Mass Spectrometry Reviews最新文献

Extracellular vesicle (EV) proteomics has emerged as a powerful platform for decoding intercellular communication and advancing biomarker discovery across human diseases. EVs carry proteins that reflect their cells of origin, offering a minimally invasive window into physiological and pathological processes. Mass spectrometry (MS) now enables deep, high-resolution EV proteome profiling, aided by improved isolation and rigorous characterization that ensure sample purity and integrity. Advanced computational pipelines integrating quantitative modeling, spectral-library prediction, machine learning and multi-omics analysis extract meaningful biological signals, revealing subtle disease-associated EV signatures and establishing EV proteomics as a strong platform for biomarker discovery and precision medicine. This review provides an integrated framework linking EV isolation principles, characterization strategies, mass-spectrometric workflows, and computational analysis to the biological and clinical insights they generate. We also highlight key challenges and future directions, including the need for standardized reference materials, unified pre-analytical workflows, and EV proteome reference atlases. Together, these innovations are transforming EV proteomics into a next-generation tool for precision medicine.

Here we present a series of tutorials demonstrating the use of various methods which integrate structural mass spectrometry (MS) data with computational protein structure prediction methods. We give usage examples of widely used modeling frameworks, including Rosetta-based approaches (ab initio modeling, comparative modeling, and protein-protein docking) and deep learning methods such as AlphaFold2. We then describe strategies for incorporating covalent labeling, ion mobility, and surface-induced dissociation MS data into these workflows through Rosetta scoring terms and specialized applications. Finally, we provide instructions on calculating structural metrics, such as solvent accessibility, collision cross sections, and energy-resolved MS data and comparing them to actual MS data. We also introduce new PyRosetta implementations of the PARCS algorithm and the SID_ERMS_Rescore application. Together, these tutorials provide a comprehensive framework for integrating computational modeling with structural MS to enhance protein structure prediction.

Extracellular vesicles (EVs) are membrane-enclosed structures secreted by virtually all living cells, serving as essential mediators of intercellular communication in both physiological and pathological processes. There is growing interest in their potential applications as biomarkers, therapeutic targets, and drug delivery systems, which entails the need for a detailed understanding of their molecular composition. The functional cargo of EVs includes all types of biological macromolecules, among which proteins are of particular importance. As the vesicular proteome becomes increasingly mapped, research attention is gradually shifting toward post-translational modifications (PTMs), which fundamentally influence protein function and play key roles in all aspects of vesicular activity, including biogenesis, cargo sorting, recognition, and uptake. In this review, we outline recent advances in the application of mass spectrometry (MS)-based analysis of PTMs in EVs. In this context, we provide an overview of the roles of various PTMs in EV biology, discuss the impact of EV isolation methods on downstream PTM analyses, and address current challenges and approaches related to MS-based investigations. We further highlight key findings concerning specific PTMs, including glycosylation, phosphorylation, acetylation, methylation, lipidation, and small ubiquitin-like modifier (SUMOylation). Finally, we discuss studies focusing on the simultaneous analysis of multiple PTMs, as well as efforts toward multiomic data integration and single-EV characterization to resolve vesicular heterogeneity, highlighting these approaches as cutting-edge directions in the field.

Apolipoprotein B (apoB) is a key biomarker for risk assessment and treatment monitoring of atherosclerotic cardiovascular disease (ASCVD). Its clinical value has been validated by multiple studies, and its predictive performance for ASCVD risk is significantly superior to conventional lipid indicators in populations with complex lipid profiles. However, the standardization of apoB detection has long been a core bottleneck restricting its widespread clinical application, as discrepancies in results between different methods and laboratories can biases in clinical decision-making. In recent years, the development of Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) technology has provided a solution for optimizing apoB standardization. Currently, International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) is promoting the development of a primary reference measurement procedure based on mass spectrometry, aiming to achieve apoB standardization traceable to the International System of Units (SI). This review systematically outlines the clinical value of apoB, main detection methods, standardization challenges, and the application and prospects of LC-MS/MS in overcoming these challenges. We aim to provide insights for further optimizing apoB detection standardization.

This review highlights advancements in mass spectrometry (MS)-based glycomics in food and nutritional science. Carbohydrates, which are vital for human health, exhibit complex structures, making their analysis challenging. MS has become an indispensable tool for elucidating the structures of carbohydrates, including glycans, through soft ionization techniques such as MALDI and ESI. Furthermore, coupling MS with advanced separation techniques enhances sensitivity and resolution. This review underscores the pivotal contributions of Professor Carlito B. Lebrilla to glycomics research, particularly regarding milk oligosaccharides and dietary fibers, and their roles in gut health. Comprehensive food glycomic databases and MS-based studies offer valuable insights into the functions of carbohydrates and their implications for nutrition.

The exploration of protein structure and function stands at the forefront of life science and represents an ever-expanding focus in the development of proteomics. As mass spectrometry (MS) offers readout of protein conformational changes at both the protein and peptide levels, MS-based structural proteomics is making significant strides in the realms of structural and molecular biology, complementing traditional structural biology techniques. This review focuses on two powerful MS-based techniques for peptide-level readout, namely limited proteolysis-mass spectrometry (LiP-MS) and cross-linking mass spectrometry (XL-MS). First, we discuss the principles, features, and different workflows of these two methods. Subsequently, we delve into the bioinformatics strategies and software tools used for interpreting data associated with these protein conformation readouts and how the data can be integrated with other computational tools. Furthermore, we provide a comprehensive summary of the noteworthy applications of LiP-MS and XL-MS in diverse areas including neurodegenerative diseases, interactome studies, membrane proteins, and artificial intelligence-based structural analysis. Finally, we discuss the factors that modulate protein conformational changes. We also highlight the remaining challenges in understanding the intricacies of protein conformational changes by LiP-MS and XL-MS technologies.