Proteomics最新文献

{"title":"In-Depth Proteome Profiling of the Hippocampus of LDLR Knockout Mice Reveals Alternation in Synaptic Signaling Pathway.","authors":"Hong-Beom Park, Hyeyoon Kim, Dohyun Han","doi":"10.1002/pmic.202400152","DOIUrl":"https://doi.org/10.1002/pmic.202400152","url":null,"abstract":"<p><p>The low-density lipoprotein receptor (LDLR) is a major apolipoprotein receptor that regulates cholesterol homeostasis. LDLR deficiency is associated with cognitive impairment by the induction of synaptopathy in the hippocampus. Despite the close relationship between LDLR and neurodegenerative disorders, proteomics research for protein profiling in the LDLR knockout (KO) model remains insufficient. Therefore, understanding LDLR KO-mediated differential protein expression within the hippocampus is crucial for elucidating a role of LDLR in neurodegenerative disorders. In this study, we conducted first-time proteomic profiling of hippocampus tissue from LDLR KO mice using tandem mass tag (TMT)-based MS analysis. LDLR deficiency induces changes in proteins associated with the transport of diverse molecules, and activity of kinase and catalyst within the hippocampus. Additionally, significant alterations in the expression of components in the major synaptic pathways were found. Furthermore, these synaptic effects were verified using a data-independent acquisition (DIA)-based proteomic method. Our data will serve as a valuable resource for further studies to discover the molecular function of LDLR in neurodegenerative disorders.</p>","PeriodicalId":224,"journal":{"name":"Proteomics","volume":" ","pages":"e202400152"},"PeriodicalIF":3.4,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142643571","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":"Review and Practical Guide for Getting Started With Single-Cell Proteomics","authors":"Hsien-Jung L. Lin,&nbsp;Kei G. I. Webber,&nbsp;Andikan J. Nwosu,&nbsp;Ryan T. Kelly","doi":"10.1002/pmic.202400021","DOIUrl":"10.1002/pmic.202400021","url":null,"abstract":"<div>\u0000 \u0000 <p>Single-cell proteomics (SCP) has advanced significantly in recent years, with new tools specifically designed for the preparation and analysis of single cells now commercially available to researchers. The field is sufficiently mature to be broadly accessible to any lab capable of isolating single cells and performing bulk-scale proteomic analyses. In this review, we highlight recent work in the SCP field that has significantly lowered the barrier to entry, thus providing a practical guide for those who are newly entering the SCP field. We outline the fundamental principles and report multiple paths to accomplish the key steps of a successful SCP experiment including sample preparation, separation, and mass spectrometry data acquisition and analysis. We recommend that researchers start with a label-free SCP workflow, as achieving high-quality and quantitatively accurate results is more straightforward than label-based multiplexed strategies. By leveraging these accessible means, researchers can confidently perform SCP experiments and make meaningful discoveries at the single-cell level.</p>\u0000 </div>","PeriodicalId":224,"journal":{"name":"Proteomics","volume":"25 1-2","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142643573","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":"Parallel Analyses by Mass Spectrometry (MS) and Reverse Phase Protein Array (RPPA) Reveal Complementary Proteomic Profiles in Triple-Negative Breast Cancer (TNBC) Patient Tissues and Cell Cultures.","authors":"Nan Wang, Yiying Zhu, Lianshui Wang, Wenshuang Dai, Taobo Hu, Zhentao Song, Xia Li, Qi Zhang, Jianfei Ma, Qianghua Xia, Jin Li, Yiqiang Liu, Mengping Long, Zhiyong Ding","doi":"10.1002/pmic.202400107","DOIUrl":"https://doi.org/10.1002/pmic.202400107","url":null,"abstract":"<p><p>High-plex proteomic technologies have made substantial contributions to mechanism studies and biomarker discovery in complex diseases, particularly cancer. Despite technological advancements, inherent limitations in individual proteomic approaches persist, impeding the achievement of comprehensive quantitative insights into the proteome. In this study, we employed two widely used proteomic technologies, mass spectrometry (MS) and reverse phase protein array (RPPA) to analyze identical samples, aiming to systematically assess the outcomes and performance of the different technologies. Additionally, we sought to establish an integrated workflow by combining these two proteomic approaches to augment the coverage of protein targets for discovery purposes. We used 14 fresh frozen tissue samples from triple-negative breast cancer (TNBC: seven tumors versus seven adjacent non-cancerous tissues) and cell line samples to evaluate both technologies and implement this dual-proteomic strategy. Using a single-step protein denaturation and extraction protocol, protein samples were subjected to reverse-phase liquid chromatography (LC) followed by electrospray ionization (ESI)-mediated MS/MS for proteomic profiling. Concurrently, identical sample aliquots were analyzed by RPPA for profiling of over 300 proteins and phosphoproteins that are in key signaling pathways or druggable targets in cancer. Both proteomic methods demonstrated the expected ability to differentiate samples by groups, revealing distinct proteomic patterns under various experimental conditions, albeit with minimal overlap in identified targets. Mechanism-based analysis uncovered divergent biological processes identified with the two proteomic technologies, capitalizing on their complementary exploratory potential.