Toward Automated Identification of Glycan Branching Patterns Using Multistage Mass Spectrometry with Intelligent Precursor Selection

Protocol for automated N-glycan sequencing using mass spectrometry and computer-assisted intelligent fragmentation

Biological functions of glycans are intimately linked to fine details in branches and linkages, which make structural identification extremely challenging. Here, we present a protocol for automated N-glycan sequencing using multi-stage mass spectrometry (MSn). We describe steps for release/purification and derivation of glycans and procedures for MSn scanning. We then detail "glycan intelligent precursor selection" to computationally guide MSn experiments. The protocol can be used for both discrete individual glycans and isomeric glycan mixtures. For complete details on the use and execution of this protocol, please refer to Sun et al.,1 Huang et al.,2 and Huang et al.3.

Human milk oligosaccharides in milk of mothers with term and preterm delivery at different lactation stage

Human milk oligosaccharides (HMOs) are structurally diverse unconjugated glycans, and play crucial roles in protecting infants from infections. Preterm birth is one of the leading causes of neonatal mortality, and preterm infants are particularly vulnerable and are in need of improved outcomes from breast-feeding due to the presence of bioactive HMOs. However, studies on specific difference in HMOs as a function of gestation time have been very limited. We established an approach to extract and analyze HMOs based on 96-well plate extraction and mass spectrometry, and determined maternal phenotypes through distinctive fragments in product-ion spectra. We enrolled 85 women delivering at different gestation times (25-41 weeks), and observed different HMOs correlating with gestation time based on 233 samples from the 85 donors. With the increase of postpartum age, we observed a regular changing trajectory of HMOs in composition and relative abundance, and found significant differences in HMOs secreted at different postpartum times. Preterm delivery induced more variations between participants with different phenotypes compared with term delivery, and more HMOs varied with postpartum age in the population of secretors. The sialylation level in mature milk decreased for women delivering preterm while such decrease was not observed for women delivering on term.

EMNGly: predicting N-linked glycosylation sites using the language models for feature extraction

MOTIVATION

N-linked glycosylation is a frequently occurring post-translational protein modification that serves critical functions in protein folding, stability, trafficking, and recognition. Its involvement spans across multiple biological processes and alterations to this process can result in various diseases. Therefore, identifying N-linked glycosylation sites is imperative for comprehending the mechanisms and systems underlying glycosylation. Due to the inherent experimental complexities, machine learning and deep learning have become indispensable tools for predicting these sites.

RESULTS

In this context, a new approach called EMNGly has been proposed. The EMNGly approach utilizes pretrained protein language model (Evolutionary Scale Modeling) and pretrained protein structure model (Inverse Folding Model) for features extraction and support vector machine for classification. Ten-fold cross-validation and independent tests show that this approach has outperformed existing techniques. And it achieves Matthews Correlation Coefficient, sensitivity, specificity, and accuracy of 0.8282, 0.9343, 0.8934, and 0.9143, respectively on a benchmark independent test set.

De novo glycan sequencing by electronic excitation dissociation MS2-guided MS3 analysis on an Omnitrap-Orbitrap hybrid instrument

Comprehensive de novo glycan sequencing remains an elusive goal due to the structural diversity and complexity of glycans. Present strategies employing collision-induced dissociation (CID) and higher energy collisional dissociation (HCD)-based multi-stage tandem mass spectrometry (MSⁿ) or MS/MS combined with sequential exoglycosidase digestions are inherently low-throughput and difficult to automate. Compared to CID and HCD, electron transfer dissociation (ETD) and electron capture dissociation (ECD) each generate more cross-ring cleavages informative about linkage positions, but electronic excitation dissociation (EED) exceeds the information content of all other methods and is also applicable to analysis of singly charged precursors. Although EED can provide extensive glycan structural information in a single stage of MS/MS, its performance has largely been limited to FTICR MS, and thus it has not been widely adopted by the glycoscience research community. Here, the effective performance of EED MS/MS was demonstrated on a hybrid Orbitrap-Omnitrap QE-HF instrument, with high sensitivity, fragmentation efficiency, and analysis speed. In addition, a novel EED MS²-guided MS³ approach was developed for detailed glycan structural analysis. Automated topology reconstruction from MS² and MS³ spectra could be achieved with a modified GlycoDeNovo software. We showed that the topology and linkage configurations of the Man₉GlcNAc₂ glycan can be accurately determined from first principles based on one EED MS² and two CID-EED MS³ analyses, without reliance on biological knowledge, a structure database or a spectral library. The presented approach holds great promise for autonomous, comprehensive and de novo glycan sequencing.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2017-2018

