J Proteome Res
· 2026 Apr · PMID 41740191
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Mitochondria play a central role in liver physiology by regulating key metabolic processes. Consequently, mitochondrial dysfunction is a hallmark of multiple liver diseases, including steatosis, steatohepatitis, and live...Mitochondria play a central role in liver physiology by regulating key metabolic processes. Consequently, mitochondrial dysfunction is a hallmark of multiple liver diseases, including steatosis, steatohepatitis, and liver failure following hepatectomy. Subcellular fractionation is widely used to isolate mitochondria from liver cells or tissue; however, the enrichment and purity of isolated fractions are critical to ensure reliable downstream functional and proteomic analyses. Conventional validation methods, such as immunoblotting of organelle-specific markers, are limited by low throughput, restricted sensitivity, and variability. In this study, we present a targeted proteomics strategy based on parallel reaction monitoring (PRM) to quantitatively assess the enrichment of cytosolic, mitochondrial, and nuclear fractions obtained from liver samples using commercial isolation kits. PRM analyses demonstrated robust and compartment-specific enrichment in both PLC/PRF/5 cells and mouse liver tissue. In PLC/PRF/5 cells, high nuclear/cytosolic enrichment was observed for Prelamin A/C, while mitochondrial markers such as ATPase showed strong mitochondrial/cytosolic ratios. Cytosolic markers consistently displayed enrichment in the cytosolic fraction. Similar trends were observed in mouse liver tissue, confirming applicability across biological systems. Overall, these results highlight PRM as a sensitive, reproducible, and cost-effective alternative to immunodetection approaches for evaluating subcellular fraction purity, supporting high-quality mitochondrial preparations for translational hepatology studies.
Alves Martins Nogueira CE, Olímpio F, Salardani M
… +11 more, Barcick U, Fonseca LR, Aimbire F, Lima Jedlicka LD, Loures FV, Capelo LP, Lima V, Monteiro de Oliveira T, Barros BCSC, Serrano SMT, Zelanis A
J Proteome Res
· 2026 Mar · PMID 41739603
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Melanoma metastasis involves extensive remodeling of the tumor microenvironment, yet the proteolytic processes underlying pulmonary colonization remain poorly defined. Using the B16F10 intravenous melanoma model in C57BL...Melanoma metastasis involves extensive remodeling of the tumor microenvironment, yet the proteolytic processes underlying pulmonary colonization remain poorly defined. Using the B16F10 intravenous melanoma model in C57BL/6J mice, we performed an integrative degradomic analysis of metastatic lung tissue, plasma, and secretome of early passaged primary cultures derived from metastatic foci. Semispecific database searches identified nearly 8,000 semitryptic peptides across compartments, with the secretome exhibiting the highest burden of cleavage events, indicating an intensely proteolytic microenvironment. Cleavage profiles were compartment-specific, dominated by actin in metastatic lung tissue, α2-macroglobulin in plasma, and SPARC in the secretome. Cleavage-site motif analysis revealed conserved His/Ser (P1/P1') preferences in tissue and plasma, whereas the secretome showed a distinct Leu/Ser pattern. Discriminant-feature analysis uncovered unique proteolytic signatures for each compartment, and peptide-level mapping implicated at least 11 proteases─including MMP2, cathepsin D, and cathepsin E─as major contributors to metastatic niche remodeling. Functional enrichment demonstrated coordinated impacts on extracellular matrix organization, inflammation, and metabolic adaptation. This work provides a multicompartment degradomic resource that captures proteolytic remodeling in melanoma lung metastasis and establishes a foundation for future functional and translational studies.
