Precursor ion survival energies of protonated N-glycopeptides and their weak dependencies on high mannose N-glycan composition in collision-induced dissociation

Expanding N-glycopeptide identifications by modeling fragmentation, elution, and glycome connectivity

Accurate glycopeptide identification in mass spectrometry-based glycoproteomics is a challenging problem at scale. Recent innovation has been made in increasing the scope and accuracy of glycopeptide identifications, with more precise uncertainty estimates for each part of the structure. We present a dynamically adapting relative retention time model for detecting and correcting ambiguous glycan assignments that are difficult to detect from fragmentation alone, a layered approach to glycopeptide fragmentation modeling that improves N-glycopeptide identification in samples without compromising identification quality, and a site-specific method to increase the depth of the glycoproteome confidently identifiable even further. We demonstrate our techniques on a set of previously published datasets, showing the performance gains at each stage of optimization. These techniques are provided in the open-source glycomics and glycoproteomics platform GlycReSoft available at https://github.com/mobiusklein/glycresoft .

Two-Dimensional Fourier Transform Ion Cyclotron Resonance Mass Spectrometry of N-Linked Glycopeptides

Glycosylation is a common modification across living organisms and plays a central role in understanding biological systems and disease. Our ability to probe the gylcome has grown exponentially in the past several decades. However, further improvements to the analytical toolbox available to researchers would allow for increased capabilities to probe structure and function of biological systems and to improve disease treatment. This article applies the developing technique of two-dimensional Fourier transform ion cyclotron resonance mass spectrometry to a glycoproteomic workflow for the standard glycoproteins coral tree lectin (CTL) and bovine ribonuclease B (BRB) to demonstrate its feasibility as a tool for glycoproteomic workflows. 2D infrared multiphoton dissociation and electron capture dissociation spectra of CTL reveal comparable structural information to their 1D counterparts, confirming the site of glycosylation and monosaccharide composition of the glycan. Spectra collected in 2D of BRB reveal correlation lines of fragment ion scans and vertical precursor ion scans for data collected using infrared multiphoton dissociation and diagonal cleavage lines for data collected by electron capture dissociation. The use of similar techniques for glycoproteomic analysis may prove valuable in instances where chromatographic separation is undesirable or quadrupole isolation is insufficient.

Can We Boost N-Glycopeptide Identification Confidence? Smart Collision Energy Choice Taking into Account Structure and Search Engine

High confidence and reproducibility are still challenges in bottom-up mass spectrometric N-glycopeptide identification. The collision energy used in the MS/MS measurements and the database search engine used to identify the species are perhaps the two most decisive factors. We investigated how the structural features of N-glycopeptides and the choice of the search engine influence the optimal collision energy, delivering the highest identification confidence. We carried out LC-MS/MS measurements using a series of collision energies on a large set of N-glycopeptides with both the glycan and peptide part varied and studied the behavior of Byonic, pGlyco, and GlycoQuest scores. We found that search engines show a range of behavior between peptide-centric and glycan-centric, which manifests itself already in the dependence of optimal collision energy on m/z. Using classical statistical and machine learning methods, we revealed that peptide hydrophobicity, glycan and peptide masses, and the number of mobile protons also have significant and search-engine-dependent influence, as opposed to a series of other parameters we probed. We envisioned an MS/MS workflow making a smart collision energy choice based on online available features such as the hydrophobicity (described by retention time) and glycan mass (potentially available from a scout MS/MS). Our assessment suggests that this workflow can lead to a significant gain (up to 100%) in the identification confidence, particularly for low-scoring hits close to the filtering limit, which has the potential to enhance reproducibility of N-glycopeptide analyses. Data are available via MassIVE (MSV000093110).

Collision energies: Optimization strategies for bottom-up proteomics

Mass-spectrometry coupled to liquid chromatography is an indispensable tool in the field of proteomics. In the last decades, more and more complex and diverse biochemical and biomedical questions have arisen. Problems to be solved involve protein identification, quantitative analysis, screening of low abundance modifications, handling matrix effect, and concentrations differing by orders of magnitude. This led the development of more tailored protocols and problem centered proteomics workflows, including advanced choice of experimental parameters. In the most widespread bottom-up approach, the choice of collision energy in tandem mass spectrometric experiments has outstanding role. This review presents the collision energy optimization strategies in the field of proteomics which can help fully exploit the potential of MS based proteomics techniques. A systematic collection of use case studies is then presented to serve as a starting point for related further scientific work. Finally, this article discusses the issue of comparing results from different studies or obtained on different instruments, and it gives some hints on methodology transfer between laboratories based on measurement of reference species.

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.

