Proteomics最新文献

{"title":"Integrative Proteomic and Phosphoproteomic Profiling Reveals the Salt-Responsive Mechanisms in Two Rice Varieties (Oryza Sativa subsp. Japonica and Indica)","authors":"Cheol Woo Min,&nbsp;Ravi Gupta,&nbsp;Gi Hyun Lee,&nbsp;Jun-Hyeon Cho,&nbsp;Yu-Jin Kim,&nbsp;Yiming Wang,&nbsp;Ki-Hong Jung,&nbsp;Sun Tae Kim","doi":"10.1002/pmic.202400251","DOIUrl":"10.1002/pmic.202400251","url":null,"abstract":"<div>\u0000 \u0000 <p>Salinity stress induces ionic and osmotic imbalances in rice plants that in turn negatively affect the photosynthesis rate, resulting in growth retardation and yield penalty. Efforts have, therefore, been carried out to understand the mechanism of salt tolerance, however, the complexity of biological processes at proteome levels remains a major challenge. Here, we performed a comparative proteome and phosphoproteome profiling of microsome enriched fractions of salt-tolerant (cv. IR73; indica) and salt-susceptible (cv. Dongjin/DJ; japonica) rice varieties. This approach led to the identification of 5856 proteins, of which 473 and 484 proteins showed differential modulation between DJ and IR73 sample sets, respectively. The phosphoproteome analysis led to the identification of a total of 10,873 phosphopeptides of which 2929 and 3049 phosphopeptides showed significant differences in DJ and IR73 sample sets, respectively. The integration of proteome and phosphoproteome data showed activation of ABA and Ca²⁺ signaling components exclusively in the salt-tolerant variety IR73 in response to salinity stress. Taken together, our results highlight the changes at proteome and phosphoproteome levels and provide a mechanistic understanding of salinity stress tolerance in rice.</p>\u0000 </div>","PeriodicalId":224,"journal":{"name":"Proteomics","volume":"25 5-6","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142567149","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":"Proteomics analysis of round and wrinkled pea (Pisum sativum L.) seeds during different development periods","authors":"Sintayehu D. Daba,&nbsp;Punyatoya Panda,&nbsp;Uma K. Aryal,&nbsp;Alecia M. Kiszonas,&nbsp;Sean M. Finnie,&nbsp;Rebecca J. McGee","doi":"10.1002/pmic.202300363","DOIUrl":"10.1002/pmic.202300363","url":null,"abstract":"<p>Seed development is complex, influenced by genetic and environmental factors. Understanding proteome profiles at different seed developmental stages is key to improving seed composition and quality. We used label-free quantitative proteomics to analyze round and wrinkled pea seeds at five growth stages: 4, 7, 12, 15, and days after anthesis (DAA), and at maturity. Wrinkled peas had lower starch content (30%) compared to round peas (47%–55%). Proteomic analysis identified 3659 protein groups, with 21%–24% shared across growth stages. More proteins were identified during early seed development than at maturity. Statistical analysis found 735 significantly different proteins between wrinkled and round seeds, regardless of the growth stage. The detected proteins were categorized into 31 functional classes, including metabolic enzymes, proteins involved in protein biosynthesis and homeostasis, carbohydrate metabolism, and cell division. Cell division-related proteins were more abundant in early stages, while storage proteins were more abundant later in seed development. Wrinkled seeds had lower levels of the starch-branching enzyme (SBEI), which is essential for amylopectin biosynthesis. Seed storage proteins like legumin and albumin (PA2) were more abundant in round peas, whereas vicilin was more prevalent in wrinkled peas. This study enhances our understanding of seed development in round and wrinkled peas.</p><p>The study highlighted the seed growth patterns and protein profiles in round and wrinkled peas during seed development. It showed how protein accumulation changed, particularly focusing on proteins implicated in cell division, seed reserve metabolism, as well as storage proteins and protease inhibitors. These findings underscore the crucial role of these proteins in seed development. By linking the proteins identified to <i>Cameor</i>-based pea reference genome, our research can open avenues for deeper investigations into individual proteins, facilitate their practical application in crop improvement, and advance our knowledge of seed development.</p>","PeriodicalId":224,"journal":{"name":"Proteomics","volume":"25 3","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/pmic.202300363","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142542423","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":"Characterization of Trivalently Crosslinked C-Terminal Telopeptide of Type I Collagen (CTX) Species in Human Plasma and Serum Using High-Resolution Mass Spectrometry","authors":"Justine Demeuse,&nbsp;William Determe,&nbsp;Elodie Grifnée,&nbsp;Philippe Massonnet,&nbsp;Matthieu Schoumacher,&nbsp;Loreen Huyghebeart,&nbsp;Thomas Dubrowski,&nbsp;Stéphanie Peeters,&nbsp;Caroline Le Goff,&nbsp;Etienne Cavalier","doi":"10.1002/pmic.202400027","DOIUrl":"10.1002/pmic.202400027","url":null,"abstract":"<div>\u0000 \u0000 <p>With an aging population, the increased interest in the monitoring of skeletal diseases such as osteoporosis led to significant progress in the discovery and measurement of bone turnover biomarkers since the 2000s. Multiple markers derived from type I collagen, such as CTX, NTX, PINP, and ICTP, have been developed. Extensive efforts have been devoted to characterizing these molecules; however, their complex crosslinked structures have posed significant analytical challenges, and to date, these biomarkers remain poorly characterized. Previous attempts at characterization involved gel-based separation methods and MALDI-TOF analysis on collagen peptides directly extracted from bone. However, using bone powder, which is rich in collagen, does not represent the true structure of the peptides in the biofluids as it was cleaved. In this study, our goal was to characterize plasma and serum CTX for subsequent LC-MS/MS method development. We extracted and characterized type I collagen peptides directly from human plasma and serum using a proteomics workflow that integrates preparative LC, affinity chromatography, and HR-MS. Subsequently, we successfully identified numerous CTX species, providing valuable insights into the characterization of these crucial biomarkers.