Journal of Proteome Research最新文献_第9页

IF 3.6 2区生物学

Journal of Proteome Research Pub Date : 2025-08-01

Yue Liu, Dianlong Ge*, Jijuan Zhou, Xiangxue Zheng, Yajing Chu, Yuzhou Yu, Wenting Liu, Li Ke, Yan Lu, Chaoqun Huang, Chengyin Shen and Yannan Chu*,

引用次数: 0

IF 3.6 2区生物学

Journal of Proteome Research Pub Date : 2025-08-01

Enzhi Luo, Neeraj Manvi Agarwal and Junjeong Choi*,

引用次数: 0

IF 3.6 2区生物学

Journal of Proteome Research Pub Date : 2025-08-01

Evan R. Stair, Brendin B. Flinn, Aaron C. Grimmett, Samantha J. Balboa, Adam J. Burr, Jessica A. Siebold, Andrea Granados Baca, Meredith H. Daughtridge, Derrick R. J. Kolling* and Leslie M. Hicks*,

引用次数: 0

IF 3.6 2区生物学

Journal of Proteome Research Pub Date : 2025-08-01

Soumya Swastik Sahoo, Shreyada N. Save, Shantanu Madiwale, Shilpy Sharma* and Jeetender Chugh*,

引用次数: 0

PSCS: Unified Sharing of Single-Cell Omics Data, Analyses, and Results. PSCS：单细胞组学数据、分析和结果的统一共享。

IF 3.6 2区生物学

Journal of Proteome Research Pub Date : 2025-08-01 DOI: 10.1021/acs.jproteome.5c00178

Alexandre Hutton, Lizhuo Ai, Jesse G Meyer

引用次数: 0

High-Throughput Workflow for Detergent-free Cell-Based Proteomic Characterization. 无洗涤剂细胞蛋白质组学表征的高通量工作流程。

IF 3.6 2区生物学

Journal of Proteome Research Pub Date : 2025-08-01 Epub Date: 2025-04-21 DOI: 10.1021/acs.jproteome.4c00892

Saeed Seyedmohammad, Alejandro Rivas, Maxim Zhgamadze, Ali Haghani, Simion Kreimer, Ajay Bharadwaj, Niveda Sundararaman, Sameer Vasantgadkar, Kasturi Pal, Eugenio Daviso, Aleksandr Stotland, Chris Murray, Koen Raedschelders, Sudha Savant, Jennifer E Van Eyk

{"title":"High-Throughput Workflow for Detergent-free Cell-Based Proteomic Characterization.","authors":"Saeed Seyedmohammad, Alejandro Rivas, Maxim Zhgamadze, Ali Haghani, Simion Kreimer, Ajay Bharadwaj, Niveda Sundararaman, Sameer Vasantgadkar, Kasturi Pal, Eugenio Daviso, Aleksandr Stotland, Chris Murray, Koen Raedschelders, Sudha Savant, Jennifer E Van Eyk","doi":"10.1021/acs.jproteome.4c00892","DOIUrl":"10.1021/acs.jproteome.4c00892","url":null,"abstract":"We have developed an automated cell-based workflow for the quantification of proteins by liquid chromatography-mass spectrometry (LC-MS) that facilitates large-scale perturbation studies carried out in a 96-well plate format and enables the preparation of one full plate in approximately 4 h, showcasing a high-throughput (HTP) concept. Cells were grown in a 96-well plate and lysed via ultrasonication. Proteins were subsequently solubilized, extracted, and processed into tryptic peptides for 2 h before being acquired by data-independent acquisition mass spectrometry (DIA-MS). This workflow leverages adaptive focused acoustics (AFA) technology for ultrasonication to aid cell lysis and protein solubilization on an automated liquid handling platform. As proof of principle, AC16 human cardiomyocyte-like cells were cultured in a 96-well plate under optimized conditions that were compatible with the downstream HTP pipeline. Over 30,000 peptides were identified, corresponding to the detection of 5100 unique proteins. 50% of measured proteins had an average coefficient of variation (CV) under 25% from approximately 30,000 cells. Our optimized detergent-free buffer consisting of ammonium bicarbonate yielded comparable findings. For the same number of cells, 5000 proteins were identified from 29,000 peptides, 40% of which demonstrated a CV under 25%.","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":" ","pages":"3762-3773"},"PeriodicalIF":3.6,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143951488","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}

