J. Proteome Res. [JOURNAL]
Sun
200 papers
Automated Microvolume Secretome Proteomics Enables Sensitive and Deep Profiling and Noninvasive Single-Embryo Analysis.
Xie J, Wang J, Ge Y … +2 more , Ye Z, Zhang H
J Proteome Res · 2026 Jul · PMID 42201804 · Publisher ↗
Cells continuously deliver proteins into the extracellular space, forming the secretome, which provides a dynamic, biologically informative, and noninvasive readout of cellular functional states. However, conventional se...
Cells continuously deliver proteins into the extracellular space, forming the secretome, which provides a dynamic, biologically informative, and noninvasive readout of cellular functional states. However, conventional secretome proteomics typically requires large sample volumes greater than 2 mL, delivers limited proteome depth, and supports low processing throughput of less than 30 samples a day. Here, we developed an automated microvolume secretome profiling workflow that integrates optimized sample pretreatment and magnetic bead-based proteome sample preparation. This workflow enables efficient secretome profiling from less than 20 μL of conditioned medium, achieving deep proteome coverage of over 3000 proteins with a sample processing throughput exceeding 96 samples per day. Using this workflow, we achieved high-depth, time-resolved secretome profiling from microscale culture medium, capturing temporal changes of secretome. We further applied the method to single mouse embryo culture medium and consistently identified more than 200 secretome proteins per embryo. Notably, Sdc4 and Ooep were consistently observed across developmental stages, highlighting the potential for noninvasive secretome profiling at the single-embryo level. Together, this work establishes a robust and scalable framework for high-depth secretome profiling from ultralow-input samples, broadening the scope of LC-MS-based analysis to microscale and longitudinal biological applications.
Response to Comment on "Deep Proteogenomics of a Photosynthetic Cyanobacterium".
Spät P, Krauspe V, Hess WR … +2 more , Maček B, Nalpas N
J Proteome Res · 2026 Jul · PMID 42201767 · Publisher ↗
This letter responds to the manuscript by Liu et al., in which the authors comment on our work previously published in (Deep Proteogenomics of a Photosynthetic Cyanobacterium. 2023, 22, 1969. DOI: 10.1021/acs.jproteome...
This letter responds to the manuscript by Liu et al., in which the authors comment on our work previously published in (Deep Proteogenomics of a Photosynthetic Cyanobacterium. 2023, 22, 1969. DOI: 10.1021/acs.jproteome.3c00065). After carefully reading their manuscript, we identified several problems with its content. The authors have overlooked or misunderstood several procedures in our proteogenomics workflow, misinterpreted several findings, and, consequently, drew partially wrong conclusions. A direct comparison of their analysis with our published data shows that their results largely confirm our conclusions. For five of the six ORFs they discuss, most notably for , their findings are fully consistent with our peptide evidence and with updated UniProt or NCBI annotations. In the remaining case, our results agree with established reference annotations and previously published MS studies. In our opinion, the criteria for "deep proteogenomic annotation" proposed by Liu et al. largely reiterate existing standards. To conclude, their letter does not contradict our findings, but instead reflects misunderstandings of our data presentation and methodology.
Proteomic Study on the Amelioration of Cognitive Impairments in 3×Tg-AD Mice by Treadmill Exercise.
Fu Q, Yi Z, Guan Y … +3 more , Tang J, Wang S, Wan C
J Proteome Res · 2026 Jun · PMID 42200610 · Publisher ↗
Alzheimer's disease (AD) is the most common neurodegenerative disorder. Exercise can delay the onset of AD and improve cognitive dysfunction, but its underlying mechanism still needs further exploration. In this study, 6...
Alzheimer's disease (AD) is the most common neurodegenerative disorder. Exercise can delay the onset of AD and improve cognitive dysfunction, but its underlying mechanism still needs further exploration. In this study, 6-month-old transgenic mice underwent a 12-week treadmill exercise intervention. The water maze experiment demonstrated that the learning and memory abilities of AD-exercise (ADE) mice were significantly superior to those of the wild-type mice. The proteomics analysis identified several proteins that were significantly upregulated or downregulated after treadmill exercise, such as SYT1, SLC25A5, and DLST in the hippocampal tissue; OPA1, NSF, DLG2, and DNM1 in the cortical tissue; and APP, APOE, MAP2, MAPT, SYP, SYN1/2, and DYNC1H1 in the cerebellar tissue. The functional enrichment analysis suggested that mitochondrial dysfunction, synaptic vesicle transport, and amyloid fibril formation in AD mice tend to recover to levels similar to those of wild-type mice. At the same time, the processes of exercise-induced axon guidance, protein stabilization, and negative regulation of apoptosis were enhanced more effectively than in wild-type animals. These results will help us understand how exercise improves cognition in AD mice.