</p>\u0000 </div>","PeriodicalId":224,"journal":{"name":"Proteomics","volume":"25 4","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142491727","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":"SWATH-MS Based Secretome Proteomic Analysis of Pseudomonas aeruginosa Against MRSA","authors":"Yi-Feng Zheng,&nbsp;Yu-Sheng Lin,&nbsp;Jing-Wen Huang,&nbsp;Kuo-Tung Tang,&nbsp;Cheng-Yu Kuo,&nbsp;Wei-Chen Wang,&nbsp;Han-Ju Chien,&nbsp;Chih-Jui Chang,&nbsp;Nien-Jen Hu,&nbsp;Chien-Chen Lai","doi":"10.1002/pmic.202300649","DOIUrl":"10.1002/pmic.202300649","url":null,"abstract":"<div>\u0000 \u0000 <p>The study uses Sequential Window Acquisition of All Theoretical Fragment Ion Mass Spectra (SWATH)-MS in conjunction with secretome proteomics to identify key proteins that <i>Pseudomonas aeruginosa</i> secretes against methicillin-resistant <i>Staphylococcus aureus</i> (MRSA). Variations in the inhibition zones indicated differences in strain resistance. Multivariate statistical methods were applied to filter the proteomic results, revealing five potential protein biomarkers, including Peptidase M23. Gene ontology (GO) analysis and sequence alignment supported their antibacterial activity. Thus, SWATH-MS provides a comprehensive understanding of the secretome of <i>P. aeruginosa</i> in its action against MRSA, guiding future antibacterial research.</p>\u0000 </div>","PeriodicalId":224,"journal":{"name":"Proteomics","volume":"25 4","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142454346","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":"Contents: Proteomics 20'24","authors":"","doi":"10.1002/pmic.202470163","DOIUrl":"https://doi.org/10.1002/pmic.202470163","url":null,"abstract":"","PeriodicalId":224,"journal":{"name":"Proteomics","volume":"24 20","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/pmic.202470163","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142429818","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":"Astronaut proteomics: Japan leads the way for transformative studies in space","authors":"Alexia Tasoula,&nbsp;Nathaniel Szewczyk","doi":"10.1002/pmic.202300645","DOIUrl":"10.1002/pmic.202300645","url":null,"abstract":"","PeriodicalId":224,"journal":{"name":"Proteomics","volume":"24 20","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142398872","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":"Editorial Board: Proteomics 20'24","authors":"","doi":"10.1002/pmic.202470162","DOIUrl":"https://doi.org/10.1002/pmic.202470162","url":null,"abstract":"","PeriodicalId":224,"journal":{"name":"Proteomics","volume":"24 20","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/pmic.202470162","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142429817","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":"CoNglyPred: Accurate Prediction of N-Linked Glycosylation Sites Using ESM-2 and Structural Features With Graph Network and Co-Attention","authors":"Hongmei Wang,&nbsp;Long Zhao,&nbsp;Ziyuan Yu,&nbsp;Ximin Zeng,&nbsp;Shaoping Shi","doi":"10.1002/pmic.202400210","DOIUrl":"10.1002/pmic.202400210","url":null,"abstract":"<div>\u0000 \u0000 <p>N-Linked glycosylation is crucial for various biological processes such as protein folding, immune response, and cellular transport. Traditional experimental methods for determining N-linked glycosylation sites entail substantial time and labor investment, which has led to the development of computational approaches as a more efficient alternative. However, due to the limited availability of 3D structural data, existing prediction methods often struggle to fully utilize structural information and fall short in integrating sequence and structural information effectively. Motivated by the progress of protein pretrained language models (pLMs) and the breakthrough in protein structure prediction, we introduced a high-accuracy model called CoNglyPred. Having compared various pLMs, we opt for the large-scale pLM ESM-2 to extract sequence embeddings, thus mitigating certain limitations associated with manual feature extraction. Meanwhile, our approach employs a graph transformer network to process the 3D protein structures predicted by AlphaFold2. The final graph output and ESM-2 embedding are intricately integrated through a co-attention mechanism. Among a series of comprehensive experiments on the independent test dataset, CoNglyPred outperforms state-of-the-art models and demonstrates exceptional performance in case study. In addition, we are the first to report the uncertainty of N-linked glycosylation predictors using expected calibration error and expected uncertainty calibration error.</p>\u0000 </div>","PeriodicalId":224,"journal":{"name":"Proteomics","volume":"25 5-6","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142363612","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":"Editorial Board: Proteomics 19'24","authors":"","doi":"10.1002/pmic.202470152","DOIUrl":"https://doi.org/10.1002/pmic.202470152","url":null,"abstract":"","PeriodicalId":224,"journal":{"name":"Proteomics","volume":"24 19","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/pmic.202470152","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142428987","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":"Standard abbreviations","authors":"","doi":"10.1002/pmic.202470154","DOIUrl":"10.1002/pmic.202470154","url":null,"abstract":"","PeriodicalId":224,"journal":{"name":"Proteomics","volume":"24 19","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142363613","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}