引用次数: 0

Machine Learning and DIA Proteomics Reveal New Insights into Carbapenem Resistance Mechanisms in Klebsiella pneumoniae. 机器学习和DIA蛋白质组学揭示肺炎克雷伯菌碳青霉烯耐药机制的新见解。

IF 3.6 2区生物学

Journal of Proteome Research Pub Date : 2025-08-01 Epub Date: 2025-07-07 DOI: 10.1021/acs.jproteome.5c00142

Guibin Wang, Ling Cao, Lingli Lian, Yuqian Wang, Juanqi Lian, Ziqiu Liu, Wenzhe Chen, Meichao Ji, Lanqing Gong, Lishan Zhang, Liping Li, Xiangmin Lin

{"title":"Machine Learning and DIA Proteomics Reveal New Insights into Carbapenem Resistance Mechanisms in Klebsiella pneumoniae.","authors":"Guibin Wang, Ling Cao, Lingli Lian, Yuqian Wang, Juanqi Lian, Ziqiu Liu, Wenzhe Chen, Meichao Ji, Lanqing Gong, Lishan Zhang, Liping Li, Xiangmin Lin","doi":"10.1021/acs.jproteome.5c00142","DOIUrl":"10.1021/acs.jproteome.5c00142","url":null,"abstract":"The emergence of Carbapenem-resistant Klebsiella pneumoniae (CRKP) represents a major public health concern, primarily driven by its ability to evade a wide range of antibiotics. Despite extensive genomic studies, proteomic insights into antibiotic resistance mechanisms remain scarce. Here, we employed a Data-Independent Acquisition (DIA)-based quantitative proteomics approach to investigate proteomic differences between 78 CRKP and 18 Carbapenem-sensitive K. pneumoniae (CSKP) clinical isolates. A total of 3380 proteins were identified, with 946 showing significant differential expression. CRKP isolates exhibited increased expression of efflux pumps, beta-lactamases, and transcriptional regulators, while proteins associated with transport were enriched in CSKP isolates. To validate our findings, a quantitative proteomics analysis in an independent cohort of 10 CRKP and 11 CSKP isolates was performed. The key biomarkers identified via machine learning in the discovery cohort, including aldehyde dehydrogenase (KPN_03361), acyltransferase (KPN_02072), uncharacterized protein (YjeJ), plasmid partition protein B (ParaB), HTH-type transcriptional activator (RhaR), and beta-lactamase (Bla), were evaluated. They collectively achieved AUC > 0.7 in the validation cohort, confirming their discriminatory capacity as diagnostic markers. These findings provide novel insights into the molecular mechanisms of antibiotic resistance and identify promising biomarkers for diagnosing carbapenem-resistant K. pneumoniae, offering potential avenues for therapeutic intervention.","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":" ","pages":"4002-4014"},"PeriodicalIF":3.6,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144574462","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}

引用次数: 0

Comparative Proteomic Characterization of Serum-Free Cultivated HepG2 Cells Reveals Upregulated Drug Metabolism and Increased Oxidative Stress Protection. 无血清培养HepG2细胞的比较蛋白质组学特征揭示了药物代谢上调和氧化应激保护增强。

IF 3.6 2区生物学

Journal of Proteome Research Pub Date : 2025-08-01 Epub Date: 2025-07-15 DOI: 10.1021/acs.jproteome.5c00100

Luisa-Marie Pfeifer, Jasjot Singh, Aline Zimmer, Marc Krenkel, Frank Fischer, Janike Sensbach, Frederic Pipp, Daniela Werkmann, Philip Hewitt

