The proteome is a dynamic landscape of proteoforms arising from genetic mutations, alternative splicing, and post-translational modifications (PTMs), which collectively drive biological function and disease phenotypes. Mass spectrometry (MS)-based proteomics has emerged as an essential technique for elucidating this molecular complexity. Although bottom-up proteomics enables deep protein identification and quantification through peptide-level analysis, it disrupts molecular connectivity and introduces a peptide-to-protein inference problem, which is suboptimal for proteoform analysis. Top-down proteomics (TDP) offers a complementary approach by analyzing intact proteins, preserving molecular connectivity, and enabling direct characterization and quantification of proteoforms. This capability is increasingly vital for understanding heterogeneous human diseases. Here, we review the evolving role of TDP in biomedical research, highlighting studies that revealed proteoform-level alterations, identified candidate biomarkers, and advanced our understanding of the roles of proteoforms in human diseases.
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.
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.
Trapped ion mobility spectrometry (TIMS) is a highly versatile alternative to the more conventional drift tube ion mobility spectrometer (DTIMS). In TIMS, ions are analyzed using an electric field that holds ions stationary against moving gas. In the basic TIMS, ions are accumulated and trapped in the electric field and then eluted over time according to their collision cross section (CCS) as the strength of the electric field is scanned down. The resultant small size and low operating voltage of TIMS compared to prior approaches make it ideal for hybridization with mass spectrometry. Since its introduction and coupling with Time-of-Flight Mass Spectrometry (TOFMS) in 2011, TIMS has been widely and successfully applied in various bioanalytical fields, including proteomics, glycomics, metabolomics, lipidomics, and native mass spectrometry. In particular, the first commercial TIMS-MS instrument introduced by Bruker Daltonics Inc. (timsTOF), launched in 2016, quickly shined as one of the main reference instruments in bottom-up proteomics. The increased peak capacity, resulting from the additional dimension of separation-that is, mobility-leads to mass spectra of reduced complexity and a greater depth of peptide identification. In this retrospective, different designs and operational modes of TIMS will be presented with a focus on the advantages, potentials and challenges of this technology within the fields of the omics sciences, spanning from metabolomics to structural biology, including single cell analysis. Additionally, the newest platforms utilizing TIMS technology will be introduced, with a focus on future applications and direction of the technology.
This review traces the first 20 years of Orbitrap mass spectrometry as a mainstream high‑resolution and accurate‑mass (HR/AM) technology. It outlines the historical development of the Orbitrap analyzer, the evolution of major instrument families, and the key technological innovations that enabled its widespread adoption. Particular emphasis is placed on hybrid and Tribrid architectures, democratization of HR/AM through benchtop platforms, extension to high‑mass and native analysis, and integration with ion mobility, advanced fragmentation methods, and emerging applications such as structural biology, isotope ratio measurements, and space research. The review concludes with a perspective on future directions and the anticipated role of Orbitrap instrumentation as the core workhorse in analytical laboratories worldwide.
Mass spectrometry (MS) has emerged as a premier method used to characterize the sequences of proteins. Top-down proteomics aims to capture the multiple sources of structural diversity reflected in proteins, such as those that arise from alternative RNA splicing events or the addition of post-translational modifications. Tandem MS (i.e., MS/MS) represents a critical component of a top-down proteomics experiment, as the resulting fragmentation patterns unveil various structural features associated with protein function. This review spotlights recent developments and applications of ion activation methods used to decipher the structural properties of intact proteins, including collisional activation and those based on the use of electrons and photons. The analysis of fragment ions generated by these MS/MS methods are also discussed, along with an outlook on future developments in the field related to instrumentation and burgeoning approaches to top-down proteomics, such as single-cell methods.
The digital ion trap (DIT) is an ion trap in which the periodic trapping field is driven by digital signals-typically with a rectangular waveform-generated by fast-switching circuits. This paper reviews the research history of rectangular wave-driven quadrupole fields, as well as the invention and development of DITs. It summarizes studies on ion motion stability and secular frequency in both 3D and 2D configurations of DITs and discusses differences in the stability diagrams of DITs arising from different definitions of the a and q parameters. Additionally, this review outlines the performance advantages of the digital driving method in mass analysis and lists the novel analytical functions that have been realized using DIT technology. Finally, it presents the latest developments in commercial DIT instruments.
Nitrooxidative stress, driven by excess reactive nitrogen species like peroxynitrite, contributes to the pathogenesis of many chronic diseases. Among its molecular footprints, 3-nitrotyrosine (3NT) has emerged as a biologically relevant marker of protein nitration. Its accumulation reflects oxidative damage and altered protein function, positioning it as a promising biomarker. Proteomics has advanced our understanding of nitrooxidative stress and its clinical implications. The integration of high-resolution MS with immunoaffinity and structural modeling enables precise mapping of nitration sites and functional interpretation. However, limitations such as low stoichiometry, ion suppression, and antibody cross-reactivity still constrain the field. Emerging computational predictors and miniaturized platforms offer promising avenues for expanding the clinical utility of 3NT. Future efforts should focus on standardizing workflows, validating site-specific modifications, and translating proteomic insights into diagnostic and therapeutic strategies. This review outlines the biochemical mechanisms of 3NT formation, emphasizing peroxynitrite-dependent and heme peroxidase-mediated pathways. Proteomic strategies for detecting and quantifying nitrated proteins are discussed, including mass spectrometry workflows, enrichment techniques, and immunodetection. Challenges in site-specific identification, antibody specificity, and ionization-induced fragmentation are addressed. Disease-specific patterns of 3NT accumulation in neurodegenerative, cardiovascular, and oncologic contexts are highlighted, along with in silico prediction of nitration sites. Despite significant methodological advances, key limitations such as low nitration stoichiometry, antibody cross-reactivity, and ionization-dependent artifacts continue to challenge confident site-specific analysis of 3-nitrotyrosine. Future progress will depend on improved enrichment strategies, standardized mass spectrometry workflows, and the integration of computational prediction tools with experimental validation. Addressing these gaps will be essential for translating nitrotyrosine profiling into robust mechanistic and clinical applications.
