Defining albumin as a glycoprotein with multiple N-linked glycosylation sites.

BACKGROUND: Glycosylation is an enzyme-catalyzed post-translational modification that is distinct from glycation and is present on a majority of plasma proteins. N-glycosylation occurs on asparagine residues predominantly within canonical N-glycosylation motifs (Asn-X-Ser/Thr) although non-canonical N-glycosylation motifs Asn-X-Cys/Val have also been reported. Albumin is the most abundant protein in plasma whose glycation is well-studied in diabetes mellitus. However, albumin has long been considered a non-glycosylated protein due to absence of canonical motifs. Albumin contains two non-canonical N-glycosylation motifs, of which one was recently reported to be glycosylated. METHODS: We enriched abundant serum proteins to investigate their N-linked glycosylation followed by trypsin digestion and glycopeptide enrichment by size-exclusion or mixed-mode anion-exchange chromatography. Glycosylation at canonical as well as non-canonical sites was evaluated by liquid chromatography-tandem mass spectrometry (LC-MS/MS) of enriched glycopeptides. Deglycosylation analysis was performed to confirm N-linked glycosylation at non-canonical sites. Albumin-derived glycopeptides were fragmented by MS3 to confirm attached glycans. Parallel reaction monitoring was carried out on twenty additional samples to validate these findings. Bovine and rabbit albumin-derived glycopeptides were similarly analyzed by LC-MS/MS. RESULTS: Human albumin is N-glycosylated at two non-canonical sites, Asn68 and Asn123. N-glycopeptides were detected at both sites bearing four complex sialylated glycans and validated by MS3-based fragmentation and deglycosylation studies. Targeted mass spectrometry confirmed glycosylation in twenty additional donor samples. Finally, the highly conserved Asn123 in bovine and rabbit serum albumin was also found to be glycosylated. CONCLUSIONS: Albumin is a glycoprotein with conserved N-linked glycosylation sites that could have potential clinical applications.

Global O-glycoproteome enrichment and analysis enabled by a combinatorial enzymatic workflow.

A comprehensive analysis of site-specific protein O-glycosylation is hindered by the absence of a consensus O-glycosylation motif, the diversity of O-glycan structures, and the lack of a universal enzyme that cleaves attached O-glycans. Here, we report the development of a robust O-glycoproteomic workflow for analyzing complex biological samples by combining four different strategies: removal of N-glycans, complementary digestion using O-glycoprotease (IMPa) with/without another protease, glycopeptide enrichment, and mass spectrometry with fragmentation of glycopeptides using stepped collision energy. Using this workflow, we cataloged 474 O-glycopeptides on 189 O-glycosites derived from 79 O-glycoproteins from human plasma. These data revealed O-glycosylation of several abundant proteins that have not been previously reported. Because many of the proteins that contained unannotated O-glycosylation sites have been extensively studied, we wished to confirm glycosylation at these sites in a targeted fashion. Thus, we analyzed selected purified proteins (kininogen-1, fetuin-A, fibrinogen, apolipoprotein E, and plasminogen) in independent experiments and validated the previously unknown O-glycosites.

A complement C4-derived glycopeptide is a biomarker for PMM2-CDG.

BACKGROUNDDiagnosis of PMM2-CDG, the most common congenital disorder of glycosylation (CDG), relies on measuring carbohydrate-deficient transferrin (CDT) and genetic testing. CDT tests have false negatives and may normalize with age. Site-specific changes in protein N-glycosylation have not been reported in sera in PMM2-CDG.METHODSUsing multistep mass spectrometry-based N-glycoproteomics, we analyzed sera from 72 individuals to discover and validate glycopeptide alterations. We performed comprehensive tandem mass tag-based discovery experiments in well-characterized patients and controls. Next, we developed a method for rapid profiling of additional samples. Finally, targeted mass spectrometry was used for validation in an independent set of samples in a blinded fashion.RESULTSOf the 3,342 N-glycopeptides identified, patients exhibited decrease in complex-type N-glycans and increase in truncated, mannose-rich, and hybrid species. We identified a glycopeptide from complement C4 carrying the glycan Man5GlcNAc2, which was not detected in controls, in 5 patients with normal CDT results, including 1 after liver transplant and 2 with a known genetic variant associated with mild disease, indicating greater sensitivity than CDT. It was detected by targeted analysis in 2 individuals with variants of uncertain significance in PMM2.CONCLUSIONComplement C4-derived Man5GlcNAc2 glycopeptide could be a biomarker for accurate diagnosis and therapeutic monitoring of patients with PMM2-CDG and other CDGs.FUNDINGU54NS115198 (Frontiers in Congenital Disorders of Glycosylation: NINDS; NCATS; Eunice Kennedy Shriver NICHD; Rare Disorders Consortium Disease Network); K08NS118119 (NINDS); Minnesota Partnership for Biotechnology and Medical Genomics; Rocket Fund; R01DK099551 (NIDDK); Mayo Clinic DERIVE Office; Mayo Clinic Center for Biomedical Discovery; IA/CRC/20/1/600002 (Center for Rare Disease Diagnosis, Research and Training; DBT/Wellcome Trust India Alliance).

