IF 3.4 4区生物学

Proteomics Pub Date : 2024-09-23 DOI: 10.1002/pmic.202300599

Frank Antony, Zora Brough, Mona Orangi, Mohammed Al-Seragi, Hiroyuki Aoki, Mohan Babu, Franck Duong van Hoa

{"title":"Sensitive Profiling of Mouse Liver Membrane Proteome Dysregulation Following a High-Fat and Alcohol Diet Treatment.","authors":"Frank Antony, Zora Brough, Mona Orangi, Mohammed Al-Seragi, Hiroyuki Aoki, Mohan Babu, Franck Duong van Hoa","doi":"10.1002/pmic.202300599","DOIUrl":"https://doi.org/10.1002/pmic.202300599","url":null,"abstract":"Alcohol consumption and high-fat (HF) diets often coincide in Western society, resulting in synergistic negative effects on liver function. Although studies have analyzed the global protein expression in the context of alcoholic liver disease (ALD) and metabolic dysfunction-associated steatotic liver disease (MASLD), none has offered specific insights on liver dysregulation at the membrane proteome level. Membrane-specific profiling of metabolic and compensatory phenomena is usually overshadowed in conventional proteomic workflows. In this study, we use the Peptidisc method to isolate and compare the membrane protein (MP) content of the liver with its unique biological functions. From mice fed with an HF diet and ethanol in drinking water, we annotate over 1500 liver proteins with half predicted to have at least one transmembrane segment. Among them, we identify 106 integral MPs that are dysregulated compared to the untreated sample. Gene Ontology analysis reveals several dysregulated membrane-associated processes like lipid metabolism, cell adhesion, xenobiotic processing, and mitochondrial membrane formation. Pathways related to cholesterol and bile acid transport are also mutually affected, suggesting an adaptive mechanism to counter the upcoming steatosis of the liver model. Taken together, our Peptidisc-based profiling of the diet-dysregulated liver provides specific insights and hypotheses into the role of the transmembrane proteome in disease development, and flags desirable MPs for therapeutic and diagnostic targeting.","PeriodicalId":224,"journal":{"name":"Proteomics","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142306811","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 Anti-Freezing Proteins From Their Evolutionary Profile. 从进化概况预测抗冻蛋白质

IF 3.4 4区生物学

Proteomics Pub Date : 2024-09-20 DOI: 10.1002/pmic.202400157

Nishant Kumar, Shubham Choudhury, Nisha Bajiya, Sumeet Patiyal, Gajendra P S Raghava

{"title":"Prediction of Anti-Freezing Proteins From Their Evolutionary Profile.","authors":"Nishant Kumar, Shubham Choudhury, Nisha Bajiya, Sumeet Patiyal, Gajendra P S Raghava","doi":"10.1002/pmic.202400157","DOIUrl":"https://doi.org/10.1002/pmic.202400157","url":null,"abstract":"Prediction of antifreeze proteins (AFPs) holds significant importance due to their diverse applications in healthcare. An inherent limitation of current AFP prediction methods is their reliance on unreviewed proteins for evaluation. This study evaluates, proposed and existing methods on an independent dataset containing 80 AFPs and 73 non-AFPs obtained from Uniport, which have been already reviewed by experts. Initially, we constructed machine learning models for AFP prediction using selected composition-based protein features and achieved a peak AUROC of 0.90 with an MCC of 0.69 on the independent dataset. Subsequently, we observed a notable enhancement in model performance, with the AUROC increasing from 0.90 to 0.93 upon incorporating evolutionary information instead of relying solely on the primary sequence of proteins. Furthermore, we explored hybrid models integrating our machine learning approaches with BLAST-based similarity and motif-based methods. However, the performance of these hybrid models either matched or was inferior to that of our best machine-learning model. Our best model based on evolutionary information outperforms all existing methods on independent/validation dataset. To facilitate users, a user-friendly web server with a standalone package named \"AFPropred\" was developed (https://webs.iiitd.edu.in/raghava/afpropred).","PeriodicalId":224,"journal":{"name":"Proteomics","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142277694","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

Matrix stiffness regulates the protein profile of extracellular vesicles of pancreatic cancer cell lines. 基质硬度调节胰腺癌细胞系细胞外囊泡的蛋白质谱。

IF 3.4 4区生物学

Proteomics Pub Date : 2024-09-16 DOI: 10.1002/pmic.202400058

Benedetta Ferrara, Sandrine Bourgoin-Voillard, Damien Habert, Benoit Vallée, Alba Nicolas-Boluda, Isidora Simanic, Michel Seve, Benoit Vingert, Florence Gazeau, Flavia Castellano, José Cohen, José Courty, Ilaria Cascone

