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Linkage isomers (α-2,3- or α-2,6-linkage) of sialylated N-glycans are involved in the emergence and progression of some diseases, so they are of great significance for diagnosing and monitoring diseases. However, the qualitative and quantitative analysis of sialylated N-glycan linkage isomers remains challenging due to their low abundance and limited isomeric separation techniques. Herein, we developed a novel strategy integrating one-step sialic acid derivatization, positive charge-sensitive separation and highly sensitive detection based on microfluidic capillary electrophoresis-mass spectrometry (MCE-MS) for fast and specific analysis of α-2,3- and α-2,6-linked sialylated N-glycan isomers. A kind of easily charged long-chain amino compound was screened first for one-step sialic acid derivatization so that only α-2,3- and α-2,6-linked isomers can be quickly and efficiently separated within 10 min by MCE due to the difference in structural conformation, whose separation mechanism was further theoretically supported by molecular dynamic simulation. In addition, different sialylated N-glycans were separated in order according to the number of sialic acids, so that a migration time-based prediction of the number of sialic acids was achieved. Finally, the sialylated N-glycome of human serum was profiled within 10 min and 6 of the 52 detected sialylated N-glycans could be potential diagnostic biomarkers of cervical cancer (CC), whose α-2,3- and α-2,6-linked isomers were distinguished by α-2,3Neuraminidase S.

Among diverse protein post-translational modifications, O-GlcNAcylation, a simple but essential monosaccharide modification, plays crucial roles in cellular processes and is closely related to various diseases. Despite its ubiquity in cells, properties of low stoichiometry and reversibility are hard nuts to crack in system-wide research of O-GlcNAc. Herein, we developed a novel method employing multi-comparative thermal proteome profiling for O-GlcNAc transferase (OGT) substrate discovery. Melting curves of proteins under different treatments were profiled and compared with high reproducibility and consistency. Consequently, proteins with significantly shifted stabilities caused by OGT and uridine-5'-diphosphate

In light of the significance of exosomes in cancer diagnosis and treatment, it is important to understand the components and functions of exosomes. Herein, an all-in-one strategy has been proposed for comprehensive characterization of exosomal proteins based on nanoporous TiO

Interpreting large-scale glycoproteomic data for intact glycopeptide identification has been tremendously advanced by software tools. However, software tools for quantitative analysis of intact glycopeptides remain lagging behind, which greatly hinders exploring the differential expression and functions of site-specific glycosylation in organisms. Here, we report pGlycoQuant, a generic software tool for accurate and convenient quantitative intact glycopeptide analysis, supporting both primary and tandem mass spectrometry quantitation for multiple quantitative strategies. pGlycoQuant enables intact glycopeptide quantitation with very low missing values via a deep residual network, thus greatly expanding the quantitative function of several powerful search engines, currently including pGlyco 2.0, pGlyco3, Byonic and MSFragger-Glyco. The pGlycoQuant-based site-specific N-glycoproteomic study conducted here quantifies 6435 intact N-glycopeptides in three hepatocellular carcinoma cell lines with different metastatic potentials and, together with in vitro molecular biology experiments, illustrates core fucosylation at site 979 of the L1 cell adhesion molecule (L1CAM) as a potential regulator of HCC metastasis. pGlycoQuant is freely available at https://github.com/expellir-arma/pGlycoQuant/releases/. We have demonstrated pGlycoQuant to be a powerful tool for the quantitative analysis of site-specific glycosylation and the exploration of potential glycosylation-related biomarker candidates, and we expect further applications in glycoproteomic studies.

Large-scale profiling of intact glycopeptides is critical but challenging in glycoproteomics. Data independent acquisition (DIA) is an emerging technology with deep proteome coverage and accurate quantitative capability in proteomics studies, but is still in the early stage of development in the field of glycoproteomics. We propose GproDIA, a framework for the proteome-wide characterization of intact glycopeptides from DIA data with comprehensive statistical control by a 2-dimentional false discovery rate approach and a glycoform inference algorithm, enabling accurate identification of intact glycopeptides using wide isolation windows. We further utilize a semi-empirical spectrum prediction strategy to expand the coverage of spectral libraries of glycopeptides. We benchmark our method for N-glycopeptide profiling on DIA data of yeast and human serum samples, demonstrating that DIA with GproDIA outperforms the data-dependent acquisition-based methods for glycoproteomics in terms of capacity and data completeness of identification, as well as accuracy and precision of quantification. We expect that this work can provide a powerful tool for glycoproteomic studies., Data independent acquisition (DIA) proteomics provides deep coverage and high quantitative accuracy, but is not yet well established in glycoproteomics. Here, the authors develop a DIA-based glycoproteomics workflow with stringent statistical controls to enable accurate glycopeptide identification.