Recent progress in mass spectrometry-based urinary proteomics.

Serum or plasma is frequently utilized in biomedical research; however, its application is impeded by the requirement for invasive sample collection. The non-invasive nature of urine collection makes it an attractive alternative for disease characterization and biomarker discovery. Mass spectrometry-based protein profiling of urine has led to the discovery of several disease-associated biomarkers. Proteomic analysis of urine has not only been applied to disorders of the kidney and urinary bladder but also to conditions affecting distant organs because proteins excreted in the urine originate from multiple organs. This review provides a progress update on urinary proteomics carried out over the past decade. Studies summarized in this review have expanded the catalog of proteins detected in the urine in a variety of clinical conditions. The wide range of applications of urine analysis-from characterizing diseases to discovering predictive, diagnostic and prognostic markers-continues to drive investigations of the urinary proteome.

sBioSITe enables sensitive identification of the cell surface proteome through direct enrichment of biotinylated peptides.

BACKGROUND: Cell surface proteins perform critical functions related to immune response, signal transduction, cell-cell interactions, and cell migration. Expression of specific cell surface proteins can determine cell-type identity, and can be altered in diseases including infections, cancer and genetic disorders. Identification of the cell surface proteome remains a challenge despite several enrichment methods exploiting their biochemical and biophysical properties. METHODS: Here, we report a novel method for enrichment of proteins localized to cell surface. We developed this new approach designated surface Biotinylation Site Identification Technology (sBioSITe) by adapting our previously published method for direct identification of biotinylated peptides. In this strategy, the primary amine groups of lysines on proteins on the surface of live cells are first labeled with biotin, and subsequently, biotinylated peptides are enriched by anti-biotin antibodies and analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). RESULTS: By direct detection of biotinylated lysines from PC-3, a prostate cancer cell line, using sBioSITe, we identified 5851 peptides biotinylated on the cell surface that were derived from 1409 proteins. Of these proteins, 533 were previously shown or predicted to be localized to the cell surface or secreted extracellularly. Several of the identified cell surface markers have known associations with prostate cancer and metastasis including CD59, 4F2 cell-surface antigen heavy chain (SLC3A2) and adhesion G protein-coupled receptor E5 (CD97). Importantly, we identified several biotinylated peptides derived from plectin and nucleolin, both of which are not annotated in surface proteome databases but have been shown to have aberrant surface localization in certain cancers highlighting the utility of this method. CONCLUSIONS: Detection of biotinylation sites on cell surface proteins using sBioSITe provides a reliable method for identifying cell surface proteins. This strategy complements existing methods for detection of cell surface expressed proteins especially in discovery-based proteomics approaches.

Whole Exome Sequencing Reveals Novel Variants in Unexplained Erythrocytosis.

Erythrocytosis is characterized by an increase in red cells in peripheral blood. Polycythemia vera, the commonest primary erythrocytosis, results from pathogenic variants in JAK2 in ∼98% of cases. Although some variants have been reported in JAK2-negative polycythemia, the causal genetic variants remain unidentified in ∼80% of cases. To discover genetic variants in unexplained erythrocytosis, we performed whole exome sequencing in 27 patients with JAK2-negative polycythemia after excluding the presence of any mutations in genes previously associated with erythrocytosis (EPOR, VHL, PHD2, EPAS1, HBA, and HBB). We found that the majority of patients (25/27) had variants in genes involved in epigenetic processes, including TET2 and ASXL1 or in genes related to hematopoietic signaling such as MPL and GFIB. Based on computational analysis, we believe that variants identified in 11 patients in this study could be pathogenic although functional studies will be required for confirmation. To our knowledge, this is the largest study reporting novel variants in individuals with unexplained erythrocytosis. Our results suggest that genes involved in epigenetic processes and hematopoietic signaling pathways are likely associated with unexplained erythrocytosis in individuals lacking JAK2 mutations. With very few previous studies targeting JAK2-negative polycythemia patients to identify underlying variants, this study opens a new avenue in evaluating and managing JAK2-negative polycythemia.

