Journal of Proteome Research最新文献

{"title":"PhoXplex: Combining Phospho-enrichable Cross-Linking with Isobaric Labeling for Quantitative Proteome-Wide Mapping of Protein Interfaces","authors":"Runa D. Hoenger Ramazanova,&nbsp;Theodoros I. Roumeliotis*,&nbsp;James C. Wright and Jyoti S. Choudhary*,&nbsp;","doi":"10.1021/acs.jproteome.4c0056710.1021/acs.jproteome.4c00567","DOIUrl":"https://doi.org/10.1021/acs.jproteome.4c00567https://doi.org/10.1021/acs.jproteome.4c00567","url":null,"abstract":"<p >Integrating cross-linking mass spectrometry (XL-MS) into structural biology workflows provides valuable information about the spatial arrangement of amino acid stretches, which can guide elucidation of protein assembly architecture. Additionally, the combination of XL-MS with peptide quantitation techniques is a powerful approach to delineate protein interface dynamics across diverse conditions. While XL-MS is increasingly effective with isolated proteins or small complexes, its application to whole-cell samples poses technical challenges related to analysis depth and throughput. The use of enrichable cross-linkers has greatly improved the detectability of protein interfaces in a proteome-wide scale, facilitating global protein–protein interaction mapping. Therefore, bringing together enrichable cross-linking and multiplexed peptide quantification is an appealing approach to enable comparative characterization of structural attributes of proteins and protein interactions. Here, we combined phospho-enrichable cross-linking with TMT labeling to develop a streamline workflow (PhoXplex) for the detection of differential structural features across a panel of cell lines in a global scale. We achieved deep coverage with quantification of over 9000 cross-links and long loop-links in total including potentially novel interactions. Overlaying AlphaFold predictions and disorder protein annotations enables exploration of the quantitative cross-linking data set, to reveal possible associations between mutations and protein structures. Lastly, we discuss current shortcomings and perspectives for deep whole-cell profiling of protein interfaces at large-scale.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acs.jproteome.4c00567","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142571164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multiomics Studies on Metabolism Changes in Alcohol-Associated Liver Disease","authors":"Liqing He,&nbsp;Raobo Xu,&nbsp;Xipeng Ma,&nbsp;Xinmin Yin,&nbsp;Eugene Mueller,&nbsp;Wenke Feng,&nbsp;Michael Menze,&nbsp;Seongho Kim,&nbsp;Craig J. McClain* and Xiang Zhang*,&nbsp;","doi":"10.1021/acs.jproteome.4c0045110.1021/acs.jproteome.4c00451","DOIUrl":"https://doi.org/10.1021/acs.jproteome.4c00451https://doi.org/10.1021/acs.jproteome.4c00451","url":null,"abstract":"<p >Metabolic dysfunction in the liver represents a predominant feature in the early stages of alcohol-associated liver disease (ALD). However, the mechanisms underlying this are only partially understood. To investigate the metabolic characteristics of the liver in ALD, we did a relative quantification of polar metabolites and lipids in the liver of mice with experimental ALD using untargeted metabolomics and untargeted lipidomics. A total of 99 polar metabolites had significant abundance alterations in the livers of alcohol-fed mice. Pathway analysis revealed that amino acid metabolism was the most affected by alcohol in the mouse liver. Metabolites involved in glycolysis and the TCA cycle were decreased, while glycerol 3-phosphate (G3P) and long-chain fatty acids were increased. Relative quantification of lipids unveiled an upregulation of multiple lipid classes, suggesting that alcohol consumption drives metabolism toward lipid synthesis. Results from enzyme expression and activity detection indicated that the decreased activity of mitochondrial glycerol 3-phosphate dehydrogenase contributed to the disordered metabolism.