Predicting the Retention Behavior of Specific O-Linked Glycopeptides

Peptide retention time prediction for electrostatic repulsion-hydrophilic interaction chromatography

Electrostatic Repulsion-Hydrophilic Interaction Chromatography (ERLIC) is one of the legacy separation tools developed by Dr. Andrew Alpert and has been used for developing unique separation methods of hydrophilic compounds, including peptides. In the past it has been studied using designed peptide libraries to elucidate major features of its separation mechanism, while comprehensive peptide retention modeling for ERLIC is still lacking. In this work we employed a proteomics-derived ∼170,000 peptide retention datasets to evaluate major ERLIC retention features using the framework of our Sequence-Specific Retention Calculator model. The separation conditions were adjusted to obtain a wider proteome coverage, particularly for non-modified peptides, resulting in a superior separation orthogonality for a 2D LC combination with reversed-phase C18 LC-MS in the second dimension. The SSRCalc ERLIC model presents a consistent theme with the existing ERLIC retention mechanism, reflecting a dependence on peptide orientation and the position of charged and hydrophilic residues across the peptide backbone. R2 values of 0.935 and 0.955 accuracy were demonstrated for the standard interpretable SSRCalc model and machine learning algorithm, respectively. The effects of various PTMs on peptide retention were evaluated in this study, covering spontaneous (oxidation, deamidation) and enzymatic (N-terminal acetylation, phosphorylation, glycosylation) modifications.

Inclusion of Porous Graphitic Carbon Chromatography Yields Greater Protein Identification and Compartment and Process Coverage and Enables More Reflective Protein-Level Label-Free Quantitation

The ubiquity of mass spectrometry-based bottom-up proteomic analyses as a component of biological investigation mandates the validation of methodologies that increase acquisition efficiency, improve sample coverage, and enhance profiling depth. Chromatographic separation is often ignored as an area of potential improvement, with most analyses relying on traditional reversed-phase liquid chromatography (RPLC); this consistent reliance on a single chromatographic paradigm fundamentally limits our view of the observable proteome. Herein, we build upon early reports and validate porous graphitic carbon chromatography (PGC) as a facile means to substantially enhance proteomic coverage without changes to sample preparation, instrument configuration, or acquisition methods. Analysis of offline fractionated cell line digests using both separations revealed an increase in peptide and protein identifications by 43% and 24%, respectively. Increased identifications provided more comprehensive coverage of cellular components and biological processes independent of protein abundance, highlighting the substantial quantity of proteomic information that may go undetected in standard analyses. We further utilize these data to reveal that label-free quantitative analyses using RPLC separations alone may not be reflective of actual protein constituency. Together, these data highlight the value and comprehension offered through PGC-MS proteomic analyses. RAW proteomic data have been uploaded to the MassIVE repository with the primary accession code MSV000091495.

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.

Liquid chromatography and capillary electrophoresis in glycomic and glycoproteomic analysis

Glycosylation is one of the most significant and abundant post-translational modifications in cells. Glycomic and glycoproteomic analyses involve the characterization of oligosaccharides (glycans) conjugated to proteins. Glycomic and glycoproteomic analysis is highly challenging because of the large diversity of structures, low abundance, site-specific heterogeneity, and poor ionization efficiency of glycans and glycopeptides in mass spectrometry (MS). MS is a key tool for characterization of glycans and glycopeptides. However, MS alone does not always provide full structural and quantitative information for many reasons, and thus MS is combined with some separation technique. This review focuses on the role of separation techniques used in glycomic and glycoproteomic analyses, liquid chromatography and capillary electrophoresis. The most important separation conditions and results are presented and discussed.

Graphical abstract

Prediction of Intact N-Glycopeptide Retention Time Windows in Hydrophilic Interaction Liquid Chromatography

Analysis of protein glycosylation is challenging due to micro- and macro-heterogeneity of the attached glycans. Hydrophilic interaction liquid chromatography (HILIC) is a mode of choice for separation of intact glycopeptides, which are inadequately resolved by reversed phase chromatography. In this work, we propose an easy-to-use model to predict retention time windows of glycopeptides in HILIC. We constructed this model based on the parameters derived from chromatographic separation of six differently glycosylated peptides obtained from tryptic digests of three plasma proteins: haptoglobin, hemopexin, and sex hormone-binding globulin. We calculated relative retention times of different glycoforms attached to the same peptide to the bi-antennary form and showed that the character of the peptide moiety did not significantly change the relative retention time differences between the glycoforms. To challenge the model, we assessed chromatographic behavior of fetuin glycopeptides experimentally, and their retention times all fell within the calculated retention time windows, which suggests that the retention time window prediction model in HILIC is sufficiently accurate. Relative retention time windows provide complementary information to mass spectrometric data, and we consider them useful for reliable determination of protein glycosylation in a site-specific manner.

Recent advancements in glycoproteomic studies: Glycopeptide enrichment and derivatization, characterization of glycosylation in SARS CoV2, and interacting glycoproteins

Proteomics studies allow for the determination of the identity, amount, and interactions of proteins under specific conditions that allow the biological state of an organism to ultimately change. These conditions can be either beneficial or detrimental. Diseases are due to detrimental changes caused by either protein overexpression or underexpression caused by as a result of a mutation or posttranslational modifications (PTM), among other factors. Identification of disease biomarkers through proteomics can be potentially used as clinical information for diagnostics. Common biomarkers to look for include PTM. For example, aberrant glycosylation of proteins is a common marker and will be a focus of interest in this review. A common way to analyze glycoproteins is by glycoproteomics involving mass spectrometry. Due to factors such as micro- and macroheterogeneity which result in a lower abundance of each version of a glycoprotein, it is difficult to obtain meaningful results unless rigorous sample preparation procedures are in place. Microheterogeneity represents the diversity of glycans at a single site, whereas macroheterogeneity depicts glycosylation levels at each site of a protein. Enrichment and derivatization of glycopeptides help to overcome these limitations. Over the time range of 2016 to 2020, several methods have been proposed in the literature and have contributed to drastically improve the outcome of glycosylation analysis, as presented in the sampling surveyed in this review. As a current topic in 2020, glycoproteins carried by pathogens can also cause disease and this is seen with SARS CoV2, causing the COVID-19 pandemic. This review will discuss glycoproteomic studies of the spike glycoprotein and interacting proteins such as the ACE2 receptor.