Mass spectrometric analysis of chondroitin sulfate-linked peptides.

Chondroitin sulfate proteoglycans (CSPGs) are extracellular matrix components composed of linear glycosaminoglycan (GAG) side chains attached to a core protein. CSPGs play a vital role in neurodevelopment, signal transduction, cellular proliferation and differentiation and tumor metastasis through interaction with growth factors and signaling proteins. These pleiotropic functions of proteoglycans are regulated spatiotemporally by the GAG chains attached to the core protein. There are over 70 chondroitin sulfate-linked proteoglycans reported in cells, cerebrospinal fluid and urine. A core glycan linker of 3-6 monosaccharides attached to specific serine residues can be extended by 20-200 disaccharide repeating units making intact CSPGs very large and impractical to analyze. The current paradigm of CSPG analysis involves digesting the GAG chains by chondroitinase enzymes and analyzing either the protein part, the disaccharide repeats, or both by mass spectrometry. This method, however, provides no information about the site of attachment or the composition of linker oligosaccharides and the degree of sulfation and/or phosphorylation. Further, the analysis by mass spectrometry and subsequent identification of novel CSPGs is hampered by technical challenges in their isolation, less optimal ionization and data analysis. Unknown identity of the linker oligosaccharide also makes it more difficult to identify the glycan composition using database searching approaches. Following chondroitinase digestion of long GAG chains linked to tryptic peptides, we identified intact GAG-linked peptides in clinically relevant samples including plasma, urine and dermal fibroblasts. These intact glycopeptides including their core linker glycans were identified by mass spectrometry using optimized stepped higher energy collision dissociation and electron-transfer/higher energy collision dissociation combined with hybrid database search/de novo glycan composition search. We identified 25 CSPGs including three novel CSPGs that have not been described earlier. Our findings demonstrate the utility of combining enrichment strategies and optimized high-resolution mass spectrometry analysis including alternative fragmentation methods for the characterization of CSPGs. Supplementary Information: The online version contains supplementary material available at 10.1007/s42485-022-00092-3.

TRIT1 defect leads to a recognizable phenotype of myoclonic epilepsy, speech delay, strabismus, progressive spasticity, and normal lactate levels.

TRIT1 defect is a rare, autosomal-recessive disorder of transcription, initially described as a condition with developmental delay, myoclonic seizures, and abnormal mitochondrial function. Currently, only 13 patients have been reported. We reviewed the genetic, clinical, and metabolic aspects of the disease in all known patients, including two novel, unrelated TRIT1 cases with abnormalities in oxidative phosphorylation complexes I and IV in fibroblasts. Taken together the features of all 15 patients, TRIT1 defect could be identified as a potentially recognizable syndrome including myoclonic epilepsy, speech delay, strabismus, progressive spasticity, and variable microcephaly, with normal lactate levels. Half of the patients had oxidative phosphorylation complex measurements and had multiple complex abnormalities.

Development of a multiomics model for identification of predictive biomarkers for COVID-19 severity: a retrospective cohort study.

