmic approaches for glycopeptide assignment. We also discuss the emerging need for unified standards to enable interlaboratory collaborations and effective monitoring of structural changes in glycoproteins.

Microflow Liquid Chromatography Coupled to Mass Spectrometry (μLC-MS) Workflow for O-Glycopeptides Isomers Analysis Combining Differential Mobility Spectrometry and Collision Induced and Electron Capture Dissociation

Peptide and protein O-glycosylation can occur mostly on any serine or threonine and could generate several positional isomers, which may coelute during liquid chromatography (LC) separation, challenging their characterization. Ion mobility has emerged as a technique of interest to separate isomeric compounds. In the different ion mobility techniques, differential ion mobility (DMS) includes the particular interest to tune ion separation by the possible addition of an organic modifier. Different microflow liquid chromatography coupled to mass spectrometry (μLC-MS) workflows were investigated for the analysis of a set of four model peptides made of three isomeric glycopeptides and a corresponding nonglycosylated peptide using differential mobility spectrometry (DMS), collision induced dissociation (CID), and electron capture dissociation (ECD). Neither DMS nor LC provided sufficient separation of the three isomeric O-glycopeptides while the nonmodified one was clearly separated by LC. The hyphenation of LC with DMS led to differentiating the three glycopeptides, and further detection and characterization (ECD/CID) with a chimeric collision cell were achieved in a single LC run. The position of the modification was determined from ECD data, while CID data characterized the sugar through its distinctive oxoniums ions in the low mass range.

Leveraging Parameter Dependencies in High-Field Asymmetric Waveform Ion-Mobility Spectrometry and Size Exclusion Chromatography for Proteome-wide Cross-Linking Mass Spectrometry

Ion-mobility spectrometry shows great promise to tackle analytically challenging research questions by adding another separation dimension to liquid chromatography-mass spectrometry. The understanding of how analyte properties influence ion mobility has increased through recent studies, but no clear rationale for the design of customized experimental settings has emerged. Here, we leverage machine learning to deepen our understanding of field asymmetric waveform ion-mobility spectrometry for the analysis of cross-linked peptides. Knowing that predominantly m/z and then the size and charge state of an analyte influence the separation, we found ideal compensation voltages correlating with the size exclusion chromatography fraction number. The effect of this relationship on the analytical depth can be substantial as exploiting it allowed us to almost double unique residue pair detections in a proteome-wide cross-linking experiment. Other applications involving liquid- and gas-phase separation may also benefit from considering such parameter dependencies.

Improved First-Principles Model of Differential Mobility Using Higher Order Two-Temperature Theory

Differential mobility spectrometry is a separation technique that may be applied to a variety of analytes ranging from small molecule drugs to peptides and proteins. Although rudimentary theoretical models of differential mobility exist, these models are often only applied to small molecules and atomic ions without considering the effects of dynamic microsolvation. Here, we advance our theoretical description of differential ion mobility in pure N₂ and microsolvating environments by incorporating higher order corrections to two-temperature theory (2TT) and a pseudoequilibrium approach to describe ion-neutral interactions. When comparing theoretical predictions to experimentally measured dispersion plots of over 300 different compounds, we find that higher order corrections to 2TT reduce errors by roughly a factor of 2 when compared to first order. Model predictions are accurate especially for pure N₂ environments (mean absolute error of 4 V at SV = 4000 V). For strongly clustering environments, accurate thermochemical corrections for ion-solvent clustering are likely required to reliably predict differential ion mobility behavior. Within our model, general trends associated with clustering strength, solvent vapor concentration, and background gas temperature are well reproduced, and fine structure visible in some dispersion plots is captured. These results provide insight into the dynamic ion-solvent clustering process that underpins the phenomenon of differential ion mobility.

Mucinomics as the Next Frontier of Mass Spectrometry

Mucin-domain glycoproteins comprise a class of proteins whose densely O-glycosylated mucin domains adopt a secondary structure with unique biophysical and biochemical properties. The canonical family of mucins is well-known to be involved in various diseases, especially cancer. Despite this, very little is known about the site-specific molecular structures and biological activities of mucins, in part because they are extremely challenging to study by mass spectrometry (MS). Here, we summarize recent advancements toward this goal, with a particular focus on mucin-domain glycoproteins as opposed to general O-glycoproteins. We summarize proteolytic digestion techniques, enrichment strategies, MS fragmentation, and intact analysis, as well as new bioinformatic platforms. In particular, we highlight mucin directed technologies such as mucin-selective proteases, tunable mucin platforms, and a mucinomics strategy to enrich mucin-domain glycoproteins from complex samples. Finally, we provide examples of targeted mucin-domain glycoproteomics that combine these techniques in comprehensive site-specific analyses of proteins. Overall, this Review summarizes the methods, challenges, and new opportunities associated with studying enigmatic mucin domains.

