Proteomics最新文献_第3页

Fecal Metaproteomics as a Tool to Monitor Functional Modifications Induced in the Gut Microbiota by Ketogenic Diet: A Case Study. 粪便宏蛋白质组学作为监测生酮饮食引起的肠道微生物群功能改变的工具：一个案例研究。

IF 3.4 4区生物学

Proteomics Pub Date : 2025-01-05 DOI: 10.1002/pmic.202400191

Alessandro Tanca, Simona Masia, Piero Giustacchini, Sergio Uzzau

{"title":"Fecal Metaproteomics as a Tool to Monitor Functional Modifications Induced in the Gut Microbiota by Ketogenic Diet: A Case Study.","authors":"Alessandro Tanca, Simona Masia, Piero Giustacchini, Sergio Uzzau","doi":"10.1002/pmic.202400191","DOIUrl":"https://doi.org/10.1002/pmic.202400191","url":null,"abstract":"Metaproteomics is a valuable approach to characterize the biological functions involved in the gut microbiota (GM) response to dietary interventions. Ketogenic diets (KDs) are very effective in controlling seizure severity and frequency in drug-resistant epilepsy (DRE) and in the weight loss management in obese/overweight individuals. This case study provides proof of concept for the suitability of metaproteomics to monitor changes in taxonomic and functional GM features in an individual on a short-term very low-calorie ketogenic diet (VLCKD, 4 weeks), followed by a low-calorie diet (LCD). A marked increase in Akkermansia and Pseudomonadota was observed during VLCKD and reversed after the partial reintroduction of carbohydrates (LCD), in agreement with the results of previous metagenomic studies. In functional terms, the relative increase in Akkermansia was associated with an increased production of proteins involved in response to stress and biosynthesis of gamma-aminobutyric acid. In addition, VLCKD caused a relative increase in enzymes involved in the synthesis of the beta-ketoacid acetoacetate and of the ketogenic amino acid leucine. Our data support the potential of fecal metaproteomics to investigate the GM-dependent effect of KD as a therapeutic option in obese/overweight individuals and DRE patients.","PeriodicalId":224,"journal":{"name":"Proteomics","volume":" ","pages":"e202400191"},"PeriodicalIF":3.4,"publicationDate":"2025-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142930184","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}

引用次数: 0

The Zebrafish Sperm Proteome 斑马鱼精子蛋白质组。

IF 3.4 4区生物学

Proteomics Pub Date : 2024-12-31 DOI: 10.1002/pmic.202400310

Jayme Cohen-Krais, Carlo Martins, Jamie Bartram, Zoe Crighton, Jean-Charles de Coriolis, Alice Godden, Daniel Marcu, Weronika Robak, Gerhard Saalbach, Simone Immler

引用次数: 0

Investigation of the Urinary Peptidome to Unravel Collagen Degradation in Health and Kidney Disease. 尿肽酶在健康和肾脏疾病中揭示胶原降解的研究。

IF 3.4 4区生物学

Proteomics Pub Date : 2024-12-30 DOI: 10.1002/pmic.202400279

Ioanna K Mina, Luis F Iglesias-Martinez, Matthias Ley, Lucas Fillinger, Paul Perco, Justyna Siwy, Harald Mischak, Vera Jankowski