BACKGROUND: COVID-19 is a multi-system disorder with high variability in clinical outcomes among patients who are admitted to hospital. Although some cytokines such as interleukin (IL)-6 are believed to be associated with severity, there are no early biomarkers that can reliably predict patients who are more likely to have adverse outcomes. Thus, it is crucial to discover predictive markers of serious complications. METHODS: In this retrospective cohort study, we analysed samples from 455 participants with COVID-19 who had had a positive SARS-CoV-2 RT-PCR result between April 14, 2020, and Dec 1, 2020 and who had visited one of three Mayo Clinic sites in the USA (Minnesota, Arizona, or Florida) in the same period. These participants were assigned to three subgroups depending on disease severity as defined by the WHO ordinal scale of clinical improvement (outpatient, severe, or critical). Our control cohort comprised of 182 anonymised age-matched and sex-matched plasma samples that were available from the Mayo Clinic Biorepository and banked before the COVID-19 pandemic. We did a deep profiling of circulatory cytokines and other proteins, lipids, and metabolites from both cohorts. Most patient samples were collected before, or around the time of, hospital admission, representing ideal samples for predictive biomarker discovery. We used proximity extension assays to quantify cytokines and circulatory proteins and tandem mass spectrometry to measure lipids and metabolites. Biomarker discovery was done by applying an AutoGluon-tabular classifier to a multiomics dataset, producing a stacked ensemble of cutting-edge machine learning algorithms. Global proteomics and glycoproteomics on a subset of patient samples with matched pre-COVID-19 plasma samples was also done. FINDINGS: We quantified 1463 cytokines and circulatory proteins, along with 902 lipids and 1018 metabolites. By developing a machine-learning-based prediction model, a set of 102 biomarkers, which predicted severe and clinical COVID-19 outcomes better than the traditional set of cytokines, were discovered. These predictive biomarkers included several novel cytokines and other proteins, lipids, and metabolites. For example, altered amounts of C-type lectin domain family 6 member A (CLEC6A), ether phosphatidylethanolamine (P-18:1/18:1), and 2-hydroxydecanoate, as reported here, have not previously been associated with severity in COVID-19. Patient samples with matched pre-COVID-19 plasma samples showed similar trends in muti-omics signatures along with differences in glycoproteomics profile. INTERPRETATION: A multiomic molecular signature in the plasma of patients with COVID-19 before being admitted to hospital can be exploited to predict a more severe course of disease. Machine learning approaches can be applied to highly complex and multidimensional profiling data to reveal novel signatures of clinical use. The absence of validation in an independent cohort remains a major limitation of the study. FUNDING: Eric and Wendy Schmidt.

Proteomic alterations in extracellular vesicles induced by oncogenic PIK3CA mutations.

PIK3CA is one of the most frequently mutated genes in human cancers, with the two most prevalent activating mutations being E545K and H1047R. Although the altered intracellular signaling pathways in these cells have been described, the effect of these mutations on their extracellular vesicles (EVs) has not yet been reported. To study altered cellular physiology and intercellular communication through proteomic analysis of EVs, MCF10A cells and their isogenic mutant versions (PIK3CA E545K and H1047R) were cultured and their EVs enriched by differential ultracentrifugation. Proteins were extracted, digested with trypsin and the peptides labeled with tandem mass tag (TMT) reagents and analyzed by liquid chromatography tandem mass spectrometry (LC-MS/MS). Four thousand six hundred and fifty-five peptides were identified from 579 proteins of which 522 proteins have been previously described in EVs. Relative quantitation revealed altered levels of EV proteins including several cell adhesion molecules. Mesothelin, E-cadherin, and epithelial cell adhesion molecule were elevated in both mutant cell-derived EVs. Markers of tumor invasion and progression like galectin-3 and transforming growth factor beta induced protein were increased in both mutants. Overall, activating mutations in PIK3CA result in altered EV composition with characteristic changes associated with these hotspot mutations.

TMT-Based Multiplexed Quantitation of N-Glycopeptides Reveals Glycoproteome Remodeling Induced by Oncogenic Mutations.

Glycoproteomics, or the simultaneous characterization of glycans and their attached peptides, is increasingly being employed to generate catalogs of glycopeptides on a large scale. Nevertheless, quantitative glycoproteomics remains challenging even though isobaric tagging reagents such as tandem mass tags (TMT) are routinely used for quantitative proteomics. Here, we present a workflow that combines the enrichment or fractionation of TMT-labeled glycopeptides with size-exclusion chromatography (SEC) for an in-depth and quantitative analysis of the glycoproteome. We applied this workflow to study the cellular glycoproteome of an isogenic mammary epithelial cell system that recapitulated oncogenic mutations in the PIK3CA gene, which codes for the phosphatidylinositol-3-kinase catalytic subunit. As compared to the parental cells, cells with mutations in exon 9 (E545K) or exon 20 (H1047R) of the PIK3CA gene exhibited site-specific glycosylation alterations in 464 of the 1999 glycopeptides quantified. Our strategy led to the discovery of site-specific glycosylation changes in PIK3CA mutant cells in several important receptors, including cell adhesion proteins such as integrin ß-6 and CD166. This study demonstrates that the SEC-based enrichment of glycopeptides is a simple and robust method with minimal sample processing that can easily be coupled with TMT-labeling for the global quantitation of glycopeptides.

Sorbitol Is a Severity Biomarker for PMM2-CDG with Therapeutic Implications.