Li XF, Lu YH, Yi LT
… +8 more, Xu K, Li C, Liu SC, Zhang YY, Li R, Meng TG, Sun QY, Xu CL
J Proteome Res
· 2026 Mar · PMID 41739453
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Normal fertilization triggers Ca oscillations in the oocyte cytoplasm. Different assisted oocyte activation (AOA) protocols differ markedly in the calcium dynamics, yet their respective impacts on embryo gene expression...Normal fertilization triggers Ca oscillations in the oocyte cytoplasm. Different assisted oocyte activation (AOA) protocols differ markedly in the calcium dynamics, yet their respective impacts on embryo gene expression remain incompletely understood. In this study, we employed strontium chloride (SrCl), which induces Ca oscillations, A-23187, which induces a single Ca rise, and RO-3306, which activates oocytes without a Ca rise by directly inhibiting CDK1 activity, to estimate the effect of different parthenogenetic activation protocols on embryo gene expression using fertilized embryos as a control. We compared the data of omics among different blastocysts. The transcriptional profiles of diverse parthenogenetic blastocysts were distinct from those of normal blastocysts, while transcriptional levels among different parthenogenetic blastocysts were relatively similar. Similarly, proteomics analysis revealed different protein expression profiles of diverse parthenogenetic blastocysts compared to those of normal blastocysts, especially proteins related to fatty acid biosynthesis, fatty acid β-oxidation metabolic, mitochondria, RNA splicing, and RNA binding. Some protein expression differences were also observed among different parthenogenetic blastocysts. However, all parthenogenetic blastocysts exhibited similar differentially expressed pathways. Our results show that gene expression in parthenogenetic embryos is distinct from that of normally fertilized embryos, and Ca rise, especially Ca oscillation, is important for proper gene expression in early embryos.
J Proteome Res
· 2026 Mar · PMID 41738589
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There is a growing interest in developing high-throughput and high-sensitivity mass spectrometry methods for proteomic profiling of low-input samples, such as sorted cells or spatially resolved tissue samples. Data-indep...There is a growing interest in developing high-throughput and high-sensitivity mass spectrometry methods for proteomic profiling of low-input samples, such as sorted cells or spatially resolved tissue samples. Data-independent acquisition mass spectrometry (DIA-MS) coupled with short-gradient liquid chromatography (LC) is gaining significant attention for providing deep proteome coverage in low-input samples, particularly with the recent release of high-speed mass spectrometers. However, the quantification performance of existing DIA workflows for low-input samples has not been extensively evaluated, and there is no consensus on optimal informatics workflows to obtain high-quality quantitative data. As such, we systematically evaluated multiple factors in low-input DIA workflows on an Astral MS, including MS acquisition parameters, data analysis software (DIA-NN, Spectronaut, and FragPipe), LC separation gradient lengths, database searching algorithms, and protein quantification approaches. Using three-species proteome samples (human, yeast, and ) with total input ranging from 0.1 ng to 10 ng and predefined quantity ratios, we focused on proteome coverage, quantification accuracy, and precision, which are the most important considerations when applying these methods in biological applications. Our evaluation suggested a preferred DIA workflow for low-input samples, which involves using a FAIMS interface, DIA-NN-based library-free database search with the enabled match between runs (MBR) function, and MS1-level protein quantification with the maxLFQ algorithm.