{"title":"Matrix stiffness regulates the protein profile of extracellular vesicles of pancreatic cancer cell lines.","authors":"Benedetta Ferrara, Sandrine Bourgoin-Voillard, Damien Habert, Benoit Vallée, Alba Nicolas-Boluda, Isidora Simanic, Michel Seve, Benoit Vingert, Florence Gazeau, Flavia Castellano, José Cohen, José Courty, Ilaria Cascone","doi":"10.1002/pmic.202400058","DOIUrl":"https://doi.org/10.1002/pmic.202400058","url":null,"abstract":"The fibrotic stroma characterizing pancreatic ductal adenocarcinoma (PDAC) derives from a progressive tissue rigidification, which induces epithelial mesenchymal transition and metastatic dissemination. The aim of this study was to investigate the influence of matrix stiffness on PDAC progression by analyzing the proteome of PDAC-derived extracellular vesicles (EVs). PDAC cell lines (mPDAC and KPC) were grown on synthetic supports with a stiffness close to non-tumor (NT) or tumor tissue (T), and the protein expression levels in cell-derived EVs were analyzed by a quantitative MSE label-free mass spectrometry approach. Our analysis figured out 15 differentially expressed proteins (DEPs) in mPDAC-EVs and 20 DEPs in KPC-EVs in response to matrix rigidification. Up-regulated proteins participate to the processes of metabolism, matrix remodeling, and immune response, altogether hallmarks of PDAC progression. A multimodal network analysis revealed that the majority of DEPs are strongly related to pancreatic cancer. Interestingly, among DEPs, 11 related genes (ACTB/ANXA7/C3/IGSF8/LAMC1/LGALS3/PCD6IP/SFN/TPM3/VARS/YWHAZ) for mPDAC-EVs and 9 (ACTB/ALDH2/GAPDH/HNRNPA2B/ITGA2/NEXN/PKM/RPN1/S100A6) for KPC-EVs were significantly overexpressed in tumor tissues according to gene expression profiling interaction analysis (GEPIA). Concerning the potential clinical relevance of these data, the cluster of ACTB, ITGA2, GAPDH and PKM genes displayed an adverse effect (p < 0.05) on the overall survival of PDAC patients.","PeriodicalId":224,"journal":{"name":"Proteomics","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142277693","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

Characterization of Exosomes Released from Mycobacterium abscessus-Infected Macrophages. 受脓肿分枝杆菌感染的巨噬细胞释放的外泌体的特征。

IF 3.4 4区生物学

Proteomics Pub Date : 2024-09-16 DOI: 10.1002/pmic.202400181

Charlie A Vermeire, Xuejuan Tan, Aidaly Ramos-Leyva, Ava Wood, Stephen K Kotey, Steven D Hartson, Yurong Liang, Lin Liu, Yong Cheng

{"title":"Characterization of Exosomes Released from Mycobacterium abscessus-Infected Macrophages.","authors":"Charlie A Vermeire, Xuejuan Tan, Aidaly Ramos-Leyva, Ava Wood, Stephen K Kotey, Steven D Hartson, Yurong Liang, Lin Liu, Yong Cheng","doi":"10.1002/pmic.202400181","DOIUrl":"https://doi.org/10.1002/pmic.202400181","url":null,"abstract":"Extracellular vesicles (EVs), such as exosomes, play a critical role in cell-to-cell communication and regulating cellular processes in recipient cells. Non-tuberculous mycobacteria (NTM), such as Mycobacterium abscessus, are a group of environmental bacteria that can cause severe lung infections in populations with pre-existing lung conditions, such as cystic fibrosis (CF) and chronic obstructive pulmonary disease (COPD). There is limited knowledge of the engagement of EVs in the host-pathogen interactions in the context of NTM infections. In this study, we found that M. abscessus infection increased the release of a subpopulation of exosomes (CD9, CD63, and/or CD81 positive) by mouse macrophages in cell culture. Proteomic analysis of these vesicles demonstrated that M. abscessus infection affects the enrichment of host proteins in exosomes released by macrophages. When compared to exosomes from uninfected macrophages, exosomes released by M. abscessus-infected macrophages significantly improved M. abscessus growth and downregulated the intracellular level of glutamine in recipient macrophages in cell culture. Increasing glutamine concentration in the medium rescued intracellular glutamine levels and M. abscessus killing in recipient macrophages that were treated with exosomes from M. abscessus-infected macrophages. Taken together, our results indicate that exosomes may serve as extracellular glutamine eliminators that interfere with glutamine-dependent M. abscessus killing in recipient macrophages.","PeriodicalId":224,"journal":{"name":"Proteomics","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142277692","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

