Comparison of DDA, scanning window DIA, and HDMSE for assigning and quantifying glycopeptides

Amino acid substitutions to viral proteins can create or remove glycosites. While research groups have published assignment of viral protein glycosylation, there remains little consensus regarding how to quantify the glycosylation changes that occur among viral variants. This is because glycosylation is inherently micro-and macro-heterogeneous, making rigorous comparison of the complete glycosylated structures of viral proteins a statistical problem. In response, we have compared glycoproteomics data acquisition and bioinformatics methods for producing confident measurements of glycosylation similarity. We compared glycoproteomics assignments and quantification from data acquired with data-dependent acquisition (DDA), scanning window data-independent acquisition (swDIA), and broad mass range data-independent acquisition coupled with ion mobility spectrometry (HDMSE), respectively. We compared DDA, swDIA, and HDMSE mass spectral data to assign and quantify (i) the five N-linked glycosylation sites of the glycoprotein standard alpha-1-acid glycoprotein (AGP), (ii) the 12 sites of an influenza A virus hemagglutinin (HA) and (iii) the 22 sites of SARS-CoV-2 spike protein. For all three proteins, we observed that swDIA provided greater depth of coverage for glycopeptide precursor ions compared with DDA. The performance improvement of swDIA was mitigated to a degree by the difficulty of assigning low abundance precursor ions confidently. For this reason, we compared the performance of HDMSE data acquired using the Waters Cyclic IMS instrument, for which there is no precursor isolation step and no need for scanned quadrupole windows. The Cyclic IMS instrument alternated scans corresponding to low and high collision energy in a collision cell located after the mobility chamber. The resulting collision energy aligned retention time curves contained no missing data.Wedeveloped a glycopeptide-aware deconvolution approach to assign the HDMSE data accurately. For this, we connected precursors and product ions according to the combined retention time (RT) and ion mobility (IM) profiles. Using this approach, we demonstrated that HDMSE improved the coverage of glycopeptides over swDIA and DDA.

Gain-of-glycosylation in breast multi-drug-resistant MCF-7 adenocarcinoma cells and cancer stem cells characterized by site- and structure-specific N-glycoproteomics.

N-linked glycosylation (N-glycosylation) is a common protein post-translational modification, occurring on more than half of mammalian proteins; in striking contract with small molecule modifications (such as methylation, phosphorylation) with only single structures, N-glycosylation has multiple dimensional structural features (monosaccharide composition, sequence, linkage, anomer), which generates enormous N-glycan structures; and these structures widely regulate protein structure and functions. For the modification site, N-glycosylation occurs on the Asn residue among the consensus N-X-S/T/C (X≠P) motif; mutation-originated amino acid change may lead to loss of such an original motif and thus loss-of-glycosylation (LoG) or gain of such a new motif and thus gain-of-glycosylation (GoG). Both LoG and GoG generates new structures and functions of glycoproteins, which has been observed in the S protein of SARS-Cov-2 as well as malignant diseases. Here we report our glycoproteome-wide qualitative N-glycoproteomics characterization of GoGs in breast cancer Adriamycin drug resistance (ADR) cells (MCF-7/ADR) and cancer stem cells (MCF-7/ADR CSCs); comprehensive N-glycosite and N-glycan structure information at the intact N-glycopeptide level were reported.

DeGlyPHER: Highly sensitive site-specific analysis of N-linked glycans on proteins.