Cao H, Xiong J, Su Y
… +6 more, Liu X, Tang T, Tang Y, Yu W, Li Y, Li D
J Proteome Res
· 2026 Mar · PMID 41736443
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Host cell proteins (HCPs) are critical process-related impurities in monoclonal antibody (mAb) production that can compromise product safety, efficacy, and stability. Traditional enzyme-linked immunosorbent assays (ELISA...Host cell proteins (HCPs) are critical process-related impurities in monoclonal antibody (mAb) production that can compromise product safety, efficacy, and stability. Traditional enzyme-linked immunosorbent assays (ELISA) provide total HCP quantification but lack the specificity to detect individual high-risk species. While mass spectrometry (MS) has emerged as a powerful orthogonal approach, offering molecular-level resolution, high sensitivity, and the ability to identify and quantify low-abundance, potentially immunogenic HCPs. This review provides a strategy-oriented and practice-driven analysis of MS-based HCP analytics, emphasizing how recent methodological advances address real-world challenges in bioprocess development and regulatory compliance. We critically examine optimized sample preparation workflows, including buffer and matrix mitigation, native and denaturing digestion, antibody depletion, and HCP enrichment, alongside multidimensional chromatographic separations and advanced acquisition strategies spanning DDA, DIA, and targeted MS. Particular attention is given to emerging hybrid and integrated workflows, such as DDA-PRM-dMRM acquisition schemes, that bridge discovery and routine quality control. Beyond these, our review places MS-based HCP analysis in evolving global regulatory expectations, providing a comparative and practical interpretation of guidance from the USP, EP, JP, BP, and ChP, with emphasis on validation, standardization, and interlaboratory reproducibility. By integrating technical advances with regulatory frameworks and case-based evidence, our review highlights how MS is transitioning from a supportive characterization tool to a core component of risk-based and multiattribute HCP control strategies in modern biopharmaceutical development.
Wang T, Huang W, Li Z
… +6 more, Cao Z, Pu K, Shao D, Wu J, Li J, Zhao N
J Proteome Res
· 2026 Mar · PMID 41734295
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Intracerebral hemorrhage (ICH) remains a major cause of morbidity and mortality, with no rapid blood-based biomarkers available to assess secondary brain injury. This study aimed to identify a circulating pan-cell death...Intracerebral hemorrhage (ICH) remains a major cause of morbidity and mortality, with no rapid blood-based biomarkers available to assess secondary brain injury. This study aimed to identify a circulating pan-cell death protein signature for diagnosing and prognosing ICH. We prospectively enrolled 60 ICH patients and 60 age/sex-matched healthy controls, collecting plasma at defined time points after ICH onset. Using Olink proteomics, we identified 13 apoptosis-related proteins with significant dysregulation. Four key proteins─TLR4, ALOX15, FTL, and BMF─were validated through ELISA and RT-qPCR, showing good diagnostic performance (AUCs 0.799-0.835). A multiprotein logistic model demonstrated excellent diagnostic accuracy (AUC = 0.955). These biomarkers correlated with clinical severity and prognosis, including hematoma volume and a 90-day modified Rankin Scale (mRS). Additionally, animal models confirmed time-dependent upregulation of TLR4 in astrocytes. This pan-cell death protein signature provides valuable insights into ICH pathology and offers a promising tool for early diagnosis, risk stratification, and therapeutic targeting.
J Proteome Res
· 2026 Mar · PMID 41732897
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Metabolites have traditionally been defined as organic molecules smaller than 1500 daltons (Da). However, recent advances in analytical technologies and chemoinformatics have uncovered a wider chemical diversity, includi...Metabolites have traditionally been defined as organic molecules smaller than 1500 daltons (Da). However, recent advances in analytical technologies and chemoinformatics have uncovered a wider chemical diversity, including biologically significant metabolites exceeding this conventional size cutoff─such as polypeptides, glycosphingolipids, and bacterial lipopolysaccharides. Detecting these larger metabolites challenges standard metabolomics approaches and necessitates optimized mass spectrometry acquisition parameters. In this perspective, the analysis of multiple databases (HMDB blood, GNPS, Plant Molecular Network [PMN], Natural Product Atlas [NPA] fungi, NPA bacteria, and MiMeDB) confirms that although most metabolites are below 1000 Da, notable populations exceed this threshold, particularly in bacterial data sets. Furthermore, reanalysis of liquid chromatography-mass spectrometry (LC-MS) data sets from diverse biological samples, especially bacteria-rich matrices like feces and skin, reveals features (peaks with / and retention time) extending beyond 1500 /. These findings underscore that metabolites are often larger than commonly recognized in the literature. Therefore, the definition of metabolites should evolve to accommodate their size diversity, ensuring accurate knowledge dissemination to new generations of metabolomics researchers.