OBJECTIVE: Epalrestat, an aldose reductase inhibitor increases phosphomannomutase (PMM) enzyme activity in a PMM2-congenital disorders of glycosylation (CDG) worm model. Epalrestat also decreases sorbitol level in diabetic neuropathy. We evaluated the genetic, biochemical, and clinical characteristics, including the Nijmegen Progression CDG Rating Scale (NPCRS), urine polyol levels and fibroblast glycoproteomics in patients with PMM2-CDG. METHODS: We performed PMM enzyme measurements, multiplexed proteomics, and glycoproteomics in PMM2-deficient fibroblasts before and after epalrestat treatment. Safety and efficacy of 0.8 mg/kg/day oral epalrestat were studied in a child with PMM2-CDG for 12 months. RESULTS: PMM enzyme activity increased post-epalrestat treatment. Compared with controls, 24% of glycopeptides had reduced abundance in PMM2-deficient fibroblasts, 46% of which improved upon treatment. Total protein N-glycosylation improved upon epalrestat treatment bringing overall glycosylation toward the control fibroblasts' glycosylation profile. Sorbitol levels were increased in the urine of 74% of patients with PMM2-CDG and correlated with the presence of peripheral neuropathy, and CDG severity rating scale. In the child with PMM2-CDG on epalrestat treatment, ataxia scores improved together with significant growth improvement. Urinary sorbitol levels nearly normalized in 3 months and blood transferrin glycosylation normalized in 6 months. INTERPRETATION: Epalrestat improved PMM enzyme activity, N-glycosylation, and glycosylation biomarkers in vitro. Leveraging cellular glycoproteome assessment, we provided a systems-level view of treatment efficacy and discovered potential novel biosignatures of therapy response. Epalrestat was well-tolerated and led to significant clinical improvements in the first pediatric patient with PMM2-CDG treated with epalrestat. We also propose urinary sorbitol as a novel biomarker for disease severity and treatment response in future clinical trials in PMM2-CDG. ANN NEUROL 20219999:n/a-n/a.

Proteomic Signature of Host Response to SARS-CoV-2 Infection in the Nasopharynx.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, has become a global health pandemic. COVID-19 severity ranges from an asymptomatic infection to a severe multiorgan disease. Although the inflammatory response has been implicated in the pathogenesis of COVID-19, the exact nature of dysregulation in signaling pathways has not yet been elucidated, underscoring the need for further molecular characterization of SARS-CoV-2 infection in humans. Here, we characterize the host response directly at the point of viral entry through analysis of nasopharyngeal swabs. Multiplexed high-resolution MS-based proteomic analysis of confirmed COVID-19 cases and negative controls identified 7582 proteins and revealed significant upregulation of interferon-mediated antiviral signaling in addition to multiple other proteins that are not encoded by interferon-stimulated genes or well characterized during viral infections. Downregulation of several proteasomal subunits, E3 ubiquitin ligases, and components of protein synthesis machinery was significant upon SARS-CoV-2 infection. Targeted proteomics to measure abundance levels of MX1, ISG15, STAT1, RIG-I, and CXCL10 detected proteomic signatures of interferon-mediated antiviral signaling that differentiated COVID-19-positive from COVID-19-negative cases. Phosphoproteomic analysis revealed increased phosphorylation of several proteins with known antiviral properties as well as several proteins involved in ciliary function (CEP131 and CFAP57) that have not previously been implicated in the context of coronavirus infections. In addition, decreased phosphorylation levels of AKT and PKC, which have been shown to play varying roles in different viral infections, were observed in infected individuals relative to controls. These data provide novel insights that add depth to our understanding of SARS-CoV-2 infection in the upper airway and establish a proteomic signature for this viral infection.

Extensive heterogeneity of glycopeptides in plasma revealed by deep glycoproteomic analysis using size-exclusion chromatography.

Several plasma glycoproteins are clinically useful as biomarkers in a variety of diseases. Although thousands of proteins are present in plasma, >95% of the plasma proteome by mass is represented by only 22 proteins. This necessitates strategies to deplete the abundant proteins and enrich other subsets of proteins. Although glycoproteins are abundant in plasma, in routine proteomic analyses, glycopeptides are not often investigated. Traditional methods such as lectin-based enrichment of glycopeptides followed by deglycosylation have helped understand the glycoproteome, but they lack any information about the attached glycans. Here, we apply size-exclusion chromatography (SEC) as a simple strategy to enrich intact N-glycopeptides based on their larger size which achieves broad selectivity regardless of the nature of attached glycans. Using this approach, we identified 1317 N-glycopeptides derived from 266 glycosylation sites on 154 plasma glycoproteins. The deep coverage achieved by this approach was evidenced by extensive heterogeneity that was observed. For instance, 20-100 glycopeptides were observed per protein for the 15 most-glycosylated glycoproteins. Notably, we discovered 615 novel glycopeptides of which 39 glycosylation sites (from 38 glycoproteins) were not included in protein databases such as Uniprot and GlyConnectDB. Finally, we also identified 12 novel glycopeptides containing di-sialic acid, which is a rare glycan epitope. Our results demonstrate the utility of SEC for efficient LC-MS/MS-based deep glycoproteomics analysis of human plasma. Overall, the SEC-based method described here is a simple, rapid and high-throughput strategy for characterization of any glycoproteome.

