SEARCH · PubMed Health

Results for “Integrated proteomics”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2Linked to original sources

PubMed2026

Multi-Omics Analysis Reveals Molecular Networks and Key Pathways Associated with Cysteine- and Methionine-Mediated Biosynthesis of Sulfur-Containing Flavor Metabolites in Lentinula edodes.

Lentinula edodes is renowned for its unique aroma, which is characterized by various volatile sulfur-containing flavor metabolites (SCFMs). Cysteine and methionine could enhance the SCFMs biosynthesis in L. edodes; however, the underlying metabolic pathways remain unclear. To bridge this gap, integrated proteomic and metabolomic analysis were performed to decipher pathways through which cysteine and methionine regulate SCFM biosynthesis. Results showed that exogenous cysteine and methionine supplementation significantly increased the content of lenthionine, the key aroma compound of shiitake mushrooms. Both treatments induced substantial changes in the proteomic and metabolomic profiles. Proteomic analysis revealed that differentially expressed proteins were predominantly enriched in cysteine and methionine metabolism and sulfur metabolism following cysteine treatment, whereas methionine treatment mainly affected proteins associated with tryptophan metabolism and sulfur metabolism. Metabolomic analysis showed that differentially accumulated metabolites were significantly enriched in D-amino acid metabolism and cysteine and methionine metabolism, with glutathione metabolism specifically enriched under cysteine treatment. Integrated omics analysis further uncovered distinct sulfur metabolite-protein regulatory networks under different sulfur nutrition and identified treatment-specific hub proteins. These findings establish a molecular regulatory framework linking SCFM biosynthesis with broader primary metabolic pathways involved in sulfur intermediate generation and regulation, providing new insights into the potential regulatory networks underlying SCFM formation in L. edodes.

Methionine↗

PubMed2026

High-Throughput Proteomic and Glycoproteomic Analyses in Benign Prostatic Hyperplasia.

Benign prostatic hyperplasia (BPH) is a disease affecting the majority of aging men; 90% of men develop histological BPH by the time they reach their eighties. BPH can lead to bothersome lower urinary tract symptoms (LUTS), which may reduce quality of life. Many patients fail current treatment options and may progress to surgical intervention. Furthermore, diagnosis is reliant on symptom questionnaires and the cause of LUTS can be difficult to distinguish. Currently, BPH can only be definitively diagnosed through histological analysis of prostate tissue, which is not the standard of care. The resulting lack of clinical tissue samples is a major limitation in investigating disease pathology. Improved understanding of disease development and progression, along with objective biomarkers of disease, is needed for BPH. This investigation uses mass spectrometry (MS)-based proteomics and glycoproteomics to compare healthy prostate tissue with prostate tissue affected by BPH to address this gap in knowledge. By integrating proteomics and glycoproteomics, we identified 206 proteins and 44 glycopeptides that were significantly altered between BPH and control samples. These findings provide deeper insight into disease-associated pathways and may facilitate the identification of clinically relevant targets for further investigation.

Male↗

PubMed2026

Phytolacca acinosa Roxb. induces intestinal toxicity through the histamine-MLCK-tight junction axis: Integrated evidence from proteomics, metabolomics, intestinal organoids and epithelial barrier validation.

Phytolacca acinosa Roxb. (PR) is a saponin-rich medicinal plant associated with gastrointestinal toxicity, but the mechanisms underlying PR-induced intestinal barrier injury remain unclear. In this study, raw PR extract was analytically characterized by UPLC-ZenoTOF-MS/MS, confirming triterpenoid saponins as the predominant constituents. C57BL/6 J mice were orally exposed to characterized PR extract (1.20 or 12.0 g/kg for 5 h), and Caco-2 cells and mouse intestinal organoids were used to assess epithelial toxicity and barrier disruption. Histopathology, ELISA, FITC-dextran permeability assays, immunofluorescence, CCK-8, LDH release, western blotting, DIA-based proteomics and untargeted metabolomics were integrated to define toxicological mechanisms. PR induced dose-dependent intestinal inflammation and barrier dysfunction, with the ileum as the most sensitive target. PR increased serum DAO and D-lactate and intestinal TNF-α and IL-1β, disrupted organoid morphology, enhanced epithelial permeability, and reduced ZO-1 expression. Proteomics revealed changes in inflammatory, lipid-metabolic, cytoskeletal and tight-junction pathways, including upregulation of MLCK3 and phospholipase-related proteins and downregulation of ZO-1 and ZO-2. Metabolomics identified histidine metabolism disturbance and histamine accumulation. Integrated multi-omics and pharmacological validation indicated that histamine activated the PLC/IP₃/Ca²⁺/CaM/MLCK cascade, promoting MLC phosphorylation, tight-junction disassembly and epithelial leakiness. MLCK inhibition partially restored ZO-1/ZO-2 expression and attenuated PR-induced epithelial injury. These findings identify the histamine-MLCK-tight junction axis as a key mechanism of PR-induced intestinal toxicity and support hazard identification of saponin-rich PR exposure.