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.

Comparison of human IgG glycopeptides separation using mixed-mode hydrophilic interaction/ion-exchange liquid chromatography and reversed-phase mode

Glycoproteomics is a challenging branch of proteomics because of the micro- and macro-heterogeneity of protein glycosylation. Hydrophilic interaction liquid chromatography (HILIC) is an advantageous alternative to reversed-phase chromatography for intact glycopeptide separation prior to their identification by mass spectrometry. Nowadays, several HILIC columns differing in used chemistries are commercially available. However, there is a lack of comparative studies assessing their performance, and thus providing guidance for the selection of an adequate stationary phase for different glycoproteomics applications. Here, we compare three HILIC columns recently developed by Advanced Chromatography Technologies (ACE)- with unfunctionalized (HILIC-A), polyhydroxy functionalized (HILIC-N), and aminopropyl functionalized (HILIC-B) silica- with a C18 reversed-phase column in the separation of human immunoglobulin G glycopeptides. HILIC-A and HILIC-B exhibit mixed-mode separation combining hydrophilic and ion-exchange interactions for analyte retention. Expectably, reversed-phase mode successfully separated clusters of immunoglobulin G1 and immunoglobulin G2 glycopeptides, which differ in amino acid sequence, but was not able to adequately separate different glycoforms of the same peptide. All ACE HILIC columns showed higher separation power for different glycoforms, and we show that each column separates a different group of glycopeptides more effectively than the others. Moreover, HILIC-A and HILIC-N columns separated the isobaric A2G1F1 glycopeptides of immunoglobulin G, and thus showed the potential for the elucidation of the structure of isomeric glycoforms. Furthermore, the possible retention mechanism for the HILIC columns is discussed on the basis of the determined chromatographic parameters.

Fundamental to achieving fast separations with high efficiency: A review of chromatography with superficially porous particles

Types of particles have been fundamental to LC separation technology for many years. Originally, LC columns were packed with large-diameter (>100 μm) calcium carbonate, silica gel, or alumina particles that prohibited fast mobile-phase speeds because of the slow diffusion of sample molecules inside deep pores. During the birth of HPLC in the 1960s, superficially porous particles (SPP, ≥30 μm) were developed as the first high-speed stationary-phase support structures commercialized, which permitted faster mobile-phase flowrates due to the fast movement of sample molecules in/out of the thin shells. These initial SPPs were displaced by smaller totally porous particles (TPP) in the mid-1970s. But SPP history repeated when UHPLC emerged in the 2000s. Stationary-phase support structures made from sub-3-μm SPPs were introduced to chromatographers in 2006. The initial purpose of this modern SPP was to enable chromatographers to achieve fast separations with high efficiency using conventional HPLCs. Later, the introduction of sub-2-μm SPPs with UHPLC instruments pushed the separation speed and efficiency to a very fast zone. This review aims at providing readers a comprehensive and up-to-date view on the advantages of SPP materials over TPPs historically and theoretically from the material science angle.

Comparison of Different HILIC Stationary Phases in the Separation of Hemopexin and Immunoglobulin G Glycopeptides and Their Isomers

Protein glycosylation analysis is challenging due to the structural variety of complex conjugates. However, chromatographically separating glycans attached to tryptic peptides enables their site-specific characterization. For this purpose, we have shown the importance of selecting a suitable hydrophilic interaction liquid chromatography (HILIC) stationary phase in the separation of glycopeptides and their isomers. Three different HILIC stationary phases, i.e., HALO® penta-HILIC, Glycan ethylene bridged hybrid (BEH) Amide, and ZIC-HILIC, were compared in the separation of complex N-glycopeptides of hemopexin and Immunoglobulin G glycoproteins. The retention time increased with the polarity of the glycans attached to the same peptide backbone in all HILIC columns tested in this study, except for the ZIC-HILIC column when adding sialic acid to the glycan moiety, which caused electrostatic repulsion with the negatively charged sulfobetaine functional group, thereby decreasing retention. The HALO® penta-HILIC column provided the best separation results, and the ZIC-HILIC column the worst. Moreover, we showed the potential of these HILIC columns for the isomeric separation of fucosylated and sialylated glycoforms. Therefore, HILIC is a useful tool for the comprehensive characterization of glycoproteins and their isomers.

Peptide retention prediction using hydrophilic interaction liquid chromatography coupled to mass spectrometry

A model that predicts retention for peptides using a HALO® penta-HILIC column and gradient elution was created. Coefficients for each amino acid were derived using linear regression analysis and these coefficients can be summed to predict the retention of peptides. This model has a high correlation between experimental and predicted retention times (0.946), which is on par with previous RP and HILIC models. External validation of the model was performed using a set of H. pylori samples on the same LC-MS system used to create the model, and the deviation from actual to predicted times was low. Apart from amino acid composition, length and location of amino acid residues on a peptide were examined and two site-specific corrections for hydrophobic residues at the N-terminus as well as hydrophobic residues one spot over from the N-terminus were created.