Molecular omics最新文献

{"title":"Identification of putative kidney-derived proteins in plasma using nanoparticle enrichment.","authors":"Daniela A Key Planas, Sumaiya Nazli, Angelica M Riojas, Arisbeth Camarillo Reyes, Avinash Jadhav, Kip Zimmerman, Laura A Cox, Michael Olivier","doi":"10.1093/molecular-omics/aaiag008","DOIUrl":"10.1093/molecular-omics/aaiag008","url":null,"abstract":"<p><p>Many diseases, including diabetes and hypertension, can lead to kidney damage, often resulting in long-term health complications and organ failure. Both animal and human studies have documented a causal relationship between high dietary sodium intake and elevated blood pressure. We explored a proteomics analysis of plasma samples to detect early kidney damage in response to a high-sodium (HS) diet through the quantification of putative kidney-derived proteins in plasma for early disease detection. Plasma samples from seven female baboons fed an HS diet for 6 weeks were collected before and after the HS diet challenge. Plasma samples were analysed using a novel nanoparticle enrichment protocol. Using Seer's Proteograph XT workflow, we identified 2294 plasma proteins across all the samples. Of these, 2139 proteins were annotated with gene IDs, including 453 proteins previously identified in kidney lysate. In the Human Protein Atlas, 1969 of these proteins were annotated as expressed in the kidney, and 37 were classified as elevated. Ninety-seven proteins were only detected in plasma samples collected after the 6-week HS diet. We also identified 35 nominally significant differentially abundant proteins (P < .05), with 84% of these detected at higher abundance after HS exposure. Additional proteins were identified in two animals that demonstrated an increase in blood pressure in response to the HS diet. Our analysis reports an increase in putative kidney-derived proteins in plasma after HS diet exposure, and demonstrates the suitability of the Seer's Proteograph technology to identify potential biomarkers for kidney tissue damage.</p>","PeriodicalId":19065,"journal":{"name":"Molecular omics","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13017961/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146202246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prostate cancer: metabolic remodelling in expressed prostatic secretions reveals cellular structural changes measured by mpMRI.","authors":"Anuj Kumar, Ashish Ranjan, Aniket Anand, Avinash D Gautam, Hira Lal, Kavindra Nath, Uday P Singh, Ashish Gupta","doi":"10.1093/molecular-omics/aaiag013","DOIUrl":"10.1093/molecular-omics/aaiag013","url":null,"abstract":"<p><p>Early and accurate differentiation of prostate cancer (PC) from benign prostatic hyperplasia (BPH) remains challenging; metabolomics enables biomarker discovery by capturing disease-specific metabolic changes. The study includes 64 expressed prostatic secretion from 31 PC cases and 33 BPH cases. Nuclear magnetic resonance spectroscopy was used for metabolomics. Multivariate analyses, including principal component analysis, orthogonal partial least squares discriminant analysis, and artificial neural network modelling, were performed to identify discriminative metabolites. Diagnostic performance was assessed using receiver operating characteristic curve analysis. Clinical correlations with prostate-specific antigen (PSA) levels, multiparametric MRI (mpMRI), and Gleason score (GS) were executed. Citrate, glutamate, myo-inositol, and cis-aconitate were identified as key metabolites distinguishing PC from BPH, showing significant correlations with PSA, mpMRI-derived Prostate Imaging Reporting and Data System scores and apparent diffusion coefficient values as well as histopathology-based GS. The identified metabolic signature demonstrates strong potential as a noninvasive tool to support early PC detection and clinical decision-making, showing correlation with PSA, mpMRI indices and GS to enhance diagnostic accuracy before structural changes become evident.</p>","PeriodicalId":19065,"journal":{"name":"Molecular omics","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147593416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Urinary metabolomics identifies lactate as a biomarker for bladder cancer detection and progression.","authors":"Ângela Carapito, Tiago Vieira de Sousa, Ana Teixeira-Marques, Rui Henrique, Carmen Jerónimo, Ana Cecília A Roque, Félix Carvalho, Joana Pinto, Paula Guedes de Pinho","doi":"10.1093/molecular-omics/aaiag004","DOIUrl":"10.1093/molecular-omics/aaiag004","url":null,"abstract":"<p><p>Bladder cancer (BC) is the ninth most prevalent malignancy worldwide. It remains a significant clinical burden due to high recurrence rates and the need for reliable, non-invasive diagnostic tools. Metabolomics is a powerful strategy for non-invasive cancer detection, with urine representing an ideal biofluid for biomarker discovery, given its direct contact with the urinary tract and its rich diversity of metabolites. This study aimed to identify urinary metabolites showing significant differences in urinary levels between BC patients and controls, and to evaluate their potential for diagnosis and disease monitoring. Beyond identifying metabolites differentiating BC