Peptidomics and Beyond: Development of a Novel Platform Based on Capillary Electrophoresis-Mass Spectrometry for Metabolomics of Medium-Molecular-Weight Compounds.
Nitta T, Yamamoto H, Tomatsu H … +3 more , Matsuta R, Kami K, Sasaki K
J Proteome Res · 2026 Jun · PMID 42199095 · Publisher ↗
Proteomics targets proteins typically >10 000 Da, while metabolomics focuses on small molecules <1000 Da. In contrast, omics approaches targeting medium-molecular-weight compounds (MMWCs) remain underdeveloped. Although...
Proteomics targets proteins typically >10 000 Da, while metabolomics focuses on small molecules <1000 Da. In contrast, omics approaches targeting medium-molecular-weight compounds (MMWCs) remain underdeveloped. Although peptidomics targets these molecules, progress has been limited by several factors, including the low abundance of bioactive peptides, their instability during sample preparation, and the lack of analytical platforms capable of comprehensively analyzing diverse modified peptides and other as-yet-uncharacterized MMWCs. Here, we developed a novel high-sensitivity platform based on capillary electrophoresis coupled with high-resolution mass spectrometry (CE-HRMS) for the comprehensive analysis of peptides and other MMWCs. To achieve this, we implemented large-volume dual preconcentration by isotachophoresis and stacking (LDIS), which increased the injection volume by 60-fold over the standard volume and enabled detection limits of 10 pg/mL for peptides such as bradykinin and ANP. We then applied this novel platform to plasma samples from hyperlipidemia patients and found significantly elevated levels of a series of peptides, including bradykinin, CLIP, and schizophrenia-related peptides, along with 63 additional protein-derived peptide fragments and two unknown MMWCs. In conclusion, this platform enables systematic exploration of previously uncharacterized molecules, facilitating the discovery of novel functional peptides and other MMWC biomarkers.
From Multiomics Discovery to Clinical Validation: Identification of Novel Noninvasive Biomarkers for Liver Fibrosis.
Wu B, Wang Z, Ji P … +5 more , Huang X, Han S, Mei C, Ren J, Wu M
J Proteome Res · 2026 Jun · PMID 42192591 · Publisher ↗
Early diagnosis of liver fibrosis is vital for preventing cirrhosis. Through integrated multiomics and single-cell sequencing, we identified Thrombospondin 2 (THBS2), Growth Differentiation Factor 15 (GDF15), and Neurofa...
Early diagnosis of liver fibrosis is vital for preventing cirrhosis. Through integrated multiomics and single-cell sequencing, we identified Thrombospondin 2 (THBS2), Growth Differentiation Factor 15 (GDF15), and Neurofascin (NFASC) as prioritized biomarkers, exhibiting prominent expression in fibroblasts and hepatocytes. studies confirmed their significant upregulation and distinct colocalization in fibrotic livers. Clinical validation showed significant biomarker elevation correlating with fibrosis severity ( < 0.001). THBS2 and GDF15 demonstrated superior diagnostic accuracy (AUCs > 0.94) over FIB-4, while NFASC effectively discriminated early-stage (F0-2) from advanced (F3-4) fibrosis (AUC = 0.877). To optimize precision, we developed a multivariable model integrating these biomarkers with clinical variables (Age, Sex, ALT, AST, PLT). This model achieved an excellent AUC of 0.925 (95% CI: 0.941-0.998), significantly enhancing risk stratification over the BiomarkerOnly model (NRI = 1.198, < 0.001). In conclusion, through a translational study combining multiomics and experimental validation, we characterized THBS2, GDF15, and NFASC as novel biomarkers for liver fibrosis, offering a promising strategy for noninvasive stratification and monitoring of fibrosis.
Comprehensive Evaluation of Coextraction Workflows for Enhanced Multiomics Integration in Complex Biological Samples.