This review is the tenth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization mass spectrometry (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2018. Also included are papers that describe methods appropriate to glycan and glycoprotein analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. Topics covered in the first part of the review include general aspects such as theory of the MALDI process, new methods, matrices, derivatization, MALDI imaging, fragmentation and the use of arrays. The second part of the review is devoted to applications to various structural types such as oligo- and poly-saccharides, glycoproteins, glycolipids, glycosides, and biopharmaceuticals. Most of the applications are presented in tabular form. The third part of the review covers medical and industrial applications of the technique, studies of enzyme reactions, and applications to chemical synthesis. The reported work shows increasing use of combined new techniques such as ion mobility and highlights the impact that MALDI imaging is having across a range of diciplines. MALDI is still an ideal technique for carbohydrate analysis and advancements in the technique and the range of applications continue steady progress.

GIPS-Mix for Accurate Identification of Isomeric Components in Glycan Mixtures Using Intelligent Group-Opting Strategy

Accurate identification of glycan structures is highly desirable as they are intimately linked to their different functions. However, glycan samples generally exist as mixtures with multiple isomeric structures, making assignment of individual glycan components very challenging, even with the aid of multistage mass spectrometry (MSⁿ). Here, we present an approach, GIPS-mix, for assignment of isomeric glycans within a mixture using an intelligent group-opting strategy. Our approach enumerates all possible combinations (groupings) of candidate glycans and opts in the best-matched glycan group(s) based on the similarity between the simulated spectra of each glycan group and the acquired experimental spectra of the mixture. In the case that a single group could not be elected, a tie break is performed by additional MSⁿ scanning using intelligently selected precursors. With 11 standard mixtures and 6 human milk oligosaccharide fractions, we demonstrate the application of GIPS-mix in assignment of individual glycans in mixtures with high accuracy and efficiency.

Recent Advances in Mass Spectrometry-Based Structural Elucidation Techniques

Mass spectrometry (MS) has become the central technique that is extensively used for the analysis of molecular structures of unknown compounds in the gas phase. It manipulates the molecules by converting them into ions using various ionization sources. With high-resolution MS, accurate molecular weights (MW) of the intact molecular ions can be measured so that they can be assigned a molecular formula with high confidence. Furthermore, the application of tandem MS has enabled detailed structural characterization by breaking the intact molecular ions and protonated or deprotonated molecules into key fragment ions. This approach is not only used for the structural elucidation of small molecules (MW < 2000 Da), but also crucial biopolymers such as proteins and polypeptides; therefore, MS has been extensively used in multiomics studies for revealing the structures and functions of important biomolecules and their interactions with each other. The high sensitivity of MS has enabled the analysis of low-level analytes in complex matrices. It is also a versatile technique that can be coupled with separation techniques, including chromatography and ion mobility, and many other analytical instruments such as NMR. In this review, we aim to focus on the technical advances of MS-based structural elucidation methods over the past five years, and provide an overview of their applications in complex mixture analysis. We hope this review can be of interest for a wide range of audiences who may not have extensive experience in MS-based techniques.