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142571131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of FGG as a Biomarker in Early Gastric Cancer via Tissue Proteomics and Clinical Verification","authors":"Wujie Chen,&nbsp;Qihua Ye,&nbsp;Biying Zhang,&nbsp;Zhenhua Ma* and Hanxiao Tu*,&nbsp;","doi":"10.1021/acs.jproteome.4c0062410.1021/acs.jproteome.4c00624","DOIUrl":"https://doi.org/10.1021/acs.jproteome.4c00624https://doi.org/10.1021/acs.jproteome.4c00624","url":null,"abstract":"<p >Early and accurate diagnosis of gastric cancer (GC) is essential for reducing mortality and improving patient well-being. However, methods for the early diagnosis of GC are still lacking. In this study, by isobaric tagging for relative and absolute quantitation (iTRAQ), we identified 336 proteins that overlapped among the upregulated differentially expressed proteins (DEPs) in early gastric cancer (EGC) versus progressive gastric cancer (PGC), upregulated DEPs in EGC versus nongastric cancer (NGC), and nonsignificant proteins in EGC versus NGC. These DEPs were involved primarily in the neutrophil-related immune response. Network analysis of proteins and pathways revealed that fibrinogen α (FGA), β (FGB), and γ (FGG) are candidates for distinguishing EGC. Furthermore, parallel reaction monitoring (PRM), immunohistochemistry (IHC), and Western blot (WB) assays of clinical samples confirmed that, compared with that in PGC and NGC, only FGG was uniquely and significantly upregulated in the gastric mucosa of EGC. Our results demonstrated that FGG in the gastric mucosa could be a novel biomarker to diagnose EGC patients via endoscopy.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142560456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characterization of the Angiogenic and Proteomic Features of Circulating Exosomes in a Canine Mandibular Model of Distraction Osteogenesis","authors":"Fengchun Liao,&nbsp;Tao Zhang,&nbsp;Weidong Jiang,&nbsp;Peiqi Zhu,&nbsp;Xiaoping Su*,&nbsp;Nuo Zhou* and Xuanping Huang*,&nbsp;","doi":"10.1021/acs.jproteome.4c0036510.1021/acs.jproteome.4c00365","DOIUrl":"https://doi.org/10.1021/acs.jproteome.4c00365https://doi.org/10.1021/acs.jproteome.4c00365","url":null,"abstract":"<p >Distraction osteogenesis (DO) represents a highly effective method for addressing significant bone defects; however, it necessitates a long treatment period. Exosomes are key mediators of intercellular communication. To investigate their role in the angiogenesis and osteogenesis of DO, we established a canine mandibular DO model with a bone defect (BD) group as the control. Higher levels of angiogenesis were observed in the regenerating tissue from the DO group compared to those from the BD group, accompanied by earlier osteogenesis. Proteomic analysis was performed on circulating exosomes at different phases of the DO using a data-independent acquisition method. Data are available <i>via</i> ProteomeXchange with the identifier PXD050531. The results indicated specific alterations in circulating exosome proteins at different phases of DO, reflecting the regenerative activities in the corresponding tissues. Notably, fibronectin 1 (FN1), thrombospondin 1 (THBS1), and transferrin receptor (TFRC) emerged as potential candidate proteins related to the angiogenic response in DO. Further cellular experiments validated the potential of DO-associated circulating exosomes to promote angiogenesis in endothelial cells. Collectively, these data reveal previously unknown mechanisms that may underlie the efficacy of DO and suggest that exosome-derived proteins may be useful as therapeutic targets for strategies designed to improve DO-related angiogenesis and bone regeneration.