{"title":"Investigation of the Urinary Peptidome to Unravel Collagen Degradation in Health and Kidney Disease.","authors":"Ioanna K Mina, Luis F Iglesias-Martinez, Matthias Ley, Lucas Fillinger, Paul Perco, Justyna Siwy, Harald Mischak, Vera Jankowski","doi":"10.1002/pmic.202400279","DOIUrl":"https://doi.org/10.1002/pmic.202400279","url":null,"abstract":"Naturally occurring fragments of collagen type I alpha 1 chain (COL1A1) have been previously associated with chronic kidney disease (CKD), with some fragments showing positive and others negative associations. Using urinary peptidome data from healthy individuals (n = 1131) and CKD patients (n = 5585) this aspect was investigated in detail. Based on the hypothesis that many collagen peptides are derived not from the full, mature collagen molecule, but from (larger) collagen degradation products, relationships between COL1A1 peptides containing identical sequences were investigated, with the smaller (offspring) peptide being a possible degradation product of the larger (parent) one. The strongest correlations were found for relationships where the parent differed by a maximum of three amino acids from the offspring, indicating an exopeptidase-regulated stepwise degradation process. Regression analysis indicated that CKD affects this degradation process. A comparison of matched CKD patients and control individuals (n = 612 each) showed that peptides at the start of the degradation process were consistently downregulated in CKD, indicating an attenuation of COL1A1 endopeptidase-mediated degradation. However, as these peptides undergo further degradation, likely mediated by exopeptidases, this downregulation can become less significant or even reverse, leading to an upregulation of later-stage fragments and potentially explaining the inconsistencies observed in previous studies.","PeriodicalId":224,"journal":{"name":"Proteomics","volume":" ","pages":"e202400279"},"PeriodicalIF":3.4,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142908802","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}

引用次数: 0

Population Proteomics: A Tool to Gain Insights Into the Inflamed Periodontium 群体蛋白质组学：一种深入了解发炎牙周组织的工具。

IF 3.4 4区生物学

Proteomics Pub Date : 2024-12-30 DOI: 10.1002/pmic.202400055

Stefan Lars Reckelkamm, Sebastian-Edgar Baumeister, Daniel Hagenfeld, Zoheir Alayash, Michael Nolde

{"title":"Population Proteomics: A Tool to Gain Insights Into the Inflamed Periodontium","authors":"Stefan Lars Reckelkamm, Sebastian-Edgar Baumeister, Daniel Hagenfeld, Zoheir Alayash, Michael Nolde","doi":"10.1002/pmic.202400055","DOIUrl":"10.1002/pmic.202400055","url":null,"abstract":"Periodontitis, characterized by inflammatory loss of tooth-supporting tissues associated with biofilm, is among the most prevalent chronic diseases globally, affecting approximately 50% of the adult population to a moderate extent and cases of severe periodontitis surpassing the one billion mark. Proteomics analyses of blood, serum, and oral fluids have provided valuable insights into the complex processes occurring in the inflamed periodontium. However, until now, proteome analyses have been primarily limited to small groups of diseased versus healthy individuals. The emergence of population-scale analysis of proteomic data offers opportunities to uncover disease-associated pathways, identify potential drug targets, and discover biomarkers. In this review, we will explore the applications of proteomics in population-based studies and discuss the advancements it brings to our understanding of periodontal inflammation. Additionally, we highlight the challenges posed by currently available data and offer perspectives for future applications in periodontal research. This review aims to explain the ongoing efforts in leveraging proteomics for elucidating the complexities of periodontal diseases and paving the way for clinical strategies.","PeriodicalId":224,"journal":{"name":"Proteomics","volume":"25 1-2","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11735663/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142908804","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}

引用次数: 0

Computational Methods for Data Integration and Imputation of Missing Values in Omics Datasets 组学数据集的数据集成与缺失值的计算方法。

