Journal of Proteome Research最新文献

Florfenicol is valued for its clinical safety, particularly its reduced bone marrow toxicity compared to other old antibiotics of chloramphenicols. However, the rise of bacterial resistance threatens its efficacy. To address this, we evolved a florfenicol-resistant strain of Vibrio parahaemolyticus (VP-R_FFC) and used metabolomics to identify a suppressed glucose metabolic state as a key vulnerability. We found that exogenous glucose potentiated florfenicol's killing effect against the resistant strain in a dose- and time-dependent manner in vitro. It also played a role in vivo. Mechanistically, glucose reactivation rewired central carbon metabolism in two ways: (1) it fueled the pyruvate cycle, enhancing the proton motive force (PMF) to promote florfenicol uptake and (2) it stimulated the pentose phosphate pathway, increasing reactive oxygen species (ROS) production to amplify antibiotic lethality. Thus, our work identifies glucose-mediated metabolic reprogramming as a potent strategy to resensitize resistant pathogens to florfenicol by simultaneously increasing drug influx and oxidative damage.

Forensic proteomics has rapidly established a significant role in forensics, particularly when DNA analysis is insufficient. Proteomics has been frequently recognized for helping reveal useful information about the origin, state and context of forensic samples. Proteins are considered crucial biomarkers in biological samples because of their ability to elucidate cellular functions and post-mortem alterations. Combining advanced mass spectrometry and bioinformatics has increased the importance of proteomics in forensic sciences. The current study examined the use of proteomic technologies, mass spectrometry, and sophisticated software across the key domains of forensic research. The procedure for Post-Mortem Interval (PMI) estimation and body fluid classification proved to be more precise because of the use of machine learning. Peptide biomarkers have helped identify various species by samples of blood, saliva, and semen, and recognize brain, muscles, and skin tissues. Despite significant advancements, the wide acceptance of forensic proteomics remains problematic due to intricate sample stability, high equipment costs, and strict legal standards. Recent advancements in analytical sensitivity, data interpretation tools, and collaborative efforts toward robust protocols position forensic proteomics as an indispensable component of the forensic toolkit. This review indicates the increasing relevance of proteomics in forensic applications, especially relating to PMI estimation, body fluid differentiation, and disease profiling. It promises to significantly enhance the depth of evidentiary interpretation and contribute to more precise and equitable outcomes in the criminal justice system. Proteomic biomarkers need further validation across a range of environments, and standardized protocols should be developed and tested to ensure that proteomics is suitable for forensic use in the courts.

Proteomics research has increasingly focused on human cells, tissues, and fluids; however, comprehensive data on dental tissues remain limited. Dentine, a mineralized component of teeth, contains structural proteins and bioactive molecules that can modulate pulp cell activity and support regeneration when released. Understanding its protein composition is therefore essential. Previous studies have identified relatively few dentine proteins, and technical challenges have hindered reproducibility. Traditional extraction methods also rely on strong acids that lack clinical relevance. In this technical note, we introduce a workflow combining EDTA-based dentine extraction under clinically relevant conditions with peptide-level fractionation using high-pH reversed-phase chromatography. This approach was compared with unfractionated samples, SDS-PAGE protein-level fractionation, and strong cation exchange (SCX) peptide-level fractionation, all followed by LC-MS/MS. Data are available via ProteomeXchange (PXD070849). This workflow enabled the identification of 514 proteins compared with 238 (unfractionated), 428 (SDS-PAGE), and 193 (SCX). High-pH reversed-phase chromatography contributed 217 unique identifications, exceeding those from other techniques. Although used in other proteomic systems, this methodology has not previously been applied to dentine matrix extracts and represents a promising approach for improving protein discovery.