Investigating the Structure of α/β Carbohydrate Linkage Isomers as a Function of Group I Metal Adduction and Degree of Polymerization as Revealed by Cyclic Ion Mobility Separations

In high-resolution ion mobility spectrometry-mass spectrometry (IMS-MS)-based separations individual, pure, oligosaccharide species often produce multiple IMS peaks presumably from their α/β anomers, cation attachment site conformations, and/or other energetically favorable structures. Herein, the use of high-resolution traveling wave-based cyclic IMS-MS to systematically investigate the origin of these multiple peaks by analyzing α1,4- and β1,4-linked d-glucose homopolymers as a function of their group I metal adducts is presented. Across varying degrees of polymerization, and for certain metal adducts, at least two major IMS peaks with relative areas that matched the ∼40:60 ratio for the α/β anomers of a reducing-end d-glucose as previously calculated by NMR were observed. To further validate that these were indeed the α/β anomers, rather than other substructures, the reduced versions of several maltooligosaccharides were analyzed and all produced a single IMS peak. This result enabled the discovery of a mobility fingerprint trend: the β anomer was always higher mobility than the α anomer for the cellooligosaccharides, while the α anomer was always higher mobility than the β anomer for the maltooligosaccharides. For maltohexaose, a spurious, high mobility, fourth peak was present. This was hypothesized to potentially be from a highly compacted conformation. To investigate this, α-cyclodextrin, a cyclic oligosaccharide, produced similar arrival times as the high mobility maltohexaose peak. It is anticipated that these findings will aid in the data deconvolution of IMS-MS-based glycomics workflows and enable the improved characterization of biologically relevant carbohydrates.

Advances in mass spectrometry-based glycoproteomics: An update covering the period 2017-2021

Protein glycosylation is one of the most common posttranslational modifications, and plays an essential role in a wide range of biological processes such as immune response, intercellular signaling, inflammation, host-pathogen interaction, and protein stability. Glycoproteomics is a proteomics subfield dedicated to identifying and characterizing the glycans and glycoproteins in a given cell or tissue. Aberrant glycosylation has been associated with various diseases such as Alzheimer's disease, viral infections, inflammation, immune deficiencies, congenital disorders, and cancers. However, glycoproteomic analysis remains challenging because of the low abundance, site-specific heterogeneity, and poor ionization efficiency of glycopeptides during LC-MS analyses. Therefore, the development of sensitive and accurate approaches to efficiently characterize protein glycosylation is crucial. Methods such as metabolic labeling, enrichment, and derivatization of glycopeptides, coupled with different mass spectrometry techniques and bioinformatics tools, have been developed to achieve sophisticated levels of quantitative and qualitative analyses of glycoproteins. This review attempts to update the recent developments in the field of glycoproteomics reported between 2017 and 2021.

Putting the pieces together: mapping the O-glycoproteome

Protein glycosylation is the most diverse and omnipresent protein modification. Glycosylation provides glycoproteins with important structural and functional properties to facilitate critical biological processes. Despite the significance of protein glycosylation, the investigation of glycoproteome, especially O-linked glycoproteome, remains elusive due to the lack of a comprehensive methodology to conform with the diversity of O-linked glycoforms of O-linked glycoproteins. In recent years, mass spectrometry has become an indispensable tool for the characterization of O-linked glycosylated proteins across biological systems. We herein highlight the recent developments in MS-based O-linked glycoproteomic technologies, quantitative data acquisition strategy and bioinformatic tools, with a special focus on mucin-type O-linked glycosylation.

The Hitchhiker's guide to glycoproteomics

Protein glycosylation is one of the most common post-translational modifications that are essential for cell function across all domains of life. Changes in glycosylation are considered a hallmark of many diseases, thus making glycoproteins important diagnostic and prognostic biomarker candidates and therapeutic targets. Glycoproteomics, the study of glycans and their carrier proteins in a system-wide context, is becoming a powerful tool in glycobiology that enables the functional analysis of protein glycosylation. This 'Hitchhiker's guide to glycoproteomics' is intended as a starting point for anyone who wants to explore the emerging world of glycoproteomics. The review moves from the techniques that have been developed for the characterisation of single glycoproteins to technologies that may be used for a successful complex glycoproteome characterisation. Examples of the variety of approaches, methodologies, and technologies currently used in the field are given. This review introduces the common strategies to capture glycoprotein-specific and system-wide glycoproteome data from tissues, body fluids, or cells, and a perspective on how integration into a multi-omics workflow enables a deep identification and characterisation of glycoproteins - a class of biomolecules essential in regulating cell function.