IF 3.4 4区生物学

Proteomics Pub Date : 2024-12-30 DOI: 10.1002/pmic.202400100

Yannis Schumann, Antonia Gocke, Julia E. Neumann

{"title":"Computational Methods for Data Integration and Imputation of Missing Values in Omics Datasets","authors":"Yannis Schumann, Antonia Gocke, Julia E. Neumann","doi":"10.1002/pmic.202400100","DOIUrl":"10.1002/pmic.202400100","url":null,"abstract":"Molecular profiling of different omic-modalities (e.g., DNA methylomics, transcriptomics, proteomics) in biological systems represents the basis for research and clinical decision-making. Measurement-specific biases, so-called batch effects, often hinder the integration of independently acquired datasets, and missing values further hamper the applicability of typical data processing algorithms. In addition to careful experimental design, well-defined standards in data acquisition and data exchange, the alleviation of these phenomena particularly requires a dedicated data integration and preprocessing pipeline. This review aims to give a comprehensive overview of computational methods for data integration and missing value imputation for omic data analyses.We provide formal definitions for missing value mechanisms and propose a novel statistical taxonomy for batch effects, especially in the presence of missing data. Based on an automated document search and systematic literature review, we describe 32 distinct data integration methods from five main methodological categories, as well as 37 algorithms for missing value imputation from five separate categories. Additionally, this review highlights multiple quantitative evaluation methods to aid researchers in selecting a suitable set of methods for their work. Finally, this work provides an integrated discussion of the relevance of batch effects and missing values in omics with corresponding method recommendations. We then propose a comprehensive three-step workflow from the study conception to final data analysis and deduce perspectives for future research. Eventually, we present a comprehensive flow chart as well as exemplary decision trees to aid practitioners in the selection of specific approaches for imputation and data integration in their studies.","PeriodicalId":224,"journal":{"name":"Proteomics","volume":"25 1-2","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/pmic.202400100","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142908798","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}

引用次数: 0

Insights on Wet and Dry Workflows for Human Gut Metaproteomics. 关于人体肠道的干湿工作流程的见解

IF 3.4 4区生物学

Proteomics Pub Date : 2024-12-30 DOI: 10.1002/pmic.202400242

Valeria Marzano, Stefano Levi Mortera, Lorenza Putignani

{"title":"Insights on Wet and Dry Workflows for Human Gut Metaproteomics.","authors":"Valeria Marzano, Stefano Levi Mortera, Lorenza Putignani","doi":"10.1002/pmic.202400242","DOIUrl":"https://doi.org/10.1002/pmic.202400242","url":null,"abstract":"The human gut microbiota (GM) is a community of microorganisms that resides in the gastrointestinal (GI) tract. Recognized as a critical element of human health, the functions of the GM extend beyond GI well-being to influence overall systemic health and susceptibility to disease. Among the other omic sciences, metaproteomics highlights additional facets that make it a highly valuable discipline in the study of GM. Indeed, it allows the protein inventory of complex microbial communities. Proteins with associated taxonomic membership and function are identified and quantified from their constituent peptides by liquid chromatography coupled to mass spectrometry analyses and by querying specific databases (DBs). The aim of this review was to compile comprehensive information on metaproteomic studies of the human GM, with a focus on the bacterial component, to assist newcomers in understanding the methods and types of research conducted in this field. The review outlines key steps in a metaproteomic-based study, such as protein extraction, DB selection, and bioinformatic workflow. The importance of standardization is emphasized. In addition, a list of previously published studies is provided as hints for researchers interested in investigating the role of GM in health and disease states.","PeriodicalId":224,"journal":{"name":"Proteomics","volume":" ","pages":"e202400242"},"PeriodicalIF":3.4,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142908800","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}

引用次数: 0

Prediction of Lung Adenocarcinoma Driver Genes Through Protein-Protein Interaction Networks Utilizing GenePlexus. 利用GenePlexus通过蛋白-蛋白相互作用网络预测肺腺癌驱动基因。

IF 3.4 4区生物学

Proteomics Pub Date : 2024-12-18 DOI: 10.1002/pmic.202400296

Fei Yuan, Yu-Hang Zhang, FeiMing Huang, Xiaoyu Cao, Lei Chen, JiaBo Li, WenFeng Shen, KaiYan Feng, YuSheng Bao, Tao Huang, Yu-Dong Cai