Diversity Matters: Optimal Collision Energies for Tandem Mass Spectrometric Analysis of a Large Set of N-Glycopeptides

Identification and characterization of N-glycopeptides from complex samples are usually based on tandem mass spectrometric measurements. Experimental settings, especially the collision energy selection method, fundamentally influence the obtained fragmentation pattern and hence the confidence of the database search results ("score"). Using standards of naturally occurring glycoproteins, we mapped the Byonic and pGlyco search engine scores of almost 200 individual N-glycopeptides as a function of collision energy settings on a quadrupole time of flight instrument. The resulting unprecedented amount of peptide-level information on such a large and diverse set of N-glycopeptides revealed that the peptide sequence heavily influences the energy for the highest score on top of an expected general linear trend with m/z. Search engine dependence may also be noteworthy. Based on the trends, we designed an experimental method and tested it on HeLa, blood plasma, and monoclonal antibody samples. As compared to the literature, these notably lower collision energies in our workflow led to 10-50% more identified N-glycopeptides, with higher scores. We recommend a simple approach based on a small set of reference N-glycopeptides easily accessible from glycoprotein standards to ease the precise determination of optimal methods on other instruments. Data sets can be accessed via the MassIVE repository (MSV000089657 and MSV000090218).

Parallel Determination of Polypeptide and Oligosaccharide Connectivities by Energy-Resolved Collison-Induced Dissociation of Protonated O-Glycopeptides Derived from Nonspecific Proteolysis

Collision-induced dissociation (CID) is by far the most broadly applied dissociation method used for tandem mass spectrometry (MS/MS). This includes MS/MS-based structural interrogation of glycopeptides for applications in glycoproteomics. The end goal of such measurements is to determine the monosaccharide connectivity of the glycan, the amino acid sequence of the peptide, and the site of glycosylation for each glycopeptide of interest. In turn, this allows inferences with respect to the glycoprofile of the intact glycoprotein. For glycopeptide analysis, CID is best known for the ability to determine glycosidic topology of the oligosaccharide group; however, CID has also been shown to produce amide bond cleavage of the polypeptide group. Whether structural information is obtained for the glycan or the peptide has been found to depend on the applied collision energy. While these energy-resolved fragmentation pathways have been the subject of several studies on N-linked glycopeptides, there remains a dearth of similar work on O-linked glycopeptides. In this study, MS/MS via CID was shown to provide substantial peptide backbone fragmentation, in addition to glycosidic fragmentation, in an energy-dependent manner. While qualitatively similar to previous findings for N-glycopeptides, the energy-resolved CID (ER-CID) of O-glycopeptides was found to be substantially more sensitive to the collision energy setting. Thus, deliberately obtaining either glycan or peptide dissociation is a more delicate undertaking for O-glycopeptides. Establishing a more complete understanding of O-glycopeptide ER-CID is likely to have a substantive impact on how O-glycoproteomic analysis is approached in the future.

Composition and charge state influence on the ion-neutral collision cross sections of protonated N-linked glycopeptides: an experimental and theoretical deconstruction of coulombic repulsion vs. charge solvation effects

Ion mobility spectrometry (IMS) is of significant interest as a platform for glycoanalysis. While much attention has been focused on the resolution of isomeric carbohydrates and glycoconjugates, another appealing aspect of IMS is the ability to sort different classes of biomolecules into distinct regions of mass vs. mobility space. This capability has potential to greatly simplify glycoproteomic analyses, as glycosylated and non-glycosylated peptides can be rapidly partitioned in the gas phase. Nevertheless, the physical and chemical characteristics of glycopeptides that dictate their mass vs. mobility loci have yet to be systematically investigated. This report presents an IMS study of model protonated glycopeptide ions with systematically varied oligosaccharide topologies, polypeptide sequences, and charge states. In all, over 110 ion-neutral collision cross sections (CCSs) were measured and analyzed in the context of the physicochemical characteristics of the analytes. Glycan size and composition emerged as a decisive factor in dictating the CCS space occupied by the glycopeptides and exerted this influence in a charge state dependent fashion. Furthermore, elongation of the glycan group was found to either increase or decrease glycopeptide CCSs depending on the ion charge state and the size of the glycan. Molecular dynamics (MD) simulations of the gas phase structures and CCSs of selected glycopeptides revealed that the experimental observations were consistent with a glycan size and charge state dependent interplay between destabilizing coulombic repulsion effects (tending to result in more extended structures) and stabilizing charge solvation effects in which the glycan plays a major role (tending to result in more compact structures). Taken together, these IMS and MD findings suggest the possibility of predicting and delineating glycopeptide-enriched regions of mass vs. mobility space for applications in glycoproteomics.