Lin S, Yao X, Guo P
… +5 more, Shi H, Luo H, Ke K, Teng T, Weng S
J Proteome Res
· 2026 Mar · PMID 41725255
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BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is characterized by extreme molecular heterogeneity and poor prognosis. Understanding its multiomics molecular heterogeneity may facilitate precise classification and i...BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is characterized by extreme molecular heterogeneity and poor prognosis. Understanding its multiomics molecular heterogeneity may facilitate precise classification and individualized treatment. METHODS: Transcriptomic and proteomic profiles from 140 PDAC patients were integrated using Similarity Network Fusion (SNF) to identify robust molecular subtypes. Sparse partial least-squares discriminant analysis (sPLS-DA), differential expression analysis, and network-based functional enrichment were employed to characterize subtype-specific features. Associations between molecular subtypes, clinicopathological variables, and patient survival were further assessed. RESULTS: Three PDAC subtypes were identified with distinct molecular and clinical profiles. The basic subtype (SNF-1) showed no significant transcriptomic or proteomic distinction. The pancreatic secretory subtype (SNF-2) exhibited highly active endocrine and exocrine secretion pathways, suggesting strong dependence on pancreatic secretory function. The glycolytic-immune suppressive subtype (SNF-3) displayed prominent immune-evasion features and activation of multiple drug-resistance pathways, consistent with its poorest prognosis. These findings reveal distinct molecular programs underlying PDAC heterogeneity and its clinical manifestations. CONCLUSION: This integrative multiomics analysis delineates three biologically and clinically distinct PDAC subtypes. The results highlight metabolic and functional diversity underlying tumor heterogeneity, offering new insights for precision stratification and the development of targeted therapeutic strategies.
J Proteome Res
· 2026 Mar · PMID 41720578
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species have attracted considerable research interest, because they are widely distributed, mostly plant-pathogenic, and exhibit unique characteristics. Abiotic factors influence intra- and interspecies variations in pat...species have attracted considerable research interest, because they are widely distributed, mostly plant-pathogenic, and exhibit unique characteristics. Abiotic factors influence intra- and interspecies variations in pathogenicity and/or virulence of these fungi. However, the mechanisms involved in causing these variations are not well understood. Iron is an indispensable element in several molecular and biological processes. Yet, excessive abundance of iron can be toxic to organisms due to Fenton-like reactions. This study aimed to gain insights into the type and extent of iron-responsive proteomic and secretomic changes in sp. strain CMW4456 cultured in liquid media supplemented with iron using a multiomics approach. Significant iron-dependent alterations of proteins involved in metabolism and growth were observed in the proteomes and secretomes. Iron supplementation at 100 μM did not elicit an oxidative stress response by the fungus. Our analyses revealed three putative siderophore biosynthetic gene clusters (BGCs) in the genome and expression of proteins encoded by some BGC genes in the proteome. This knowledge contributes to a better understanding of the mechanisms employed by an sp. in response to iron, gives insights into possible modes for inhibiting or attenuating the pathogenicity and/or virulence of spp., and can be valorized for more biotechnological applications.
Wang X, Archarya DD, Brown CJ
… +7 more, Clevenger K, Hu J, Kretsch A, Menegatti C, Xiong Q, Bittremieux W, Wang M
J Proteome Res
· 2026 Mar · PMID 41709631
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Tandem mass spectrometry (MS/MS) has become the analytical backbone of large-scale untargeted metabolomics, routinely generating millions of spectra per study. However, existing clustering methods struggle to process thi...Tandem mass spectrometry (MS/MS) has become the analytical backbone of large-scale untargeted metabolomics, routinely generating millions of spectra per study. However, existing clustering methods struggle to process this scale due to computational and memory bottlenecks, limiting the utility of clustering in downstream analysis. This bottleneck is especially acute in long-term studies and public repositories, where new data are continuously added over time. Here we present a scalable clustering framework for MS/MS metabolomics data. Our method incrementally incorporates new spectra batches while preserving clustering performance through a novel spectrum pooling strategy, which propagates local density structure across batches. Using both database-search-based evaluation on proteomics data sets and the MS1-retention time (MS-RT) method on metabolomics data sets, we show that incremental clustering achieves comparable performance to the state-of-the-art clustering methods in terms of cluster purity and completeness. Critically, our approach scales up to clustering tasks consisting of 368 million spectra clustering task and millions of clusters, completing in under 10,000 CPU hours, while traditional methods could not scale to this data volume and failed to complete due to excessive memory or time requirements. Our method offers a practical solution for large-scale, continuously growing MS/MS studies and is well suited for integration into public metabolomics platforms such as GNPS2.