patients from controls, we also assessed whether urinary metabolic patterns could distinguish BC subtypes [non-muscle invasive BC (NMIBC) versus muscle-invasive BC (MIBC)]. Following chemical derivatization, urinary samples were analysed by gas chromatography-mass spectrometry, and the resulting datasets were evaluated using univariate and multivariate statistical approaches. Among the 32 metabolites identified (e.g. amino acids, organic acids, alcohols, and sugar-derivatives), lactate was identified as significantly upregulated in BC versus controls, particularly in MIBC cases. Receiver operating characteristic analysis demonstrated a good performance for overall BC detection and in discriminating between MIBC and NMIBC cases. These results, independent of smoking status and sex, position lactate as a promising non-invasive biomarker for invasive BC.</p>","PeriodicalId":19065,"journal":{"name":"Molecular omics","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146143022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Native PGC-LC-MS profiling reveals distinct O-acetylation patterns of sialylated N-glycans across mammalian sera.","authors":"Christopher Ashwood","doi":"10.1093/molecular-omics/aaiag010","DOIUrl":"10.1093/molecular-omics/aaiag010","url":null,"abstract":"<p><p>O-acetylation of sialic acids represents an additional layer of structural diversity and biological complexity, occurring at various hydroxyl positions (commonly C-7, C-8, or C-9) of the sialic acid residue. This modification modulates the recognition of sialylated glycans by lectins, antibodies, and viral proteins, and contributes to viral tropism and host susceptibility, particularly in influenza and coronaviruses that bind O-acetylated sialylated receptors. However, current LC-MS glycomics workflows commonly employ reduction or permethylation, which, while improving chromatographic stability and ionization, result in the loss of labile O-acetyl groups, obscuring their biological relevance. Native glycan analysis, in contrast, preserves the complete structural integrity of glycans, enabling accurate detection of labile modifications. Using a native released glycan workflow limited to pH ≤8, O-acetylated N-glycans were detected in mouse and rat sera that were previously undetectable under basic derivatization conditions. Beam-type collision-induced dissociation generated the most informative fragmentation spectra, with diagnostic ions confirming O-acetylated NeuGc and NeuAc residues. Chromatographic profiling revealed later elution and broadened peak shapes for O-acetylated species, consistent with increased hydrophobicity and microheterogeneity. A checkpoint-based identification workflow incorporating isotopic, chromatographic, and MS2 criteria reduced false positives, retaining only 3%-5% of putative O-acetylated glycans as confident identifications. Quantitative comparison across species revealed extensive O-acetylation in rat (53.4%) and moderate modification in mouse (8.8%), but none detectable in human serum. These findings establish a robust analytical framework for native detection and characterization of O-acetylated N-glycans, revealing species-specific regulation of this labile modification.</p>","PeriodicalId":19065,"journal":{"name":"Molecular omics","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147369775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Need for speed: advances in the era of high throughput interaction proteomics.","authors":"Fabian Frommelt, Uliana Federico, Ruedi Aebersold, Andrea Fossati","doi":"10.1093/molecular-omics/aaiag012","DOIUrl":"10.1093/molecular-omics/aaiag012","url":null,"abstract":"<p><p>Protein-protein interactions are central to virtually all biological processes, forming intricate networks that operate in a highly regulated manner. These interactions are not permanent but rather continuously adapt to environmental changes, developmental cues, or disease-related stress. Understanding which protein interactions are present in a specific cellular state and how they adapt to specific stimuli is one of the long-standing goals of modern systems biology. Mass spectrometry (MS)-based proteomics has emerged as the primary tool for charting these networks. Over the past two decades, continuous advances in instrumentation, sample preparation, and data analysis have enabled researchers to explore the protein interaction landscape with increasing depth and accuracy. This has led to important discoveries in areas ranging from fundamental cell signalling to the identification of new therapeutic targets. We present the current state of MS-based protein interaction analysis, focusing on the three most widely utilized approaches: affinity purification, proximity labelling, and co-fractionation MS. For each, we discuss the fundamental approach, technical considerations, limitations, and highlight the potential integration with future technologies and datasets. Recent innovations such as short-gradient chromatography and faster data acquisition have further improved sensitivity and throughput. Together, these developments are bringing researchers closer to mapping the dynamic, context-dependent architecture of protein networks in unprecedented detail.