Animals↗

PubMed2026

Proteomic and metabolomic profiling reveals dysregulation of immune states, mucin-type glycosylation and steroid metabolism in extramammary Paget's disease.

BACKGROUND: Extramammary Paget's disease is a rare cutaneous adenocarcinoma characterized by mucin-rich Paget cells and chronic inflammation, yet its molecular basis remains unclear. OBJECTIVE: To systematically characterize the proteomic and metabolomic landscape of EMPD, uncover immune heterogeneity, and identify molecular pathways underlying tumor progression and microenvironment remodeling. METHODS: We performed integrated proteomic and metabolomic analyses on 92 male tumor patients and 30 healthy controls, identifying 10,217 proteins and 1466 metabolites. RESULTS: Extramammary Paget's disease lesions exhibited broad activation of inflammatory pathways. Immune profiling further uncovered substantial inflammatory heterogeneity, delineating immune-cold and immune-hot subtypes, with the latter associated with stronger invasive potential. Aberrant mucin-type glycosylation was also prominent, featuring Tn-modified MUC1 and MUC5AC accompanied by elevated GALNT7, GALNT6, GALNT4, and ST6GAL1, which correlated with inflammatory intensity. Metabolomic data demonstrated elevated levels of testosterone, dehydroepiandrosterone, and related intermediates in tumor tissues, indicating an androgen-enriched metabolic profile in extramammary Paget's disease. CONCLUSION: These findings reveal immune, glycoproteomic, and metabolomic pathways in extramammary Paget's disease pathogenesis and provide novel insights for molecular classification and therapeutic targeting.

Humans↗

PubMed2025

Longevity of cardiac and skeletal muscle proteins is dependent on tissue and subcellular compartmentation patterns.

Myocytes are exceptionally long-lived cells that must maintain proteome integrity over decades while adjusting for changes in functional output and metabolic demand. We used in vivo stable isotope labeling combined with mass spectrometry proteomics and correlated multi-isotope imaging mass spectrometry to quantify and visualize protein turnover across cardiac, fast-twitch, and slow-twitch skeletal muscles, creating a resource of hundreds of individual protein turnover rates from each tissue. We found that cardiac muscle has the highest rate of protein turnover, followed by slow-twitch skeletal muscle and then fast-twitch skeletal muscle, and that these different rates of protein turnover are driven by different levels of muscle use, rather than myosin isoform composition. We also identified protein age heterogeneity at the myofiber and sarcomere levels. These findings uncover fundamental principles of muscle protein maintenance and have broad implications for understanding cellular aging, muscle disease, and the design of therapeutic strategies targeting muscle protein turnover.

Animals↗

PubMed2026

Systemic Proteome Profiling to Differentiate Primary Glomerular Diseases.

