Pub Date : 2025-12-26DOI: 10.1021/acs.jproteome.5c00610
Shujun Liu*, , , Yating Ma, , , Bo Sun, , , Mei Yang, , , Mindi Zhao, , and , Chuanbao Li*,
Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer and is difficult to distinguish from benign pulmonary nodules (BPNs), particularly at early stages. Extracellular vesicles (EVs) represent a promising source of biomarkers for the diagnosis of malignant pulmonary nodules. This study aimed to identify robust and clinically relevant EV-based protein biomarkers via isolation with EXODUS, a system that enables efficient direct capture of plasma EVs, followed by data-independent acquisition mass spectrometry (DIA–MS) for in-depth proteomic profiling. A total of 1383 proteins were identified from the plasma EVs obtained from 25 individuals (10 BPN and 15 early stage LUAD), while dysregulated protein signatures were revealed through differential expression analysis. Machine learning algorithms incorporating demographic variables, imaging features, EV protein profiles, and conventional tumor markers were applied to select diagnostic candidates. Random forest analysis revealed two upregulated proteins, NTN3 and APOA4, as promising biomarkers. Subsequently, their diagnostic performance and net clinical benefits were validated in an independent EV cohort (6 LUAD and 6 BPN) using ELISAs and decision curve analysis. In summary, we present an integrated pipeline that combines EXODUS-based isolation, DIA–MS, and machine learning to detect markers from plasma EVs for distinguishing early stage lung cancer from benign nodules.
{"title":"Proteomic Profiling of Plasma Extracellular Vesicles Combined with Multivariate Modeling Identified Potential Biomarkers for Distinguishing Benign Pulmonary Nodules from Early-Stage Lung Adenocarcinoma","authors":"Shujun Liu*, , , Yating Ma, , , Bo Sun, , , Mei Yang, , , Mindi Zhao, , and , Chuanbao Li*, ","doi":"10.1021/acs.jproteome.5c00610","DOIUrl":"10.1021/acs.jproteome.5c00610","url":null,"abstract":"<p >Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer and is difficult to distinguish from benign pulmonary nodules (BPNs), particularly at early stages. Extracellular vesicles (EVs) represent a promising source of biomarkers for the diagnosis of malignant pulmonary nodules. This study aimed to identify robust and clinically relevant EV-based protein biomarkers via isolation with EXODUS, a system that enables efficient direct capture of plasma EVs, followed by data-independent acquisition mass spectrometry (DIA–MS) for in-depth proteomic profiling. A total of 1383 proteins were identified from the plasma EVs obtained from 25 individuals (10 BPN and 15 early stage LUAD), while dysregulated protein signatures were revealed through differential expression analysis. Machine learning algorithms incorporating demographic variables, imaging features, EV protein profiles, and conventional tumor markers were applied to select diagnostic candidates. Random forest analysis revealed two upregulated proteins, NTN3 and APOA4, as promising biomarkers. Subsequently, their diagnostic performance and net clinical benefits were validated in an independent EV cohort (6 LUAD and 6 BPN) using ELISAs and decision curve analysis. In summary, we present an integrated pipeline that combines EXODUS-based isolation, DIA–MS, and machine learning to detect markers from plasma EVs for distinguishing early stage lung cancer from benign nodules.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":"25 2","pages":"735–754"},"PeriodicalIF":3.6,"publicationDate":"2025-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145843065","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}
The underlying metabolic mechanisms between healthy lifestyle behaviors and a lower risk of chronic liver diseases (CLD) remain elusive. This prospective cohort study of 168,260 UK Biobank participants without baseline liver disease identified a healthy lifestyle–associated metabolic signature using elastic net regression and examined its relationship with CLD. The resulting signature, comprising 66 metabolites, was strongly correlated with healthy lifestyle scores (r = 0.434, P < 0.001) and was inversely associated with the risks of MASLD, cirrhosis, liver cancer, and liver-related mortality, with hazard ratios ranging from 0.55 to 0.70 per standard deviation increase. Mediation analyses showed that this metabolic signature explained 20.3–49.6% of the protective effects of a healthy lifestyle on these CLDs, while Mendelian randomization suggested potential causal roles of these metabolites in CLD development. Overall, the findings underscore the importance of early lifestyle interventions and metabolic monitoring for the precise prevention of CLD.
