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The advantages of small extracellular vesicles (sEV) in disease management have become increasingly prominent, with the main challenge lying in meeting the demands of large‐scale extraction and high‐throughput analysis, a crucial aspect in the realm of precision medicine. To overcome this challenge, an engineered on‐plate aptamer array (16×24 spots) is developed for continuous scale‐up microextraction of plasma sEV and their in situ metabolic analysis using mass spectrometry. With this integrated array strategy, metabolic profiles of sEV are acquired from the plasma of 274 antenatal or postpartum women, reducing analysis time by half (7.5 h) and sample volume by 95% (only 0.125 µL usage) compared to the traditional suspension method. Moreover, using machine learning algorithms on sEV metabolic profiles, a risk score system is constructed that accurately assesses the need for epidural analgesia during childbirth and the likelihood of post‐administration fever. The system, based on admission samples, achieves an impressive 94% accuracy. Furthermore, post‐administration fever can be identified from delivery samples, reaching an overall accuracy rate of 88%. This work offers real‐time monitoring of the childbirth process that can provide timely guidance for maternal delivery, underscoring the significance of sEV detection in large‐scale clinical samples for medicine innovation and advancement. [ABSTRACT FROM AUTHOR]

Bladder cancer (BCa) exhibits the escalating incidence and mortality due to the untimely and inaccurate early diagnosis. Urinary exosome metabolites, carrying critical tumor cell information and directly related to bladder, emerge as promising non-invasive diagnostic biomarkers of BCa. Herein, the magnetic 3D ordered macroporous zeolitic imidazolate framework-8 (magMZIF-8) is synthesized and used for efficient urinary exosome isolation. Notably, beyond retaining the single crystals and micropores of conventional ZIF-8, MZIF-8 is further enhanced with highly oriented and ordered macropores (150 nm) and the large specific surface area (973 m2·g–1), which could enable the high purity and yield separation of exosomes via leveraging the combination of size exclusion, affinity, and electrostatic interactions between magMZIF-8 and the surfaces of exosome. Furthermore, the magnetic and hydrophilic properties of magMZIF-8 will further simplify the process and enhance the efficiency of separation. After conditional optimization, a 50 mL of urine is sufficient for exosome metabolomics analysis, and the time for isolating exosomes from 42 urine samples was 2 hours only. Incorporating machine learning algorithms with LC-MS/MS analysis of the metabolic patterns obtained from isolated exosomes, early-stage BCa patients were differentiated from healthy controls, with area under the curve (AUC) value of 0.844–0.9970 in the training set and 0.875-1.00 in the test set, signifying its potential as a reliable diagnostic tool. This study offers a promising approach for the non-invasive and efficient diagnosis of BCa on a large scale via exosome metabolomics. [ABSTRACT FROM AUTHOR]

Developing a standardized screening tool for the detection of early and small hepatocellular carcinoma (HCC) through urinary metabolic analysis poses a challenging yet intriguing research endeavor. In this study, a range of intricately interlaced 2D rough nanosheets featuring well‐defined sharp edges is fabricated, with the aim of constructing diverse trimetal oxide heterojunctions exhibiting multiscale structures. By carefully engineering synergistic effects in composition and structure, including improved adsorption, diffusion, and other surface‐driven processes, the optimized heterojunctions demonstrate a substantial enhancement in signal intensity compared to monometallic or bimetallic oxides, as well as fragmented trimetallic oxides. Additionally, optimal heterojunctions enable the extraction of high‐quality urinary metabolic fingerprints using high‐throughput mass spectrometry. Leveraging machine learning, discrimination of HCC patients from high‐risk and healthy populations achieves impressive performance, with area under the curve values of 0.940 and 0.916 for receiver operating characteristic and precision‐recall curves, respectively. Six crucial metabolites are identified, enabling accurate detection of early, small‐tumor, alpha‐fetoprotein‐negative HCC (93.3%–97.3%). A comprehensive screening strategy tailored to clinical reality yields precision metrics (accuracy, precision, recall, and F1 score) exceeding 95.0%. This study advances the application of cutting‐edge matrices‐based metabolic phenotyping in practical clinical diagnostics. [ABSTRACT FROM AUTHOR]