Khan FM, El Awady R, Mehmood S
… +3 more, Hussain Z, Othman MI, Abdul Majeed AB
J Proteome Res
· 2026 Mar · PMID 41706583
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Cancer cachexia is a multifactorial syndrome marked by involuntary weight loss, skeletal muscle wasting, adipose tissue remodeling, and systemic metabolic dysfunction. Exosome-derived microRNAs (miRNAs) have emerged as k...Cancer cachexia is a multifactorial syndrome marked by involuntary weight loss, skeletal muscle wasting, adipose tissue remodeling, and systemic metabolic dysfunction. Exosome-derived microRNAs (miRNAs) have emerged as key mediators, reprogramming host tissues and driving these hallmarks. However, no integrated framework has linked exosomal miRNAs to the proteomic and metabolomic alterations that characterize cachexia. This review critically synthesizes evidence on exosomal miRNAs in muscle atrophy, adipose browning, and systemic metabolic disruption. Tumor-secreted exosomal miRNAs activate proteolytic pathways (miR-21/29a via TLR7/8NF-κB/JNK), suppress antiapoptotic signals (miR-195/125b targeting BCL-2), induce ER stress (miR-181a-3p), impair mitochondrial quality control (miR-122), and remodel metabolic signaling (miR-155, miR-183-5p). These mechanisms converge to produce proteomic signatures of enhanced proteolysis, apoptosis, and lipolysis, alongside metabolomic shifts toward amino acid efflux, fatty acid mobilization, and glycolytic inefficiency. This is the first integrated review linking exosomal miRNAs with proteomic and metabolomic signatures of cancer cachexia, offering a multiomics framework for biomarker discovery and therapeutic targeting. We highlight their potential as early biomarkers, therapeutic targets, and modulators of rehabilitation response, while outlining research gaps including limited clinical validation, intertumor heterogeneity, and the need for multiomics integration to advance translation into patient care.
Nartey LK, Weke K, Yuen V
… +3 more, Kibsey P, Chen MX, Goodlett DR
J Proteome Res
· 2026 Mar · PMID 41698857
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Urinary tract infections (UTIs) are among the most prevalent bacterial infections worldwide, with responsible for the majority of cases. While much of what is known about physiology comes from laboratory culture, this...Urinary tract infections (UTIs) are among the most prevalent bacterial infections worldwide, with responsible for the majority of cases. While much of what is known about physiology comes from laboratory culture, this paradigm overlooks the critical influence of the unique host environment on bacterial adaptation and pathogenesis. Here, we analyzed the proteome directly from the urine of five UTI-positive patients and compared it to their respective isolates after a single in vitro passage. The comparison revealed profound proteomic changes; notably, 37 proteins consistently expressed across all patient-derived samples were uniformly absent postculture. Functional analysis of the host-adapted proteome versus after a single laboratory passage (i.e., culture) points to key roles in nutrient acquisition, virulence, stress tolerance, and host interaction, highlighting adaptive features that are lost during culture. Among these were outer membrane transporters such as FepA, CirA, and YfiB, surface-exposed proteins with diagnostic and vaccine potential, and metabolic or stress-response enzymes such as SodA, NirB, MetE, and IlvA, which represent attractive drug targets due to their essential in vivo roles and absence in humans. Our findings demonstrate the value of profiling pathogens taken directly from the host environment, revealing proteins that may serve as novel biomarkers or therapeutic targets for UTIs.