KEY POINTS: Plasma proteome profiling identified distinct signatures across biopsy-proven primary glomerular disease subtypes. An elastic net model using 93 proteins classified primary glomerular disease subtypes and controls, with external validation. Integrating proteomics with machine learning yields biologically interpretable insights in primary glomerular diseases. BACKGROUND: Primary GN is a heterogeneous group of kidney disorders where understanding of their pathophysiology remains incomplete. Despite the diagnostic potential of high-throughput proteomics, constrained proteomic depth and a reliance on binary comparisons have left the feasibility of using systemic signatures to differentiate multiple GN subtypes largely unexplored. METHODS: To identify protein signatures that noninvasively differentiate major primary glomerular disease subtypes and provide mechanistic insights, we performed large-scale systemic proteome profiling of 5416 plasma proteins via Olink Explore HT in a discovery cohort ( n =147) and an external validation cohort ( n =85) of Korean participants (mean age, 41±13 years; 46% female). The study population included patients with four GN subtypes-focal segmental glomerulosclerosis, IgA nephropathy, minimal change disease, and membranous nephropathy-alongside healthy controls. We developed a machine learning (ML) model using logistic regression with elastic net regularization to classify disease groups based on proteomic profiles and evaluated its performance in the independent validation cohort. RESULTS: Plasma proteome profiles were distinct among disease subtypes, emerging as a significant source of data variation independent of conventional markers such as eGFR or proteinuria levels. The ML model performed robustly in both the discovery and validation cohorts, achieving an area under the receiver operating characteristic curve >0.8 for differentiating minimal change disease, membranous nephropathy, and IgA nephropathy. The model, even without clinical information, correctly identified 93% of minimal change disease cases (14 of 15) and 63% of IgA nephropathy cases (20 of 32), but its performance was limited for focal segmental glomerulosclerosis, with only 21% of cases (three of 14) correctly classified. Functional analysis of key proteins highlighted distinct biologic pathways, such as hemostasis in minimal change disease. CONCLUSIONS: We identified distinct systemic proteome signatures for primary glomerular diseases, where disease subtype served as a major determinant of proteomic variance alongside conventional clinical markers. ML models demonstrated robust discriminatory performance for minimal change disease, membranous nephropathy, and IgA nephropathy, underscoring the potential for proteome-based classification.

Humans↗

PubMed2026

Opposing kinase signaling may underlie the inverse relationship between cancer and Alzheimer's disease.

Cancer and Alzheimer's disease (AD) are leading causes of mortality and exhibit an inverse relationship, where AD patients have reduced cancer risk and vice versa. However, the molecular basis of this relationship remains poorly understood. We reanalyzed published proteomic and phosphoproteomic datasets to investigate this relationship. Differentially abundant proteins were identified in lung adenocarcinoma and glioblastoma samples relative to controls and compared with proteins altered in AD brains, revealing 37 proteins with opposing abundance patterns. Protein-protein interaction and pathway analyses revealed enrichment in kinase signaling and phosphorylation pathways. Phosphoproteomic analysis identified 52 differentially phosphorylated sites with opposing patterns, while kinase-substrate enrichment analysis identified 44 kinases with opposing inferred activity profiles. Integration of kinase activity and phosphosite data identified 29 kinase-phosphosite pairs, including 4 prioritized pairs with opposing patterns relevant to both diseases. Across seven independent cancer cohorts, 17 of 20 statistically significant phosphosite-cohort comparisons (85%) were concordant with the discovery findings, supporting reproducibility of the prioritized phosphosites. Together, these findings highlight opposing kinase signaling as a prominent feature of the inverse relationship and suggest potential biomarkers and therapeutic targets. This study provides a novel systems-level framework for investigating inverse relationships, supported by an R Shiny application for data exploration (https://advscancer.shinyapps.io/advscancer/). SIGNIFICANCE: This study presents an integrated proteomic and phosphoproteomic framework for investigating the inverse relationship between cancer and Alzheimer's disease (AD). By integrating differential protein abundance, phosphosite phosphorylation, inferred kinase activity, and curated kinase-substrate relationships, we identified opposing signaling patterns and prioritized four kinase-phosphosite pairs. Independent evaluation across seven CPTAC cancer cohorts supported the reproducibility of the prioritized phosphosite patterns. These findings provide insight into molecular processes potentially associated with the inverse relationship between cancer and AD, identify candidate biomarkers and therapeutic targets, and demonstrate the value of systems-level, data-driven approaches for investigating shared and opposing disease processes.

Humans↗

PubMed2025

Protective effects of liver-derived apolipoprotein A1 against heat stress-induced hypothalamic lipid metabolism and blood-brain barrier integrity.

