An integrated strategy for high-sensitive and multi-level glycoproteome analysis from low micrograms of protein samples

Bottom-Up Proteomics: Advancements in Sample Preparation

Liquid chromatography–tandem mass spectrometry (LC–MS/MS)-based proteomics is a powerful technique for profiling proteomes of cells, tissues, and body fluids. Typical bottom-up proteomic workflows consist of the following three major steps: sample preparation, LC–MS/MS analysis, and data analysis. LC–MS/MS and data analysis techniques have been intensively developed, whereas sample preparation, a laborious process, remains a difficult task and the main challenge in different applications. Sample preparation is a crucial stage that affects the overall efficiency of a proteomic study; however, it is prone to errors and has low reproducibility and throughput. In-solution digestion and filter-aided sample preparation are the typical and widely used methods. In the past decade, novel methods to improve and facilitate the entire sample preparation process or integrate sample preparation and fractionation have been reported to reduce time, increase throughput, and improve reproducibility. In this review, we have outlined the current methods used for sample preparation in proteomics, including on-membrane digestion, bead-based digestion, immobilized enzymatic digestion, and suspension trapping. Additionally, we have summarized and discussed current devices and methods for integrating different steps of sample preparation and peptide fractionation.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2019-2020

This review is the tenth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2020. Also included are papers that describe methods appropriate to analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. The review is basically divided into three sections: (1) general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, quantification and the use of arrays. (2) Applications to various structural types such as oligo- and polysaccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals, and (3) other areas such as medicine, industrial processes and glycan synthesis where MALDI is extensively used. Much of the material relating to applications is presented in tabular form. The reported work shows increasing use of incorporation of new techniques such as ion mobility and the enormous impact that MALDI imaging is having. MALDI, although invented nearly 40 years ago is still an ideal technique for carbohydrate analysis and advancements in the technique and range of applications show little sign of diminishing.

A fully integrated sample preparation strategy for highly sensitive intact glycoproteomics

A fully integrated sample preparation technology, termed Intact GlycoSISPROT, was developed for the highly sensitive analysis of site-specific glycopeptides. Through integrating all glycoproteomic sample preparation steps into a single spintip, Intact GlycoSISPROT provided a tool for site-specific glycosylation analysis with low micrograms to even nanograms of protein sample.

Elevated N-Glycosylation Contributes to the Cisplatin Resistance of Non-Small Cell Lung Cancer Cells Revealed by Membrane Proteomic and Glycoproteomic Analysis

Chemoresistance is the major restriction on the clinical use of cisplatin. Aberrant changes in protein glycosylation are closely associated with drug resistance. Comprehensive study on the role of protein glycosylation in the development of cisplatin resistance would contribute to precise elucidation of the complicated mechanism of resistance. However, comprehensive characterization of glycosylated proteins remains a big challenge. In this work, we integrated proteomic and N-glycoproteomic workflow to comprehensively characterize the cisplatin resistance-related membrane proteins. Using this method, we found that proteins implicated in cell adhesion, migration, response to drug, and signal transduction were significantly altered in both protein abundance and glycosylation level during the development of cisplatin resistance in the non-small cell lung cancer cell line. Accordingly, the ability of cell migration and invasion was markedly increased in cisplatin-resistant cells, hence intensifying their malignancy. In contrast, the intracellular cisplatin accumulation was significantly reduced in the resistant cells concomitant with the down-regulation of drug uptake channel protein, LRRC8A, and over-expression of drug efflux pump proteins, MRP1 and MRP4. Moreover, the global glycosylation was elevated in the cisplatin-resistant cells. Consequently, inhibition of N-glycosylation reduced cell resistance to cisplatin, whereas promoting the high-mannose or sialylated type of glycosylation enhanced the resistance, suggesting that critical glycosylation type contributes to cisplatin resistance. These results demonstrate the high efficiency of the integrated proteomic and N-glycoproteomic workflow in discovering drug resistance-related targets, and provide new insights into the mechanism of cisplatin resistance.

Recent Advances in Software Tools for More Generic and Precise Intact Glycopeptide Analysis

Intact glycopeptide identification has long been known as a key and challenging barrier to the comprehensive and accurate understanding the role of glycosylation in an organism. Intact glycopeptide analysis is a blossoming field that has received increasing attention in recent years. MS-based strategies and relative software tools are major drivers that have greatly facilitated the analysis of intact glycopeptides, particularly intact N-glycopeptides. This article provides a systematic review of the intact glycopeptide-identification process using MS data generated in shotgun proteomic experiments, which typically focus on N-glycopeptide analysis. Particular attention is paid to the software tools that have been recently developed in the last decade for the interpretation and quality control of glycopeptide spectra acquired using different MS strategies. The review also provides information about the characteristics and applications of these software tools, discusses their advantages and disadvantages, and concludes with a discussion of outstanding tools.

