ABSTRACT Top-down proteomics approaches have emerged as powerful strategies for investigating the effects of proteoform modifications, such as amino acid substitutions, truncation, and post-translational modifications (PTMs), on protein function and activity in biological systems. In addition to proteoform structure, proteoform abundance also influences cellular biochemistry by regulating signaling pathways and altering protein–protein interaction dynamics. Thus, accurate measurement of proteoform abundance is critical for examining cellular phenotypes and disease states. The application of quantitative proteomics strategies to top-down proteomics, however, has been challenging due to difficulties in extracting and solubilizing intact proteins, the wide dynamic range in proteoform abundance, limited sensitivity for low‑abundance species, and the need for advanced separations and robust deconvolution algorithms. Recent advances in top-down proteomics strategies, including methods to improve proteoform mass spectrometry data collection, sample preparation, and data analysis, have laid the groundwork for quantitative top-down proteomics. Here, we provide a comprehensive review of current quantitative top-down proteomics strategies and examine the applications, advantages, and challenges, including label-free, metabolic labeling, chemical tag labeling, and targeted quantification strategies.

ABSTRACT Spatial heterogeneity is a defining feature of tissue organization, yet conventional proteomic analysis provides limited information about the spatial origins of identified proteins. Spatially guided proteomics addresses this limitation by using tissue imaging techniques to select regions of interest (ROIs) for localized analysis by liquid chromatography-tandem mass spectrometry (LC–MS/MS). Among the imaging modalities available for this purpose, mass spectrometry imaging (MSI) stands out for its ability to map diverse molecular species directly within tissue without predefined targets, allowing chemically distinct regions to guide tissue sampling. By bridging spatial molecular profiles with high protein coverage, MSI-guided proteomics offers comprehensive biological insight. This review examines the workflow from MSI data acquisition through ROI definition, image registration, tissue isolation, and sample preparation to LC–MS/MS analysis. We compare common MSI modalities, discuss methods for ROI isolation, and summarize advances in nanoproteomics methods that support analysis of tissue samples at the microscopic scale. We critically evaluate applications in cancer research, infectious disease, neuroscience, and environmental science. Finally, we discuss the challenges and future directions of MSI-guided proteomics. We conclude that ongoing developments in the MSI-guided proteomics workflow position it as an emerging strategy for investigating localized biological processes within heterogeneous tissues.

ABSTRACT Posttranslational modifications (PTMs) play critical regulatory roles in cellular processes, and their dysregulation is implicated in numerous diseases and pathological conditions. Their importance to biological functions has spawned many efforts to accurately identify and quantify protein modifications using high-throughput methods, especially liquid chromatography tandem-mass spectrometry (LC-MS/MS). The typically low stoichiometry of PTMs in biological samples often necessitates enrichment strategies to achieve sufficient analytical sensitivity. However, the growing number and diversity of published enrichment methods have made it challenging to evaluate key methodological differences and their respective advantages. This review examines enrichment strategies for the major PTM classes: phosphorylation, acetylation, ubiquitination, SUMOylation, methylation, glycosylation, and ADP-ribosylation. Immunoaffinity-based, chromatographic, and chemical derivatization approaches are compared for each class in terms of their underlying principles and practical trade-offs. Based on published methods, the review considers enrichment specificity, coverage depth, sample input requirements, and workflow compatibility, with the aim of providing a consolidated reference to guide method selection and optimization for single- and multi-PTM profiling.

ABSTRACT Top-down proteomics and top-down mass spectrometry approaches provide direct characterization of proteoforms; the specific molecular forms of proteins, including post-translational modifications, truncations, alternative splicing, and sequence variants. To date, most top-down studies have been performed under denaturing conditions, losing critical information about protein folding and noncovalent protein-protein and protein-ligand interactions. However, recent efforts to apply non-denaturing, or native, ionization to top-down mass spectrometry and top-down proteomics have shown substantial promise for characterizing these higher-order and more transient interactions. This review covers progress over the last 35 years in non-denaturing top-down approaches and addresses the inherent strengths and challenges of the technique. We cover three major areas of applications: (1) Ligand binding and drug discovery, (2) Structural biology, and (3) Proteomics aspects and bioinformatics.