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142560461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"LC-Orbitrap HRMS-Based Proteomics Reveals Novel Mitochondrial Dynamics Regulatory Proteins Associated with RasV12-Induced Glioblastoma (GBM) of Drosophila","authors":"Pradeep Kumar,&nbsp;Rohit Kumar,&nbsp;Prabhat Kumar,&nbsp;Sunaina Kushwaha,&nbsp;Sandhya Kumari,&nbsp;Neha Yadav and Saripella Srikrishna*,&nbsp;","doi":"10.1021/acs.jproteome.4c0050210.1021/acs.jproteome.4c00502","DOIUrl":"https://doi.org/10.1021/acs.jproteome.4c00502https://doi.org/10.1021/acs.jproteome.4c00502","url":null,"abstract":"<p >Glioblastoma multiforme (GBM) is the most prevalent and aggressive brain tumor found in adult humans with a poor prognosis and average survival of 14–15 months. In order to have a comprehensive understanding of proteome and identify novel therapeutic targets, this study focused mainly on the differentially abundant proteins (DAPs) of <i>Ras</i>^<i>V12</i>-induced GBM. <i>Ras</i>^<i>V12</i> is a constitutively active Ras mutant form essential for tumor progression by continuously activating signaling pathways leading to uncontrolled tumor growth. This study used a transgenic <i>Drosophila</i> model with <i>Ras</i>^<i>V12</i> overexpression using the <i>repo-GAL4</i> driver line, specifically in glial cells, to study GBM. The high-resolution mass spectrometry (HRMS)-based proteomic analysis of the GBM larval central nervous system identified three novel DAPs specific to mitochondria. These DAPs, probable maleylacetoacetate isomerase 2 (Q9VHD2), bifunctional methylene tetrahydrofolate dehydrogenase (Q04448), and glutamine synthetase1 (P20477), identified through HRMS were further validated by qRT-PCR. The protein–protein interaction analysis revealed interactions between Ras^V12 and DAPs, with functional links to mitochondrial dynamics regulators such as Drp1, Marf, Parkin, and HtrA2. Notably, altered expressions of Q9VHD2, P20477, and Q04448 were observed during GBM progression, which offers new insights into the involvement of mitochondrial dynamic regulators in <i>Ras</i>^<i>V12</i>-induced GBM pathophysiology.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142560409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of a Proteomics-Guided Protein Signature for Breast Cancer Detection in Breast Tissue","authors":"Aldo Moreno-Ulloa*,&nbsp;Vareska L. Zárate-Córdova,&nbsp;Israel Ramírez-Sánchez,&nbsp;Juan Carlos Cruz-López,&nbsp;Andric Perez-Ortiz,&nbsp;Cynthia Villarreal-Garza,&nbsp;José Díaz-Chávez,&nbsp;Benito Estrada-Mena,&nbsp;Bani Antonio-Aguirre,&nbsp;Perla Ximena López-Almanza,&nbsp;Esmeralda Lira-Romero and Fco. Javier Estrada-Mena*,&nbsp;","doi":"10.1021/acs.jproteome.4c0029510.1021/acs.jproteome.4c00295","DOIUrl":"https://doi.org/10.1021/acs.jproteome.4c00295https://doi.org/10.1021/acs.jproteome.4c00295","url":null,"abstract":"<p >The distinction between noncancerous and cancerous breast tissues is challenging in clinical settings, and discovering new proteomics-based biomarkers remains underexplored. Through a pilot proteomic study (discovery cohort), we aimed to identify a protein signature indicative of breast cancer for subsequent validation using six published proteomics/transcriptomics data sets (validation cohorts). Sequential window acquisition of all theoretical (SWATH)-based mass spectrometry revealed 370 differentially abundant proteins between noncancerous tissue and breast cancer. Protein–protein interaction-based networks and enrichment analyses revealed dysregulation in pathways associated with extracellular matrix organization, platelet degranulation, the innate immune system, and RNA metabolism in breast cancer. Through multivariate unsupervised analysis, we identified a four-protein signature (OGN, LUM, DCN, and COL14A1) capable of distinguishing breast cancer. This dysregulation pattern was consistently verified across diverse proteomics and transcriptomics data sets. Dysregulation magnitude was notably higher in poor-prognosis breast cancer subtypes like Basal-Like and HER2 compared to Luminal A. Diagnostic evaluation (receiver operating characteristic (ROC) curves) of the signature in distinguishing breast cancer from noncancerous tissue revealed area under the curve (AUC) ranging from 0.87 to 0.9 with predictive accuracy of 80% to 82%. Upon stratifying, to solely include the Basal-Like/Triple-Negative subtype, the ROC AUC increased to 0.922–0.959 with predictive accuracy of 84.2%–89%. These findings suggest a potential role for the identified signature in distinguishing cancerous from noncancerous breast tissue, offering insights into enhancing diagnostic accuracy.