Herein, we synthesised a series of nonstoichiometric Nd−Ce−O composite oxides with a fluorite or rare‐earth C‐type phase structure using the glycine combustion method for the oxidative coupling of methane (OCM) reaction. As the amount of Nd3+ increases, the oxygen vacancies in this series of composite oxides gradually increase, leading to an amount increasing in the C2‐selective oxygen species O2− generated by the oxygen vacancies. In addition, with the increase in Nd3+, the number of moderate basic sites on the catalyst surface also improves, another significant factor affecting the OCM reaction performance of the composite oxides. Nd0.9Ce0.1O1.55 possesses optimal low‐temperature OCM reaction performance, achieving 8.0 % C2 yield at 450 °C and 14.1 % C2 yield at 700 °C. This can be attributed to the nonstoichiometric rare‐earth C‐type crystalline phase structure of Nd0.9Ce0.1O1.55, which exhibits the highest abundance of oxygen vacancies, selective oxygen species O2−, and moderate basic sites. [ABSTRACT FROM AUTHOR]

Liver disease remains a global health challenge, with its incidence steadily increasing worldwide. Herein, zwitterionic mesoporous engineering was developed for the identification of different liver diseases including liver cirrhosis and liver cancer. Based on this engineering, a total of 2633 m/z signals were observed to be enriched. Notably, three key peptides were identified and showed high accuracy and precision for distinguishing the healthy and disease states, propelling the field of nanomedicine toward genuine personalized medicine. [ABSTRACT FROM AUTHOR]

Soft-template carbonized mesopores were developed for the purpose of enriching urinary exosomal glycans through organic–organic self-assembly using block copolymers and resol precursors. With a high surface area of 229 m2 g−1, a small pore size of 3.1 nm, and a significant amount of carbon that specifically interacts with oligosaccharides in glycans, this carbonized mesopore material exhibits high selectivity and low limits of detection (5 ng μL−1) towards glycans. Our analysis of complex urine samples from healthy volunteers and bladder carcinoma patients successfully profiled 48 and 56 exosomal glycans, respectively, and 16 of them were significantly changed. Moreover, one upregulated bisecting N-acetylglucosamine (GlcNAc)-type glycan with core fucose, two upregulated and two downregulated terminal-sialylated glycans were revealed to be linked to bladder carcinoma. This approach is of significant importance for understanding diseases that arise from protein glycosylation mutations, and it may contribute to the development of novel diagnostic and therapeutic strategies for bladder carcinoma. [ABSTRACT FROM AUTHOR]

Acute coronary syndrome (ACS), comprising unstable angina (UA) and acute myocardial infarction (AMI), is the leading cause of death worldwide. Currently, lacking effective strategies for classifying ACS hinders the prognosis improvement of ACS patients. Disclosing the nature of metabolic disorders holds the potential to reflect disease progress and high‐throughput mass spectrometry‐based metabolic analysis is a promising tool for large‐scale screening. Herein, a hollow crystallization COF capsuled MOF hybrids (UiO‐66@HCOF) assisted serum metabolic analysis is developed for the early diagnosis and risk stratification of ACS. UiO‐66@HCOF exhibits unrivaled chemical and structural stability as well as endowing satisfying desorption/ionization efficiency in the detection of metabolites. Paired with machine learning algorithms, early diagnosis of ACS is achieved with the area under the curve (AUC) value of 0.945 for validation sets. Besides, a comprehensive ACS risk stratification method is established, and the AUC value for the discrimination of ACS from healthy controls, and AMI from UA are 0.890, and 0.928. Moreover, the AUC value of the subtyping of AMI is 0.964. Finally, the potential biomarkers exhibit high sensitivity and specificity. This study makes metabolic molecular diagnosis a reality and provided new insight into the progress of ACS. [ABSTRACT FROM AUTHOR]