Traditional mass spectrometry-based glycoproteomic approaches have been widely used for site-specific N-glycoform analysis, but a large amount of starting material is needed to obtain sampling that is representative of the vast diversity of N-glycans on glycoproteins. These methods also often include a complicated workflow and very challenging data analysis. These limitations have prevented glycoproteomics from being adapted to high-throughput platforms, and the sensitivity of the analysis is currently inadequate for elucidating N-glycan heterogeneity in clinical samples. Heavily glycosylated spike proteins of enveloped viruses, recombinantly expressed as potential vaccines, are prime targets for glycoproteomic analysis. Since the immunogenicity of spike proteins may be impacted by their glycosylation patterns, site-specific analysis of N-glycoforms provides critical information for vaccine design. Using recombinantly expressed soluble HIV Env trimer, we describe DeGlyPHER, a modification of our previously reported sequential deglycosylation strategy to yield a "single-pot" process. DeGlyPHER is an ultrasensitive, simple, rapid, robust, and efficient approach for site-specific analysis of protein N-glycoforms, that we developed for analysis of limited quantities of glycoproteins.

LC-MS/MS-PRM Quantification of IgG Glycoforms Using Stable Isotope Labeled IgG1 Fc Glycopeptide Standard.

Targeted quantification of proteins is a standard methodology with broad utility, but targeted quantification of glycoproteins has not reached its full potential. The lack of optimized workflows and isotopically labeled standards limits the acceptance of glycoproteomics quantification. In this work, we introduce an efficient and streamlined chemoenzymatic synthesis of a library of isotopically labeled glycopeptides of IgG1 which we use for quantification in an energy optimized LC-MS/MS-PRM workflow. Incorporation of the stable isotope labeled N-acetylglucosamine enables an efficient monitoring of all major fragment ions of the glycopeptides generated under the soft higher-energy C-trap dissociation (HCD) conditions, which reduces the coefficients of variability (CVs) of the quantification to 0.7-2.8%. Our results document, for the first time, that the workflow using a combination of stable isotope labeled standards with intrascan normalization enables quantification of the glycopeptides by an electron transfer dissociation (ETD) workflow, as well as the HCD workflow, with the highest sensitivity compared to traditional workflows. This was exemplified by a rapid quantification (13 min) of IgG1 Fc glycoforms from COVID-19 patients.

Sialic acid linkage-specific quantitative N-glycoproteomics using selective alkylamidation and multiplex TMT-labeling.

Protein sialylation participates many biological processes in a linkage-specific manner, and aberrant sialylation has been associated with many malignant diseases. Mass spectrometry-based quantitative N-glycoproteomics has been widely adopted for quantitative analysis of aberrant sialylation, yet multiplexing method at intact N-glycopeptides level is still lacking. Here we report our study of sialic acid linkage-specific quantitative N-glycoproteomics using selective alkylamidation and multiplex tandem mass tags (TMT)-labeling. With lung cancer as a model system, differential sialylation in cancer tissues relative to adjacent non-tumor tissues was characterized at the intact N-glycopeptide level with N-glycosite information. TMT-labeled intact N-glycopeptides with and without sialic acid alkylamidation were subject to reversed-phase liquid chromatography-nano-electron spray ionization-tandem mass spectrometry (RPLC-nanoESI-MS/MS) analysis to provide comprehensive characterization of N-glycosylation with and without sialic acid at the intact N-glycopeptide level with structure and N-glycosite. In this study, 6384 intact N-glycopeptides without sialylation were identified and 521 differentially expressed intact N-glycopeptides from 254 intact N-glycoproteins were quantified. Eight intact N-glycoproteins responsible for N-glycan biosynthesis were identified as glycosyltransferases. In total, 307 sialylated intact N-glycopeptides with linkage-specific sialic acid residues were identified together with 29 N-glycans with α2,6-linked sialic acids and 55 N-glycans with α2,3-linked sialic acids. Intact N-glycoproteins with α2,6-sialylation were associated with coronavirus disease-(COVID)-19. Additionally, many types of N-glycosylation including terminal N-galactosylation, core and/or branch fucosylation, α2,6-sialylation and terminal bisecting N-acetylglucosamine were identified and quantified in intact N-glycoproteins from immunoglobulin family.

Sialic Acid and Fucose Residues on the SARS-CoV-2 Receptor-Binding Domain Modulate IgG Antibody Reactivity.