Shao X, Chu B, Duan X … +7 more , Zhang J, Liu S, Li S, Hou Y, Shen L, Niu M, Wang H
J Proteome Res · 2026 Jun · PMID 42186800 · Publisher ↗
Integrative multiomics analysis offers valuable insights into complex biological systems, yet conventional stepwise extraction methods are often limited by tissue spatial heterogeneity and technical biases introduced thr...
Integrative multiomics analysis offers valuable insights into complex biological systems, yet conventional stepwise extraction methods are often limited by tissue spatial heterogeneity and technical biases introduced through repeated processing, which may compromise cross-omics comparability. To address this, we evaluated a coextraction strategy for multiomics profiling of mouse brain tissue. This approach increased RNA yield per milligram of tissue by 32.55% compared with traditional methods while maintaining comparable sequence coverage (88.14%) and reproducibility ( > 0.98). At the proteome level, approximately 7100 proteins were identified, comparable to conventional protocols, with consistent representation of neural functional protein categories, including membrane proteins, kinases, ubiquitin ligase complexes, and transcription factors. Phosphoproteomic analysis revealed increased coverage with 4347 additional high-confidence phosphosites identified, enabling enhanced resolution of regulatory signaling pathways. Integrated multiomics analysis further showed higher RNA-protein correlations (median value from 0.25 to 0.56) and strengthened enrichment of neural pathways such as synaptic transmission and nervous system development. Overall, this coextraction strategy provides a practical workflow for multiomics integration and may facilitate studies of complex molecular regulation in brain systems.
Metabolomic Profiling of Squid Chromatophores Reveals Differential Biochemical Fingerprints across Red, Yellow, and Brown Colors.
Bagwe K, Schrimpe-Rutledge AC, Codreanu SG … +3 more , Sherrod SD, McLean JA, Deravi LF
J Proteome Res · 2026 Jun · PMID 42186259 · Full text
Cephalopods possess the ability to camouflage using specialized dermal organs, including chromatophores that modulate pigment-based color, iridophores that produce structural iridescence, and leucophores that scatter lig...
Cephalopods possess the ability to camouflage using specialized dermal organs, including chromatophores that modulate pigment-based color, iridophores that produce structural iridescence, and leucophores that scatter light to create diffuse white. Among these organs, chromatophores─present as yellow, red, and brown variants─contribute to rapid color changes during camouflage, as their multicellular architecture expands under neuromuscular control. While the general structure and function of chromatophores have been characterized, the specific biochemical features that drive their distinct pigmentation remain poorly understood. To address this gap, we performed untargeted LC-MS/MS metabolomics across manually isolated yellow, red, and brown chromatophores. We detected over 4,000 compounds with extensive overlap across all three chromatophore types. However, differential abundance patterns through directed pairwise comparisons revealed variation in metabolic activity among the colors, where yellow chromatophores exhibited enrichment in oxidative pathways, brown chromatophores showed enrichment in pigment-related metabolites, and red chromatophores displayed an intermediary state. While future targeted biochemical studies are required to connect these differences to their functional contributions in camouflage, our findings introduce a framework suggesting that chromatophore color identity stems from subtle differences across a metabolic continuum, rather than from discrete, isolated biochemical states. These differences may reflect a level of developmental programming of color unique to cephalopods.
A Comment on "Deep Proteogenomics of a Photosynthetic Cyanobacterium".
Liu H, Pakrasi HB, Gross ML
J Proteome Res · 2026 Jul · PMID 42166791 · Publisher ↗
Proteomic researchers strive to achieve complete annotation of protein-coding DNA sequences to provide a foundational context for their relevant biological data. A recent deep proteogenomic study using a photosynthetic c...
Proteomic researchers strive to achieve complete annotation of protein-coding DNA sequences to provide a foundational context for their relevant biological data. A recent deep proteogenomic study using a photosynthetic cyanobacterium . PCC 6803 by Spät et al. proposed 64 refined open reading frames (ORFs). By searching LC-MS/MS data from affinity chromatography-isolated protein complexes, our laboratory identified that six of these high-abundance ORFs possess N-terminal initiation start sites that differ than those proposed in the alternative models. Our findings are supported by highly confident MS2 data, phylogenetic analysis, chemical labeling, and established data from two independent research groups. Based on these high-quality experimental identifications, we subsequently propose a standardized strategy and set of criteria for future deep proteogenomic efforts to ensure accurate and stringent proteogenomic annotation.