Objective Interleukin (IL)-37 is a natural suppressor of inflammation. Macrophages play an important role in acute gout flare by dominating the inflammation and spontaneous relief. We have reported that IL-37 could limit runaway inflammation in gout. Here we focus on whether IL-37 inhibits gouty inflammation by altering macrophage functions, and how it does so. Methods Macrophage functions were evaluated in terms of phagocytosis, pyroptosis, polarization and metabolism. Phagocytosis and polarization of macrophages were detected by side scattering and double-labelling induced nitrogen monoxide synthase (iNOS)/arginase-1 (Arg-1) using flow cytometry, respectively. Transcription of pyroptosis-related molecules was detected by qPCR. Metabolomics was performed by liquid chromatograph mass spectrometer. Human IL-37 knock-in mice and a model with point mutation (S9A) at mouse Gsk3b locus were created by CRISPR/Cas-mediated genome engineering. MSU was injected into the paws and peritoneal cavity to model acute gout. Vernier calliper was used to measure the thickness of the paws. The mice paws and human synovium tissues or tophi were collected for pathological staining. Peritoneal fluid of mice was used to enrich macrophages to detect polarization. Results IL-37 promoted non-inflammatory phagocytic activity of macrophages by enhancing phagocytosis of MSU, reducing transcription of pyroptosis-related proteins and release of inflammatory cytokines, protecting mitochondrial function, and mediating metabolic reprogramming in MSU-treated THP-1 cells. These multifaceted roles of IL-37 were partly depended on the mediation of glycogen synthase kinase-3β (GSK-3β). Conclusions Our study revealed that IL-37 could shape macrophages into a 'silent' non-inflammatory phagocytic fashion. IL-37 may become a potentially valuable treatment option for patients of chronic gout, especially for those with tophi. [ABSTRACT FROM AUTHOR]

Diabetes and high myopia as well‐known high‐risk factors can aggravate cataracts, yet clinical coping strategy remains a bottleneck. Metabolic analysis tends to be powerful for precisely detection and mechanism exploration since most of diseases including cataracts are accompanied by metabolic disorder. Herein, a layered binary co‐ionizers assisted aqueous humor metabolic analysis tool is proposed for potentially etiological typing and detection of cataracts, including age‐related cataracts (ARC), cataracts with diabetes mellitus (CDM), and cataracts with high myopia (CHM). Startlingly, taking advantage of the optimal machine learning algorithm and all metabolic fingerprints, 100% of accuracy, precision, and recall rates are achieved for arbitrary comparison between groups. Moreover, 11, 9, and 7 key metabolites with explicit identities are confirmed as markers of discriminating CDM from ARC, CHM from ARC, and CDM from CHM, and the corresponding area under the curve values of validation cohorts are 0.985, 1.000, and 1.000. Finally, the critical impact of diabetes/high myopia on cataracts is revealed by excavating the change levels and metabolic pathways of key metabolites. This work updates the insights of prevention and treatment about cataracts at metabolic level and throws out huge surprises and progresses metabolic diagnosis toward a reality. [ABSTRACT FROM AUTHOR]

Sentence simplification is an essential task in natural language processing and aims to simplify complex sentences while retaining their primary meanings. To date, the main research works on sentence simplification models have been based on sequence‐to‐sequence (Seq2Seq) models. However, these Seq2Seq models are incapable of analysing the hierarchical structure of sentences, which is of great significance for sentence simplification. The problem can be addressed with an ON‐MULTI‐STAGE model constructed based on the improved MULTI‐STAGE encoder model. In this model, an ordered neurons network is introduced and can provide sentence‐level structural information for the encoder and decoder. A weak attention connection method is then employed to make the decoder use the sentence‐level structural details. Experimental results on two open data sets demonstrated that the constructed model outperforms the state‐of‐the‐art baseline models in sentence simplification. [ABSTRACT FROM AUTHOR]