Background: Bicuspid aortic valve (BAV) is the most common congenital cardiovascular disease in general population and is frequently associated with the development of thoracic aortic aneurysm (TAA). There is no effective strategy to intervene with TAA progression due to an incomplete understanding of the pathogenesis. Insufficiency of NOTCH1 expression is highly related to BAV-TAA, but the underlying mechanism remains to be clarified. Methods: A comparative proteomics analysis was used to explore the biological differences between non-diseased and BAV-TAA aortic tissues. A microfluidics-based aorta smooth muscle-on-a-chip model was constructed to evaluate the effect of NOTCH1 deficiency on contractile phenotype and mitochondrial dynamics of human aortic smooth muscle cells (HAoSMCs). Results: Protein analyses of human aortic tissues showed the insufficient expression of NOTCH1 and impaired mitochondrial dynamics in BAV-TAA. HAoSMCs with NOTCH1-knockdown exhibited reduced contractile phenotype and were accompanied by attenuated mitochondrial fusion. Furthermore, we identified that mitochondrial fusion activators (leflunomide and teriflunomide) or mitochondrial fission inhibitor (Mdivi-1) partially rescued the disorders of mitochondrial dynamics in HAoSMCs derived from BAV-TAA patients. Conclusions: The aorta smooth muscle-on-a-chip model simulates the human pathophysiological parameters of aorta biomechanics and provides a platform for molecular mechanism studies of aortic disease and related drug screening. This aorta smooth muscle-on-a-chip model and human tissue proteomic analysis revealed that impaired mitochondrial dynamics could be a potential therapeutic target for BAV-TAA. Funding: National Key R and D Program of China, National Natural Science Foundation of China, Shanghai Municipal Science and Technology Major Project, Shanghai Science and Technology Commission, and Shanghai Municipal Education Commission., eLife digest To function properly, the heart must remain a one-way system, pumping out oxygenated blood into the aorta – the largest artery in the body – so it can be distributed across the organism. The aortic valve, which sits at the entrance of the aorta, is a key component of this system. Its three flaps (or ‘cusps’) are pushed open when the blood exits the heart, and they shut tightly so it does not flow back in the incorrect direction. Nearly 1.4% of people around the world are born with ‘bicuspid’ aortic valves that only have two flaps. These valves may harden or become leaky, forcing the heart to work harder. This defect is also associated with bulges on the aorta which progressively weaken the artery, sometimes causing it to rupture. Open-heart surgery is currently the only way to treat these bulges (or ‘aneurysms’), as no drug exists that could slow down disease progression. This is partly because the biological processes involved in the aneurysms worsening and bursting open is unclear. Recent studies have highlighted that many individuals with bicuspid aortic valves also have lower levels of a protein known as NOTCH1, which plays a key signalling role for cells. Problems in the mitochondria – the structures that power up a cell – are also observed. However, it is not known how these findings are connected or linked with the aneurysms developing. To answer this question, Abudupataer et al. analyzed the proteins present in diseased and healthy aortic muscle cells, confirming a lower production of NOTCH1 and impaired mitochondria in diseased tissues. They also created an ‘aorta-on-a-chip’ model where aortic muscle cells were grown in the laboratory under conditions resembling those found in the body – including the rhythmic strain that the aorta is under because of the heart beating. Abudupataer et al. then reduced NOTCH1 levels in healthy samples, which made the muscle tissue less able to contract and reduced the activity of the mitochondria. Applying drugs that tweak mitochondrial activity helped tissues from patients with bicuspid aortic valves to work better. These compounds could potentially benefit individuals with deficient aortic valves, but experiments in animals and clinical trials would be needed first to confirm the results and assess safety. The aorta-on-a-chip model developed by Abudupataer et al. also provides a platform to screen for drugs and examine the molecular mechanisms at play in aortic diseases.