Proteomics最新文献_第6页

A complementary metaproteomic approach to interrogate microbiome cultivated from clinical colon biopsies. 一种互补的元蛋白组方法，用于研究从临床结肠活检中培养的微生物组。

IF 3.4 4区生物学

Proteomics Pub Date : 2024-06-02 DOI: 10.1002/pmic.202400078

Van-An Duong, Altai Enkhbayar, Nobel Bhasin, Lakmini Senavirathna, Eva C Preisner, Kristi L Hoffman, Richa Shukla, Robert R Jenq, Kai Cheng, Mary P Bronner, Daniel Figeys, Robert A Britton, Sheng Pan, Ru Chen

{"title":"A complementary metaproteomic approach to interrogate microbiome cultivated from clinical colon biopsies.","authors":"Van-An Duong, Altai Enkhbayar, Nobel Bhasin, Lakmini Senavirathna, Eva C Preisner, Kristi L Hoffman, Richa Shukla, Robert R Jenq, Kai Cheng, Mary P Bronner, Daniel Figeys, Robert A Britton, Sheng Pan, Ru Chen","doi":"10.1002/pmic.202400078","DOIUrl":"10.1002/pmic.202400078","url":null,"abstract":"The human gut microbiome plays a vital role in preserving individual health and is intricately involved in essential functions. Imbalances or dysbiosis within the microbiome can significantly impact human health and are associated with many diseases. Several metaproteomics platforms are currently available to study microbial proteins within complex microbial communities. In this study, we attempted to develop an integrated pipeline to provide deeper insights into both the taxonomic and functional aspects of the cultivated human gut microbiomes derived from clinical colon biopsies. We combined a rapid peptide search by MSFragger against the Unified Human Gastrointestinal Protein database and the taxonomic and functional analyses with Unipept Desktop and MetaLab-MAG. Across seven samples, we identified and matched nearly 36,000 unique peptides to approximately 300 species and 11 phyla. Unipept Desktop provided gene ontology, InterPro entries, and enzyme commission number annotations, facilitating the identification of relevant metabolic pathways. MetaLab-MAG contributed functional annotations through Clusters of Orthologous Genes and Non-supervised Orthologous Groups categories. These results unveiled functional similarities and differences among the samples. This integrated pipeline holds the potential to provide deeper insights into the taxonomy and functions of the human gut microbiome for interrogating the intricate connections between microbiome balance and diseases.","PeriodicalId":224,"journal":{"name":"Proteomics","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141198517","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

Identification of RNA‐dependent liquid‐liquid phase separation proteins using an artificial intelligence strategy. 利用人工智能策略识别依赖于 RNA 的液-液相分离蛋白质。

IF 3.4 4区生物学

Proteomics Pub Date : 2024-06-02 DOI: 10.1002/pmic.202400044

Zahoor Ahmed, Kiran Shahzadi, Yanting Jin, Rui Li, Biffon Manyura Momanyi, Hasan Zulfiqar, Lin Ning, Hao Lin

{"title":"Identification of RNA‐dependent liquid‐liquid phase separation proteins using an artificial intelligence strategy.","authors":"Zahoor Ahmed, Kiran Shahzadi, Yanting Jin, Rui Li, Biffon Manyura Momanyi, Hasan Zulfiqar, Lin Ning, Hao Lin","doi":"10.1002/pmic.202400044","DOIUrl":"https://doi.org/10.1002/pmic.202400044","url":null,"abstract":"RNA-dependent liquid-liquid phase separation (LLPS) proteins play critical roles in cellular processes such as stress granule formation, DNA repair, RNA metabolism, germ cell development, and protein translation regulation. The abnormal behavior of these proteins is associated with various diseases, particularly neurodegenerative disorders like amyotrophic lateral sclerosis and frontotemporal dementia, making their identification crucial. However, conventional biochemistry-based methods for identifying these proteins are time-consuming and costly. Addressing this challenge, our study developed a robust computational model for their identification. We constructed a comprehensive dataset containing 137 RNA-dependent and 606 non-RNA-dependent LLPS protein sequences, which were then encoded using amino acid composition, composition of K-spaced amino acid pairs, Geary autocorrelation, and conjoined triad methods. Through a combination of correlation analysis, mutual information scoring, and incremental feature selection, we identified an optimal feature subset. This subset was used to train a random forest model, which achieved an accuracy of 90% when tested against an independent dataset. This study demonstrates the potential of computational methods as efficient alternatives for the identification of RNA-dependent LLPS proteins. To enhance the accessibility of the model, a user-centric web server has been established and can be accessed via the link: http://rpp.lin-group.cn.","PeriodicalId":224,"journal":{"name":"Proteomics","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141198523","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