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142560399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GraphPI: Efficient Protein Inference with Graph Neural Networks","authors":"Zheng Ma,&nbsp;Jiazhen Chen,&nbsp;Lei Xin and Ali Ghodsi*,&nbsp;","doi":"10.1021/acs.jproteome.3c0084510.1021/acs.jproteome.3c00845","DOIUrl":"https://doi.org/10.1021/acs.jproteome.3c00845https://doi.org/10.1021/acs.jproteome.3c00845","url":null,"abstract":"<p >The integration of deep learning approaches in biomedical research has been transformative, enabling breakthroughs in various applications. Despite these strides, its application in protein inference is impeded by the scarcity of extensively labeled data sets, a challenge compounded by the high costs and complexities of accurate protein annotation. In this study, we introduce GraphPI, a novel framework that treats protein inference as a node classification problem. We treat proteins as interconnected nodes within a protein–peptide–PSM graph, utilizing a graph neural network-based architecture to elucidate their interrelations. To address label scarcity, we train the model on a set of unlabeled public protein data sets with pseudolabels derived from an existing protein inference algorithm, enhanced by self-training to iteratively refine labels based on confidence scores. Contrary to prevalent methodologies necessitating data set-specific training, our research illustrates that GraphPI, due to the well-normalized nature of Percolator features, exhibits universal applicability without data set-specific fine-tuning, a feature that not only mitigates the risk of overfitting but also enhances computational efficiency. Our empirical experiments reveal notable performance on various test data sets and deliver significantly reduced computation times compared to common protein inference algorithms.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142560370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Equine Protein Atlas Highlights Synovial Fluid Proteome Dynamics during Experimentally LPS-Induced Arthritis","authors":"Louise Bundgaard*,&nbsp;Filip Årman,&nbsp;Emma Åhrman,&nbsp;Marie Walters,&nbsp;Ulrich auf dem Keller,&nbsp;Johan Malmström and Stine Jacobsen,&nbsp;","doi":"10.1021/acs.jproteome.4c0012510.1021/acs.jproteome.4c00125","DOIUrl":"https://doi.org/10.1021/acs.jproteome.4c00125https://doi.org/10.1021/acs.jproteome.4c00125","url":null,"abstract":"<p >In human proteomics, substantial efforts are ongoing to leverage large collections of mass spectrometry (MS) fragment ion spectra into extensive spectral libraries (SL) as a resource for data independent acquisition (DIA) analysis. Currently, such initiatives in equine research are still missing. Here we present a large-scale equine SL, comprising 6394 canonical proteins and 89,329 unique peptides, based on data dependent acquisition analysis of 75 tissue and body fluid samples from horses. The SL enabled large-scale DIA-MS based quantification of the same samples to generate a quantitative equine protein distribution atlas to infer dominant proteins in different organs and body fluids. Data mining revealed 163 proteins uniquely identified in a specific type of tissue or body fluid, serving as a starting point to determine tissue-specific or tissue-type-specific proteins. We showcase the SL by highlighting proteome dynamics in equine synovial fluid samples during experimental lipopolysaccharide-induced arthritis. A fuzzy c-means cluster analysis pinpointed SERPINB1, ATRN, NGAL, LTF, MMP1, and LBP as putative biomarkers for joint inflammation. This SL provides an extendable resource for future equine studies employing DIA-MS.