Standard abbreviations 标准缩略语

IF 3.4 4区生物学

Proteomics Pub Date : 2024-09-13 DOI: 10.1002/pmic.202470144

引用次数: 0

Editorial Board: Proteomics 18'24 编辑委员会：蛋白质组学 18'24

IF 3.4 4区生物学

Proteomics Pub Date : 2024-09-13 DOI: 10.1002/pmic.202470142

引用次数: 0

Contents: Proteomics 18'24 内容：蛋白质组学 18'24

IF 3.4 4区生物学

Proteomics Pub Date : 2024-09-13 DOI: 10.1002/pmic.202470143

引用次数: 0

A semi-automated workflow for DIA-based global discovery to pathway-driven PRM analysis. 从基于 DIA 的全球发现到通路驱动的 PRM 分析的半自动化工作流程。

IF 3.4 4区生物学

Proteomics Pub Date : 2024-09-05 DOI: 10.1002/pmic.202400129

Jennifer Guergues, Jessica Wohlfahrt, John M Koomen, Jonathan R Krieger, Sameer Varma, Stanley M Stevens

{"title":"A semi-automated workflow for DIA-based global discovery to pathway-driven PRM analysis.","authors":"Jennifer Guergues, Jessica Wohlfahrt, John M Koomen, Jonathan R Krieger, Sameer Varma, Stanley M Stevens","doi":"10.1002/pmic.202400129","DOIUrl":"https://doi.org/10.1002/pmic.202400129","url":null,"abstract":"Targeted proteomics, which includes parallel reaction monitoring (PRM), is typically utilized for more precise detection and quantitation of key proteins and/or pathways derived from complex discovery proteomics datasets. Initial discovery-based analysis using data independent acquisition (DIA) can obtain deep proteome coverage with low data missingness while targeted PRM assays can provide additional benefits in further eliminating missing data and optimizing measurement precision. However, PRM method development from bioinformatic predictions can be tedious and time-consuming because of the DIA output complexity. We address this limitation with a Python script that rapidly generates a PRM method for the TIMS-TOF platform using DIA data and a user-defined target list. To evaluate the script, DIA data obtained from HeLa cell lysate (200 ng, 45-min gradient method) as well as canonical pathway information from Ingenuity Pathway Analysis was utilized to generate a pathway-driven PRM method. Subsequent PRM analysis of targets within the example pathway, regulation of apoptosis, resulted in improved chromatographic data and enhanced quantitation precision (100% peptides below 10% CV with a median CV of 2.9%, n = 3 technical replicates). The script is freely available at https://github.com/StevensOmicsLab/PRM-script and provides a framework that can be adapted to multiple DDA/DIA data outputs and instrument-specific PRM method types.","PeriodicalId":224,"journal":{"name":"Proteomics","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142131400","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

Top-down mass spectrometry analysis of capsid proteins of recombinant adeno-associated virus using multiple ion activations and proton transfer charge reduction. 利用多重离子活化和质子转移电荷还原对重组腺相关病毒的囊膜蛋白进行自上而下的质谱分析。

IF 3.4 4区生物学

Proteomics Pub Date : 2024-09-05 DOI: 10.1002/pmic.202400223

Jake T Kline, Jingjing Huang, Linda B Lieu, Kristina Srzentić, David Bergen, Christopher Mullen, Graeme C McAlister, Kenneth R Durbin, Rafael D Melani, Luca Fornelli

{"title":"Top-down mass spectrometry analysis of capsid proteins of recombinant adeno-associated virus using multiple ion activations and proton transfer charge reduction.","authors":"Jake T Kline, Jingjing Huang, Linda B Lieu, Kristina Srzentić, David Bergen, Christopher Mullen, Graeme C McAlister, Kenneth R Durbin, Rafael D Melani, Luca Fornelli","doi":"10.1002/pmic.202400223","DOIUrl":"https://doi.org/10.1002/pmic.202400223","url":null,"abstract":"Adeno-associated viruses (AAVs) are common vectors for emerging gene therapies due to their lack of pathogenicity in humans. Here, we present our investigation of the viral proteins (i.e., VP1, VP2, and VP3) of the capsid of AAVs via top-down mass spectrometry (MS). These proteins, ranging from 59 to 81 kDa, were chromatographically separated using hydrophilic interaction liquid chromatography and characterized in the gas-phase by high-resolution Orbitrap Fourier transform MS. Complementary ion dissociation methods were utilized to improve the overall sequence coverage. By reducing the overlap of product ion signals via proton transfer charge reduction on the Orbitrap Ascend BioPharma Tribrid mass spectrometer, the sequence coverage of each VP was significantly increased, reaching up to ∼40% in the case of VP3. These results showcase the improvements in the sequencing of proteins >30 kDa that can be achieved by manipulating product ions via gas-phase reactions to obtain easy-to-interpret fragmentation mass spectra.","PeriodicalId":224,"journal":{"name":"Proteomics","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142131401","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

Editorial Board: Proteomics 17'24 编辑委员会：蛋白质组学 17'24

IF 3.4 4区生物学

Proteomics Pub Date : 2024-09-04 DOI: 10.1002/pmic.202470132

引用次数: 0

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