The receptor-binding domain (RBD) of the SARS-CoV-2 spike protein is a conserved domain and a target for neutralizing antibodies. We defined the carbohydrate content of the recombinant RBD produced in different mammalian cells. We found a higher degree of complex-type N-linked glycans, with less sialylation and more fucosylation, when the RBD was produced in human embryonic kidney cells compared to the same protein produced in Chinese hamster ovary cells. The carbohydrates on the RBD proteins were enzymatically modulated, and the effect on antibody reactivity was evaluated with serum samples from SARS-CoV-2 positive patients. Removal of all carbohydrates diminished antibody reactivity, while removal of only sialic acids or terminal fucoses improved the reactivity. The RBD produced in Lec3.2.8.1-cells, which generate carbohydrate structures devoid of sialic acids and with reduced fucose content, exhibited enhanced antibody reactivity, verifying the importance of these specific monosaccharides. The results can be of importance for the design of future vaccine candidates, indicating that it is possible to enhance the immunogenicity of recombinant viral proteins.

Site-specific glycosylation of SARS-CoV-2: Big challenges in mass spectrometry analysis.

Glycosylation of viral proteins is required for the progeny formation and infectivity of virtually all viruses. It is increasingly clear that distinct glycans also play pivotal roles in the virus's ability to shield and evade the host's immune system. Recently, there has been a great advancement in structural identification and quantitation of viral glycosylation, especially spike proteins. Given the ongoing pandemic and the high demand for structure analysis of SARS-CoV-2 densely glycosylated spike protein, mass spectrometry methodologies have been employed to accurately determine glycosylation patterns. There are still many challenges in the determination of site-specific glycosylation of SARS-CoV-2 viral spike protein. This is compounded by some conflicting results regarding glycan site occupancy and glycan structural characterization. These are probably due to differences in the expression systems, form of expressed spike glycoprotein, MS methodologies, and analysis software. In this review, we recap the glycosylation of spike protein and compare among various studies. Also, we describe the most recent advancements in glycosylation analysis in greater detail and we explain some misinterpretation of previously observed data in recent publications. Our study provides a comprehensive view of the spike protein glycosylation and highlights the importance of consistent glycosylation determination.

Differential Peripheral Blood Glycoprotein Profiles in Symptomatic and Asymptomatic COVID-19.

Glycosylation is the most common form of post-translational modification of proteins, critically affecting their structure and function. Using liquid chromatography and mass spectrometry for high-resolution site-specific quantification of glycopeptides coupled with high-throughput artificial intelligence-powered data processing, we analyzed differential protein glycoisoform distributions of 597 abundant serum glycopeptides and nonglycosylated peptides in 50 individuals who had been seriously ill with COVID-19 and in 22 individuals who had recovered after an asymptomatic course of COVID-19. As additional comparison reference phenotypes, we included 12 individuals with a history of infection with a common cold coronavirus, 16 patients with bacterial sepsis, and 15 healthy subjects without history of coronavirus exposure. We found statistically significant differences, at FDR < 0.05, for normalized abundances of 374 of the 597 peptides and glycopeptides interrogated between symptomatic and asymptomatic COVID-19 patients. Similar statistically significant differences were seen when comparing symptomatic COVID-19 patients to healthy controls (350 differentially abundant peptides and glycopeptides) and common cold coronavirus seropositive subjects (353 differentially abundant peptides and glycopeptides). Among healthy controls and sepsis patients, 326 peptides and glycopeptides were found to be differentially abundant, of which 277 overlapped with biomarkers that showed differential expression between symptomatic COVID-19 cases and healthy controls. Among symptomatic COVID-19 cases and sepsis patients, 101 glycopeptide and peptide biomarkers were found to be statistically significantly abundant. Using both supervised and unsupervised machine learning techniques, we found specific glycoprotein profiles to be strongly predictive of symptomatic COVID-19 infection. LASSO-regularized multivariable logistic regression and K-means clustering yielded accuracies of 100% in an independent test set and of 96% overall, respectively. Our findings are consistent with the interpretation that a majority of glycoprotein modifications observed which are shared among symptomatic COVID-19 and sepsis patients likely represent a generic consequence of a severe systemic immune and inflammatory state. However, there are glycoisoform changes that are specific and particular to severe COVID-19 infection. These may be representative of either COVID-19-specific consequences or susceptibility to or predisposition for a severe course of the disease. Our findings support the potential value of glycoproteomic biomarkers in the biomedical understanding and, potentially, the clinical management of serious acute infectious conditions.