Heat stress (HS), a prevalent occupational and environmental hazard, has increasingly been recognized as a major contributor to multiple physiological disorders. The hypothalamus, a key regulator of thermoregulation and endocrine signaling, is especially susceptible to metabolic and inflammatory disturbances induced by HS. This study investigates the interplay among lipid metabolism, blood-brain barrier (BBB) integrity, and neuroinflammation in the hypothalamus under HS conditions, with a specific focus on apolipoprotein A1 (APOA1) as a potential protective factor. To achieve this, we integrated proteomic and lipidomic analyses with experimental validation in porcine and murine models. Proteomic analysis identified 266 differentially expressed proteins (DEPs) in the hypothalamus following HS, with significant enrichment in lipid metabolism pathways-especially glycerophospholipid (GP) metabolism-in which APOA1 displayed a marked increase. Lipidomic profiling further revealed HS-induced disruptions in phosphatidylcholine (PC), phosphatidylethanolamine (PE), and cardiolipin (CL) metabolism. Additionally, blood-brain barrier integrity was compromised, as evidenced by increased perivascular IgG extravasation, reduced pericyte coverage, and decreased expression of tight junction proteins ZO-1 and Occludin. HS also triggered pronounced neuroinflammation, characterized by elevated levels of iNOS, GFAP, and pro-inflammatory cytokines (TNF-α, IL-1β, and IL-6). Notably, administration of D-4F, an APOA1 mimetic peptide, alleviated blood-brain barrier damage, reduced neuroinflammation, and preserved synaptic integrity, thereby suggesting a neuroprotective role for APOA1 in HS-induced hypothalamic dysfunction. These findings underscore the critical role of lipid metabolism in maintaining hypothalamic homeostasis under HS conditions and position APOA1 as a key regulator with potential therapeutic implications for mitigating HS-related neuroinflammatory and metabolic disturbances.

Blood-Brain Barrier↗

PubMed2026

AI proteomics: from protein identification to virtual cells.

Artificial intelligence (AI) is transforming scientific research, including proteomics. In this Perspective, we highlight key mass spectrometry (MS)-based proteomics areas where AI is driving innovation, ranging from protein identification to building AI virtual cells. These include improving peptide and protein identification and quantification; characterizing protein-protein interactions and protein complexes; advancing spatial and perturbation proteomics; integrating multi-omics data; and, ultimately, enabling AI virtual cells. Finally, we call for global collaboration among data producers, data consumers and other stakeholders to establish an AI-friendly ecosystem for MS-based proteomics, laying the foundation for transformative advancements in proteomics driven by AI.

Proteomics↗

PubMed2025

Cilia.Pro database of ciliary proteins from vertebrates, Chlamydomonas, and Caenorhabditis.

Cilia and flagella are microtubule-based organelles that generate force and sense the extracellular environment. In humans, these structures are essential for development, homeostasis, and reproduction, with defects contributing to a wide array of congenital and degenerative disorders. As cilia were present on the last common ancestor of all eukaryotes, research on cilia across model organisms holds significant relevance for understanding human disease. The green alga Chlamydomonas, which diverged from the human lineage with the animal-plant split, shares striking similarities in ciliary structure and function with humans. Two decades ago, our group published the proteome of the Chlamydomonas cilium, identifying hundreds of new ciliary proteins that were organized in an online database. Since then, advances have brought us a more comprehensive understanding of both Chlamydomonas and mammalian cilia. Our database, www.Cilia.Pro, has been continually updated to integrate proteomic, transcriptomic, and genomic data from Chlamydomonas and Caenorhabditis along with humans, and other vertebrates providing a valuable tool for the ciliary research community.

Cilia↗

PubMed2026

Occupationally relevant vibrations and the brain: frequency-dependent proteomics signatures in a rat model.