Stephan N, Halama A, Thareja G
… +7 more, Sarwath H, Grallert H, Peters A, Gieger C, Schmidt F, Graumann J, Suhre K
J Proteome Res
· 2026 Mar · PMID 41697000
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Accurate quantification of circulating proteins is critical for assessing biological variation and integrating proteomics with other omics to understand biological processes and disease mechanisms. Protein measurements,...Accurate quantification of circulating proteins is critical for assessing biological variation and integrating proteomics with other omics to understand biological processes and disease mechanisms. Protein measurements, however, can be substantially influenced by preanalytical variability arising from differences in sample collection, handling, and storage, whereas technical variation introduced by the assay and workflow is typically well controlled through established validation procedures. Identifying proteins that capture these systematic influences enables their incorporation into downstream analyzes, thereby improving statistical power. In this study, we applied highly multiplexed aptamer-based affinity proteomics to plasma samples from three independent cohorts─German, Arab-Asian and Qatari to evaluate how adjusting for all measured proteins influences protein quantitative trait loci (pQTLs) associations. Using the p-gain statistic as an indicator of improved association strength, we identified clusters of proteins whose covariation patterns suggested potential preanalytical effects. One cluster contained HSP90 (Heat Shock Protein 90), a marker linked to white blood cell lysis, while others were enriched for proteins involved in complement and coagulation cascades or platelet activation. Our work presents a data-driven framework for detecting latent sources of variation in large-scale proteomic data sets and lay the groundwork for future efforts to quantify the impact of hidden confounding factors.
Roumelioti G, Montoya A, Fisher GLM
… +21 more, Navarro EP, Woods A, Bennett J, Navaratnam N, Gonzalez-Carvajal O, Birch J, Pyman E, Yu S, Gruevska A, Vuillemenot LA, Lushchak O, Hall Z, Barr AR, Speck C, Vernia S, Scott WR, Gil J, Aragon L, Fets L, Carling D, Shliaha PV
J Proteome Res
· 2026 Mar · PMID 41693659
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High-throughput proteomics requires efficient and highly reproducible sample processing, yet workflows─particularly for PTM profiling─remain complex and costly to fully automate. Here, we present a practical intermediate...High-throughput proteomics requires efficient and highly reproducible sample processing, yet workflows─particularly for PTM profiling─remain complex and costly to fully automate. Here, we present a practical intermediate solution using manually operated 96-channel devices: the Gilson Platemaster P220 pipettor and VP Scientific 96-well magnetic pin device. Using this setup, we achieved robust and reproducible phosphoproteomics in a 96-well format, completing protein aggregation capture (PAC/SP3) digestion, desalting, phosphopeptide enrichment, and a second desalting step within 2 days while minimizing operator workload and variability. Several innovations enable this workflow. First, we describe a cost-efficient method to generate 96-well solid-phase extraction plates by directly packing the Oasis HLB sorbent into tapered filter plates. We extensively characterize these plates in terms of loading capacity, lipid removal efficiency, and suitability for high-pH fractionation. Second, we demonstrate that efficient PAC digestion does not require continuous bead suspension; instead, digestion can be achieved by briefly aspirating beads in protease solution, eliminating the need for orbital shaking and simplifying automation. The presented workflow familiarizes users with 96-channel devices and hence serves as a good step toward full automation.