A facile "one-material" strategy for tandem enrichment of small extracellular vesicles phosphoproteome

Small extracellular vesicles (SEVs), are cell-derived, membrane-enclosed nanometer-sized vesicles that play vital roles in many biological processes. Recent years, more and more evidences proved that small EVs have close relationship with many diseases such as cancers and Alzheimer's disease. The use of phosphoproteins in SEVs as potential biomarkers is a promising new choice for early diagnosis and prognosis of cancer. However, current techniques for SEVs isolation still facing many challenges, such as highly instrument dependent, time consuming and insufficient purity. Furthermore, complex enrichment procedures and low microgram amounts of proteins available from clinical sources largely limit the throughput and the coveage depth of SEVs phosphoproteome mapping. Here, we synthesized Ti⁴⁺-modified magnetic graphene-oxide composites (GFST) and developed a "one-material" strategy for facile and efficient phosphoproteome enrichment and identification in SEVs from human serum. By taking advantage of chelation and electrostatic interactions between metal ions and phosphate groups, GFST shows excellent performance in both SEVs isolation and phosphopeptide enrichment. Close to 85% recovery is achieved within a few minutes by simple incubation with GFST and magnetic separation. Proteome profiling of the isolated serum SEVs without phosphopeptide enrichment results in 515 proteins, which is approximately one-fold more than those otained by ultracentrifugation or coprecipitation kits. Further application of GFST in one-material-based enrichment led to identification of 859 phosphosites in 530 phosphoproteins. Kinase-substrate correlation analysis reveals enriched substrates of CAMK in serum SEVs phosphoproteome. Therefore, we expect that the low instrument dependency and the limited sample requirement of this new strategy may facilitate clinical investigations in SEV-based transportation of abnormal kinases and substrates for drug target discovery and cancer monitoring.

[Advances in high-throughput proteomic analysis]

Proteomic analysis aims at characterizing proteins on a large scale, including their relative abundance, post-translational modifications, protein-protein interactions and so on. Proteomic profiling helps to elucidate the mechanisms of disease occurrence and to discover new diagnostic markers and therapeutic targets. Mass spectrometry (MS)-based proteomic technologies have advanced to allow comprehensive qualitative and quantitative proteome profiling across a myriad proteins in cells and tissues. High-throughput proteomics is the core technique for large-scale protein characterization. With the increased demand for large cohort proteomic analysis in the biomedical research field, high-throughput proteomic analysis has become a critical issue that needs to be urgently addressed. The standard shotgun proteomic workflow comprises four steps, including sample preparation, peptide separation, MS acquisition, and data analysis. Advances in these four steps have contributed to the development of high-throughput proteomics. In this review, we aimed at summarizing the current information on the state-of-the-art development of high-throughput proteomic analysis, mainly including the following topics: (1) High-throughput, automatic proteomic sample preparation methods based on liquid-handling workstations. The automation of the proteomic sample preparation steps is essential for high-throughput proteomic analysis, which will significantly reduce variation of manual operation and sample loss by multistep sample processing. The commercial liquid handling workstations, including King FisherTM Flex, Agilent Bravo, AssayMAP Bravo, and Biomek® NXP, perform the handling steps of 96- or 384-channel microplate formats using a mechanical arm that increases the throughput and robustness of sample preparation. (2) High-throughput proteomic detection methods based on microliter-flow-rate liquid chromatography coupled with mass spectrometry (micro-flow LC-MS/MS). Nanoliter-flow-rate liquid chromatography coupled with mass spectrometry (Nano-flow LC-MS/MS) is widely used in classic proteomic research due to its excellent sensitivity, which often comes at the expense of robustness. Owing to the improved robustness and decreased injection-to-injection overheads, micro-flow LC-MS/MS has become increasingly popular in high-throughput proteomic analysis. (3) Using MS instrumentation with high sensitivity and fast scanning speed to realize in-depth proteomic analysis coupled with short chromatographic gradient separation. In recent years, new MS instrumentation continues to exhibit speed of analysis and sensitivity enables the large-scale profiling of hundreds of samples. In particular, ion mobility-based MS, such as timsTOF Pro and Exploris 480 equipped with a front-end high field asymmetric waveform ion mobility spectrometry (FAIMS), which provides fast, sensitive, and robust proteome profiling, thus shifting proteomics to the high-throughput era. (4) Artificial intelligence-, deep neural network-, and machine learning-based proteome data analysis methods. These approaches have improved comprehensive proteomic analysis efficiency. Specifically, the emergence of new algorithms and the up gradation of search engines accelerate the process of high-throughput data analysis. Additionally, the challenges and future development of high-throughput proteomics are prospected. In conclusion, high-throughput proteomic technologies are expected to gradually "transform" and become powerful tools for large cohort proteomic analysis in the near future.

MicroPOTS Analysis of Barrett's Esophageal Cell Line Models Identifies Proteomic Changes after Physiologic and Radiation Stress

Moving from macroscale preparative systems in proteomics to micro- and nanotechnologies offers researchers the ability to deeply profile smaller numbers of cells that are more likely to be encountered in clinical settings. Herein a recently developed microscale proteomic method, microdroplet processing in one pot for trace samples (microPOTS), was employed to identify proteomic changes in ∼200 Barrett’s esophageal cells following physiologic and radiation stress exposure. From this small population of cells, microPOTS confidently identified >1500 protein groups, and achieved a high reproducibility with a Pearson’s correlation coefficient value of R > 0.9 and over 50% protein overlap from replicates. A Barrett’s cell line model treated with either lithocholic acid (LCA) or X-ray had 21 (e.g., ASNS, RALY, FAM120A, UBE2M, IDH1, ESD) and 32 (e.g., GLUL, CALU, SH3BGRL3, S100A9, FKBP3, AGR2) overexpressed proteins, respectively, compared to the untreated set. These results demonstrate the ability of microPOTS to routinely identify and quantify differentially expressed proteins from limited numbers of cells.