Proteomics is advancing the understanding of stallion sperm biology 蛋白质组学加深了人们对种公马精子生物学的了解。

IF 3.4 4区生物学

Proteomics Pub Date : 2024-05-29 DOI: 10.1002/pmic.202300522

Fernando J. Peña, Francisco Eduardo Martín-Cano, Laura Becerro-Rey, Cristina Ortega-Ferrusola, Gemma Gaitskell-Phillips, Eva da Silva-Álvarez, María Cruz Gil

{"title":"Proteomics is advancing the understanding of stallion sperm biology","authors":"Fernando J. Peña, Francisco Eduardo Martín-Cano, Laura Becerro-Rey, Cristina Ortega-Ferrusola, Gemma Gaitskell-Phillips, Eva da Silva-Álvarez, María Cruz Gil","doi":"10.1002/pmic.202300522","DOIUrl":"10.1002/pmic.202300522","url":null,"abstract":"The mammalian ejaculate is very well suited to proteomics studies. As such, research concerning sperm proteomics is offering a huge amount of new information on the biology of spermatozoa. Among domestic animals, horses represent a species of special interest, in which reproductive technologies and a sizeable market of genetic material have grown exponentially in the last decade. Studies using proteomic approaches have been conducted in recent years, showing that proteomics is a potent tool to dig into the biology of the stallion spermatozoa. The aim of this review is to present an overview of the research conducted, and how these studies have improved our knowledge of stallion sperm biology. The main outcomes of the research conducted so far have been an improved knowledge of metabolism, and its importance in sperm functions, the impact of different technologies on the sperm proteome, and the identification of potential biomarkers. Moreover, proteomics of seminal plasma and phosphoproteomics are identified as areas of major interest.","PeriodicalId":224,"journal":{"name":"Proteomics","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/pmic.202300522","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141160859","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

Metaproteomic analysis of King Ghezo tomb wall (Abomey, Benin) confirms 19th century voodoo sacrifices 对 Ghezo 国王墓壁（贝宁阿波美）进行的元蛋白质组分析证实了 19 世纪的巫毒祭祀。

IF 3.4 4区生物学

Proteomics Pub Date : 2024-05-29 DOI: 10.1002/pmic.202400048

Philippe Charlier, Virginie Bourdin, Didier N'Dah, Mélodie Kielbasa, Olivier Pible, Jean Armengaud

{"title":"Metaproteomic analysis of King Ghezo tomb wall (Abomey, Benin) confirms 19th century voodoo sacrifices","authors":"Philippe Charlier, Virginie Bourdin, Didier N'Dah, Mélodie Kielbasa, Olivier Pible, Jean Armengaud","doi":"10.1002/pmic.202400048","DOIUrl":"10.1002/pmic.202400048","url":null,"abstract":"The palace of King Ghezo in Abomey, capital of the ancient kingdom of Dahomey (present-day Benin), houses two sacred huts which are specific funerary structures. It is claimed that the binder in their walls is made of human blood. In the study presented here, we conceived an original strategy to analyze the proteins present on minute amounts of the cladding sampled from the inner facade of the cenotaph wall and establish their origin. The extracted proteins were proteolyzed and the resulting peptides were characterized by high-resolution tandem mass spectrometry. Over 6397 distinct molecular entities were identified using cascading searches. Starting from without a priori searches of an extended generic database, the peptide repertoire was narrowed down to the most representative organisms—identified by means of taxon-specific peptides. A wide diversity of bacteria, fungi, plants, and animals were detected through the available protein material. This inventory was used to archaeologically reconstruct the voodoo rituals of consecration and maintenance of vitality. Several indicators attested to the presence of traces of human and poultry blood in the material taken. This study shows the essential advantages of paleoproteomics and metaproteomics for the study of ancient residues from archaeological excavations or historical monuments.","PeriodicalId":224,"journal":{"name":"Proteomics","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/pmic.202400048","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141160858","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

Prediction of peptide hormones using an ensemble of machine learning and similarity-based methods. 利用机器学习和基于相似性的方法组合预测肽类激素。