Development of high-throughput UPLC-MS/MS using multiple reaction monitoring for quantitation of complex human milk oligosaccharides and application to large population survey of secretor status and Lewis blood group

Human milk oligosaccharides (HMOs) have attracted increasing attention due to the emerging evidence of their positive roles for infant's health. A high-throughput method for absolute quantitation of the complex HMOs including multiple isomeric structures is important but very challenging, due to the highly divers nature and wide variation in content of HMOs from different individuals. Here we used UPLC-MS-MRM in the negative-ion mode for accurate quantitation of 23 complex HMOs in just 15 min. The selected oligosaccharides are in their native forms and include neutral and sialylated, fucosylated and non-fucosylated, linear and branched, and secretor and Lewis phenotype indicators. The well validated method with good sensitivity, recovery and reproducibility was then applied to a large population quantitative survey of 251 Chinese mothers from five different ethnic groups (Han, Zhuang, Hui, Mongolian and Tibetan) living in different geographical regions for their secretor's status and Lewis phenotypes.

The effect of N-glycosylation of SARS-CoV-2 spike protein on the virus interaction with the host cell ACE2 receptor

The densely glycosylated spike (S) protein highly exposed on severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) surface mediates host cell entry by binding to the receptor angiotensin-converting enzyme 2 (ACE2). However, the role of glycosylation has not been fully understood. In this study, we investigated the effect of different N-glycosylation of S1 protein on its binding to ACE2. Using real-time surface plasmon resonance assay the negative effects were demonstrated by the considerable increase of binding affinities of de-N-glycosylated S1 proteins produced from three different expression systems including baculovirus-insect, Chinese hamster ovarian and two variants of human embryonic kidney 293 cells. Molecular dynamic simulations of the S1 protein-ACE2 receptor complex revealed the steric hindrance and Coulombic repulsion effects of different types of N-glycans on the S1 protein interaction with ACE2. The results should contribute to future pathological studies of SARS-CoV-2 and therapeutic development of Covid-19, particularly using recombinant S1 proteins as models.

Best-first search guided multistage mass spectrometry-based glycan identification

MOTIVATION

Glycan identification has long been hampered by complicated branching patterns and various isomeric structures of glycans. Multistage mass spectrometry (MSn) is a promising glycan identification technique as it generates multiple-level fragments of a glycan, which can be explored to deduce branching pattern of the glycan and further distinguish it from other candidates with identical mass. However, the automatic glycan identification still remains a challenge since it mainly relies on expertise to guide a MSn instrument to generate spectra.

RESULTS

Here, we proposed a novel method, named bestFSA, based on a best-first search algorithm to guide the process of spectrum producing in glycan identification using MSn. BestFSA is able to select the most appropriate peaks for next round of experiments and complete the identification using as few experimental rounds. Our analysis of seven representative glycans shows that bestFSA correctly distinguishes actual glycans efficiently and suggested bestFSA could be used in practical glycan identification. The combination of the MSn technology coupled with bestFSA should greatly facilitate the automatic identification of glycan branching patterns, with significantly improved identification sensitivity, and reduce time and cost of MSn experiments.

AVAILABILITY AND IMPLEMENTATION

http://glycan.ict.ac.cn.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Simplifying Glycan Profiling through a High-Throughput Micropermethylation Strategy