Kuik C, Seccaroni M, Freulings K
… +8 more, Pressanto MC, Sforna M, Bordoni M, Calzoni E, Emiliani C, Pepe M, Cillero-Pastor B, Chiaradia E
J Proteome Res
· 2026 Mar · PMID 41693177
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Osteochondrosis is an orthopedic developmental disease that affects subchondral bone and articular cartilage in humans and domestic animals, resulting in lameness and joint effusion. Here, we compared the molecular compo...Osteochondrosis is an orthopedic developmental disease that affects subchondral bone and articular cartilage in humans and domestic animals, resulting in lameness and joint effusion. Here, we compared the molecular compositions of cartilage from healthy and osteochondrotic equine metacarpophalangeal joints to investigate the pathogenic processes of the disease. This comparison was carried out using an SP3-label-free proteomics workflow, analyzing the differences in protein abundance. Furthermore, mass spectrometry imaging (MSI) was employed for spatially resolved lipid analysis, providing a deeper understanding of osteochondrosis pathogenesis through molecular pathway analysis. Lipid readouts showed increased phosphatidylcholine (PC) lipid species and a downregulation of sphingomyelin (SM) lipids in osteochondrosis biopsies compared to healthy cartilage. Furthermore, spatial analysis of lipids revealed a higher presence of PC lipids in the superficial layer of the cartilage compared with the deep layer. Osteochondrosis-downregulated proteins were mainly involved in extracellular matrix (ECM) organization, protein folding, and hydroxylation, highlighting the importance of ECM imbalance in the osteochondrosis development. Protein-metabolite integration analysis reported a downregulation of glycolysis in the osteochondrosis group, which might lead to chondrocyte hypertrophy and ECM degradation. Our work provides novel insights into the underlying mechanisms associated with the development of osteochondrosis.
Lu ZH, Tang C, Guo R
… +3 more, Chang H, Xu YR, Zhang J
J Proteome Res
· 2026 Mar · PMID 41691569
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Metabolite metadata enrichment remains a significant challenge in metabolomics due to the limitations of static databases, incomplete metabolite coverage, and the labor-intensive nature of manual verification. Here, we p...Metabolite metadata enrichment remains a significant challenge in metabolomics due to the limitations of static databases, incomplete metabolite coverage, and the labor-intensive nature of manual verification. Here, we present MetaboliteAnnotator, an R Shiny-based application for AI-assisted metabolite name harmonization and metadata enrichment. MetaboliteAnnotator implements a hierarchical procedure, including preprocessing of input metabolite names, matching against a curated local resource (covering information on ∼640,000 metabolites names), PubChem-based real-time retrieval, and AI-assisted matching for ambiguous compounds, followed by real-time integration of KEGG, CTD, Reactome, and ChEBI. Compared with MetaboAnalyst 6.0 and MetaboliteIDmapping, MetaboliteAnnotator achieved significantly higher name hit rates across all six MetaboLights data sets 93.2% in positive mode (4021/4314 names) and 93.5% in negative mode (2344/2510 names). MetaboliteAnnotator outputs standardized identifiers (e.g., InChIKey, PubChem CID), endogenous/exogenous information, pathway mappings, and metabolite-gene/phenotype associations for downstream biological interpretation.
J Proteome Res
· 2026 Mar · PMID 41688403
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There have been various strategies to increase protein's half-life in blood, such as glycosylation or protein fusion, but one of the most widely used approaches is the addition of PEG (polyethylene-glycol). Attaching a l...There have been various strategies to increase protein's half-life in blood, such as glycosylation or protein fusion, but one of the most widely used approaches is the addition of PEG (polyethylene-glycol). Attaching a large, polydisperse PEG moiety to the therapeutics makes the analytical characterization challenging due to conjugation chemistry and increased heterogeneity. In this study, we aimed to develop a mass-spectrometry-based workflow to mitigate challenges. Using Orbitrap-based charge detection mass spectrometry, we determined the intact mass of a heavily glycosylated protein modality which is likely to carry a 30 kDa PEG. It has been demonstrated that the technique is suitable for impurity analysis, such as the remaining underivatized PEG in the formulated drug. Our data suggest mono-PEGylation of glycoprotein. Analyzing the digests of the protein generated by Lys-C and Glu-C and the combination of both enzymes in data-dependent acquisition allowed us to identify PEGylation sites on K45 and K52 residues and the -terminus. Software-assisted data processing of PEGylation from digests yielded by the three digestion conditions generated results complementary to each other and led to a highly confident assignment of PEGylation sites. The methodology introduced here overcomes bottlenecks caused by PEGylation and can be routinely used for the comprehensive characterization of PEGylated therapeutics.