</p>","PeriodicalId":19065,"journal":{"name":"Molecular omics","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147369893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Gene expression analysis of carbohydrate catabolism in Leucoagaricus gongylophorus LEU18496.","authors":"Freddy Castillo-Alfonso, Gabriela Cejas-Añón, Cecilio Valadez-Cano, Juan Carlos Sigala-Alanis, Gabriel Vigueras-Ramírez, Roberto Olivares-Hernández","doi":"10.1093/molecular-omics/aaiag007","DOIUrl":"10.1093/molecular-omics/aaiag007","url":null,"abstract":"<p><p>The fungal symbiont of leaf-cutter ant Atta mexicana, Leucoagaricus gongylophorus LEU18496 has the capability to produce enzymes such as cellulases, hemicellulases, and ligninases for plant biomass degradation. In this study, the fungus has been cultivated in submerged culture conditions using glucose and cellulose as carbon sources to explore gene expression level and unravel the molecular mechanisms responsible of enzyme production and carbohydrate catabolism. The transcriptomic analysis of L. gongylophorus LEU18496 using RNA-seq data, allowed the examination of the gene expression profiles across different carbon sources and growth phases. During the exponential growth phase on glucose there is a constitutive expression of several CAZymes, including β-glucosidase, pectinase, and endo-β-1,3-glucanase. The transcriptome data showed high expression of the creA repressor gene in the presence of glucose, underscoring its regulatory role in carbohydrate degradation and suggesting a regulatory mechanism governing CAZyme production and secretion when glucose is used as a carbon source. This study offers detailed insights into the pathways of cellulose and glucose catabolism, emphasizing the expression of key components involved in carbohydrate metabolism unravelling the metabolic strategies of L. gongylophorus providing information of the CAZymes and FOLymes production as high-value product suitable for biotechnological applications.</p>","PeriodicalId":19065,"journal":{"name":"Molecular omics","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146195172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Uncovering urinary proteogenomic signatures associated with head and neck squamous cell carcinoma.","authors":"Oriana Barros, Joaquim Castro Silva, Eurico Monteiro, Susana Aveiro, Pedro Domingues, Pedro Valente Sousa, Carolina Castro, Catarina Rodrigues, António Barros, Francisco Amado, Saeid Ghavami, Vito G D'Agostino, Rita Ferreira, Rui Vitorino, Lúcio Lara Santos","doi":"10.1093/molecular-omics/aaiag002","DOIUrl":"10.1093/molecular-omics/aaiag002","url":null,"abstract":"<p><p>Head and neck squamous cell carcinoma (HNSCC) is a major clinical challenge due to its aggressive nature and poor prognosis in advanced stages. Late detection, often due to a delayed diagnosis, limits treatment success. With the aim of improving the early diagnosis of HNSCC, we analysed urine samples from 19 male HNSCC patients and 10 healthy male subjects and identified 1427 proteins by mass spectrometry (MS)-based proteomics. Of these, 351 proteins were consistently detected in all subjects and selected for quantitative comparisons, which highlighted potential prognostic markers such as RNASE1, LRG1, and CD44. Proteogenomic cross-referencing of MS-identified peptides with cancer variant databases suggested the presence of HNSCC-associated protein variants [e.g. GAA p.(Trp746Cys) and SIAE p.(Pro210Leu)] as potential indicators of advanced disease. Functional analyses linked the identified proteins to important tumour-related processes, including the epithelial-mesenchymal transition and neutrophil degranulation. These results support urine as a valuable body fluid for proteogenomic profiling, as it can be collected non-invasively, is available in large volumes, and enables the longitudinal monitoring of molecular changes over time, providing a convenient window into systemic and tumour-associated processes. This study provides a proof of concept that tumour-related protein variants originating from HNSCC can be detected in urine, supporting its potential as a source of biomarkers for early detection. However, given the small, male-only cohort, these findings should be regarded as preliminary and will require validation in larger, sex-balanced cohorts, including patients with benign or inflammatory head and neck conditions, to confirm disease specificity. Altogether, our data underscore the translational promise of urinary proteogenomics in HNSCC management.