Glycoproteins play key roles in various molecular and cellular functions and are among the most difficult to analyze biomolecules on account of their microheterogeneity, non-template-driven synthesis, and low abundances. The stability, serum half-life, immunogenicity, and biological activity of therapeutic glycoproteins, including antibodies, vaccines, and biomarkers, are regulated by their glycosylation profile. Thus, there is increasing demand for the qualitative and quantitative characterization and validation of glycosylation on glycoproteins. One of the most important derivatization processes for the structural characterization of released glycans by mass spectrometry (MS) is permethylation. We have recently developed a permethylation strategy in microscale that allows facile permethylation of glycans and permits the processing of large sample sets in nanogram amounts through high-throughput sample handling. Here, we are reporting the wide potential of micropermethylation-based high-throughput structural analysis of glycans from various sources, including human plasma, mammalian cells, and purified glycoproteins, through an automated tandem electrospray ionization-mass spectrometry (ESI-MSn) platform. The glycans released from the plasma, cells, and glycoproteins are permethylated in microscale in a 96-well plate or microcentrifuge tube and isolated by a C18 tip-based cleanup through a shorter and simple process. We have developed a workflow to accomplish an in-depth automated structural characterization MS program for permethylated N/O-glycans through an automated high-throughput multistage tandem MS acquisition. We have demonstrated the utility of this workflow using the examples of sialic acid linkages and bisecting GlcNAc (N-acetylglucosamine) on the glycans. This approach can automate the high-throughput screening of glycosylation on large sample sets of glycoproteins, including clinical glycan biomarkers and glycoprotein therapeutics.

Identification of glycan branching patterns using multistage mass spectrometry with spectra tree analysis

Glycans are crucial to a wide range of biological processes, and their biological activities are closely related to the branching patterns of structures. Different from the simple linear chains of proteins, branching patterns of glycans are more complicated, making their identification extremely challenging. Tandem mass spectrometry (MS²) cannot provide sufficient structural information to deduce glycan branching patterns even with the assistance of various bioinformatic tools and algorithms.The promising technology to identify glycan branching patterns is multi-stage mass spectrometry (MSⁿ). The production-relationship among MSⁿ spectra of a glycan is essentially a tree, making deducing glycan structures from MSⁿ spectra a great challenge. In the present study, we report an approach called glyBranch (glycan Branching pattern identification based on spectra tree) to fully exploit the information contained in the MSⁿ spectra tree for glycan identification. Using 14 glycan standards, including 2 pairs with isomeric sequence, and 16 complex N-glycans isolated from RNase B and IgG, we demonstrated the successful application of glyBranch to branching pattern analysis. The source code of glyBranch is available at https://github.com/bigict/glyBranch/. We have also developed a web-server, which is freely accessible at http://glycan.ict.ac.cn/glyBranch/. SIGNIFICANCE: Glycans are crucial in various biological processes and their functions are closely related to the details of their structures; thus, the identification of glycan branching patterns is of great significance to biological studies. Multistage mass spectrometry (MSⁿ) can provide detailed structural information by generating multiple-level fragments through consecutive fragmentation; however, the interpretation of numerous MSⁿ spectra is extremely challenging. In this study, we present an approach called glyBranch (glycan Branching pattern identification based on spectra tree) to exploit the information contained in MSⁿ spectra tree for glycan identification. This approach will greatly facilitate the automated identification of glycan structures and related biological studies.

Bovine serum albumin affects N-glycoforms of murine IgG monoclonal antibody purified from hybridoma supernatants

Immunoglobulin G (IgG) is a class of monoclonal antibodies (mAbs) commonly produced in mammalian cell lines. These cell lines are grown in finely adjusted culture media, which contain components that may impact glycoforms. As variation of N-glycoforms can impact the biological properties of IgGs, medium composition should be controlled. Here, we studied the effects on IgG N-glycoforms of different components in hybridoma culture media, specifically compared bovine serum albumin (BSA) with other small molecules, using a matrix-assisted laser desorption/ionization quadrupole ion trap time-of-flight multistage mass spectrometry (MALDI-QIT-TOF MSⁿ)-based approach. We show that small molecular additives caused little change in glycan species, though a number of these reagents, especially glutamine, affected levels of glycosylation. In comparison, the addition of macromolecular protein BSA significantly changed IgG N-glycan patterns, not only in species but also in glycosylation levels. Together, our finding suggests that BSA increases the complexity of IgG N-glycoforms, thus raising the difficulty in maintaining glycoforms consistency during antibody production. Therefore, the effect of BSA on IgG N-glycans should be considered when designing optimal medium formulations for IgG production. KEY POINTS: • Small molecular medium additives only affect glycosylation levels of IgG N-glycans. • BSA significantly changes IgG N-glycoforms as a medium additive. • BSA's skewing of IgG N-glycoforms should be considered in IgG production.