Exosomes are regarded as the emerging potential targets for liquid biopsy and bioprocess study owing to their abundant inclusive cargos that carry significant disease information. In addition, metabolites have been promising biomarkers for diagnosis. However, little metabolic research on exosomes is carried out by now. Herein, the mix‐crystal titania‐assisted laser desorption/ionization mass spectrometry (LDI‐MS) method is established, which features fast speed, high throughput, and efficiency, to directly extract urinary exosome metabolic patterns of healthy controls (HC) and membrane nephropathy (MN) patients. Besides, this method is also adopted to acquire the primitive urinary metabolic patterns from the same samples for comparison. By taking advantage of principal component analysis, unpaired parametric t‐test, and orthogonal partial least squares discriminant analysis on the exosome metabolic patterns, 27 significant m/z signals are filtrated, which possess more prominent differentiation capacity toward HC and MN patients (AUC = 0.942), and hold greater potential in MN diagnosis, compared to primitive urine (AUC = 0.801). The work reveals the important clinical value of exosome metabolic analysis, and paves a way to exosome‐based diagnosis at metabolomic level toward large‐scale clinical use. [ABSTRACT FROM AUTHOR]

An effective matrix is very important for impact laser desorption/ionization mass spectrometry (LDI-MS), and the physicochemical properties of the matrix nanostructures can impact the LDI-MS performance. In this study, a simple and efficient single-nozzle electrospinning strategy using polystyrene (PS) spheres and polyvinyl pyrrolidone (PVP) to construct a mesoporous NiO@ZnO nanofiber membrane was developed. Compared with the NiO and ZnO nanomaterials alone, the obtained NiO@ZnO nanofiber membrane was proven to be an efficient material as the matrix to increase the intensity of the mass spectrum speaks of small molecules. The NiO@ZnO nanofiber membrane was used as the matrix for the LDI-MS method for the urine metabolism analysis of smokers, which revealed differences in the metabolic and the possible metabolic markers of smokers through the statistical analysis of the urine samples of 27 smokers and 11 nonsmoker controls. [ABSTRACT FROM AUTHOR]

Human health is always under global spotlight, but now it suffers from severe environmental issue and various diseases. Developing highly selective and effective extraction technique for environmental pollutant removal and target protein/peptide molecules conduces to the solution of environmental contamination and early disease detection, which will promise human health to a great degree. Metal-organic frameworks (MOFs) are typical porous nanomaterials featuring rigid structure, large specific surface area, thermal and chemical stability, numerous active sites and easy functionalization. Moreover, multitudinous combination of metal centers and organic ligands often endows MOFs with structure and function diversity. Owing to such splendid merits, MOFs are able to act as advanced adsorbents for sample-pretreatment in proteomics and environmental field, which indicates great efficiency, reproducibility, convenience and cost-effectiveness. In this review, the novel design of MOFs and their applications in proteomics and environmental research are roughly summarized. We first introduce the representative researches of functional MOFs in protein post-translational modifications including glycosylation and phosphorylation, mainly focusing on hydrophilic interaction liquid chromatography (HILIC) or metal-oxide affinity chromatography (MOAC). The important role of MOFs in enzyme immobilization is also covered. Then MOF-based adsorptive removal of diverse environmental contaminants embracing plasticizers, pesticides and varied water pollutants (pharmaceutical and personal care products, organic dyes and heavy metals), in which multiple chemical and non-chemical interactions play a vital role, is emphatically discussed. Finally, we analyze the existing problems and challenges in the way of wider practical applications and put forward prospective anticipation. [ABSTRACT FROM AUTHOR]

Serum N-glycan patterns from 50 Crohn's disease (CD) patients and 50 healthy controls were acquired using a carbon matrix, from which eight N-glycans with significant difference were screened out to reveal remarkale performance for CD diagnosis. This research is expected to help future glycan-based disease detection not limited to CD. [ABSTRACT FROM AUTHOR]