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acs.jproteome.4c00125","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142560436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Proteomic Analysis Reveals Major Proteins and Pathways That Mediate the Effect of 17-β-Estradiol in Cell Division and Apoptosis in Breast Cancer MCF7 Cells","authors":"Zhenqi Zhou,&nbsp;Brihget Sicairos,&nbsp;Jianhong Zhou and Yuchun Du*,&nbsp;","doi":"10.1021/acs.jproteome.4c0010210.1021/acs.jproteome.4c00102","DOIUrl":"https://doi.org/10.1021/acs.jproteome.4c00102https://doi.org/10.1021/acs.jproteome.4c00102","url":null,"abstract":"<p >Despite extensive research, the genes/proteins and pathways responsible for the physiological effects of estrogen remain elusive. In this study, we determined the effect of estrogen on global protein expression in breast cancer MCF7 cells using a proteomic method. The expression of 77 cytosolic, 74 nuclear, and 81 membrane/organelle proteins was significantly altered by 17-β-estradiol (E2). Protein enrichment analyses suggest that E2 may stimulate cell division primarily by promoting the G1 to S phase transition and advancing the G2/M checkpoint. The effect of E2 on cell survival was complex, as it could simultaneously enhance and inhibit apoptosis. Bioinformatics analysis suggests that E2 may enhance apoptosis by promoting the accumulation of the pore-forming protein Bax in the mitochondria and inhibit apoptosis by activating the PI3K/AKT/mTOR signaling pathway. We verified the activation of the PI3K signaling and the accumulation of Bax in the membrane/organelle fraction in E2-treated cells using immunoblotting. Treatment of MCF7 cells with E2 and the PI3K inhibitor Ly294002 significantly enhanced apoptosis compared to those treated with E2 alone, suggesting that combining estrogen with a PI3K inhibitor could be a promising strategy for treating ERα-positive breast cancer. Interestingly, many of the E2-upregulated proteins contained the HEAT, KH, and RRM domains.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acs.jproteome.4c00102","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142560430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Longitudinal Assessment of Nasopharyngeal Biomarkers Post-COVID-19: Unveiling Persistent Markers and Severity Correlations","authors":"Francisco Javier Redondo-Calvo,&nbsp;Yoana Rabanal-Ruiz,&nbsp;Gema Verdugo-Moreno,&nbsp;Natalia Bejarano-Ramírez,&nbsp;Raquel Bodoque-Villar,&nbsp;Mario Durán-Prado,&nbsp;Soledad Illescas,&nbsp;Eduardo Chicano-Galvez,&nbsp;Francisco Javier Gómez-Romero,&nbsp;José Martinez-Alarcón,&nbsp;Javier Arias-Pardilla,&nbsp;Pilar Lopez-Juarez,&nbsp;Juan Fernando Padin,&nbsp;Juan Ramón Peinado* and Leticia Serrano-Oviedo*,&nbsp;","doi":"10.1021/acs.jproteome.4c0053610.1021/acs.jproteome.4c00536","DOIUrl":"https://doi.org/10.1021/acs.jproteome.4c00536https://doi.org/10.1021/acs.jproteome.4c00536","url":null,"abstract":"<p >SARS-CoV-19 infection provokes a variety of symptoms; most patients present mild/moderate symptoms, whereas a small proportion of patients progress to severe illness with multiorgan failure accompanied by metabolic disturbances requiring ICU-level care. Given the importance of the disease, researchers focused on identifying severity-associated biomarkers in infected patients as well as markers associated with patients suffering long-COVID. However, little is known about the presence of biomarkers that remain a few years after SARS-CoV-2 infection once the patients fully recover of the symptoms. In this study, we evaluated the presence of persistent biomarkers in the nasopharyngeal tract two years after SARS-Cov-2 infection in fully asymptomatic patients, taking into account the severity of their infection (mild/moderate and severe infections). In addition to the direct identification of several components of the Coronavirus Infection Pathway in those individuals that suffered severe infections, we describe herein 371 proteins and their associated canonical pathways that define the different adverse effects of SARS-CoV-2 infections. The persistence of these biomarkers for up to two years after infection, along with their ability to distinguish the severity of the infection endured, highlights the surprising presence of persistent nasopharyngeal exudate changes in fully recovered patients.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acs.jproteome.4c00536","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142560433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}