健康生活方式行为与慢性肝病(CLD)低风险之间的潜在代谢机制仍然难以捉摸。这项前瞻性队列研究纳入了168,260名无基线肝病的英国生物银行参与者,使用弹性网络回归确定了健康生活方式相关的代谢特征,并检查了其与CLD的关系。所得到的特征包括66种代谢物,与健康生活方式评分密切相关(r = 0.434, P < 0.001),与MASLD、肝硬化、肝癌和肝脏相关死亡率的风险呈负相关,每增加一个标准差的风险比为0.55至0.70。中介分析显示,这一代谢特征解释了20.3-49.6%的健康生活方式对这些CLD的保护作用,而孟德尔随机化表明这些代谢物在CLD发展中的潜在因果作用。总的来说,研究结果强调了早期生活方式干预和代谢监测对于精确预防CLD的重要性。
{"title":"Metabolic Signature of a Healthy Lifestyle and the Risk of MASLD and Other Chronic Liver Diseases: An Observational and Mendelian Randomization Study","authors":"Zhuoshuai Liang, , , Huizhen Jin, , , Wenhui Gao, , , Hongrui Zhang, , , Xinmeng Hu, , , Ruofei Li, , , Xiaoyang Li, , , Yi Cheng, , , Lingfei Guo*, , and , Yawen Liu*, ","doi":"10.1021/acs.jproteome.5c00677","DOIUrl":"10.1021/acs.jproteome.5c00677","url":null,"abstract":"<p >The underlying metabolic mechanisms between healthy lifestyle behaviors and a lower risk of chronic liver diseases (CLD) remain elusive. This prospective cohort study of 168,260 UK Biobank participants without baseline liver disease identified a healthy lifestyle–associated metabolic signature using elastic net regression and examined its relationship with CLD. The resulting signature, comprising 66 metabolites, was strongly correlated with healthy lifestyle scores (<i>r</i> = 0.434, <i>P</i> < 0.001) and was inversely associated with the risks of MASLD, cirrhosis, liver cancer, and liver-related mortality, with hazard ratios ranging from 0.55 to 0.70 per standard deviation increase. Mediation analyses showed that this metabolic signature explained 20.3–49.6% of the protective effects of a healthy lifestyle on these CLDs, while Mendelian randomization suggested potential causal roles of these metabolites in CLD development. Overall, the findings underscore the importance of early lifestyle interventions and metabolic monitoring for the precise prevention of CLD.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":"25 2","pages":"700–712"},"PeriodicalIF":3.6,"publicationDate":"2025-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145831729","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}
Pub Date : 2025-12-24DOI: 10.1021/acs.jproteome.5c00831
Ting Cao, , , Wenli Li, , , Jungang Pang, , , Shaohua Tan, , and , Jun Liu*,
Unstable angina (UA) represents a prevalent cardiovascular condition characterized by significant morbidity and mortality, necessitating the development of effective early diagnostic biomarkers. This study sought to identify plasma protein biomarkers associated with UA utilizing Olink proteomics. A cohort of 120 participants, comprising 60 individuals diagnosed with UA and 60 healthy controls, was recruited. A total of 92 inflammation-related plasma proteins were quantified through a proximity extension assay. In the discovery cohort, differential expression analysis revealed significant alterations in 49 proteins, which were predominantly enriched in cytokine-mediated signaling and MAPK pathways, as demonstrated by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. Least absolute shrinkage and selection operator regression and random forest methodologies prioritized three biomarkers─SPON2, PTX3, and GBGT1─that exhibited elevated levels in UA patients compared to controls. Receiver operating characteristic analysis demonstrated area under the curve values of 0.859, 0.937, and 0.900 for SPON2, PTX3, and GBGT1, respectively. A combined diagnostic model incorporating these three proteins achieved an AUC of 0.979 and demonstrated robust performance in an independent validation cohort. These results suggest that SPON2, PTX3, GBGT1, and their composite model hold promise as diagnostic biomarkers for UA.