DIA-Based Proteome Profiling of Nasopharyngeal Swabs from COVID-19 Patients.

Since the recent outbreak of COVID-19, there have been intense efforts to understand viral pathogenesis and host immune response to combat SARS-CoV-2. It has become evident that different host alterations can be identified in SARS-CoV-2 infection based on whether infected cells, animal models or clinical samples are studied. Although nasopharyngeal swabs are routinely collected for SARS-CoV-2 detection by RT-PCR testing, host alterations in the nasopharynx at the proteomic level have not been systematically investigated. Thus, we sought to characterize the host response through global proteome profiling of nasopharyngeal swab specimens. A mass spectrometer combining trapped ion mobility spectrometry (TIMS) and high-resolution QTOF mass spectrometer with parallel accumulation-serial fragmentation (PASEF) was deployed for unbiased proteome profiling. First, deep proteome profiling of pooled nasopharyngeal swab samples was performed in the PASEF enabled DDA mode, which identified 7723 proteins that were then used to generate a spectral library. This approach provided peptide level evidence of five missing proteins for which MS/MS spectrum and mobilograms were validated with synthetic peptides. Subsequently, quantitative proteomic profiling was carried out for 90 individual nasopharyngeal swab samples (45 positive and 45 negative) in DIA combined with PASEF, termed as diaPASEF mode, which resulted in a total of 5023 protein identifications. Of these, 577 proteins were found to be upregulated in SARS-CoV-2 positive samples. Functional analysis of these upregulated proteins revealed alterations in several biological processes including innate immune response, viral protein assembly, and exocytosis. To the best of our knowledge, this study is the first to deploy diaPASEF for quantitative proteomic profiling of clinical samples and shows the feasibility of adopting such an approach to understand mechanisms and pathways altered in diseases.

Digging deeper into the immunopeptidome: characterization of post-translationally modified peptides presented by MHC I.

Peptides presented by MHC molecules on the cell surface, or the immunopeptidome, play an important role in the adaptive arm of the immune response. Antigen processing for MHC class I molecules is a ubiquitous pathway present in all nucleated cells which generates and presents peptides of both self and non-self-origin. Peptides with post-translational modifications represent one category of peptides presented by MHC class I molecules. However, owing to the complexity of self-peptides presented by cells, the diversity of peptides with post-translational modifications is not well-studied. In this study, we carried out MHC Class I immunopeptidomics analysis of Loucy T-cell leukemia and A375 malignant melanoma cell line to characterize the diversity of post-translational modifications of MHC class I-bound peptides. Using high resolution mass spectrometry, we identified 25,761 MHC-bound peptides across both cell lines using Bolt and Sequest search engines. The enrichment method was highly specific as ~ 90% of the peptides were of typical length (8-12 amino acids long) and the motifs were expected based on previously reported motifs for MHC I alleles. Among the MHC-bound peptides, we identified phosphorylation as a major post-translational modification followed by deamidation. We observed site-specific localization of these post-translational modifications, at position P4 for phosphorylated peptides and position P3 for deamidated peptides. We identified a smaller number of peptides with acetylated and methylated lysine, possibly due to very low stoichiometric levels of these PTMs compared to phosphorylation and deamidation. Using PEAKS de novo sequencing algorithm, we identified spliced peptides that accounted for ~ 5-7% of MHC-bound peptides that were otherwise similar in their features as normal MHC-bound peptides. We validated the identity of several post-translationally modified peptides and spliced peptides through mass spectrometric analysis of synthetic peptides. Our study confirms post-translationally modified peptides to be present at low stoichiometric levels along with unusual spliced peptides through unbiased identification using high resolution mass spectrometry. Supplementary Information: The online version contains supplementary material available at 10.1007/s42485-021-00066-x.