Currently, most Crohn's disease (CD) patients suffer from serious complications and even surgery due to delayed diagnosis; therefore, point‐of‐care diagnosis of CD is urgently required. In this work, a covalent organic framework@Au (COF‐V@Au) matrix material with excellent laser absorption is prepared, endowing metabolites with great ionization efficiency in laser desorption/ionization mass spectrometry (LDI‐MS) analysis. In addition, the COF‐V@Au matrix possesses 1093 m2 g−1 of large specific surface area and around 2 nm of average pore size, providing abundant sites and efficient structure for metabolite adsorption. Benefiting from high throughput, high sensitivity, and high ionization efficiency of COF‐V@Au assisted LDI‐MS, the extraction of serum metabolic fingerprints of CD group and healthy group is implemented. Moreover, the two groups are successfully distinguished with an area under the curve (AUC) value of 0.984 by establishing an orthogonal partial least squares discriminant analysis (OPLS‐DA) model of Crohn's patients versus healthy controls. Moreover, the expression of 25 features is determined as the prominent metabolic differences between CD patients and the controls. Furthermore, the terminal ileum and ileocolon subtypes of CD are also distinguished from healthy controls with AUC value of 0.989 and 0.991, respectively. Thus, this COF‐V@Au‐assisted LDI‐MS method is expected to be a clinical diagnostic technology in the future. [ABSTRACT FROM AUTHOR]

A hydrophilic probe is employed to enrich exosomes from three kinds of cancer cells by TiO2–phosphate interaction and exosomal glycoproteins by hydrophilic interaction in succession. The probe performs efficiently in both the enrichment processes. And the analytical results confirm that unique exosomal glycoproteins can distinguish parent exosomes from others. [ABSTRACT FROM AUTHOR]

Body fluids contain a large number of disease markers including proteins, exosomes and cells, the concentration of which indicates the health status of a body system and can be hence applied to predict the degree of seriousness of a disease. However, the content of disease markers is relatively low. For solving this problem, a variety of pretreatment methods have been developed, among which aptamer-based nanomaterials hold great potential for biomarker capture because of various natural properties of nano-substrates such as high specific surface area, as well as the high affinity of aptamer towards target and the higher stability than antibody. In this review, we summarized the recent aptamer-based nanomaterials for the separation and analysis of different biomarkers including proteins, exosomes and cells. More specifically, the standard of classification description was based on the applied substrates including magnetic substrates and non-magnetic substrates. Moreover, the perspective of aptamer-based nanomaterials was discussed. [ABSTRACT FROM AUTHOR]

A magnetic porous carbon-dependent platform is established to separate and determine N-glycans from urine exosomes of healthy people and patients with gastric cancer. The results of the comparison reveal that 6 N-glycans shared by the two groups are downregulated, most of which present core fucose or bisecting N-acetylglucosamine (GlcNAc) type. In addition, five shared N-glycans including two of sialic acid type are upregulated. These obvious differences indicate the close relationship between glycans and gastric cancer thus permitting early diagnosis. [ABSTRACT FROM AUTHOR]

Herein, boric-acid-modified multifunctional Zr-based metal-organic frameworks (denoted as Fe3O4@PDA@B-UiO-66) were synthesized by hydrothermal reaction and surface modification. Compared to traditional matrix, Fe3O4@PDA@B-UiO-66 has the advantages of high ionization efficiency, high surface area, low matrix background, porous structure, and numerous boric-acid-active sites. By combining matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), Fe3O4@PDA@B-UiO-66 was used as an adsorbent and matrix for enrichment and detection of glucose, based on a specific reaction between boric acid and glucose. The limit of detection was 58.5 nM. The proposed method provides a simple and efficient approach for the sensitive and quantitative detection of glucose in complex samples based on MALDI-TOF MS. [ABSTRACT FROM AUTHOR]

Part‐of‐speech (POS) and dependency grammar (DG) are the basic components of natural language processing. However, current word vector models have not made full use of both POS information and DG information, and hence the models' performances are limited to some extent. The authors first put forward the concept of POS vector, and then, based on continuous bag‐of‐words (CBOW), constructed four models: CBOW + P, CBOW + PW, CBOW + G, and CBOW + G + P to incorporate POS information and DG information into word vectors. The CBOW + P and CBOW + PW models are based on POS tagging, the CBOW + G model is based on DG parsing, and the CBOW + G + P model is based on POS tagging and DG parsing. POS information is integrated into the training process of word vectors through the POS vector to solve the problem of the POS similarity being difficult to measure. The POS vector correlation coefficient and distance weighting function are used to train the POS vector as well as the word vector. DG information is used to correct the information loss caused by fixed context windows. Dependency relations weight is used to measure the difference of dependency relations. Experiments demonstrated the superior performance of their models while the time complexity is still kept the same as the base model of CBOW. [ABSTRACT FROM AUTHOR]