</p>","PeriodicalId":224,"journal":{"name":"Proteomics","volume":" ","pages":"e202400107"},"PeriodicalIF":3.4,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142643572","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":"Omics Studies in CKD: Diagnostic Opportunities and Therapeutic Potential.","authors":"Merita Rroji, Goce Spasovski","doi":"10.1002/pmic.202400151","DOIUrl":"https://doi.org/10.1002/pmic.202400151","url":null,"abstract":"<p><p>Omics technologies have significantly advanced the prediction and therapeutic approaches for chronic kidney disease (CKD) by providing comprehensive molecular insights. This is a review of the current state and future prospects of integrating biomarkers into the clinical practice for CKD, aiming to improve patient outcomes by targeted therapeutic interventions. In fact, the integration of genomic, transcriptomic, proteomic, and metabolomic data has enhanced our understanding of CKD pathogenesis and identified novel biomarkers for an early diagnosis and targeted treatment. Advanced computational methods and artificial intelligence (AI) have further refined multi-omics data analysis, leading to more accurate prediction models for disease progression and therapeutic responses. These developments highlight the potential to improve CKD patient care with a precise and individualized treatment plan .</p>","PeriodicalId":224,"journal":{"name":"Proteomics","volume":" ","pages":"e202400151"},"PeriodicalIF":3.4,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142612513","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":"Transforming peptide hormone prediction: The role of AI in modern proteomics","authors":"Nguyen Quoc Khanh Le","doi":"10.1002/pmic.202400156","DOIUrl":"10.1002/pmic.202400156","url":null,"abstract":"","PeriodicalId":224,"journal":{"name":"Proteomics","volume":"25 3","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142602744","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":"Proteome integral solubility alteration via label-free DIA approach (PISA-DIA), game changer in drug target deconvolution","authors":"Zheng Ser,&nbsp;Radoslaw M. Sobota","doi":"10.1002/pmic.202400147","DOIUrl":"10.1002/pmic.202400147","url":null,"abstract":"<p>Drug protein-target identification in past decades required screening compound libraries against known proteins to determine drugs binding to specific protein. Protein targets used in drug-target screening were selected predominantly used laborious genetic manipulation assays. In 2013, a team led by Pär Nordlund from Karolinska Institutet (Stockholm, Sweden) developed Cellular Thermal Shift Assay (CETSA), a method which, for the first time, enabled the possibility of drug protein-target identification in the complex cellular proteome. High throughput, quantitative mass spectrometry (MS) proteomics appeared as a compatible analytical method of choice to complement CETSA, aka Thermal Protein Profiling assay (TPP). Since the seminal CETSA-MS/ TPP-MS publications, different protein-target deconvolution strategies emerged including Proteome Integral Solubility Alteration (PISA). The work of Emery–Corbin et al. (Proteomics 2024, 2300644), titled Proteome Integral Solubility Alteration via label-free DIA approach (PISA-DIA), introduces Data–Independent Acquisition (DIA) as a quantification method, opening new avenues in drug target-deconvolution field. Application of DIA for target deconvolution offers attractive alternative to widely used data dependent methodology.</p>","PeriodicalId":224,"journal":{"name":"Proteomics","volume":"25 3","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142602743","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":"Integrative Proteomic and Phosphoproteomic Profiling Reveals the Salt-Responsive Mechanisms in Two Rice Varieties (Oryza Sativa subsp. Japonica and Indica).","authors":"Cheol Woo Min, Ravi Gupta, Gi Hyun Lee, Jun-Hyeon Cho, Yu-Jin Kim, Yiming Wang, Ki-Hong Jung, Sun Tae Kim","doi":"10.1002/pmic.202400251","DOIUrl":"https://doi.org/10.1002/pmic.202400251","url":null,"abstract":"<p><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>","PeriodicalId":224,"journal":{"name":"Proteomics","volume":" ","pages":"e202400251"},"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, William Determe, Elodie Grifnée, Philippe Massonnet, Matthieu Schoumacher, Loreen Huyghebeart, Thomas Dubrowski, Stéphanie Peeters, Caroline Le Goff, Etienne Cavalier","doi":"10.1002/pmic.202400027","DOIUrl":"https://doi.org/10.1002/pmic.202400027","url":null,"abstract":"<p><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>","PeriodicalId":224,"journal":{"name":"Proteomics","volume":" ","pages":"e202400027"},"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, Yu-Sheng Lin, Jing-Wen Huang, Kuo-Tung Tang, Cheng-Yu Kuo, Wei-Chen Wang, Han-Ju Chien, Chih-Jui Chang, Nien-Jen Hu, Chien-Chen Lai","doi":"10.1002/pmic.202300649","DOIUrl":"https://doi.org/10.1002/pmic.202300649","url":null,"abstract":"<p><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 Pseudomonas aeruginosa secretes against methicillin-resistant Staphylococcus aureus (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 P. aeruginosa in its action against MRSA, guiding future antibacterial research.</p>","PeriodicalId":224,"journal":{"name":"Proteomics","volume":" ","pages":"e202300649"},"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}