A Linkage-specific Sialic Acid Labeling Strategy Reveals Different Site-specific Glycosylation Patterns in SARS-CoV-2 Spike Protein Produced in CHO and HEK Cell Substrates.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus utilizes the extensively glycosylated spike (S) protein protruding from the viral envelope to bind to angiotensin-converting enzyme-related carboxypeptidase (ACE2) as its primary receptor to mediate host-cell entry. Currently, the main recombinant S protein production hosts are Chinese hamster ovary (CHO) and human embryonic kidney (HEK) cells. In this study, a recombinant S protein truncated at the transmembrane domain and engineered to express a C-terminal trimerization motif was transiently produced in CHO and HEK cell suspensions. To further evaluate the sialic acid linkages presenting on S protein, a two-step amidation process, employing dimethylamine and ammonium hydroxide reactions in a solid support system, was developed to differentially modify the sialic acid linkages on the glycans and glycopeptides from the S protein. The process also adds a charge to Asp and Glu which aids in ionization. We used MALDI-TOF and LC-MS/MS with electron-transfer/higher-energy collision dissociation (EThcD) fragmentation to determine global and site-specific N-linked glycosylation patterns. We identified 21 and 19 out of the 22 predicted N-glycosites of the SARS-CoV-2 S proteins produced in CHO and HEK, respectively. It was found that the N-glycosite at 1,158 position (N1158) and at 122, 282 and 1,158 positions (N122, N282 and N1158) were absent on S from CHO and HEK cells, respectively. The structural mapping of glycans of recombinant human S proteins reveals that CHO-Spike exhibits more complex and higher sialylation (α2,3-linked) content while HEK-Spike exhibits more high-mannose and a small amount of α2,3- and α2,6-linked sialic acids. The N74 site represents the most abundant glycosite on both spike proteins. The relatively higher amount of high-mannose abundant sites (N17, N234, N343, N616, N709, N717, N801, and N1134) on HEK-Spike suggests that glycan-shielding may differ among the two constructs. HEK-Spike can also provide different host immune system interaction profiles based on known immune system active lectins. Collectively, these data underscore the importance of characterizing the site-specific glycosylation of recombinant human spike proteins from HEK and CHO cells in order to better understand the impact of the production host on this complex and important protein used in research, diagnostics and vaccines.

Data-independent acquisition mass spectrometry for site-specific glycoproteomics characterization of SARS-CoV-2 spike protein.

The spike protein of SARS-CoV-2, the virus responsible for the global pandemic of COVID-19, is an abundant, heavily glycosylated surface protein that plays a key role in receptor binding and host cell fusion, and is the focus of all current vaccine development efforts. Variants of concern are now circulating worldwide that exhibit mutations in the spike protein. Protein sequence and glycosylation variations of the spike may affect viral fitness, antigenicity, and immune evasion. Global surveillance of the virus currently involves genome sequencing, but tracking emerging variants should include quantitative measurement of changes in site-specific glycosylation as well. In this work, we used data-dependent acquisition (DDA) and data-independent acquisition (DIA) mass spectrometry to quantitatively characterize the five N-linked glycosylation sites of the glycoprotein standard alpha-1-acid glycoprotein (AGP), as well as the 22 sites of the SARS-CoV-2 spike protein. We found that DIA compared favorably to DDA in sensitivity, resulting in more assignments of low-abundance glycopeptides. However, the reproducibility across replicates of DIA-identified glycopeptides was lower than that of DDA, possibly due to the difficulty of reliably assigning low-abundance glycopeptides confidently. The differences in the data acquired between the two methods suggest that DIA outperforms DDA in terms of glycoprotein coverage but that overall performance is a balance of sensitivity, selectivity, and statistical confidence in glycoproteomics. We assert that these analytical and bioinformatics methods for assigning and quantifying glycoforms would benefit the process of tracking viral variants as well as for vaccine development.

