Journal of Proteome Research最新文献

Hepatic fibrosis, a pathological consequence of chronic liver injury, is characterized by excessive extracellular matrix (ECM) deposition, increasing the risk of hepatocellular carcinoma. The carbon tetrachloride (CCl₄)-induced mouse model is well-established for studying the pathogenesis and treatment of hepatic fibrosis, yet the effect of administration routes on fibrotic development and characteristics remains unclear. This study employed comparative proteomics to evaluate fibrosis induced via three CCl₄ delivery methods: intraperitoneal (IP), subcutaneous (SC), and intragastric (IG) administration. The results demonstrated that the administration route critically determined fibrotic severity, with IG causing the most severe fibro-inflammatory injury, followed by SC and IP. Proteomic profiling identified distinct molecular pathways: IG and SC were closely associated with tissue remodeling, while IP was correlated with immune activation. Cross-species analysis further highlighted conserved profibrotic mechanisms and the hub gene patterns of hepatic ECM remodeling and metabolism differing from mice and humans. These findings underscore the importance of the CCl₄ administration method as a crucial variable influencing the extent and nature of fibrosis in mouse models, and identify IG as the most effective modeling for advanced fibrosis. These insights offer a valuable foundation for refining experimental approaches to better mimic human hepatic fibrosis and enhance the translational relevance of research outcomes.

Growth failure in infants born preterm is a significant issue, increasing the risk of poorer neurodevelopmental outcomes and metabolic syndrome later in life. The aim of this study was to characterize patterns associated with urinary metabolites in extremely preterm and very preterm infants and to explore relationships with growth over time. Untargeted hydrogen-1 nuclear magnetic resonance (¹H NMR) spectroscopy was used to characterize changes in urinary metabolites over time and explore relationships with growth and nutritional intake. Partial least-squares regression models were constructed to identify metabolic variation associated with age, growth, and nutrition. Biochemical aging differed between very (mean 29.4 weeks ± 1.08 gestational age; n = 21) and extremely (≤28 weeks gestational age; n = 33) preterm infants, but these differences were not apparent when urinary metabolites were aligned to postmenstrual age. Citrate was the only metabolite significantly positively associated with weight-for-age Z-score. At weeks 1 and 2, citrate was positively associated with gestational age and a greater increase in WAZ from birth to discharge. Biochemical aging aligned to chronological age differed between very and extremely preterm infants, but this variation was lost when aligned to postmenstrual age. Urinary citrate excretion in the first two weeks of life was associated with weight gain and may be a future modifiable biomarker to improve growth outcomes.

Age is a key risk factor for morbidity in coronavirus disease 2019 (COVID-19). This study investigates how "inflammaging" predisposes older hosts to severe SARS-CoV-2 outcomes through systemic and localized metabolic shifts. SARS-CoV-2 infection experiments were conducted respectively on 8 week-old mice and 16 week-old mice. An integrated multiomics approach was employed to delineate age-dependent molecular signatures and metabolic-immune crosstalk. 16 week-old mice exhibited significantly exacerbated weight loss and pulmonary pathology, successfully recapitulating age-related susceptibility. Multiomics integration revealed a "systemic bioenergetic gap": suppressed plasma TCA cycle metabolites correlated with depleted pulmonary nucleotide pools (AMP, GMP, UMP and uracil). This metabolic failure led to a paradoxical proteomic profile: despite interferon pathway activation, key antiviral effectors (RSAD2, ISG15, IFIT3B) were downregulated, while stress markers (CYP1A1, MAPK8) increased. Furthermore, threonic acid, betaine, and d-ribose were identified as robust, age-dependent biomarkers of infection severity. Our findings suggest that COVID-19 severity in the aging host is driven by the failure of a systemic-to-local metabolic-immune axis. The exhaustion of circulating energetic precursors constrains localized pulmonary nucleotide metabolism, thereby impairing essential antiviral responses and tissue repair. This study identifies the "systemic bioenergetic gap" as a novel therapeutic target, suggesting that systemic metabolic resuscitation may improve clinical outcomes in elderly populations.