Bridging Simplicity and Depth in Single-Cell Proteomics: A Cost-Effective Workflow and an Expanded Framework for Data Evaluation.
Chi S, Rogalski J, Zhong H … +8 more , Garcia Martinez E, Ebrahimi A, Wong R, Bailey ML, Marra MA, Maier CS, Snutch TP, Foster LJ
J Proteome Res · 2026 Jun · PMID 42154441 · Publisher ↗
Single-cell proteomics (SCP) offers direct insight into functional protein states that drive cellular heterogeneity, complementing genomic and transcriptomic analyses. Although recent reports have demonstrated improved p...
Single-cell proteomics (SCP) offers direct insight into functional protein states that drive cellular heterogeneity, complementing genomic and transcriptomic analyses. Although recent reports have demonstrated improved proteome coverage, their reliance on specialized instrumentation limits the broader adoption. Additionally, current evaluation practices remain largely centered on protein and peptide identification counts, which alone do not fully reflect data quality or biological interpretability. Here, we describe an accessible, label-free SCP workflow that implements easily accessible laboratory equipment: a single-cell dispenser, conventional multiwell plates, and an incubator with water-bath-based humidity control. Using trapped ion mobility spectrometry─time-of-flight mass spectrometry (timsTOF), we systematically optimized key sample preparation variables, including trypsin concentration, incubation time, reduction/alkylation, digestion conditions, and plate types, which together maximize data quality and reproducibility. We further introduce a data quality framework that moves beyond identification counts, emphasizing quantitative consistency and biological interpretability via individual protein coverage completeness across cells, coefficients of variation across technical replicates, peptide-to-protein ratios, and single-cell-to-bulk correlations. Collectively, our approach lowers technical barriers to accessing SCPs while enabling more rigorous, interpretable, and scalable SCP analysis across diverse research contexts.
Proteomic Identification of Small-Subunit Ribosome Assembly Factors in .
Perez GG, Hiraiwa PM, da Silva VS … +2 more , Zanchin NIT, Guimarães BG
J Proteome Res · 2026 Jun · PMID 42150138 · Full text
Trypanosomatid ribosomes display distinctive features, including extensive ribosomal RNA (rRNA) expansions and additional insertions in ribosomal proteins. Moreover, the region corresponding to the human 28S rRNA is frag...
Trypanosomatid ribosomes display distinctive features, including extensive ribosomal RNA (rRNA) expansions and additional insertions in ribosomal proteins. Moreover, the region corresponding to the human 28S rRNA is fragmented into six molecules in these organisms with a duplication of the 3' fragment (ε) in. Although these differences suggest that ribosome biogenesis in trypanosomatids may involve unique processing events, the molecular mechanisms underlying this process are still poorly characterized. In this study, we investigated the protein composition of pre-small-subunit (pre-SSU) complexes in . We generated cell lines expressing tagged versions of UTP6 and PNO1, two conserved ribosome biogenesis factors that provide complementary access to complexes of early SSU processome intermediates and later pre-40S maturation stages. Affinity purification followed by mass spectrometry identified numerous conserved ribosome biogenesis factors alongside a substantial set of trypanosomatid-specific proteins with no assigned function. Structural analyses revealed that many of these uncharacterized proteins contain predicted RNA-binding motifs or protein-protein interaction domains, and have been previously localized to the nucleolus, supporting potential roles in ribosome synthesis. Our findings expand the repertoire of candidate SSU assembly factors in kinetoplastids and highlight species-specific adaptations in ribosome biogenesis, providing a foundation for future functional studies targeting these unique components.
Optimized NMR-Based Metabolomic Protocol for Salivary Analysis in Clinical Practice.
Campas M, Germay C, Cirillo A … +5 more , Schoumacher M, Pinsart A, Defauwes I, Cavalier E, de Tullio P
J Proteome Res · 2026 Jun · PMID 42149665 · Publisher ↗
Saliva remains underexplored in metabolomics compared with widely used biofluids such as blood and urine. However, its noninvasive, rapid, and cost-effective collection, together with its suitability for self-sampling, m...