Ca²⁺/calmodulin-dependent kinase 1 delta (CaMK1δ) plays a central role in regulatory pathways associated with ATP, reduction potential, and Ca²⁺/calmodulin (CaM). Mass spectrometry (MS)-based structural proteomics incorporating FragPipe and pLink cross-link analysis was used to reveal conformation selection induced by dialysis with ATP, reducing agents, and CaM. The structural changes were mediated via cysteine and phosphate cross-linking and loop-linking of the activation loop within the C-terminal. Phosphate loop-linking was validated by β-elimination and Michael addition (BEMAD) reactions, aligning these findings with phosphoproteomics analyses of phosphorylation events. Oxidizing conditions inhibited the functionality of CaMK1δ wild-type. A novel mechanism of autoinhibition via cysteine cross-linking between the activation loop (αT) and C-terminal (αI) helices was identified. The microenvironment associated with CaMK1δ, including ATP availability, CaM concentration, and reduction potential, modulates the structural rearrangements underlying autophosphorylation. Phosphoproteomics, cysteine and phosphate cross-linking MS, and structural molecular modeling were used to describe kinase activation, allowing the activation of regulatory kinases to be reevaluated. We propose that regulatory kinases respond to an array of kinase family-specific distinct second messengers which can be studied using this multiomics framework, giving significant new insights into PTMs as well as the associated protein structure rearrangements.

Affinity-based protein profiling (AfBPP) allows us to identify target proteins that bind drugs or other small molecules of interest in complex samples. As an enrichment technique, label-free AfBPP often generates data with high missingness, particularly in negative control samples. We developed an R package, chemoprotR, which enables both quantitative and qualitative statistical analyses of chemoproteomic data, and applied it to the identification of specific benzodiazepine drug targets in the brain. Benzodiazepines comprise a class of drugs that affect GABA_A receptors through positive allosteric modulation, but benzodiazepine interactions with other proteins are not fully understood. To this end, we synthesized benzodiazepine affinity-based probes (AfBPs) and applied them to rat brain synaptosomes. Our benzodiazepine AfBPs identified GABA_A receptor subunits and other proteins with ion channel functions. Across the three probes, there was minimal overlap in protein targets identified by competitive labeling with flurazepam, and FR-DA, the probe based on flurazepam, yielded more significant protein targets than the probes based on flunitrazepam. These results demonstrate the ability of benzodiazepine AfBPs to identify protein targets when used with an authentic benzodiazepine to compete for binding sites and highlight the utility of combined statistical analyses for the interpretation of presence-absence data in AfBPP data sets.

Cisplatin is a widely used chemotherapeutic agent for triple-negative breast cancer (TNBC), but resistance remains a major challenge. Understanding the molecular alterations driving this resistance is essential for identifying therapeutic targets. In this study, we employed an integrated proteomics and lipidomics approach to elucidate key pathways associated with cisplatin resistance. Employing high-resolution mass spectrometry, we conducted a comparative analysis between cisplatin-resistant (cisR) and cisplatin-sensitive (cisS) TNBC cell lines to discover resistance-associated alterations in protein and lipid expression. Proteomic analysis revealed overexpression of extracellular matrix (ECM) remodeling proteins, COL6A1, COL6A2, COL6A3, and VTN, that support epithelial-mesenchymal transition (EMT) and chemoresistance. Membrane-associated proteins such as TIMP2, MMP14, and APP were also elevated, indicating enhanced invasive and pro-survival signaling. Lipidomic alterations, including upregulation of FABP3, FABP4, LPL, and downregulation of PLA2G4A, indicated increased lipid uptake, metabolic rewiring, and membrane restructuring. Notably, elevated long-chain phosphatidylcholines and decreased sphingomyelins suggested increased membrane rigidity and reduced cisplatin permeability. Additionally, dysregulation of CDK activity through CCND2, CCND3, and CCNB2 overexpression indicated accelerated cell cycle progression and evasion of DNA damage checkpoints. Together, this integrative analysis highlights ECM remodeling, cytoskeletal dynamics, and lipid metabolism as major contributors to cisplatin resistance and identifies potential therapeutic markers for TNBC.