Tendinopathy is a painful overuse disorder marked by a progressive functional decline. Although chronic disease mechanisms have been described, early molecular changes remain poorly defined. Here, we performed temporal proteomic profiling of human patellar tendon biopsies across one, two, and three months of symptom duration and evaluated proteome differences between symptomatic and nonsymptomatic contralateral tendons. Biopsies were collected from participants with unilateral patellar tendinopathy and symptoms lasting three months or less for analysis by data-independent acquisition liquid chromatography-mass spectrometry. Peptide- and protein-level abundances were quantified as part of a bottom-up proteomics workflow and assessed using two-way ANOVA with factors of symptom status and symptom duration. Symptom duration had a significant main effect: 12 proteins and 14 peptides changed significantly over time, with most peptides corresponding to the altered proteins. However, there was no interaction between the symptom status and symptom duration, no sex differences, and no detectable proteomic difference between symptomatic and contralateral tendons. These findings indicate that protein-level changes are detectable within the first three months of tendinopathy, and similar proteomic changes were also observed in contralateral tendons. Together, these observations suggest that early phase patellar tendinopathy is associated with time-dependent proteomic changes that are not confined to the symptomatic tendon.

Mass spectrometry (MS)-based proteomics has empowered comprehensive protein profiling of biological specimens. However, formalin-fixed paraffin-embedded (FFPE) tissues─critical resources for clinical biomarker discovery-remain underexplored in the setting of long-term storage (>15 years). Herein, we systematically evaluated the impact of storage time on proteomic analyses of 80 colorectal adenocarcinoma (CRC) FFPE samples, which were stratified by two key variables: storage time (>15 years vs <1 year) and tissue type (tumor vs adjacent normal tissue). We adopted a standardized protein extraction strategy, and subsequent proteomic profiling was performed via data-dependent acquisition and data-independent acquisition MS workflows. Our results demonstrated that FFPE tissue storage time impacts protein extraction efficiency, peptide yields, PTM identification, and protein quantification. The impacts were more pronounced on the peptide level. However, the biological enrichments (Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis) from the global proteome profile and from differentially expressed proteins in CRC tissues were independent of archival time. Five clinically relevant biomarkers of CRC were further validated via immunohistochemistry. Collectively, our findings confirm that FFPE tissues retain stability for proteomic analyses even following >15 years of storage, thereby providing critical insights for leveraging archival FFPE biobanks to advance clinical proteomics and archival pathology research.

Objective: 19-Hydroxybufalin (19-H) is a natural bioactive compound with anticancer potential, but its molecular target and mechanism of action remain unclear. This study aimed to systematically evaluate its antigastric cancer activity and identify potential molecular targets.

Methods: The antitumor effect of 19-H was evaluated in both in vitro and in vivo models. Multiomics analysis, thermal proteome profiling, molecular docking, and molecular dynamics simulations were employed to elucidate the mechanism of action. Functional assays were further conducted to validate the key target.

Results: 19-H exhibited nanomolar-level inhibitory activity against various gastric cancer cell lines, significantly suppressing tumor growth in subcutaneous xenograft and patient-derived xenograft models. Multiomics analysis revealed that 19-H reshaped metabolic pathways in gastric cancer. TPP screening identified PLPP2 as a potential target with significantly increased thermal stability upon 19-H treatment. Molecular simulations further revealed that 19-H binds stably to the α-helical region of PLPP2.

Conclusions: 19-H exerts its antigastric cancer effect by targeting PLPP2 and remodeling the metabolic network. PLPP2 may represent a novel therapeutic target for gastric cancer.

Cytomegalovirus (CMV) is a major cause of morbidity in immunocompromised individuals and represents the leading infectious cause of neonatal congenital deafness. When acquired during pregnancy, CMV can be vertically transmitted to the fetus, potentially resulting in permanent sequelae characterized by intellectual and neurosensory impairments. To investigate metabolic alterations associated with primary maternal CMV infection, we conducted a metabolomics-based analysis of amniotic fluid (AF) from pregnant women who acquired CMV infection during the first trimester, as confirmed by IgG seroconversion, IgM positivity, and low-to-moderate IgG avidity indices. Our findings revealed that the AF metabolomic profiles from CMV transmitter and nontransmitter mothers were remarkably similar. In contrast, both the CMV-exposed groups showed profound metabolic dysregulation compared to uninfected controls, suggesting that CMV-related metabolic disparities may persist irrespective of vertical transmission. Specifically, we observed a significant downregulation of glutamate (p < 0.0001) and acetylcarnitine (p < 0.0001) in CMV groups compared to control AF samples. Notably, the combined reduction of these two metabolites emerged as a surrogate biomarker signature of recent primary CMV infection of the mother, indicating that AF from both transmitting and nontransmitting pregnancies may share common metabolic adaptations. These alterations may reflect early perturbations of neurobiochemical pathways with unknown effects on babies negative at birth, supporting the need for risk assessment and clinical monitoring even in the absence of congenital CMV infection.