Saliva remains underexplored in metabolomics compared with widely used biofluids such as blood and urine. However, its noninvasive, rapid, and cost-effective collection, together with its suitability for self-sampling, makes it attractive for clinical and personalized medicine. Moreover, saliva is expected to provide complementary metabolic information on other biofluids. In this context, this study aims to identify an optimal sample collection and preparation protocol for maximizing informative metabolomic data from salivary nuclear magnetic resonance (NMR) profiles. Four preparation protocols, selected and adapted from the literature, were systematically compared using the number of identified metabolites, their concentrations, and intraday repeatability as evaluation criteria. Among them, an in-house-adapted method combining centrifugation, freeze-drying, and ultrafiltration proved most effective. This approach provided the broadest metabolome coverage, with 42 metabolites quantified. This method was further assessed using analysis of variance to determine intra- and interday precision. Most metabolites demonstrated excellent repeatability (coefficients of variation below 10%), confirming the protocol reliability for quantitative metabolomics. Overall, the optimized approach yields high-quality spectra, wide metabolic coverage, and strong analytical precision, supporting reproducible salivary NMR metabolomics. Beyond its methodological contribution, this work highlights saliva as a promising biofluid for diagnostics, disease monitoring, and personalized medicine, provided that collection and preparation procedures are appropriately standardized.
AI-Based Digital Pathology-Enabled Spatial-Omics Data Analyses of the Human Kidney.
Beishembieva N, Gorman B, Paul AS … +7 more , Veličković M, Veličković D, Clair G, Sharma K, Sarder P, Anderton CR, Kidney Precision Medicine Project
J Proteome Res · 2026 Jun · PMID 42139323 · Publisher ↗
Identification of tissue-region-specific changes in glycosylation is crucial for understanding the pathogenesis of kidney diseases, yet it remains a great challenge. We developed a workflow that combines matrix-assisted...
Identification of tissue-region-specific changes in glycosylation is crucial for understanding the pathogenesis of kidney diseases, yet it remains a great challenge. We developed a workflow that combines matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) data with AI-based digital pathology annotations of kidney functional tissue units (FTUs) to profile N-glycan distributions within biopsy tissues. This approach can generate molecular-level data relevant to diverse pathological outcomes, thereby aiding in the elucidation of disease mechanisms. As a proof-of-concept, we demonstrate that this AI-based digital pathology approach to MALDI data segmentation enables the detection and differentiation of N-glycosylation within FTUs of healthy kidney tissue. We then elucidated differences in N-glycosylation between the diseased kidney tissue samples from patients with different diagnoses. Sialic acid N-glycans, which have been linked to various kidney diseases, displayed enrichment in the glomeruli and tubules of tissues from patients diagnosed with diabetic kidney disease (DKD), whereas they were enriched in the tubules and arteries from patients with acute kidney injury (AKI), in comparison to healthy tissue. Furthermore, we found that polylactosamine N-glycans were enriched only in the AKI samples, indicating their potential roles in tubular injury and inflammation. This workflow has the potential to bridge the gap between region-specific glycosylation and its implications on FTUs in diseases, paving the way for targeted molecular imaging studies in the kidney and other tissues.
S100 Calcium-Binding Protein P Predicts Early Recurrence and Poor Survival in Distal Cholangiocarcinoma: A Proteomics Study.
Kim H, Huh S, Han IW … +10 more , Choi YH, Choi K, Lee SE, Lee SH, Jang KT, Lee JK, Lee KT, Park JK, Kim MS, Lee KH
J Proteome Res · 2026 Jun · PMID 42136396 · Publisher ↗
Distal cholangiocarcinoma (dCCA) is a rare malignancy with a poor prognosis, necessitating novel biomarkers for acute prognosis and optimal treatment selection. This study aimed to elucidate the proteomic landscape of dC...
Distal cholangiocarcinoma (dCCA) is a rare malignancy with a poor prognosis, necessitating novel biomarkers for acute prognosis and optimal treatment selection. This study aimed to elucidate the proteomic landscape of dCCA and identify novel biomarkers associated with improved patient outcomes. Proteomic profiling was conducted on 18 surgical samples from patients with dCCA by using shotgun liquid chromatography with tandem mass spectrometry. Patients were categorized into early recurrence ( = 9) and nonearly recurrence ( = 9) groups. Validation was performed via immunohistochemical (IHC) analysis on an independent dCCA cohort of 26 tissue microarray samples. A total of 6804 proteins were identified, and differential expression and functional enrichment analyses revealed 219 upregulated proteins in the early recurrence group, associated with biological processes of the extracellular matrix and cellular interaction. Among these, S100 calcium-binding protein P (S100P) correlated with EZR, and LGALS3BP was significantly overexpressed in the early recurrence group. Furthermore, high S100P expression was identified as a strong independent risk factor for recurrence, with a hazard ratio (HR) of 4.55 (95% CI, 1.609-12.841, = 0.004) and mortality (HR 4.99, 95% CI 1.794-12.880, = 0.002). These findings identify S100P as a prognostic biomarker for dCCA, suggesting its clinical utility for postoperative risk stratification and patient management.