</p>","PeriodicalId":19065,"journal":{"name":"Molecular omics","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146125954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring infection biology with mass spectrometry-based proteomics.","authors":"Grisna I Prensa, Andrea García Navarro, David Parker, Andrea Fossati","doi":"10.1093/molecular-omics/aaiag009","DOIUrl":"10.1093/molecular-omics/aaiag009","url":null,"abstract":"<p><p>Investigating host-pathogen interactions at the molecular level is critical for understanding infection mechanisms and identifying potential therapeutic targets. Mass spectrometry (MS)-based proteomics has rapidly become one of the most employed techniques for the study of almost every aspect of the proteome, hence offering strong potential to study protein dynamics during viral infections. This review presents an overview of key MS-based approaches used in host-virus research to study changes in protein expression, cell signalling, and protein-protein interactions. For each method, we outline its underlying principles, practical and analytical expertise required and key strengths and limitations, with a particular focus on how each can be applied to study specific aspects of the dynamic interplay between host and virus. By comparing these approaches side by side, the review aims to give researchers a conceptual and practical guide on how to select the adequate MS technique for their specific biological questions in infectious biology. Ultimately, this resource is intended to support informed experimental design in host-pathogen research, helping to harness the full potential of MS-based proteomics in uncovering the complexity of infection biology.</p>","PeriodicalId":19065,"journal":{"name":"Molecular omics","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146220359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Green synthesis of silver nanoparticles using Padina tetrastromatica against malaria and deciphering the mechanism through machine learning-driven metabolomics and network pharmacology.","authors":"Nikhila Yaladanda, Yashwanth Kumar Budige, Dileepkumar Veeragoni, Jhansi Venkata Nagamani Josyula, Ramesh Rodda, Vineeta Singh, Prabhakar Sripadi, Srinivasa Rao Mutheneni","doi":"10.1093/molecular-omics/aaiag011","DOIUrl":"10.1093/molecular-omics/aaiag011","url":null,"abstract":"<p><p>Malaria remains a major public health challenge due to drug and insecticide resistance, underscoring the need for novel therapies with distinct mechanisms of action. In this study, silver nanoparticles were green-synthesized using the brown marine algae Padina tetrastromatica (Ag-PT) and evaluated through integrated in vitro, in vivo, metabolomics, network pharmacology, and in silico approaches. Ag-PT showed potent antiplasmodial activity, with significantly lower IC50 values and superior parasite suppression compared to chemically synthesized silver nanoparticles. Untargeted metabolomics revealed that Ag-PT treatment specifically restored malaria-induced disruptions in fatty acid, arginine, and arachidonic acid metabolism. This included elevating precursors of specialized pro-resolving mediators such as DHA, 14-HDHA, and 18-HEPE, and replenishing l-arginine to improve nitric oxide synthesis and vascular function. Integration with network pharmacology identified COX-2 (PTGS2) as a key hub gene. Molecular docking and dynamics confirmed strong binding of the Ag-PT phytochemical eriodictyol to COX-2, suggesting inhibition that shifts arachidonic acid metabolism toward anti-inflammatory specialized pro-resolving mediator production. Collectively, these findings reveal that Ag-PT offers a multifaceted therapeutic strategy by simultaneously targeting the parasite while modulating host inflammatory and metabolic pathways. This integrated therapeutic strategy highlights the potential of eco-friendly, plant-based nanomedicines as a next-generation intervention for malaria management.</p>","PeriodicalId":19065,"journal":{"name":"Molecular omics","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147369813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-omics integration in genome-scale metabolic models: a review of constraint-based approaches.","authors":"Nabia Shahreen, Abraham Osinuga, Sunayana Malla, Tahereh Razmpour, Masoud Tabibian, Rajib Saha","doi":"10.1093/molecular-omics/aaiag005","DOIUrl":"10.1093/molecular-omics/aaiag005","url":null,"abstract":"<p><p>Genome-scale metabolic models (GEMs) have progressed from stoichiometric reconstructions to predictive, constraint-aware platforms. In this review, we organize strategies for multi-omics integration not by data type, but by the constraint logic they impose on model solution spaces. Biomass functions enforce composition and maintenance demands, while transcriptomic switches prune network feasibility. Enzyme and expression valves cap flux capacity, proteome budgeting enforces allocation trade-offs, and thermodynamics and fluxomics provide physical and experimental calibration. Machine learning (ML) bridges to infer missing priors while retaining mechanistic structure. These categories translate into practical workflows, spanning enzyme-constrained modelling, thermodynamic embedding, and fluxomics-guided calibration, together with minimal reporting standards to ensure transparency and reproducibility. Emerging directions include the integration of single-cell and spatial data, physics-informed and graph-based ML, and translational pipelines that couple computational predictions with experimental validation. By framing omics integration through constraint architectures, this review provides a coherent agenda for making GEMs reproducible, portable, and biologically meaningful across biotechnology, medicine, agriculture, and environmental applications.</p>","PeriodicalId":19065,"journal":{"name":"Molecular omics","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146143041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}