Colorectal cancer (CRC) remains a leading cause of cancer-related mortality, highlighting the need for accurate, noninvasive biomarkers. This study investigated protein glycopatterns in saliva and serum from CRC patients compared with healthy controls, and evaluated their diagnostic potential individually and in combination using machine learning. Paired serum and saliva samples from 44 CRC patients and 45 healthy volunteers were analyzed using lectin microarrays, identifying 15 lectins with distinctive binding profiles in serum and 18 in saliva. Nine lectins (e.g., ACA, PNA, HHL) exhibited consistent patterns across both fluids, indicating systemic CRC-associated glycoprotein remodeling, whereas others (e.g., DBA, PTL-II) displayed opposite trends, reflecting fluid-specific responses. Interfluid correlations were further examined through paired analyses, highlighting both shared and distinct glycosylation characteristics. Random forest models achieved diagnostic accuracies of 92.6% using either serum or saliva alone and 96.3% when combining both, demonstrating the enhanced predictive power of integrated analysis. These findings establish glycosylation profiling of saliva and serum as a promising noninvasive approach for CRC detection and support its potential application in population screening pending validation in larger cohorts.

Rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE) are systemic autoimmune diseases associated with increased cardiovascular risk and metabolic alterations. We applied ¹H NMR spectroscopy to profile lipoproteins and metabolites in women with RA, SLE, and healthy controls. Both RA and SLE showed shared alterations in HDL metabolism, including reduced HDL particle size and lower concentrations of small HDL particles compared with controls. RA exhibited additional changes, notably a significant reduction in small LDL particle concentration. Metabolite profiling further differentiated RA, revealing significantly lower circulating levels of glutamine, alanine, and GlycB. Correlation analyses demonstrated that in RA, LDL particle concentrations were positively associated with disease activity (DAS28-ESR), and large LDL particles correlated positively with IFN-γ and VEGF. In SLE, HDL particle measures were associated with complement components, with small HDL particles positively correlated with C3 and HDL particle size inversely correlated with C3, while large LDL particles correlated positively with IL-6 and negatively with MDC. Together, these results indicate that RA and SLE share common lipoprotein alterations, while RA displays additional metabolic changes. NMR-derived lipoprotein and metabolite profiles may provide complementary information for assessing inflammation and cardiovascular risk in autoimmune diseases.

Plasma proteomics is a rapid, noninvasive, and highly informative approach for identifying disease biomarkers. However, the wide dynamic range of protein concentration limits the depth of liquid chromatography-tandem mass spectrometry proteomics. To address this challenge, we evaluated, with an Orbitrap Astral instrument using DIA, the performance of several protein depleting and enriching technologies on platelet-free plasma. Specifically, we assessed: perchloric acid depletion, immunodepletion, ProteoMiner, MagNet-SAX, ENRICHplus, Proteonano and the combination of ProteoMiner and immunodepletion. All methods were assessed in terms of proteomic depths, protein quantification precision, and functional analysis. Proteonano exhibited the most effective enrichment for the lowest abundance proteins, confidently identifying 299 proteins with mapped blood concentrations below 10⁶ pg/L. Immunodepletion yielded the highest proteome coverage in the moderate abundance range (660 confident proteins). Also, ENRICHplus quantitative profile closely matched that of the neat plasma (93% correlation). Additionally, high repeatability (median coefficient of variation) was demonstrated by MagNet-SAX (13%), ProteoMiner (15%), and immunodepletion (16%). Combining ProteoMiner and immunodepletion reduced the plasma protein dynamic range, enabling deeper low abundance protein analysis but decreased repeatability. These results obtained on platelet-free plasma deviate from previously reported results on platelet-rich plasma, highlighting the crucial sample preparation stage for plasma proteomics.