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Mass spectrometry (MS)-based proteomics workflows typically involve complex, multi-step processes, presenting challenges with sample losses, reproducibility, requiring substantial time and financial investments, and specialized skills. Here we introduce One-Tip, a proteomics methodology that seamlessly integrates efficient, one-pot sample preparation with precise, narrow-window data-independent acquisition (nDIA) analysis. One-Tip substantially simplifies sample processing, enabling the reproducible identification of >9000 proteins from ~1000 HeLa cells. The versatility of One-Tip is highlighted by nDIA identification of ~6000 proteins in single cells from early mouse embryos. Additionally, the study incorporates the Uno Single Cell Dispenser™, demonstrating the capability of One-Tip in single-cell proteomics with >3000 proteins identified per HeLa cell. We also extend One-Tip workflow to analysis of extracellular vesicles (EVs) extracted from blood plasma, demonstrating its high sensitivity by identifying >3000 proteins from 16 ng EV preparation. One-Tip expands capabilities of proteomics, offering greater depth and throughput across a range of sample types.

Protein arginine methylations are important post-translational modifications (PTMs) in eukaryotes, regulating many biological processes. However, traditional collision-based mass spectrometry methods inevitably cause neutral losses of methylarginines, preventing the deep mining of biologically important sites. Herein we developed an optimized mass spectrometry workflow based on electron-transfer dissociation (ETD) with supplemental activation for proteomic profiling of arginine methylation in human cells. Using symmetric dimethylarginine (sDMA) as an example, we show that the ETD-based optimized workflow significantly improved the identification and site localization of sDMA. Quantitative proteomics identified 138 novel sDMA sites as potential PRMT5 substrates in HeLa cells. Further biochemical studies on SERBP1, a newly identified PRMT5 substrate, confirmed the coexistence of sDMA and asymmetric dimethylarginine in the central RGG/RG motif, and loss of either methylation caused increased the recruitment of SERBP1 to stress granules under oxidative stress. Overall, our optimized workflow not only enabled the identification and localization of extensive, nonoverlapping sDMA sites in human cells but also revealed novel PRMT5 substrates whose sDMA may play potentially important biological functions., Protein arginine methylations are important post-translational modifications (PTMs) in eukaryotes, regulating many biological processes. However, traditional collision-based mass spectrometry methods inevitably cause neutral losses of methylarginines, preventing the deep mining of biologically important sites. Herein we developed an optimized mass spectrometry workflow based on electron-transfer dissociation (ETD) with supplemental activation for proteomic profiling of arginine methylation in human cells. Using symmetric dimethylarginine (sDMA) as an example, we show that the ETD-based optimized workflow significantly improved the identification and site localization of sDMA. Quantitative proteomics identified 138 novel sDMA sites as potential PRMT5 substrates in HeLa cells. Further biochemical studies on SERBP1, a newly identified PRMT5 substrate, confirmed the coexistence of sDMA and asymmetric dimethylarginine in the central RGG/RG motif, and loss of either methylation caused increased the recruitment of SERBP1 to stress granules under oxidative stress. Overall, our optimized workflow not only enabled the identification and localization of extensive, nonoverlapping sDMA sites in human cells but also revealed novel PRMT5 substrates whose sDMA may play potentially important biological functions.

Cell surface glycans are essential for establishing cell communication, adhesion, and migration. However, it remains challenging to obtain cell surface-specific information about glycoconjugate structures. Acquiring this information is essential for unraveling the functional role of glycans and for exploiting them as clinical targets. To specifically analyze the N-glycoprotein forms expressed at the cell surface, we developed a C18 liquid chromatography (LC)-mass spectrometry (MS)-based glycoproteomics method in combination with highly specific cell surface protein labeling and enrichment using a biotin label. The surface-specificity of the method was validated by MS-based proteomics of subcellular component marker proteins. Using the human keratinocytes N/TERT-1 as a model system, we identified and quantified the glycosylation of hundreds of cell surface N-glycosylation sites. This approach allowed us to study the glycoforms present at the functional relevant cell surface, omitting immaturely glycosylated proteins present in the secretory pathway. Interestingly, the different stages of N-glycan processing at individual sites displayed at the cell surface were found to correlate with their accessibility for ER-residing processing enzymes, as investigated through molecular dynamics simulations. Using the new approach, we compared N-glycosylation sites of proteins expressed on the cell surface to their counterparts in a total cell lysate, showing profound differences in glycosylation between the subcellular components and indicating the relevance of the method for future studies in understanding contextual glycan functions.