INTRODUCTION: Occupational exposure to whole-body vibration (WBV), particularly in agricultural environments, has been associated with adverse cognitive and physiological effects. This study examined the neurophysiological impact of WBV in a rat model at 4 Hz and 30 Hz, frequencies representative of off-road and on-road vehicle operation. METHODOLOGY: Forty-four Sprague-Dawley rats were assigned to control (0 Hz), low-frequency (4 Hz), or high-frequency (30 Hz) vibration conditions. After three days of exposure, brain tissues were collected and analyzed using mass spectrometry-based proteomics to identify differentially expressed proteins. RESULTS: Proteomic profiling revealed distinct, frequency-dependent alterations in brain protein expression. Compared with controls, 32 cognition-related proteins were differentially regulated at 4 Hz and 29 at 30 Hz, with 13 differing between the two vibration conditions. Principal component analysis showed clear separation among groups, indicating unique proteomic signatures for each exposure frequency. Functional enrichment and protein-protein interaction analyses demonstrated involvement of synaptic plasticity, cytoskeletal organization, calcium regulation, and neurotransmitter release. Exposure to 4 Hz was associated with the upregulation of proteins involved in calcium homeostasis and synaptic integrity, suggesting potential disruption of cognitive processes. In contrast, 30 Hz increased the expression of proteins related to axonal guidance and neuroprotection, indicating a less clearly adverse response that may reflect adaptive or potentially beneficial effects. DISCUSSION: These findings provide new insight into biological mechanisms underlying WBV-induced cognitive changes and underscore the importance of vibration frequency in shaping neurophysiological outcomes. They also establish a foundation for future studies integrating proteomics with behavioural assessments in animals and humans.

Animals↗

PubMed2026

Integrated multi-omics profiling of amniotic fluid identifies predictive biomarkers for fetal growth restriction trajectories.

BACKGROUND: Fetal growth restriction (FGR) is a complex condition with highly heterogeneous clinical outcomes, making prenatal distinction between transient and persistent growth failure challenging. This study aims to identify amniotic fluid (AF) biomarkers capable of differentiating distinct FGR trajectories and characterizing persistent growth failure mechanisms. METHODS: Integrated proteomic and metabolomic profiling was performed on AF samples from transient FGR (n = 11), persistent FGR (n = 9), and healthy controls (n = 13). Diagnostic and prognostic models were developed using multivariate analysis. Selected protein candidates were validated via ELISA in an independent cohort (n = 69). RESULTS: Multi-omics analysis revealed distinct molecular signatures for FGR stratification. A two-protein diagnostic panel (PDGFA and phospho-STAT5A) achieved an AUC of 1.000 in the discovery stage and 0.780 in the external validation cohort. For prognostic assessment, a molecular signature including IREB2, HLA-C, and PLXNB2 accurately predicted persistent growth failure from transient recovery (AUC = 0.966). Cross-platform integration highlighted the mass spectrometry-derived WASHC2C as a central hub protein with a significant progressive increase across the control, transient, and persistent groups (p < 0.001). CONCLUSIONS: This study establishes a multi-omics framework for prenatal FGR stratification. Our findings identify distinct molecular signatures reflecting the intrauterine environment and provide high-performance molecular tools for predicting divergent fetal growth trajectories to guide personalized clinical decision-making.

Humans↗

PubMed2026

Proteomics combined with single-cell sequencing reveals key genes and computational lead compound related to ligamentum flavum hypertrophy, lactate metabolism and lactate modification.

Ligamentum flavum hypertrophy (LFH) is a hallmark pathological feature of lumbar spinal stenosis; however, its underlying molecular mechanisms remain incompletely understood. Lactate metabolism and related lactylation modifications have emerged as critical links between cellular metabolism and epigenetic regulation, with established roles in various fibrotic and inflammatory diseases. Nevertheless, the specific contribution of lactylation to LFH pathogenesis remains unexplored. In this study, we integrated proteomic profiling of ligamentum flavum tissues with single-cell transcriptomic data to identify differentially expressed proteins associated with LFH. Cross-referencing these genes with genes involved in lactate metabolism and lactylation yielded 16 candidate genes. Through functional enrichment analysis, protein-protein interaction network construction, and GraphBAN model prediction, we identified five hub genes (NDUFS2, HMOX1, SPR, FABP5, and PFKP) and two potential lead compounds (ZINC000014879975 and ZINC000242437513). Molecular docking analysis confirmed favorable binding affinities between these compounds, suggesting that they may serve as potential lead compounds worthy of further experimental investigation. Single-cell analysis further revealed that macrophages occupy a central position in the LFH microenvironment, resulting in pronounced metabolic reprogramming and remodeling of intercellular communication networks, particularly via the MIF-CD74/CD44 axis, under pathological conditions.