Hydrophilic Fe3O4@PDA@UIO-66-NH2 is employed to consecutively enrich urinary exosomes and exosomal phosphopeptides through the strong bond between Zr and phosphate groups. The recovery of exosomes reached 95% and 707 phosphopeptides were identified from 255 phosphoproteins via LC-MS/MS. This work will make a great contribution to further functional analysis of exosomes. [ABSTRACT FROM AUTHOR]

A hydrophilic carbohydrate functionalized magnetic metal organic framework (Mag Zr-MOF@G6P) was synthesized via a facile one-step modification strategy for selective glycopeptide capture in virtue of hydrophilic interaction chromatography technique. The inherently hydrophilic Zr-MOF layer not only provides selective size-sieving pore structures but also offers large specific surface area to afford abundant affinity sites. Hydroxyl-rich glucose-6-phosphate was immobilized onto the Zr-MOF via a straightforward coordination manner to regulate its surface property, for the purpose of enhancing its hydrophilicity. Benefitting from the merits of Zr-MOF and glucose-6-phosphate, the as-designed composite exhibits good selectivity (the mass ratio of HRP digests to BSA digests was up to1:200) and low limit of detection (0.1 fmol μL−1) towards the recognition of glycopeptides from standard samples. More excitingly, glycopeptides in urine of healthy people and patients with kidney cancer were successfully enriched and identified by the combined liquid chromatography-mass spectrometry/mass spectrometry technology (LC-MS/MS). Further gene ontology analysis of molecular function and biological process revealed that 13 original glycoproteins of the identified glycopeptides from urine of patients significantly participate in diverse cancer-associated events, including collagen binding, immunoglobulin receptor binding, antigen binding, and complement activation process. [ABSTRACT FROM AUTHOR]

A Ti–tannic acid modified magnetic nanoprobe was synthesized via one step, and applied to phosphopeptide extraction. 3456 phosphopeptides and 1285 phosphoproteins were finally identified from 100 μg HeLa cell extracts. This opens up a new avenue for metal phenolic networks in phosphoproteomics research. [ABSTRACT FROM AUTHOR]

For the first time, dual metal ions (Ti4+-Zr4+) were successfully modified into the channel of magnetic mesoporous silica to obtain an affinity probe for highly selective capture of endogenous phosphopeptides in biological samples. The newly prepared Fe3O4@mSiO2@Ti4+-Zr4+ composites possessed the advantages of ordered mesoporous channels, superparamagnetism, and enhanced affinity properties of dual metal ions of Ti4+ and Zr4+. The phosphopeptide enrichment efficiency of the Fe3O4@mSiO2@Ti4+-Zr4+ composite was investigated, and the result indicated an ultrahigh size exclusive ability (weight ratio of β-casein tryptic digests, BSA, and α-casein protein reached up to 1:1000:1000). Compared to magnetic affinity probes with single metal ions (Fe3O4@mSiO2@Ti4+, Fe3O4@mSiO2@Zr4+), the composite possessed stronger specificity, higher sensitivity, and better efficiency; and more importantly, it showed much enhanced enrichment ability towards both mono- and multi-phosphorylated peptides. Additionally, by utilizing the Fe3O4@mSiO2@Ti4+-Zr4+ affinity probe, a total number of 104 endogenous phosphopeptides including 95 mono-phosphopeptides and 9 multi-phosphopeptides were captured and identified from human saliva, indicating the great potential for the application of the novel probe for the peptidome analysis in the future. [ABSTRACT FROM AUTHOR]