O-linked β-N-acetylglucosamine (O-GlcNAc) modification (O-GlcNAcylation) underlies the pathogenesis of multiple cancers, including hepatocellular carcinoma (HCC). However, comprehensive and quantitative characterization of site-specific O-GlcNAcylation at the proteome scale remains technically challenging. Here, we employed an integrated workflow for the quantitative O-GlcNAc proteomics of HCC and controls. Proteins from liver samples were subjected to chemoenzymatic labeling, photocleavable alkyne-biotin-based enrichment, proteolytic digestion, and isotopic labeling with tandem mass tags. The O-GlcNAc peptides were analyzed by a nanoUPLC-MS/MS system in HCD product-dependent EThcD (HCD-pd-EThcD) mode for site mapping and quantification. A total of 440 O-GlcNAc peptides, representing 305 sites on 196 proteins, were confidently identified. Differential analysis revealed 190 O-GlcNAc peptides from 121 proteins significantly upregulated in HCC after normalization to their corresponding protein abundance. Functional enrichment and protein-protein interaction analyses indicate that proteins with increased levels of O-GlcNAcylation are involved in nuclear transport, transcriptional regulation, and ATP-dependent chromatin remodeling. Our work provides quantitative proteomic insights into O-GlcNAcylation in HCC, revealing global upregulation and functional clustering of O-GlcNAc-modified proteins. These findings will help elucidate the functional roles of O-GlcNAcylation in liver cancer, facilitating the development of novel therapeutics and sensitive biomarkers.

Cystic fibrosis (CF), also known as mucoviscidosis, is a rare, autosomal recessive genetic disease. It is caused by various mutations in the CFTR (Cystic Fibrosis Transmembrane Conductance Regulator) gene, which disrupt the normal function of the chloride ion channel. Clinical manifestations of CF typically include recurrent respiratory infections, chronic airway inflammation, a progressive decline in lung function, and intermittent pulmonary exacerbations. The primary aim of our study is to identify plasma biomarkers in patients with cystic fibrosis through untargeted metabolomic and lipidomic analyses, with the goal of enabling early detection, accurate diagnosis, and effective monitoring of the disease. Liquid chromatography (LC) coupled with time-of-flight mass spectrometry (TOF-MS) was employed to discriminate the 24 cystic fibrosis patients from the 26 age- and gender-matched healthy controls. Multivariate statistical and pathway enrichment analyses revealed dysregulation in galactose metabolism, glycolysis/gluconeogenesis, bile acid metabolism, fatty acid metabolism, steroid hormone biosynthesis, and amino acid catabolism. The quantification of the targeted cystic fibrosis biomarkers identified by combined lipidomic and metabolomic analyses will be valuable for early diagnosis and treatment.

Proteases play crucial roles in numerous biological processes through specific protein cleavage, and their dysregulation has been implicated in various diseases. To better understand protease specificity, we developed a lauroylation-assisted proteomic identification of protease cleavage sites (PICS) workflow that labels and enriches targeted protease-generated neo-N-termini using economical reagents and standard laboratory equipment. The lauroylation enables both discrimination of the neo-N-termini in LC-MS/MS and efficient enrichment on a C18 StageTip by exploiting its hydrophobicity. Among tested acylations, we found lauroylation to be optimal for PICS and improved enrichment and fractionation conditions. We demonstrated that this method can profile specificities of multiple proteases with high sensitivity. Furthermore, we extended this concept to N-terminomics to examine proteolysis at the protein level. Protein N-terminal dimethylation is used for labeling, and tryptic internal peptides are lauroylated for removal. This approach identified over 1500 cleavages induced by etoposide, including 912 Asp-cleaved sites consistent with caspase-3 motifs and sensitive to inhibition by Z-DEVD-FMK. Additionally, 2286 protein N-termini were identified in untreated cells, including 1794 non-ORF N-termini with 665 previously annotated processing sites. These results demonstrate that our workflow provides a simple, economical, and widely applicable method for characterizing protease cleavage at both peptide and protein levels.