Yu J, Zhou D, Li D
… +7 more, Chen Y, Zhao D, Chen F, Wang D, Li X, Gao J, Chen J
J Proteome Res
· 2026 Mar · PMID 41685791
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Diabetic nephropathy (DN) represents the predominant microvascular complication associated with diabetes mellitus; however, existing diagnostic techniques are inadequate. This study evaluated candidate urinary protein bi...Diabetic nephropathy (DN) represents the predominant microvascular complication associated with diabetes mellitus; however, existing diagnostic techniques are inadequate. This study evaluated candidate urinary protein biomarkers for diagnosing DN. A cohort comprising 59 patients with type 2 diabetes, 60 patients with DN, and 60 healthy volunteers was recruited. Urine proteomics was utilized to investigate differential protein expression levels among various patient groups and to identify potential biomarkers in conjunction with data analysis from the gene expression omnibus database. Machine learning classification methods were utilized to construct differential diagnosis models for DN. The data set IPX0003092000 was used to validate these diagnostic models. Six potential biomarkers─SERPINF1, FABP4, CP, CFB, C4A, and A1BG─were identified. The diagnostic models for DN, constructed by using machine learning algorithms, demonstrated robust diagnostic performance. Notably, models employing the glmnet, plr, and ranger classification methods achieved AUC values exceeding 0.800 in both the training and test data sets. In the validation cohort, the AUC values for models constructed using the ranger, glmnet, and plr methods were 0.928, 0.942, and 0.850, respectively. We evaluated six candidate urinary biomarkers (SERPINF1, FABP4, CP, CFB, C4A, and A1BG) using urinary proteomics and developed a diagnostic model for DN using machine learning algorithms.
Dunne JB, Rujchanarong D, Park Y
… +13 more, Spruill L, Jensen-Smith H, Schwamborn K, Hollingsworth MA, Macdonald JK, Hulahan TS, Taylor HB, Sandusky GE, Mehta AS, Drake RR, Ford ME, Nakshatri H, Angel PM
J Proteome Res
· 2026 Mar · PMID 41685602
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Collagen breast stroma can become a breast cancer risk factor, yet proteomic regulation of normal breast stroma remains poorly defined. This study evaluates the spatial regulation of the collagen proteome from normal bre...Collagen breast stroma can become a breast cancer risk factor, yet proteomic regulation of normal breast stroma remains poorly defined. This study evaluates the spatial regulation of the collagen proteome from normal breast tissue. Normal breast tissue sections from the Susan G. Komen tissue bank were used ( = 40), with data including genetic ancestry ( = 20 African ancestry; = 20 European ancestry), body-mass-index (BMI), age, and mammogram density by the Breast Imaging Reporting and Data System (BI-RADS). 10-plex cell marker staining showed CD44 and COL1A1 markers modulated with BMI. Collagen fiber widths by second harmonic generation microscopy contrasted in BMI categories by genetic ancestry. Targeted extracellular matrix proteomics mass spectrometry imaging showed the collagen alpha-1(I) chain proteome was spatially heterogeneous across the normal breast microenvironment with site-specific post-translational modification of proline hydroxylation. Signatures computationally extracted from stroma-rich regions reported that 47 collagen peptides distinguished BI-RADS categories (area under the receiver operating curve >0.7; -value >0.05). Multivariate modeling of collagen peptides, fiber metrics, and clinical features supported a strong positive association with BMI as a determinant of collagen alterations in the normal breast. This study provides a foundation for larger studies investigating the clinical value of spatial collagen proteome alterations in human breast.