Proteomics↗

PubMed2025

A clinically applicable method for early interstitial lung disease detection in incident rheumatoid arthritis cases: integration of protein biomarkers and clinical factors.

BACKGROUND: This study aimed to develop an early diagnostic method integrating proteomic biomarkers and clinical parameters for screening interstitial lung disease (ILD) in patients with newly diagnosed rheumatoid arthritis (RA) through a multi-phase research strategy. METHODS: A three-phase study was conducted: (1) Discovery: Tandem mass tag (TMT)-labeled quantitative proteomics with liquid chromatography-tandem mass spectrometry (LC-MS/MS) analyzed serum protein profiles in 5 RA-ILD and 5 RA-non-ILD patients, identifying candidates via bioinformatics. (2) Verification: Enzyme-linked immunosorbent assay (ELISA) validated candidates in an independent cohort (13 RA-ILD vs 14 RA-non-ILD). (3) Application: Biomarkers combined with clinical indicators (Krebs von den Lungen-6 [KL-6], age, sex) were evaluated in 110 patients (51 RA-ILD vs 59 RA-non-ILD) to build a predictive model. RESULTS: Proteomic analysis identified matrix metalloproteinase-3 (MMP3), von Willebrand factor (VWF), and other significantly differentially expressed proteins. ELISA validation confirmed that serum MMP3 and VWF levels were significantly higher in the RA-ILD group than in the RA-non-ILD group (p = 0.025 and 0.027, respectively). Expanded validation demonstrated superior diagnostic performance when combining MMP3 and VWF with KL-6 (area under the curve [AUC] = 0.90). The nomogram prediction model based on univariate analysis exhibited excellent discrimination (AUC = 0.89) and calibration. CONCLUSION: This systematic study from discovery to validation identified MMP3 and VWF as potential biomarkers for RA-ILD. The integrated predictive model combining these biomarkers with clinical parameters (KL-6, age, sex) provides a potential tool for early ILD screening in RA patients, offering novel strategies for early diagnosis and intervention of RA-ILD.

Humans↗

PubMed2026

Male accessory gland proteins in Grapholita molesta: Identification and reproductive functional validation of four accessory gland-specific lipases.

Accessory gland proteins (Acps), synthesized in the male accessory glands (AGs), are transferred to females via spermatophores during mating and elicit diverse post-mating physiological and behavioral responses. However, Acps have not been comprehensively characterized in Grapholita molesta, a cosmopolitan orchard pest. Here, using data-independent acquisition mass spectrometry, we describe an integrated proteomic approach combining comparative AG analyses (virgin vs. newly mated) with spermatophore profiling to identify Acps in G. molesta. According to the established screening criteria, we identified 83 confirmed Acps, which were classified into nine categories. Tissue-specific expression patterns of 20 randomly selected Acp genes were evaluated, revealing that these genes were specifically or highly expressed in male AGs. Among the 83 confirmed Acps, four Acps harbored the PLN02872 superfamily domain and were classified into the canonical lipase family. Notably, their transcripts were all highly expressed in the AGs during the pre-maturation stage. These four Acps were selected for preliminary validation of their male reproductive functions. RNAi-mediated knockdown of three out of four lipase genes in G. molesta males significantly decreased the fertility of mated females, with phenotypes including a significant reduction in egg production and egg hatching rate. This study provides a comprehensive catalog of high-confidence Acps, lays a foundation for subsequent in-depth functional characterization of these reproductive proteins, and offers promising molecular targets for the development of novel genetic regulation-based integrated pest management strategies.

Animals↗

PubMed2026

Mass spectrometry-based mapping of the ubiquitin chaperone code.