{"title":"Comparative Proteomic Characterization of Serum-Free Cultivated HepG2 Cells Reveals Upregulated Drug Metabolism and Increased Oxidative Stress Protection.","authors":"Luisa-Marie Pfeifer, Jasjot Singh, Aline Zimmer, Marc Krenkel, Frank Fischer, Janike Sensbach, Frederic Pipp, Daniela Werkmann, Philip Hewitt","doi":"10.1021/acs.jproteome.5c00100","DOIUrl":"10.1021/acs.jproteome.5c00100","url":null,"abstract":"Fetal bovine serum (FBS) is commonly used in cell culture models despite being considered critical from both an ethical and scientific standpoint. Since it has been used for many years with a variety of different cells and cell types, research has become dependent on its use, and scientists hesitate to change their working model without solid data demonstrating the usability of serum-free cultivated cells in their desired applications. To shed light on the highly complex issue of dietary demands of cells in culture and the impact of media supplements on cellular behavior, we performed a comparative proteomic characterization between HepG2 cells cultivated in serum-free or FBS-containing conditions with a focus set on drug metabolism and oxidative stress response, the main application field of the HepG2 cell line. We observed the predicted upregulation of multiple pathways associated with drug metabolism and oxidative stress protection, as well as a strong overexpression of multiple antioxidative enzymes such as glutathione peroxidase and glutathione S-transferase at the protein expression level. We confirmed that increased enzyme expression correlates with higher enzyme activity in vitro and linked increased glutathione peroxidase activity to selenium supranutrition under serum-free conditions.","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":" ","pages":"3961-3978"},"PeriodicalIF":3.6,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144641246","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}

引用次数: 0

Activating Cancer Hallmarks through Changes in mRNA/Protein Regulation. 通过改变mRNA/蛋白调控激活癌症标志。

IF 3.6 2区生物学

Journal of Proteome Research Pub Date : 2025-08-01 Epub Date: 2025-07-17 DOI: 10.1021/acs.jproteome.4c00284

Jose Humberto Giraldez Chavez, Nathaniel Barton, Caleb M Lindgren, Bryn Mendenhall, Benjamin Kimball, Samuel H Payne

{"title":"Activating Cancer Hallmarks through Changes in mRNA/Protein Regulation.","authors":"Jose Humberto Giraldez Chavez, Nathaniel Barton, Caleb M Lindgren, Bryn Mendenhall, Benjamin Kimball, Samuel H Payne","doi":"10.1021/acs.jproteome.4c00284","DOIUrl":"10.1021/acs.jproteome.4c00284","url":null,"abstract":"As a diverse family of diseases, cancer is unified by a set of common dysfunctions, such as limitless growth potential and an insensitivity to antigrowth signals. These shared overarching biological processes have been termed the hallmarks of cancer. To better understand the root cause of cellular dysregulation, intense molecular characterization of tumors has utilized DNA, RNA, and protein measurement techniques to produce proteogenomic data. In large cancer cohort studies, genomic and proteogenomic data have frequently identified many cancer hallmarks including cell cycle and cell signaling. However, altered metabolism, a known cancer hallmark, is not as clearly identified in mutation screens or differential expression analyses. Here, we introduce a new computational method to identify changes in cellular regulation by focusing on the mRNA/protein relationship. We create a metric, Δ_corr, to capture when the mRNA/protein correlation changes significantly between tumor and normal tissues and show that it is distinct from differential expression and also not associated with DNA mutation profiles. Our method clearly highlights altered metabolic pathways across multiple tumor types. Δ_corr gives researchers a new perspective on the dysfunction of tumor cells and introduces a novel method for proteogenomic data integration.","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":" ","pages":"3902-3912"},"PeriodicalIF":3.6,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144657877","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}

引用次数: 0

IF 3.6 2区生物学

Journal of Proteome Research Pub Date : 2025-08-01

Gelio Alves*, Aleksey Y Ogurtsov and Yi-Kuo Yu*,

引用次数: 0