{"title":"Identification and Validation of Novel Biomarkers for Unstable Angina Using Olink Proteomics","authors":"Ting Cao, , , Wenli Li, , , Jungang Pang, , , Shaohua Tan, , and , Jun Liu*, ","doi":"10.1021/acs.jproteome.5c00831","DOIUrl":"10.1021/acs.jproteome.5c00831","url":null,"abstract":"<p >Unstable angina (UA) represents a prevalent cardiovascular condition characterized by significant morbidity and mortality, necessitating the development of effective early diagnostic biomarkers. This study sought to identify plasma protein biomarkers associated with UA utilizing Olink proteomics. A cohort of 120 participants, comprising 60 individuals diagnosed with UA and 60 healthy controls, was recruited. A total of 92 inflammation-related plasma proteins were quantified through a proximity extension assay. In the discovery cohort, differential expression analysis revealed significant alterations in 49 proteins, which were predominantly enriched in cytokine-mediated signaling and MAPK pathways, as demonstrated by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. Least absolute shrinkage and selection operator regression and random forest methodologies prioritized three biomarkers─SPON2, PTX3, and GBGT1─that exhibited elevated levels in UA patients compared to controls. Receiver operating characteristic analysis demonstrated area under the curve values of 0.859, 0.937, and 0.900 for SPON2, PTX3, and GBGT1, respectively. A combined diagnostic model incorporating these three proteins achieved an AUC of 0.979 and demonstrated robust performance in an independent validation cohort. These results suggest that SPON2, PTX3, GBGT1, and their composite model hold promise as diagnostic biomarkers for UA.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":"25 2","pages":"895–902"},"PeriodicalIF":3.6,"publicationDate":"2025-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145825449","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}
Pub Date : 2025-12-24DOI: 10.1021/acs.jproteome.5c00934
Cameron S. Movassaghi, and , Jesse G. Meyer*,
Antibiotics are routinely added to mammalian cell culture media to prevent bacterial growth. However, the use of antibiotics in a cell culture can confound downstream experimental results. While genomic and transcriptomic differences between cell cultures treated with and without antibiotics are well-documented, far fewer, if any, comprehensive proteomic comparisons on the use of antibiotics in cell culture have been performed. Here, we present a study on the proteome-wide differences of culturing HepG2 cells in antibiotic (i.e., penicillin/streptomycin) and nonantibiotic-containing media. Using a longitudinal and crossover treatment study design, we analyzed 119 samples across nine passages and four conditions. On average, 9,374 proteins were detected per sample, and we identified 383 proteins that were differentially abundant between conditions. These changes included ribosomal and mitochondrial proteins, demonstrating that off-target effects of antibiotics on mammalian cells occur at the protein level. Linear mixed-effect modeling suggested that the proteomic impact of antibiotic treatment is strongest in the first passage after treatment and stabilizes after approximately three passages. Furthermore, initiating antibiotic treatment induced a greater number of differentially abundant proteins than discontinuing treatment. Lastly, we compared our results to existing literature on the use of common antibiotics in mammalian cell culture. We identified proteins and pathways conserved across studies, omics layers, and cell types. We hope that this detailed proteomic survey of the ubiquitous pencillin–streptyomcin-treated HepG2 in vitro model will aid researchers in comparing cross-study or cross-condition results from antibiotic-treated mammalian cells and inform appropriate experimental designs for the use of antibiotics in cell culture.