Owing to the formidable challenge posed by microheterogeneities in glycosylation sites, macroheterogeneity of the modification number of glycans, and low abundance and ionization efficiency of glycosylation, the crucial premise for conducting in-depth profiling of the glycoproteome is to develop highly efficient technology for separation and enrichment. The appearance of hydrophilic interaction chromatography (HILIC) has considerably accelerated the progress in glycoproteomics. In particular, additional hydrophilic nanomaterials have been developed for glycoproteomics research in the recent years. In this review, we mainly summarize the recent progresses made in the design and synthesis of different hydrophilic nanomaterials, as well as their applications in glycoproteomics, according to the classification of the main hydrophilic functional molecules on the surface. Further, we briefly illustrate the potential retention mechanism of the HILIC mode and discuss the limits and barriers of hydrophilic nanomaterials in glycoproteomics, as well as propose their possible development trends in the future. [ABSTRACT FROM AUTHOR]

Protein glycosylation is one of the most important post-translational modifications. Also, efficient enrichment and separation of glycopeptides from complex samples are crucial for the thorough analysis of glycosylation. Developing novel hydrophilic materials with facile and easily popularized synthesis is an urgent need in large-scale glycoproteomics research. Herein, for the first time, a one-step functionalization strategy based on metal-organic coordination was proposed and FeO nanoparticles were directly functionalized with zwitterionic hydrophilic l-cysteine (L-Cys), greatly simplifying the synthetic procedure. The easily synthesized FeO/L-Cys possessed excellent hydrophilicity and brief composition, contributing to affinity for glycopeptides and reduction in nonspecific interaction. Thus, FeO/L-Cys nanoparticles showed outstanding sensitivity (25 amol/μL), high selectivity (mixture of bovine serum albumin and horseradish peroxidase tryptic digests at a mass ratio of 100:1), good reusability (five repeated times), and stability (room temperature storage of 1 month). Encouragingly, in the glycosylation analysis of human serum, a total of 376 glycopeptides with 393 N-glycosylation sites corresponding to 118 glycoproteins were identified after enrichment with FeO/L-Cys, which was superior to ever reported L-Cys modified magnetic materials. Furthermore, applying the one-step functionalization strategy, cysteamine and glutathione respectively direct-functionalized FeO nanoparticles were successfully synthesized and also achieved efficient glycopeptide enrichment in human serum. The results indicated that we have presented an efficient and easily popularized strategy in glycoproteomics as well as in the synthesis of novel materials. [ABSTRACT FROM AUTHOR]

Glycosylation and phosphorylation as the commonest and most important posttranslational modifications of proteins play critical roles in biological processes. Specific and sensitive strategies have been developed to identify the glycosylation and phosphorylation of proteins by mass spectrometry but most of these methods have mainly focused on enriching glycopeptides or phosphopeptides separately, and few of them can enrich both of them. In this work, highly selective SiO-NH@TiO hollow microspheres were designed and synthesized for the simultaneous selective enrichment of both phosphopeptides and glycopeptides. Because of the bifunctionalized property of the titanium dioxide and the amino group, the hollow microspheres were successfully applied for the simultaneous enrichment of phosphopeptides and glycopeptides. We evaluated the enrichment selectivity of the SiO-NH@TiO hollow microspheres by capturing phosphopeptides and glycopeptides from a peptide mixture of bovine β-casein, horseradish peroxidase, and bovine serum albumin in a molar ratio of 1:1:500 (1.7 × 10 mol β-casein and horseradish peroxidase, 8.5 × 10 mol bovine serum albumin in 100 μL). [ABSTRACT FROM AUTHOR]

The process of protein digestion is a critical step for successful protein identification in proteomic analysis. Many efforts have been dedicated to enhancing the digestion efficiency for sufficient digestion. Among these approaches, protein complete denaturation with denaturants is a common process for better digestion. However, the removal of denaturants was tedious or would cause protein loss and other problems. In this work, a feasible digestion approach, immobilized protein digestion (IPD), based on covalent binding has been developed. Proteins can be completely denatured and immobilized on the surface of functional materials by covalent binding to form a monolayer. Subsequently, varieties of denaturants or contaminants would be removed thoroughly by washing. To achieve fast immobilization and high digestion efficiency, different functional materials and denaturants were selected. Compared with traditional in-solution digestion, the method achieved a prominent increase in identified peptides numbers and sequence coverage of proteins. Data analysis also showed that covalent binding could evidently decrease enzymatic missed cleavage for various protein sequences. Furthermore, possible peptide losses due to covalent binding were also investigated. Also, it has been proved to be efficient for complex biological sample digestion. [ABSTRACT FROM AUTHOR]