Mass Spectrometry-based Proteomics and Glycoproteomics in COVID-19 Biomarkers Identification: A Mini-review.

The first corona-pandemic, coronavirus disease 2019 (COVID-19) caused a huge health crisis and incalculable damage worldwide. Knowledge of how to cure the disease is urgently needed. Emerging immune escaping mutants of the virus suggested that it may be potentially persistent in human society as a regular health threat as the flu virus. Therefore, it is imperative to identify appropriate biomarkers to indicate pathological and physiological states, and more importantly, clinic outcomes. Proteins are the performers of life functions, and their abundance and modification status can directly reflect the immune status. Protein glycosylation serves a great impact in modulating protein function. The use of both unmodified and glycosylated proteins as biomarkers has also been proved feasible in the studies of SARS, Zika virus, influenza, etc. In recent years, mass spectrometry-based glycoproteomics, as well as proteomics approaches, advanced significantly due to the evolution of mass spectrometry. We focus on the current development of the mass spectrometry-based strategy for COVID-19 biomarkers' investigation. Potential application of glycoproteomics approaches and challenges in biomarkers identification are also discussed.

The Need for Community Standards to Enable Accurate Comparison of Glycoproteomics Algorithm Performance.

Protein glycosylation that mediates interactions among viral proteins, host receptors, and immune molecules is an important consideration for predicting viral antigenicity. Viral spike proteins, the proteins responsible for host cell invasion, are especially important to be examined. However, there is a lack of consensus within the field of glycoproteomics regarding identification strategy and false discovery rate (FDR) calculation that impedes our examinations. As a case study in the overlap between software, here as a case study, we examine recently published SARS-CoV-2 glycoprotein datasets with four glycoproteomics identification software with their recommended protocols: GlycReSoft, Byonic, pGlyco2, and MSFragger-Glyco. These software use different Target-Decoy Analysis (TDA) forms to estimate FDR and have different database-oriented search methods with varying degrees of quantification capabilities. Instead of an ideal overlap between software, we observed different sets of identifications with the intersection. When clustering by glycopeptide identifications, we see higher degrees of relatedness within software than within glycosites. Taking the consensus between results yields a conservative and non-informative conclusion as we lose identifications in the desire for caution; these non-consensus identifications are often lower abundance and, therefore, more susceptible to nuanced changes. We conclude that present glycoproteomics softwares are not directly comparable, and that methods are needed to assess their overall results and FDR estimation performance. Once such tools are developed, it will be possible to improve FDR methods and quantify complex glycoproteomes with acceptable confidence, rather than potentially misleading broad strokes.

Fecal multi-omics analysis reveals diverse molecular alterations of gut ecosystem in COVID-19 patients.