ABSTRACT Non-targeted screening (NTS) coupled with high-resolution mass spectrometry (HRMS) has revolutionized detection of unknown contaminants of emerging concern (CECs), including pharmaceutical transformation products, novel disinfection byproducts, emerging PFAS variants, and a wide diversity of other organic micropollutants, without reliance on reference standards. This critical review focuses on aquatic matrices (wastewater, surface water, drinking water, and related environmental waters) and examines current trends in LC-HRMS and GC-HRMS workflows, highlighting their complementarity for comprehensive chemical-space coverage in complex environmental matrices. Principal advances include generic sample preparation strategies, advanced data processing tools (MZmine, patRoon, Compound Discoverer), Schymanski et al.-based identification frameworks with recent harmonization efforts, and the integration of suspect-enhanced non-target approaches. Complementary LC/GC workflows, enhanced by ion mobility and multi-dimensional separations, significantly improve feature detection and identification confidence for unknowns. The review further explores the translation of NTS data into risk-assessment frameworks via effect-directed and virtual EDA approaches, as well as selected applications in wastewater-based epidemiology (WBE). Key challenges persist, including high data volume and complexity, false positives/negatives, matrix effects, semi-quantification uncertainty, and limited inter-laboratory reproducibility. Recent harmonization initiatives by the NORMAN network and interlaboratory studies are progressively addressing these gaps through standardized QA/QC and reporting practices. In conclusion, LC/GC-HRMS NTS offers transformative potential for early-risk detection and proactive regulatory decision-making, particularly in the context of expanding EPA PFAS monitoring. Future perspectives emphasize AI-driven automation, multi-omics integration, real-time monitoring platforms, and stronger linkage to policy frameworks. As harmonization and technological advances mature, NTS will shift environmental analysis from reactive targeted monitoring toward predictive, systems-level protection of human and ecological health.

ABSTRACT Mass spectrometry-based proteomics has been applied with considerable success to the analysis of formalin-fixed, paraffin-embedded (FFPE) tissues, and this success raises the question of whether the same methods can be applied to the embalmed human cadaveric specimens that are used in anatomical education and research. In this review, a theoretical framework is presented for the application of proteomic methods to embalmed cadaveric tissues, in which the feasibility of the approach is evaluated on the basis of the methods that have been established for FFPE tissue, and the critical gaps in the evidence are identified. Four questions are addressed: which of the methods that have been established for FFPE tissue can be transferred to embalmed tissue; how the post-mortem interval and the chemistry of the embalming fluid limit that transfer; which acquisition and quantification strategies are suited to proteins that carry a heavy burden of chemical modification; and which applications are already established in preserved human tissue and which of them still require validation in embalmed specimens. A comprehensive review of the literature was carried out on the proteomic methods for FFPE tissue, on the kinetics of post-mortem protein degradation, on the chemistry of embalming, and on the strategies for the reversal of crosslinks. Studies of post-mortem protein degradation place the critical threshold for embalming at 24 h if protein integrity is to be maintained; preservation is best when embalming takes place within 6−12 h. Embalming with formaldehyde produces extensive crosslinks between the proteins that are similar to those of the FFPE processing, and this suggests that the strategies for the reversal of the crosslinks that have been established for FFPE tissue may be compatible with embalmed tissue. The alternative methods of embalming, which include the ethanol-based and the salt-based approaches, may offer a better preservation of the proteins. However, the extended periods of preservation and the multi-component chemical environment of cadaveric embalming present challenges that exceed those of the clinical FFPE specimens. No published study has yet carried out a full proteomic analysis of an embalmed human cadaver. The rates of protein identification and the effectiveness of the processing remain theoretical projections that require experimental validation. Although the theoretical considerations suggest that the approach is feasible, there are significant gaps in the evidence between the established methods for FFPE tissue and the requirements of cadaveric specimens. The framework identifies the priority areas for experimental validation, which are the optimization of the reversal of the crosslinks, the assessment of the recovery of proteins with the different methods of embalming, and the development of specialized protocols for processing. The successful development of cadaveric proteomics could improve anatomical education through the characterization of the tissues at the molecular level, could support forensic applications, and could enable biomedical research on human specimens that are well characterized. However, extensive experimental validation will be required before what is possible in theory can be turned into a method that is used in practice.