Predicting differential ion mobility behaviour in silico using machine learning

Although there has been a surge in popularity of differential mobility spectrometry (DMS) within analytical workflows, determining separation conditions within the DMS parameter space still requires manual optimization. A means of accurately predicting differential ion mobility would benefit practitioners by significantly reducing the time associated with method development. Here, we report a machine learning (ML) approach that predicts dispersion curves in an N2 environment, which are the compensation voltages (CVs) required for optimal ion transmission across a range of separation voltages (SVs) between 1500 to 4000 V. After training a random-forest based model using the DMS information of 409 cationic analytes, dispersion curves were reproduced with a mean absolute error (MAE) of ≤ 2.4 V, approaching typical experimental peak FWHMs of ±1.5 V. The predictive ML model was trained using only m/z and ion-neutral collision cross section (CCS) as inputs, both of which can be obtained from experimental databases before being extensively validated. By updating the model via inclusion of two CV datapoints at lower SVs (1500 V and 2000 V) accuracy was further improved to MAE ≤ 1.2 V. This improvement stems from the ability of the "guided" ML routine to accurately capture Type A and B behaviour, which was exhibited by only 2% and 17% of ions, respectively, within the dataset. Dispersion curve predictions of the database's most common Type C ions (81%) using the unguided and guided approaches exhibited average errors of 0.6 V and 0.1 V, respectively.

Towards structure-focused glycoproteomics

Facilitated by advances in the separation sciences, mass spectrometry and informatics, glycoproteomics, the analysis of intact glycopeptides at scale, has recently matured enabling new insights into the complex glycoproteome. While diverse quantitative glycoproteomics strategies capable of mapping monosaccharide compositions of N- and O-linked glycans to discrete sites of proteins within complex biological mixtures with considerable sensitivity, quantitative accuracy and coverage have become available, developments supporting the advancement of structure-focused glycoproteomics, a recognised frontier in the field, have emerged. Technologies capable of providing site-specific information of the glycan fine structures in a glycoproteome-wide context are indeed necessary to address many pending questions in glycobiology. In this review, we firstly survey the latest glycoproteomics studies published in 2018–2020, their approaches and their findings, and then summarise important technological innovations in structure-focused glycoproteomics. Our review illustrates that while the O-glycoproteome remains comparably under-explored despite the emergence of new O-glycan-selective mucinases and other innovative tools aiding O-glycoproteome profiling, quantitative glycoproteomics is increasingly used to profile the N-glycoproteome to tackle diverse biological questions. Excitingly, new strategies compatible with structure-focused glycoproteomics including novel chemoenzymatic labelling, enrichment, separation, and mass spectrometry-based detection methods are rapidly emerging revealing glycan fine structural details including bisecting GlcNAcylation, core and antenna fucosylation, and sialyl-linkage information with protein site resolution. Glycoproteomics has clearly become a mainstay within the glycosciences that continues to reach a broader community. It transpires that structure-focused glycoproteomics holds a considerable potential to aid our understanding of systems glycobiology and unlock secrets of the glycoproteome in the immediate future.

A Pragmatic Guide to Enrichment Strategies for Mass Spectrometry-Based Glycoproteomics

Glycosylation is a prevalent, yet heterogeneous modification with a broad range of implications in molecular biology. This heterogeneity precludes enrichment strategies that can be universally beneficial for all glycan classes. Thus, choice of enrichment strategy has profound implications on experimental outcomes. Here we review common enrichment strategies used in modern mass spectrometry-based glycoproteomic experiments, including lectins and other affinity chromatographies, hydrophilic interaction chromatography and its derivatives, porous graphitic carbon, reversible and irreversible chemical coupling strategies, and chemical biology tools that often leverage bioorthogonal handles. Interest in glycoproteomics continues to surge as mass spectrometry instrumentation and software improve, so this review aims to help equip researchers with the necessary information to choose appropriate enrichment strategies that best complement these efforts.

What Are We Missing by Using Hydrophilic Enrichment? Improving Bacterial Glycoproteome Coverage Using Total Proteome and FAIMS Analyses

Hydrophilic interaction liquid chromatography (HILIC) glycopeptide enrichment is an indispensable tool for the high-throughput characterization of glycoproteomes. Despite its utility, HILIC enrichment is associated with a number of shortcomings, including requiring large amounts of starting materials, potentially introducing chemical artifacts such as formylation when high concentrations of formic acid are used, and biasing/undersampling specific classes of glycopeptides. Here, we investigate HILIC enrichment-independent approaches for the study of bacterial glycoproteomes. Using three Burkholderia species (Burkholderia cenocepacia, Burkholderia Dolosa, and Burkholderia ubonensis), we demonstrate that short aliphatic O-linked glycopeptides are typically absent from HILIC enrichments, yet are readily identified in whole proteome samples. Using high-field asymmetric waveform ion mobility spectrometry (FAIMS) fractionation, we show that at high compensation voltages (CVs), short aliphatic glycopeptides can be enriched from complex samples, providing an alternative means to identify glycopeptide recalcitrant to hydrophilic-based enrichment. Combining whole proteome and FAIMS analyses, we show that the observable glycoproteome of these Burkholderia species is at least 25% larger than what was initially thought. Excitingly, the ability to enrich glycopeptides using FAIMS appears generally applicable, with the N-linked glycopeptides of Campylobacter fetus subsp. fetus also being enrichable at high FAIMS CVs. Taken together, these results demonstrate that FAIMS provides an alternative means to access glycopeptides and is a valuable tool for glycoproteomic analysis.