Gut ecosystem has profound effects on host physiology and health. Gastrointestinal (GI) symptoms were frequently observed in patients with COVID-19. Compared with other organs, gut antiviral response can result in more complicated immune responses because of the interactions between the gut microbiota and host immunity. However, there are still large knowledge gaps in the impact of COVID-19 on gut molecular profiles and commensal microbiome, hindering our comprehensive understanding of the pathogenesis of SARS-CoV-2 and the treatment of COVID-19. We performed longitudinal stool multi-omics profiling to systemically investigate the molecular phenomics alterations of gut ecosystem in COVID-19. Gut proteomes of COVID-19 were characterized by disturbed immune, proteolysis and redox homeostasis. The expression and glycosylation of proteins involved in neutrophil degranulation and migration were suppressed, while those of proteases were upregulated. The variable domains of Ig heavy chains were downregulated and the overall glycosylation of IgA heavy chain constant regions, IgGFc-binding protein, and J chain were suppressed with glycan-specific variations. There was a reduction of beneficial gut bacteria and an enrichment of bacteria derived deleterious metabolites potentially associated with multiple types of diseases (such as ethyl glucuronide). The reduction of Ig heave chain variable domains may contribute to the increase of some Bacteroidetes species. Many bacteria ceramide lipids with a C17-sphingoid based were downregulated in COVID-19. In many cases, the gut phenome did not restore two months after symptom onset. Our study indicates widely disturbed gut molecular profiles which may play a role in the development of symptoms in COVID-19. Our findings also emphasis the need for ongoing investigation of the long-term gut molecular and microbial alterations during COVID-19 recovery process. Considering the gut ecosystem as a potential target could offer a valuable approach in managing the disease.

Fostering "Education": Do Extracellular Vesicles Exploit Their Own Delivery Code?

Extracellular vesicles (EVs), comprising large microvesicles (MVs) and exosomes (EXs), play a key role in intercellular communication, both in physiological and in a wide variety of pathological conditions. However, the education of EV target cells has so far mainly been investigated as a function of EX cargo, while few studies have focused on the characterization of EV surface membrane molecules and the mechanisms that mediate the addressability of specific EVs to different cell types and tissues. Identifying these mechanisms will help fulfill the diagnostic, prognostic, and therapeutic promises fueled by our growing knowledge of EVs. In this review, we first discuss published studies on the presumed EV "delivery code" and on the combinations of the hypothesized EV surface membrane "sender" and "recipient" molecules that may mediate EV targeting in intercellular communication. Then we briefly review the main experimental approaches and techniques, and the bioinformatic tools that can be used to identify and characterize the structure and functional role of EV surface membrane molecules. In the final part, we present innovative techniques and directions for future research that would improve and deepen our understandings of EV-cell targeting.

Site-specific characterization of SARS-CoV-2 spike glycoprotein receptor-binding domain.

The novel coronavirus SARS-CoV-2, the infective agent causing COVID-19, is having a global impact both in terms of human disease as well as socially and economically. Its heavily glycosylated spike glycoprotein is fundamental for the infection process, via its receptor-binding domains interaction with the glycoprotein angiotensin-converting enzyme 2 on human cell surfaces. We therefore utilized an integrated glycomic and glycoproteomic analytical strategy to characterize both N- and O- glycan site-specific glycosylation within the receptor-binding domain. We demonstrate the presence of complex-type N-glycans with unusual fucosylated LacdiNAc at both sites N331 and N343 and a single site of O-glycosylation on T323.

Site-Specific O-Glycosylation Analysis of SARS-CoV-2 Spike Protein Produced in Insect and Human Cells.

Enveloped viruses hijack not only the host translation processes, but also its glycosylation machinery, and to a variable extent cover viral surface proteins with tolerogenic host-like structures. SARS-CoV-2 surface protein S presents as a trimer on the viral surface and is covered by a dense shield of N-linked glycans, and a few O-glycosites have been reported. The location of O-glycans is controlled by a large family of initiating enzymes with variable expression in cells and tissues and hence is difficult to predict. Here, we used our well-established O-glycoproteomic workflows to map the precise positions of O-linked glycosylation sites on three different entities of protein S-insect cell or human cell-produced ectodomains, or insect cell derived receptor binding domain (RBD). In total 25 O-glycosites were identified, with similar patterns in the two ectodomains of different cell origin, and a distinct pattern of the monomeric RBD. Strikingly, 16 out of 25 O-glycosites were located within three amino acids from known N-glycosites. However, O-glycosylation was primarily found on peptides that were unoccupied by N-glycans, and otherwise had low overall occupancy. This suggests possible complementary functions of O-glycans in immune shielding and negligible effects of O-glycosylation on subunit vaccine design for SARS-CoV-2.

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.