Aggregation Methods for Quantifying PTM and Structural Changes in Bottom-Up Proteomics.
VonKaenel ED, Rozum JC, Zhang T … +7 more , Stratton KG, Bramer LM, Wiley HS, Qian WJ, Sims AC, Melchior JT, Feng S
J Proteome Res · 2026 Jun · PMID 42136314 · Full text
Bottom-up proteomic workflows rely on sequential preprocessing steps, commonly including peptide-to-protein aggregation ("roll-up"), to enhance data reliability and interpretability. While roll-up is effective for protei...
Bottom-up proteomic workflows rely on sequential preprocessing steps, commonly including peptide-to-protein aggregation ("roll-up"), to enhance data reliability and interpretability. While roll-up is effective for protein-centered analyses, it may be suboptimal for applications focused on post-translational modifications (PTMs) or protein structural changes, such as limited proteolysis-mass spectrometry (LiP-MS). Here, we investigate how different roll-up strategies influence site-level quantification in PTM differential analysis. Moreover, we introduce a novel site-centric roll-up approach tailored for LiP-MS, which quantifies proteolytic fragments rather than solely tryptic peptides. We benchmark these methods through simulation studies, comparing their sensitivity and specificity in detecting structural and PTM-driven changes. We found that the and roll-up methods outperform the method in both PTM and LiP proteomics, and site-level quantification in LiP outperforms peptide-level quantification. Our findings offer the first systematic, data-driven guidance for selecting roll-up techniques in site-level proteomic analyses, with implications for both PTM-focused and structural proteomics studies.
Drug-Induced Alterations of Mouse Aorta Lipidome and Their Potential Correlations with the Gut Ecosystem.
He F, Lin Q, Tan Y … +3 more , Yan Z, He H, Lin L
J Proteome Res · 2026 Jun · PMID 42135208 · Publisher ↗
Drug-induced cardiovascular risk is one of the primary concerns in drug development and clinical practice. Meanwhile, drugs can also alter the gut microbiome, the disturbance of which is correlated with cardiovascular di...
Drug-induced cardiovascular risk is one of the primary concerns in drug development and clinical practice. Meanwhile, drugs can also alter the gut microbiome, the disturbance of which is correlated with cardiovascular diseases. However, the detailed molecular information underlying these associations is still unclear. Here, we comprehensively investigated the impact of 33 commonly used drugs on the mouse aorta lipidome and gut metaproteome, revealing that 6 out of 8 (75.0%) anticancer drugs and 2 out of 16 (12.5%) cardiovascular drugs significantly altered the aorta lipids, with the majority being downregulated. Drugs triggered a greater increase in phosphatidylethanolamine (PE) with longer fatty acyl chains and higher degrees of unsaturation rather than hydrophobicity. Drugs also tend to suppress gut microbial producers of short-chain fatty acids. Antibiotic pretreatment and conventional mouse models revealed potential drug-host-microbe interactions on the gut-vascular axis. This study provides a deeper insight into the pharmacological actions of the studied drugs with a molecular basis for the management of cancer treatment-related cardiovascular diseases.
Metabolism and Excretion of Synthetic Extended Viperin Pathway Deoxydidehydronucleosides in the Sprague-Dawley Rat.
Sala S, Nitschke P, Castillo AM … +11 more , Bernal A, Masuda R, Wood JM, Buckler JN, Grove TL, Almo SC, Harris LD, Holmes E, Wist J, Wilson ID, Nicholson JK
J Proteome Res · 2026 Jun · PMID 42128411 · Full text
Broad-spectrum viral biomarkers offer a promising approach to distinguishing viral from bacterial infections, thereby reducing inappropriate antibiotic use and improving diagnostic response during emerging infectious dis...