In this work, the bifunctional TiO@SiO-B(OH)@FeO@TiO sandwich-like nanosheets were designed and synthesized for the sequential selective enrichment of phosphopeptides and glycopeptides. Due to the bifunctional property of the titanium dioxide and the boronic acid group, the nanosheets were successfully applied to the enrichment of phosphopeptides and glycopeptides sequentially, evaluated by capturing phosphopeptides from tryptic digestion of model phosphoprotein bovine β-casein diluted to 0.02 ng/μL (8 × 10 mol/μL) and glycopeptides from tryptic digestion of model glycoprotein horseradish peroxidase (HRP) diluted to 0.1 ng/μL (2.5 × 10 mol/μL). The enrichment selectivity of the bifunctional nanosheets was evaluated by capturing phosphopeptides from a peptide mixture of β-casein and bovine serum albumin (BSA) with the molar ratio of 1:1000 (8.3 × 10 mol of β-casein and 8.3 × 10 mol of BSA in 100 μL) and glycopeptides from a peptide mixture of HRP and BSA up to the ratio of 1:50 (5.0 × 10 mol of HRP and 2.5 × 10 mol of BSA in 100 μL). [Figure not available: see fulltext.] [ABSTRACT FROM AUTHOR]

Ti4+ immobilized SiO2 graphene-like multilayer nanosheets were designed and synthesized for the ultrasensitive enrichment of phosphopeptides with the detection limit of 1.0 pg μL−1 (4 × 10−17 mol μL−1). The enrichment selectivity of the nanosheets was evaluated by capturing phosphopeptides from a peptide mixture of bovine β-casein (β-casein) and bovine serum albumin (BSA) with the molar ratio of 1 : 1000 (1.7 × 10−12 mol of β-casein and 1.7 × 10−9 mol of BSA in 100 μL). [ABSTRACT FROM AUTHOR]

An integrated system was developed for directly processing living cells into peptides of membrane proteins. Living cells were directly injected into the system and cracked in a capillary column by ultrasonic treatment. Owing to hydrophilicity for broken pieces of the cell membrane, the obtained membranes were retained in a well-designed bi-filter. While cytoplasm proteins were eluted from the bi-filter, the membranes were dissolved and protein released by flushing 4 % SDS buffer through the bi-filter. The membrane proteins were subsequently transferred into a micro-reactor and covalently bound in the reactor for purification and digestion. As the system greatly simplified the whole pretreatment processes and minimized both sample loss and contamination, it could be used to analyze the membrane proteome samples of thousand-cell-scales with acceptable reliability and stability. We totally identified 1348 proteins from 5000 HepG2 cells, 615 of which were annotated as membrane proteins. In contrast, with conventional method, only 233 membrane proteins were identified. It is adequately demonstrated that the integrated system shows promising practicability for the membrane proteome analysis of small amount of cells. [Figure not available: see fulltext.] [ABSTRACT FROM AUTHOR]

A novel method to isolate global N-termini using sulfydryl tagging and gold-nanoparticle-based depletion (STagAu method) is presented. The N-terminal and lysine amino groups were first completely dimethylated at the protein level, after which the proteins were digested. The newly generated internal peptides were tagged with sulfydryl by Traut's reagent through digested N-terminal amines in yields of 96 %. The resulting sulfydryl peptides were depleted through binding onto nano gold composite materials. The Au-S bond is stable and widely used in materials science. Nano gold composite materials showed nearly complete depletion of sulfydryl peptides. A set of the acetylated and dimethylated N-terminal peptides were analyzed by liquid chromatography-tandem mass spectrometry. This method was demonstrated to be an efficient N-terminus enrichment method because of the use of an effective derivatization reaction, in combination with robust and relative easy to implement Au-S coupling. We identified 632 N-terminal peptides from 386 proteins in a mouse liver sample. The STagAu approach presented is therefore a facile and efficient method for mass-spectrometry-based analysis of proteome N-termini or protease-generated cleavage products. [ABSTRACT FROM AUTHOR]