A linear ion trap (LIT) is an affordable, robust mass spectrometer that provides fast scanning speed and high sensitivity, where its primary disadvantage is inferior mass accuracy compared to more commonly used time-of-flight or orbitrap (OT) mass analyzers. Previous efforts to utilize the LIT for low-input proteomics analysis still rely on either built-in OTs for collecting precursor data or OT-based library generation. Here, we demonstrate the potential versatility of the LIT for low-input proteomics as a stand-alone mass analyzer for all mass spectrometry (MS) measurements, including library generation. To test this approach, we first optimized LIT data acquisition methods and performed library-free searches with and without entrapment peptides to evaluate both the detection and quantification accuracy. We then generated matrix-matched calibration curves to estimate the lower limit of quantification using only 10 ng of starting material. While LIT-MS1 measurements provided poor quantitative accuracy, LIT-MS2 measurements were quantitatively accurate down to 0.5 ng on the column. Finally, we optimized a suitable strategy for spectral library generation from low-input material, which we used to analyze single-cell samples by LIT-DIA using LIT-based libraries generated from as few as 40 cells., A linear ion trap (LIT) is an affordable, robust mass spectrometer that provides fast scanning speed and high sensitivity, where its primary disadvantage is inferior mass accuracy compared to more commonly used time-of-flight or orbitrap (OT) mass analyzers. Previous efforts to utilize the LIT for low-input proteomics analysis still rely on either built-in OTs for collecting precursor data or OT-based library generation. Here, we demonstrate the potential versatility of the LIT for low-input proteomics as a stand-alone mass analyzer for all mass spectrometry (MS) measurements, including library generation. To test this approach, we first optimized LIT data acquisition methods and performed library-free searches with and without entrapment peptides to evaluate both the detection and quantification accuracy. We then generated matrix-matched calibration curves to estimate the lower limit of quantification using only 10 ng of starting material. While LIT-MS1 measurements provided poor quantitative accuracy, LIT-MS2 measurements were quantitatively accurate down to 0.5 ng on the column. Finally, we optimized a suitable strategy for spectral library generation from low-input material, which we used to analyze single-cell samples by LIT-DIA using LIT-based libraries generated from as few as 40 cells.

DNA mismatch repair (MMR) is a highly conserved pathway that corrects both base–base mispairs and insertion-deletion loops (IDLs) generated during DNA replication. Defects in MMR have been linked to carcinogenesis and drug resistance. However, the regulation of MMR is poorly understood. Interestingly, CNOT6 is one of four deadenylase subunits in the conserved CCR4-NOT complex and it targets poly(A) tails of mRNAs for degradation. CNOT6 is overexpressed in acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML) and androgen-independent prostate cancer cells, which suggests that an altered expression of CNOT6 may play a role in tumorigenesis. Here, we report that a depletion of CNOT6 sensitizes human U2OS cells to N-methyl-N′nitro-N-nitrosoguanidine (MNNG) and leads to enhanced apoptosis. We also demonstrate that the depletion of CNOT6 upregulates MMR and decreases the mutation frequency in MMR-proficient cells. Furthermore, the depletion of CNOT6 increases the stability of mRNA transcripts from MMR genes, leading to the increased expression of MMR proteins. Our work provides insight into a novel CNOT6-dependent mechanism for regulating MMR.

Dissecting site-specific functions of O-glycosylation requires simultaneous identification and quantification of differentially expressed O-glycopeptides by mass spectrometry. However, different dissociation methods have not been systematically compared in their performance in terms of identification, glycosite localization, and quantification with isobaric labeling. Here, we conducted this comparison on highly enriched unlabeled O-glycopeptides with higher-energy collision dissociation (HCD), electron-transfer/collision-induced dissociation (ETciD), and electron transfer/higher-energy collisional dissociation (EThcD), concluding that ETciD and EThcD with optimal supplemental activation resulted in superior identification of glycopeptides and unambiguous site localizations than HCD in a database search by Sequest HT. We later described a pseudo-EThcD strategy that in silica concatenates the electron transfer dissociation spectrum with the paired HCD spectrum acquired sequentially for the same precursor ions, which combines the identification advantage of ETciD/EThcD with the superior reporter ion quality of HCD. We demonstrated its improvements in identification and quantification of isobaric mass tag-labeled O-glycopeptides and showcased the discovery of the specific glycosites of GalNAc transferase 11 (GALNT11) in HepG2 cells.

Data-independent acquisition (DIA) is now an emerging method in bottom-up proteomics and capable of achieving deep proteome coverage and accurate label-free quantification. However, for post-translational modifications, such as glycosylation, DIA methodology is still in the early stage of development. The full characterization of glycoproteins requires site-specific glycan identification as well as subsequent quantification of glycan structures at each site. The tremendous complexity of glycosylation represents a significant analytical challenge in glycoproteomics. This review focuses on the development and perspectives of DIA methodology for N- and O-linked glycoproteomics and posits that DIA-based glycoproteomics could be a method of choice to address some of the challenging aspects of glycoproteomics. First, the current challenges in glycoproteomics and the basic principles of DIA are briefly introduced. DIA-based glycoproteomics is then summarized and described into four aspects based on the actual samples. Finally, we discussed the important challenges and future perspectives in the field. We believe that DIA can significantly facilitate glycoproteomic studies and contribute to the development of future advanced tools and approaches in the field of glycoproteomics.