{"title":"Prediction of Lung Adenocarcinoma Driver Genes Through Protein-Protein Interaction Networks Utilizing GenePlexus.","authors":"Fei Yuan, Yu-Hang Zhang, FeiMing Huang, Xiaoyu Cao, Lei Chen, JiaBo Li, WenFeng Shen, KaiYan Feng, YuSheng Bao, Tao Huang, Yu-Dong Cai","doi":"10.1002/pmic.202400296","DOIUrl":"https://doi.org/10.1002/pmic.202400296","url":null,"abstract":"Lung adenocarcinoma, a subtype of lung cancer, is produced by uncontrolled proliferation of somatic cells affected by some tumorigenic factors. The origin of this disease can be attributed to the concept of \"cancer driver,\" which links the occurrence of tumor with specific changes in some key genes. These key genes can be identified at various molecular levels. Our innovative method uses a groundbreaking computing technology called GenePlexus to mine new genes related to lung adenocarcinoma. Initially, a vast network was synthesized from protein-protein interactions. Utilizing GenePlexus, we traversed paths interlinking aberrant genes across different layers and pinpointed emerging candidate genes situated on these trajectories. Finally, the candidate genes that were obtained underwent a series of filtering processes, including a permutation test, interaction test, and enrichment test. Compared with the shortest path method, GenePlexus has identified previously neglected genes involved in lung adenocarcinoma. For example, genes such as EGR2, EPHA3, FGFR4, HOXB1, and HEY1 play key roles at multiple molecular levels, including methylation, microRNA, mRNA and mutation, which affect tumorigenesis and lung cancer progression. These genes regulate various processes, from gene expression and cell proliferation to drug resistance to therapeutic drugs and the progress of lung adenocarcinoma.","PeriodicalId":224,"journal":{"name":"Proteomics","volume":" ","pages":"e202400296"},"PeriodicalIF":3.4,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142851688","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}

引用次数: 0

Advancements in Global Phosphoproteomics Profiling: Overcoming Challenges in Sensitivity and Quantification 全球磷蛋白组学分析的进展：克服敏感性和定量方面的挑战。

IF 3.4 4区生物学

Proteomics Pub Date : 2024-12-18 DOI: 10.1002/pmic.202400087

Gul Muneer, Ciao-Syuan Chen, Yu-Ju Chen

{"title":"Advancements in Global Phosphoproteomics Profiling: Overcoming Challenges in Sensitivity and Quantification","authors":"Gul Muneer, Ciao-Syuan Chen, Yu-Ju Chen","doi":"10.1002/pmic.202400087","DOIUrl":"10.1002/pmic.202400087","url":null,"abstract":"Protein phosphorylation introduces post-genomic diversity to proteins, which plays a crucial role in various cellular activities. Elucidation of system-wide signaling cascades requires high-performance tools for precise identification and quantification of dynamics of site-specific phosphorylation events. Recent advances in phosphoproteomic technologies have enabled the comprehensive mapping of the dynamic phosphoproteomic landscape, which has opened new avenues for exploring cell type-specific functional networks underlying cellular functions and clinical phenotypes. Here, we provide an overview of the basics and challenges of phosphoproteomics, as well as the technological evolution and current state-of-the-art global and quantitative phosphoproteomics methodologies. With a specific focus on highly sensitive platforms, we summarize recent trends and innovations in miniaturized sample preparation strategies for micro-to-nanoscale and single-cell profiling, data-independent acquisition mass spectrometry (DIA-MS) for enhanced coverage, and quantitative phosphoproteomic pipelines for deep mapping of cell and disease biology. Each aspect of phosphoproteomic analysis presents unique challenges and opportunities for improvement and innovation. We specifically highlight evolving phosphoproteomic technologies that enable deep profiling from low-input samples. Finally, we discuss the persistent challenges in phosphoproteomic technologies, including the feasibility of nanoscale and single-cell phosphoproteomics, as well as future outlooks for biomedical applications.","PeriodicalId":224,"journal":{"name":"Proteomics","volume":"25 1-2","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11735659/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142851687","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}

引用次数: 0

Key Regulators of Parasite Biology Viewed Through a Post-Translational Modification Repertoire. 通过翻译后修饰库观察寄生虫生物学的关键调控因子。

IF 3.4 4区生物学

Proteomics Pub Date : 2024-12-17 DOI: 10.1002/pmic.202400120

Naiwen Zhang, Ning Jiang, Qijun Chen

引用次数: 0

Standard abbreviations 标准的缩写。

IF 3.4 4区生物学

Proteomics Pub Date : 2024-12-16 DOI: 10.1002/pmic.202470184

引用次数: 0