Liquid chromatography-mass spectrometry (LC-MS) has become an indispensable tool for elucidating molecular structures and quantifying diverse compounds within complex mixtures. Despite its versatility, it faces various challenges such as ion suppression, low sensitivity, analyte instability, and matrix effects, which are being overcome by different kinds of offline and online derivatization techniques to improve specificity and reduce potential interferences. In this context, considerable advancements have been made in reviewing and critically evaluating a wide range of developed methods and techniques; however, little attention has been given to post-column derivatization (PCD) in LC-MS. Therefore, this comprehensive review highlights state-of-the-art advancements in LC-MS with a specific focus on various types of chemical and physical PCD, and in-source derivatization. It also examines the latest instrumentation developments, highlights methods and influencing factors, and explores applications in food, proteomics, biology, pharmaceuticals, and environmental analysis from the past four decades. Besides, this review critically examines the role of PCD in LC-MS along with outlining its advantages and disadvantages. Furthermore, special emphasis is also made on prospects and insights for developing more versatile LC-PCD-MS techniques and in-source methodologies, to address ongoing challenges and aim to open new research avenues for analysts.
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.
Cancer treatment is far from optimal also because current classification systems do not reflect the complex molecular status of the tumor and its phenotype in sufficient detail. To construct molecular tumor classifiers, omics tools provide complex molecular data reflecting many aspects from genotype to phenotype. However, the true molecular effectors in the cells are proteins which often serve as potent cancer biomarkers and therapy targets. This review summarizes the method aspects that allowed the data-independent acquisition (DIA) mass spectrometry (MS) to outperform the traditional, data-dependent acquisition (DDA) approach in recent years. DIA-MS studies have already recapitulated molecular classification of colorectal and breast cancer, provided data improving molecular classification of prostate and other cancers, and led to validated diagnostic, prognostic, predictive biomarkers and therapy targets for common solid tumors. Tissue-specific spectral libraries are important for a deep characterization of tissue proteomes. Further perspectives of current cancer proteomics lie in the fields of single-cell and spatial proteomics and their integration with clinical data. The importance of functional and clinical validation is highlighted to allow stratified and/or personalized targeted therapy.
Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) has rapidly advanced in biomedical research, enabling label-free, untargeted spatial detection of metabolites, lipids, proteins, and glycans in tissue sections. However, challenges such as low ionization efficiency and chemical instability limit the detection of certain molecules. To address these issues, on-tissue chemical derivatization (OTCD) has been widely applied as an effective strategy to enhance imaging capabilities. This review systematically summarizes the development of derivatization reagents targeting different reactive functional groups and their applications in MALDI-MSI, including strategies for the derivatization of amines, carbonyls, carboxyls, double bonds, hydroxyls, thiols, and platinum-based drugs. Particular attention is given to how these derivatization reagents enhance the detection range and biological relevance by increasing molecular weight, improving ionization efficiency, and reducing background noise interference. Additionally, we explore the application of OTCD in various biological samples and discuss challenges related to experimental workflows, derivatization efficiency, and tissue integrity. This review provides important theoretical support for the advancement of MSI technology and highlights its broad potential applications in biomedical research.
Tannins are widespread specialized plant metabolites that contribute significantly to the polyphenol content of plant-based diets. Their effects on human and animal health vary depending on their structure, with potential benefits including antioxidative, antimicrobial, anthelmintic, and anticarcinogenic properties. Understanding tannin composition and quantity in plant products is essential, as their bioactivities are influenced by their functional groups. Mass spectrometry-based techniques excel in tannin analysis, offering both qualitative and quantitative insights. Combining ultrahigh-performance liquid chromatography with electrospray ionization and high-resolution and triple quadrupole mass analyzers is optimal for comprehensive tannin profiling. Such an approach enables precise analysis and helps predict tannin bioactivities. This review highlights the mass spectrometric analysis of proanthocyanidins and hydrolysable tannins, addressing ionization techniques, interpretation of multiply charged ions, characteristic fragmentations, and reaction monitoring. Applications related to tannin bioactivities are also briefly discussed, demonstrating the utility of mass spectrometry in tannin analysis in complex sample matrices.
Glycosylation, the enzymatic addition of carbohydrate moieties to proteins, is essential for immune recognition, protein folding, and disease progression. The structural complexity of glycans and the heterogeneity of glycosylation sites present significant challenges towards accurate identification and quantification, necessitating advanced methodologies for comprehensive characterization. Tandem MS (MS/MS) has emerged as the primary analytical platform for glycomics and glycoproteomics. This review highlights the recent developments in fragmentation techniques, ranging from well-established techniques such as CID/HCD and ETD, to newer and more advanced techniques such as electron-based methods (EThcD), photodissociation strategies (UVPD, IRMPD), and hybrid approaches (sceHCD, EThcD-sceHCD, HCD-pd-ETD), each providing distinct advantages towards glycan structure elucidation and glycosite mapping. This review also discusses emerging computational strategies, especially deep learning for automated interpretation of complex glycomics and glycoproteomics data.