Peptide hormones and neuropeptides encompass a large class of bioactive peptides that regulate physiological processes like anxiety, blood glucose, appetite, inflammation and blood pressure. Here, we execute a focused discovery strategy to provide an extensive map of O-glycans on peptide hormones. We find that almost one third of the 279 classified peptide hormones carry O-glycans. Many of the identified O-glycosites are conserved and are predicted to serve roles in proprotein processing, receptor interaction, biodistribution and biostability. We demonstrate that O-glycans positioned within the receptor binding motifs of members of the neuropeptide Y and glucagon families modulate receptor activation properties and substantially extend peptide half-lives. Our study highlights the importance of O-glycosylation in the biology of peptide hormones, and our map of O-glycosites in this large class of biomolecules serves as a discovery platform for an important class of molecules with potential opportunities for drug designs. O-glycosylation is an abundant post-translational modification but its relevance for bioactive peptides is unclear. Here, the authors detect O-glycans on almost one third of the classified peptide hormones and show that O-glycosylation can modulate peptide half-lives and receptor activation properties.

Glycosylation, the posttranslational linking of sugar molecules to proteins, is notoriously altered during tumor transformation. More specifically in carcinomas, GalNAc‐type O‐ glycosylation, is characterized by biosynthetically immature truncated glycans present on the cancer cell surface, which profoundly impact anti‐tumor immune recognition. The tumor‐associated glycan pattern may thus be regarded as a biomarker of immune modulation. In epithelial ovarian cancer (EOC) there is a particular lack of specific biomarkers and molecular targets to aid early diagnosis and develop novel therapeutic interventions. The aim of this study was to investigate the ovarian cancer O‐glycoproteome and identify tumor‐associated glycoproteins relevant in tumor– dendritic cell (DC) interactions, mediated by macrophage galactose‐like C type lectin (MGL), which recognizes the tumor‐associated Tn O‐glycan. Lectin weak affinity chromatography (LWAC) was employed to probe the O‐glycopeptidome by MGL and Vicia villosa agglutinin (VVA) lectin using glycoengineered ovarian cancer cell lines and ovarian cancer tissues as input material. Biochemical and bioinformatics analysis gave information on the glycan arrangement recognized by MGL in tumor cells. The potential MGL binders identified were located, as expected, at the cell membrane, but also within the intracellular compartment and the matrisome, suggesting that MGL in vivo may play a complex role in sensing microenvironmental cues. The tumor glycoproteins binders for MGL may become relevant to characterize the interaction between the immune system and tumor progression and contribute to the design of glycan targeting‐based strategies for EOC immunotherapeutic interventions.

The glycome undergoes characteristic changes during histogenesis and organogenesis, but our understanding of the importance of select glycan structures for tissue formation and homeostasis is incomplete. Here, we present a human organotypic platform that allows genetic dissection of cellular glycosylation capacities and systematic interrogation of the roles of distinct glycan types in tissue formation. We used CRISPR-Cas9 gene targeting to generate a library of 3D organotypic skin tissues that selectively differ in their capacity to produce glycan structures on the main types of N- and O-linked glycoproteins and glycolipids. This tissue library revealed distinct changes in skin formation associated with a loss of features for all tested glycoconjugates. The organotypic skin model provides phenotypic cues for the distinct functions of glycoconjugates and serves as a unique resource for further genetic dissection and identification of the specific structural features involved. The strategy is also applicable to other organotypic tissue models.

We report a liquid chromatography coupled to tandem mass spectrometry O-glycoproteomics strategy using data-independent acquisition (DIA) mode for direct analysis of O-glycoproteins. This approach enables characterization of glycopeptides and structures of O-glycans on a proteome-wide scale with quantification of stoichiometries (though it does not allow for direct unambiguous glycosite identification). The method relies on a spectral library of O-glycopeptides; the Glyco-DIA library contains sublibraries obtained from human cell lines and human serum, and it currently covers 2,076 O-glycoproteins (11,452 unique glycopeptide sequences) and the 5 most common core1 O-glycan structures. Applying the Glyco-DIA library to human serum without enrichment for glycopeptides enabled us to identify and quantify 269 distinct glycopeptide sequences bearing up to 5 different core1 O-glycans from 159 glycoproteins in a SingleShot analysis.