IF 3.4 4区生物学

Proteomics Pub Date : 2024-05-27 DOI: 10.1002/pmic.202400004

Dashleen Kaur, Akanksha Arora, Palani Vigneshwar, Gajendra P S Raghava

{"title":"Prediction of peptide hormones using an ensemble of machine learning and similarity-based methods.","authors":"Dashleen Kaur, Akanksha Arora, Palani Vigneshwar, Gajendra P S Raghava","doi":"10.1002/pmic.202400004","DOIUrl":"https://doi.org/10.1002/pmic.202400004","url":null,"abstract":"Peptide hormones serve as genome-encoded signal transduction molecules that play essential roles in multicellular organisms, and their dysregulation can lead to various health problems. In this study, we propose a method for predicting hormonal peptides with high accuracy. The dataset used for training, testing, and evaluating our models consisted of 1174 hormonal and 1174 non-hormonal peptide sequences. Initially, we developed similarity-based methods utilizing BLAST and MERCI software. Although these similarity-based methods provided a high probability of correct prediction, they had limitations, such as no hits or prediction of limited sequences. To overcome these limitations, we further developed machine and deep learning-based models. Our logistic regression-based model achieved a maximum AUROC of 0.93 with an accuracy of 86% on an independent/validation dataset. To harness the power of similarity-based and machine learning-based models, we developed an ensemble method that achieved an AUROC of 0.96 with an accuracy of 89.79% and a Matthews correlation coefficient (MCC) of 0.8 on the validation set. To facilitate researchers in predicting and designing hormone peptides, we developed a web-based server called HOPPred. This server offers a unique feature that allows the identification of hormone-associated motifs within hormone peptides. The server can be accessed at: https://webs.iiitd.edu.in/raghava/hoppred/.","PeriodicalId":224,"journal":{"name":"Proteomics","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141157042","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

Spectral entropy as a measure of the metaproteome complexity 作为元蛋白质组复杂性衡量标准的谱熵。

IF 3.4 4区生物学

Proteomics Pub Date : 2024-05-25 DOI: 10.1002/pmic.202300570

Haonan Duan, Zhibin Ning, Ailing Zhang, Daniel Figeys

引用次数: 0

Capillary blood self-collection for high-throughput proteomics 用于高通量蛋白质组学的毛细管自采血。

IF 3.4 4区生物学

Proteomics Pub Date : 2024-05-24 DOI: 10.1002/pmic.202300607

Bassim El-Sabawi, Shi Huang, Kahraman Tanriverdi, Andrew S. Perry, Kaushik Amancherla, Natalie Jackson, Jenna Hulsey, Jane E. Freedman, Ravi Shah, Brian R. Lindman

{"title":"Capillary blood self-collection for high-throughput proteomics","authors":"Bassim El-Sabawi, Shi Huang, Kahraman Tanriverdi, Andrew S. Perry, Kaushik Amancherla, Natalie Jackson, Jenna Hulsey, Jane E. Freedman, Ravi Shah, Brian R. Lindman","doi":"10.1002/pmic.202300607","DOIUrl":"10.1002/pmic.202300607","url":null,"abstract":"In this study, we sought to compare protein concentrations obtained from a high-throughput proteomics platform (Olink) on samples collected using capillary blood self-collection (with the Tasso+ device) versus standard venipuncture (control). Blood collection was performed on 20 volunteers, including one sample obtained via venipuncture and two via capillary blood using the Tasso+ device. Tasso+ samples were stored at 2°C–8°C for 24-hs (Tasso-24) or 48-h (Tasso-48) prior to processing to simulate shipping times from a study participant's home. Proteomics were analyzed using Olink (384 Inflammatory Panel). Tasso+ blood collection was successful in 37/40 attempts. Of 230 proteins included in our analysis, Pearson correlations (r) and mean coefficient of variation (CV) between Tasso-24 or Tasso-48 versus venipuncture were variable. In the Tasso-24 analysis, 34 proteins (14.8%) had both a correlation r > 0.5 and CV < 0.20. In the Tasso-48 analysis, 68 proteins (29.6%) had a correlation r > 0.5 and CV < 0.20. Combining the Tasso-24 and Tasso-48 analyses, 26 (11.3%) proteins met these thresholds. We concluded that protein concentrations from Tasso+ samples processed 24–48 h after collection demonstrated wide technical variability and variable correlation with a venipuncture gold-standard. Use of home capillary blood self-collection for large-scale proteomics should be limited to select proteins with good agreement with venipuncture.","PeriodicalId":224,"journal":{"name":"Proteomics","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/pmic.202300607","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141086383","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

Improved drug target deconvolution with PISA-DIA using an extended, overlapping temperature gradient 利用扩展、重叠温度梯度的 PISA-DIA 技术改进药物目标解卷积。