Broad-spectrum viral biomarkers offer a promising approach to distinguishing viral from bacterial infections, thereby reducing inappropriate antibiotic use and improving diagnostic response during emerging infectious disease outbreaks. Among these, the deoxydidehydronucleoside (ddhN) class of nucleoside derivatives has emerged as a potential tool for early detection of viral infections in settings where pathogen-specific diagnostics are unavailable. To assess the clinical utility of these compounds, we investigated the metabolism and excretion rates of four principal ddhN metabolites, 3'-deoxy-3',4'-didehydrocytidine (ddhC), 3'-deoxy-3',4'-didehydrocytidine-5'-carboxylate (ddhC-5'CA), 3'-deoxy-3',4'-didehydrouridine (ddhU), and 3'-deoxy-3',4'-didehydrocytidine-5'-homocysteine (ddhC-5'Hcy), in the Sprague-Dawley rat model following a single intravenous dose. Time-resolved biological sampling was used to characterize urinary excretion and downstream biotransformation. All four metabolites exhibited rapid urinary clearance, ranging from approximately 3 to 8 h, consistent with a transient acute-phase profile. Notably, ddhC-5'Hcy underwent extensive biotransformation, with key metabolites produced via functionalization and conjugation identified following integration of nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) analyses. No adverse clinical signs were observed in any treatment group at any time point. These findings support further research into the ddhN series as markers of active viral infection for clinical application, particularly in critical care environments, where timely differentiation of infectious etiology is essential.
Structural Diversity and Analytical Characterization of Acylhomocarnitines.
Weinberg J, Crandall WJ, Jarrell ZR … +7 more , Lim G, Liu K, Lee HY, Patel S, Gacasan CA, Go YM, Jones DP
J Proteome Res · 2026 Jun · PMID 42127330 · Full text
Homocarnitine is a five-carbon analog of carnitine produced in mammals through hydroxylation of the microbiome-derived metabolite δ-valerobetaine. Here, we describe liquid chromatography-mass spectrometry methods for the...
Homocarnitine is a five-carbon analog of carnitine produced in mammals through hydroxylation of the microbiome-derived metabolite δ-valerobetaine. Here, we describe liquid chromatography-mass spectrometry methods for the measurement of fatty acyl-homocarnitines, a previously uncharacterized family of mammalian metabolites. These acyl-homocarnitines are homologs of acyl-carnitines, in which the fatty acid is extended by one carbon. We show that short-chain fatty acyl-CoAs are converted to corresponding acyl-homocarnitines by carnitine acetyltransferase and that these enzyme-generated standards exhibit retention times and ion dissociation patterns identical to acyl-homocarnitines produced by mammalian cells. C-homocarnitine isotope tracer studies showed that mammalian cells produce short-, medium-, and long-chain acyl-homocarnitines. Ion dissociation analyses established diagnostic product ions to distinguish acyl-homocarnitines from isomeric acyl-carnitines. Sample preparation and chromatographic methods are provided to separate and analyze isomers in extracts of mouse tissues. These findings expand knowledge of carnitine analogs and establish analytical strategies to differentiate acyl-homocarnitines from isomeric acyl-carnitines.
The Combination of Machine Learning and Metabolomics for the Clinical Diagnosis of Hepatocellular Carcinoma.
Wang S, Chang ZP, Yin Y … +4 more , Li YN, Cheng K, Zhao YS, Cao LL
J Proteome Res · 2026 Jun · PMID 42126022 · Publisher ↗
The early diagnosis of hepatocellular carcinoma (HCC) lacks biomarkers with a high sensitivity and specificity. This study was to find sensitive and specific diagnostic markers for HCC by analyzing the imbalance of serum...
The early diagnosis of hepatocellular carcinoma (HCC) lacks biomarkers with a high sensitivity and specificity. This study was to find sensitive and specific diagnostic markers for HCC by analyzing the imbalance of serum metabolites in patients with HCC. Nontargeted and targeted metabolomic analyses were used to explore dysregulated metabolites, and many bile acids (such as DCA, GUDCA, GCDCA, GCA, TCDCA, TDCA, TCA, LCA, and TUDCA) and steroid hormones (such as DHEAS, DHEA, Aldo, Cortisone, and 18-OHF) were found to be dysregulated in HCC. A machine-learning model based on bile acids and steroid hormones was constructed using XGBoost to distinguish HCC from normal controls (NC), patients with chronic hepatitis B (CHB), and patients with metabolic dysfunction-associated steatotic liver disease (MASLD). We found that the levels of bile acids and steroid hormones in HCC patients were disturbed compared with NC, CHB, and MASLD patients. The XGBoost model showed strong diagnostic ability in the internal test subset of the training cohort (AUC = 0.876) and was verified in an independent test cohort (AUC = 0.813). It exhibited good diagnostic performance in the detection of early-stage and small-size HCC (AUC = 0.896 and AUC = 0.830) and performed better than the classical biomarker alpha-fetoprotein (AFP). In conclusion, our study established a novel XGBoost model based on bile acids and steroid hormones and might be helpful for the early diagnosis of HCC.