Maintenance of proteome integrity is essential for cellular homeostasis and organismal health. This integrity depends on proteostasis, a coordinated network of protein quality control systems that regulate protein folding, stabilization, and degradation. Molecular chaperones, together with proteolytic pathways such as the ubiquitin-proteasome system (UPS) and the autophagy-lysosomal pathway, prevent the accumulation of misfolded and aggregation-prone proteins. Perturbations, including genetic mutations, environmental stress, and aging challenge protein folding fidelity, leading to proteotoxic stress and contributing to the pathogenesis of neurodegenerative disorders. Among the chaperone machinery, the HSP70 and HSP90 families play central roles in maintaining protein conformational homeostasis and directing damaged or misfolded substrates toward refolding or degradation pathways. Recent studies show that chaperone activity is dynamically regulated by diverse post-translational modifications (PTMs), including phosphorylation, acetylation, and ubiquitination, collectively termed the "chaperone code." These modifications modulate chaperone-client interactions, enzymatic activity, localization, and coordination with protein degradation systems. Mass spectrometry (MS)-based proteomics has emerged as a powerful approach for mapping ubiquitination sites and quantifying ubiquitin signaling dynamics. This chapter outlines experimental and computational strategies for MS-based analysis of the ubiquitin chaperone code, including di-glycine peptide enrichment, site identification, quantitative analysis, and validation.

Humans↗

PubMed2026

NAD+ Metabolism Licenses Zygotic Genome Activation via PARP7-Mediated ADP-Ribosylation of UHRF1 in Mouse Early Embryos.

Zygotic genome activation (ZGA) is a critical developmental milestone whose metabolic regulation remains unclear. This study identifies a pivotal role for Nicotinamide adenine dinucleotide (NAD+) metabolism in regulating ZGA through poly(ADP‑ribose) polymerase 7(PARP7)-mediated ADP-ribosylation. Using ultra-low input embryo metabolomics, we profiled metabolism from zygote to blastocyst, revealing a significant NAD+ decline at the 2-cell stage. This shift coincided with specific upregulation of the mono-ADP-ribosyltransferase PARP7, confirmed by transcriptomics, quantitative RT-PCR, western blot, and immunofluorescence. Genetic knockdown via trim-away technology or pharmacological inhibition with RBN-2397 caused developmental delay/arrest at the 2-cell stage, impaired blastocyst formation, and defective ZGA. Mechanistically, PARP7 deficiency reduced chromatin accessibility (ATAC-seq), diminished H3K4ac and H3K27ac marks, and impaired RNA polymerase II transcription. Integrated proteomics and ADP-ribosylome analysis of late 2-cell embryos identified UHRF1 as a key PARP7 target, mono-ADP-ribosylated at lysines K30 and K31. This modification stabilized UHRF1 protein (cycloheximide chase), and UHRF1 overexpression partially rescued the transcriptional defects associated with ZGA from PARP7 inhibition. Our findings establish a metabolic-epigenetic axis wherein NAD+ metabolism, via PARP7-mediated ADP-ribosylation of UHRF1, regulates chromatin remodeling and transcriptional activation during ZGA, offering fundamental insights into early development.

Animals↗

PubMed2026

Cross-tissue immune profiling of APOE ε4 reveals early dysregulation in Alzheimer's disease.

INTRODUCTION: Apolipoprotein E (APOE) ε4 is the strongest genetic risk factor for late-onset Alzheimer's disease (AD), but its contribution to disease pathogenesis remains incompletely understood. METHODS: Here, we integrate proteomic profiling of plasma (n = 9028), cerebrospinal fluid (n = 1099), dorsolateral prefrontal cortex (n = 720), and superior temporal gyrus (n = 105) to define the immune phenotype associated with APOE ε4. RESULTS: We identify a conserved, allele dose-dependent pro-inflammatory immune protein signature across peripheral and central tissues independent of AD diagnosis. This signature also emerges in patient-derived cortical organoids prior to amyloid beta and tau pathology, supporting a genotype-driven mechanism. Cross-tissue comparisons reveal shared innate and antiviral responses alongside tissue-specific immune signaling. Notably, a 12-week medical ketogenic diet partially reversed the APOE ε4 immune signature. DISCUSSION: These findings position immune dysregulation as an early and tractable driver of AD risk in APOE ε4 carriers with direct implications for targeted prevention strategies.

Humans↗