Mass Spectrometry Reviews, Volume 45, Issue 6, Page 1025-1026, November/December 2026.

ABSTRACT The use of MALDI mass spectrometry for the analysis of carbohydrates and glycoconjugates is a well-established technique and this comprehensive review is the twelfth update of the original article published in 1999 and brings coverage of the literature to the end of 2024. Although still popular for glycoconjugate analysis, recent years have seen a slight drop in its usage with electrospray and LC-MS techniques becoming more widely used. The review follows the same general format as previous reviews. Much of the material relating to applications is presented in tabular form whereas papers relating to method development are discussed in more detail. The review is divided into three sections: (1) general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, quantification, and the use of computer software for structural identification. (2) Applications to various structural types such as oligo- and polysaccharides, glycoproteins, glycated proteins, glycolipids and natural products, and (3) other general areas such as medicine, biopharmaceuticals, industrial processes and glycan synthesis where MALDI is extensively used. As with previous reviews in this series, this review also includes a few papers that describe methods appropriate to analysis by MALDI, such as sample preparation, even though the ionization method is not MALDI. Much of this work is tabulated. MALDI is still an ideal technique for carbohydrate analysis, particularly in its rapidity, ease of use and its ability to produce single ions from each analyte. Improvements in the technique and range of applications show little sign of diminishing.

Mass Spectrometry Reviews, EarlyView.

ABSTRACT Identification of a chemical agent yields insights into its physicochemical properties. By examining the intrinsic characteristics and environment of a compound, information about its history can be gathered. The main objective of authentication/forensic approaches to chemicals is to trace the history of the compound's origin, regardless of its nature (e.g., environmental pollutants, drugs, or toxicants). This review presents several scientific fields that share a common objective: using mass spectrometry (MS) to obtain source information from diverse samples and chemicals. From targeted analysis to the full screening of non-targeted chemical space, direct and coupled MS approaches provide powerful capabilities for addressing source-determination concerns, as described in this review. Novel sampling and ionization methods have proven to have a significant impact on expanding MS applications across diverse sample types. This review covers the main methods for determining chemical origins, ranging from targeted confirmation of known compounds to non-targeted identification of unknown compounds under challenging experimental and matrix-related conditions.

ABSTRACT 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.

ABSTRACT The high prevalence and substantial burden of kidney diseases necessitate advanced approaches to elucidate molecular mechanisms and promote precision medicine. Mass spectrometry (MS)-based proteomics has evolved into a widely used analytical platform, delivering high-sensitivity, high-throughput protein profiling capabilities that have contributed substantially to biomarker discovery, mechanistic dissection, and therapeutic target identification across a broad range of kidney diseases. This review provides a comprehensive overview of MS-based proteomics applications in kidney disease research, covering progress in biomarker identification, pathogenic mechanism interrogation, and clinical translation. It highlights methodological advances, emerging trends, and persistent challenges that shape the field. Existing literature has uncovered abundant disease-specific biomarkers and revealed key pathogenic pathways, including podocyte injury-associated protein interaction networks, dysregulated complement activation, and metabolic reprogramming, and have critically assessed their translational potential. Additionally, investigations into posttranslational modifications such as phosphorylation and glycosylation have provided valuable insights for targeted therapies. Collectively, these findings illustrate the contributions of MS-based proteomics to the characterization of disease molecular heterogeneity, the identification of key pathogenic drivers, and the development of precision medicine approaches. This review further addresses current challenges in clinical applications, including sample heterogeneity, data complexity, and standardization issues. We additionally emphasize the critical need for minimum reporting standards and multicenter harmonization to accelerate the clinical translation of renal proteomics. Future research should focus on integrating multiomics and artificial intelligence-driven data mining to enhance precise disease subtyping, dynamic monitoring, and personalized treatment strategies.

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