DIA-PASEF Proteomic Profiling of under MpkA-Dependent Iron Stress.
Lee J, West OK, Huso WD … +9 more , Doan AG, Grey K, Edwards H, Tran JT, Carman DR, Betenbaugh MJ, Srivastava R, Harris S, Marten MR
J Proteome Res · 2026 Jun · PMID 42117284 · Publisher ↗
Filamentous fungi play important roles in both biotechnology (as producers of valuable bioproducts) and in human health (as opportunistic pathogens). The fungus is a widely used model organism; however, proteome coverag...
Filamentous fungi play important roles in both biotechnology (as producers of valuable bioproducts) and in human health (as opportunistic pathogens). The fungus is a widely used model organism; however, proteome coverage remains below 15%, limiting comprehensive proteomic analyses. Here, we applied data-independent acquisition-parallel accumulation serial fragmentation (DIA-PASEF) for high-depth proteome profiling of . Using DIA-PASEF, we identified 3,904 proteins across biological triplicates grown in complex medium. This represents a > 140% increase in protein identifications with over 5-fold reduction in analysis time, expanding proteome coverage to 37%. We further integrated proteomic and phosphoproteomic analyses under iron-depleted conditions in an MpkA-deficient mutant (). Deletion of resulted in extensive remodeling of metabolic and signaling networks, with ∼500 additional proteins and >1,800 phosphosites identified relative to the control. Differential expression and phosphorylation increased by more than an order of magnitude in the Δ mutant across Fe conditions. Gene Ontology analysis revealed expanded and distinct biological processes under iron limitation, reflecting adaptive responses to combined iron stress and MAPK disruption. Overall, this study establishes a high-coverage proteomic resource and demonstrates that iron limitation and MAPK pathway disruption enhance siderophore biosynthesis.
Mapping of the hSOX10 Proximal Protein Interactome in Human Melanoma.
Newsom-Stewart CM, Bhatt DP, Major MB … +1 more , Kaufman CK
J Proteome Res · 2026 Jun · PMID 42117278 · Full text
The transcription factor SOX10 is a central regulator of melanoma, influencing tumor initiation, progression, phenotypic plasticity, and therapeutic resistance, yet the protein-protein interactions underlying its functio...
The transcription factor SOX10 is a central regulator of melanoma, influencing tumor initiation, progression, phenotypic plasticity, and therapeutic resistance, yet the protein-protein interactions underlying its function remain poorly defined. To address this, we conducted the first dedicated, comprehensive mapping of the human SOX10 (hSOX10) proximal protein interactome using miniTurbo (mT) proximity-dependent biotinylation coupled with mass spectrometry in A375 melanoma cells. Stable lines expressing N- or C-terminal mT-tagged hSOX10 fusion proteins at near-endogenous levels enabled the unbiased capture of proximal proteins in a native cellular context, identifying 847 melanoma-enriched candidate hSOX10 interactors. Stringent statistical filtering, contaminant frequency profiling, and subcellular localization context refined this to 180 high-confidence candidates, including known hSOX10 partners and previously unidentified candidates. Integration of orthogonal biological relevance criteria (functional enrichment and network context, transcriptomic coexpression with hSOX10, and genomic co-occurrence in melanoma) further refined the dataset to 124 biologically relevant candidates enriched for transcriptional regulators, cofactors, chromatin-modifying complexes, and associated pathways. These proteins were stratified using an evidence-based prioritization framework incorporating transcriptomic, genomic, and chromatin-based context without additional exclusion. Collectively, this work provides a high-confidence resource for the hSOX10 proximal protein interactome in melanoma and a framework for generating testable hypotheses regarding hSOX10-associated regulatory networks, melanoma biology, and therapeutic vulnerabilities.
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