IF 3.4 4区生物学

Proteomics Pub Date : 2024-05-20 DOI: 10.1002/pmic.202300644

Samantha J. Emery-Corbin, Jumana M. Yousef, Subash Adhikari, Fransisca Sumardy, Duong Nhu, Mark F. van Delft, Guillaume Lessene, Jerzy Dziekan, Andrew I. Webb, Laura F. Dagley

{"title":"Improved drug target deconvolution with PISA-DIA using an extended, overlapping temperature gradient","authors":"Samantha J. Emery-Corbin, Jumana M. Yousef, Subash Adhikari, Fransisca Sumardy, Duong Nhu, Mark F. van Delft, Guillaume Lessene, Jerzy Dziekan, Andrew I. Webb, Laura F. Dagley","doi":"10.1002/pmic.202300644","DOIUrl":"10.1002/pmic.202300644","url":null,"abstract":"Thermal proteome profiling (TPP) is a powerful tool for drug target deconvolution. Recently, data-independent acquisition mass spectrometry (DIA-MS) approaches have demonstrated significant improvements to depth and missingness in proteome data, but traditional TPP (a.k.a. CEllular Thermal Shift Assay “CETSA”) workflows typically employ multiplexing reagents reliant on data-dependent acquisition (DDA). Herein, we introduce a new experimental design for the Proteome Integral Solubility Alteration via label-free DIA approach (PISA-DIA). We highlight the proteome coverage and sensitivity achieved by using multiple overlapping thermal gradients alongside DIA-MS, which maximizes efficiencies in PISA sample concatenation and safeguards against missing protein targets that exist at high melting temperatures. We demonstrate our extended PISA-DIA design has superior proteome coverage as compared to using tandem-mass tags (TMT) necessitating DDA-MS analysis. Importantly, we demonstrate our PISA-DIA approach has the quantitative and statistical rigor using A-1331852, a specific inhibitor of BCL-xL. Due to the high melt temperature of this protein target, we utilized our extended multiple gradient PISA-DIA workflow to identify BCL-xL. We assert our novel overlapping gradient PISA-DIA-MS approach is ideal for unbiased drug target deconvolution, spanning a large temperature range whilst minimizing target dropout between gradients, increasing the likelihood of resolving the protein targets of novel compounds.","PeriodicalId":224,"journal":{"name":"Proteomics","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/pmic.202300644","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141064275","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

Understanding bacterial pathogen diversity: A proteogenomic analysis and use of an array of genome assemblies to identify novel virulence factors of the honey bee bacterial pathogen Paenibacillus larvae 了解细菌病原体的多样性：蛋白质基因组分析和基因组组装阵列的使用，以确定蜜蜂细菌病原体幼虫担子菌的新型毒力因子。

IF 3.4 4区生物学

Proteomics Pub Date : 2024-05-14 DOI: 10.1002/pmic.202300280

Tomas Erban, Bruno Sopko

{"title":"Understanding bacterial pathogen diversity: A proteogenomic analysis and use of an array of genome assemblies to identify novel virulence factors of the honey bee bacterial pathogen Paenibacillus larvae","authors":"Tomas Erban, Bruno Sopko","doi":"10.1002/pmic.202300280","DOIUrl":"10.1002/pmic.202300280","url":null,"abstract":"Mass spectrometry proteomics data are typically evaluated against publicly available annotated sequences, but the proteogenomics approach is a useful alternative. A single genome is commonly utilized in custom proteomic and proteogenomic data analysis. We pose the question of whether utilizing numerous different genome assemblies in a search database would be beneficial. We reanalyzed raw data from the exoprotein fraction of four reference Enterobacterial Repetitive Intergenic Consensus (ERIC) I–IV genotypes of the honey bee bacterial pathogen Paenibacillus larvae and evaluated them against three reference databases (from NCBI-protein, RefSeq, and UniProt) together with an array of protein sequences generated by six-frame direct translation of 15 genome assemblies from GenBank. The wide search yielded 453 protein hits/groups, which UpSet analysis categorized into 50 groups based on the success of protein identification by the 18 database components. Nine hits that were not identified by a unique peptide were not considered for marker selection, which discarded the only protein that was not identified by the reference databases. We propose that the variability in successful identifications between genome assemblies is useful for marker mining. The results suggest that various strains of P. larvae can exhibit specific traits that set them apart from the established genotypes ERIC I–V.","PeriodicalId":224,"journal":{"name":"Proteomics","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/pmic.202300280","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140920261","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

Contents: Proteomics 10'24 内容：蛋白质组学 10'24

IF 3.4 4区生物学

Proteomics Pub Date : 2024-05-13 DOI: 10.1002/pmic.202470073

引用次数: 0