Novel methods in glycomics: a 2019 update

Introduction: Glycomics, which aims to define the glycome of a biological system to better assess the biological attributes of the glycans, has attracted increasing interest. However, the complexity and diversity of glycans present challenging barriers to glycome definition. Technological advances are major drivers in glycomics.Areas covered: This review summarizes the main methods and emphasizes the most recent advances in mass spectrometry-based methods regarding glycomics following the general workflow in glycomic analysis.Expert opinion: Recent mass spectrometry-based technological advances have significantly lowered the barriers in glycomics. The field of glycomics is moving toward both generic and precise analysis.

Toward Automatic and Comprehensive Glycan Characterization by Online PGC-LC-EED MS/MS

Despite the recent advances in mass spectrometry (MS)-based methods for glycan structural analysis, characterization of glycomes remains a significant analytical challenge, in part due to the widespread presence of isomeric structures and the need to define the many structural variables for each glycan. Interpretation of the complex tandem mass spectra of glycans is often laborious and requires substantial expertise. Broad adoption of MS methods for glycomics, within and outside the glycoscience community, has been hindered by the shortage of bioinformatics tools for rapid and accurate glycan sequencing. Here, we developed an online porous graphitic carbon liquid chromatography (PGC-LC)-electronic excitation dissociation (EED) MS/MS method that takes advantage of the superior isomer resolving power of PGC and the structural details provided by EED MS/MS for characterization of glycan mixtures. We also made improvements to GlycoDeNovo, our de novo glycan sequencing algorithm, so that it can automatically and accurately identify glycan topologies from EED tandem mass spectra acquired online. The majority of linkages can also be determined de novo, although in some cases, biological insight may be needed to fully define the glycan structure. Application of this method to the analysis of N-glycans released from ribonuclease B not only revealed the presence of 18 high-mannose structures, including new isomers not previously reported, but also provided relative quantification for each isomeric structure. With fully automated data acquisition and topology analysis, the approach presented here holds great potential for automated and comprehensive glycan characterization.

Automation of mass spectrometric detection of analytes and related workflows: A review

The developments in mass spectrometry (MS) in the past few decades reveal the power and versatility of this technology. MS methods are utilized in routine analyses as well as research activities involving a broad range of analytes (elements and molecules) and countless matrices. However, manual MS analysis is gradually becoming a thing of the past. In this article, the available MS automation strategies are critically evaluated. Automation of analytical workflows culminating with MS detection encompasses involvement of automated operations in any of the steps related to sample handling/treatment before MS detection, sample introduction, MS data acquisition, and MS data processing. Automated MS workflows help to overcome the intrinsic limitations of MS methodology regarding reproducibility, throughput, and the expertise required to operate MS instruments. Such workflows often comprise automated off-line and on-line steps such as sampling, extraction, derivatization, and separation. The most common instrumental tools include autosamplers, multi-axis robots, flow injection systems, and lab-on-a-chip. Prototyping customized automated MS systems is a way to introduce non-standard automated features to MS workflows. The review highlights the enabling role of automated MS procedures in various sectors of academic research and industry. Examples include applications of automated MS workflows in bioscience, environmental studies, and exploration of the outer space.

Ti3C2 MXene as a novel substrate provides rapid differentiation and quantitation of glycan isomers with LDI-MS

Here we report Ti₃C₂ MXene assisted LDI-LIFT-TOF/TOF for robust differentiation and relative quantitation of glycan isomers that differ in composition, connectivity and configuration.

Distribution of abnormal IgG glycosylation patterns from rheumatoid arthritis and osteoarthritis patients by MALDI-TOF-MSn

IgG glycosylation differs in rheumatoid arthritis (RA) and osteoarthritis (OA), which should contribute to their pathogenesis research and diagnosis.