{"title":"Penicillin–Streptomycin Treatment Rewires Core Metabolic and Ribosomal Programs in HepG2 Cells","authors":"Cameron S. Movassaghi, and , Jesse G. Meyer*, ","doi":"10.1021/acs.jproteome.5c00934","DOIUrl":"10.1021/acs.jproteome.5c00934","url":null,"abstract":"<p >Antibiotics are routinely added to mammalian cell culture media to prevent bacterial growth. However, the use of antibiotics in a cell culture can confound downstream experimental results. While genomic and transcriptomic differences between cell cultures treated with and without antibiotics are well-documented, far fewer, if any, comprehensive proteomic comparisons on the use of antibiotics in cell culture have been performed. Here, we present a study on the proteome-wide differences of culturing HepG2 cells in antibiotic (i.e., penicillin/streptomycin) and nonantibiotic-containing media. Using a longitudinal and crossover treatment study design, we analyzed 119 samples across nine passages and four conditions. On average, 9,374 proteins were detected per sample, and we identified 383 proteins that were differentially abundant between conditions. These changes included ribosomal and mitochondrial proteins, demonstrating that off-target effects of antibiotics on mammalian cells occur at the protein level. Linear mixed-effect modeling suggested that the proteomic impact of antibiotic treatment is strongest in the first passage after treatment and stabilizes after approximately three passages. Furthermore, initiating antibiotic treatment induced a greater number of differentially abundant proteins than discontinuing treatment. Lastly, we compared our results to existing literature on the use of common antibiotics in mammalian cell culture. We identified proteins and pathways conserved across studies, omics layers, and cell types. We hope that this detailed proteomic survey of the ubiquitous pencillin–streptyomcin-treated HepG2 <i>in vitro</i> model will aid researchers in comparing cross-study or cross-condition results from antibiotic-treated mammalian cells and inform appropriate experimental designs for the use of antibiotics in cell culture.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":"25 2","pages":"1082–1094"},"PeriodicalIF":3.6,"publicationDate":"2025-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.jproteome.5c00934","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145825427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-23DOI: 10.1021/acs.jproteome.5c00179
Cristina Chiva, , , Zahra Elhamraoui, , , Julia Morales-Sanfrutos, , , Olga Pastor, , and , Eduard Sabidó*,
Mass spectrometry (MS)-based proteomics is known for its high accuracy in quantifying peptides and proteins using various calibration strategies including internal and external calibration curves. While external multipoint calibration curves are created from serial dilutions, they often fail to account for sample-specific matrix effects. In contrast, internal calibration curves account for the sample matrix but face scalability and cost challenges for whole proteome analyses. In this manuscript, we present a novel TMT-based multipoint internal calibration curve strategy, which enables the generation of internal calibration curves for all peptides identified within a proteome in a single experiment to assess their linearity prior relative quantification. We applied this strategy to human ovarian cancer cells to evaluate the linear quantitative responses of all of the identified peptides and reveal the significant proteome changes associated with cisplatin treatment.
{"title":"Proteome-Wide Multipoint Internal Calibration Curves for Evaluating Peptide-Level Linearity in Relative Quantitative Proteomics","authors":"Cristina Chiva, , , Zahra Elhamraoui, , , Julia Morales-Sanfrutos, , , Olga Pastor, , and , Eduard Sabidó*, ","doi":"10.1021/acs.jproteome.5c00179","DOIUrl":"10.1021/acs.jproteome.5c00179","url":null,"abstract":"<p >Mass spectrometry (MS)-based proteomics is known for its high accuracy in quantifying peptides and proteins using various calibration strategies including internal and external calibration curves. While external multipoint calibration curves are created from serial dilutions, they often fail to account for sample-specific matrix effects. In contrast, internal calibration curves account for the sample matrix but face scalability and cost challenges for whole proteome analyses. In this manuscript, we present a novel TMT-based multipoint internal calibration curve strategy, which enables the generation of internal calibration curves for all peptides identified within a proteome in a single experiment to assess their linearity prior relative quantification. We applied this strategy to human ovarian cancer cells to evaluate the linear quantitative responses of all of the identified peptides and reveal the significant proteome changes associated with cisplatin treatment.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":"25 2","pages":"1204–1210"},"PeriodicalIF":3.6,"publicationDate":"2025-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.jproteome.5c00179","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145808962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-23DOI: 10.1021/acs.jproteome.5c00771
Jack Scanlan, , , Parul Mittal, , , Noor A. Lokman, , , Martin K. Oehler, , , Peter Hoffmann, , and , Manuela Klingler-Hoffmann*,
The accumulation of malignant ascites in the peritoneal cavity is a hallmark of high-grade serous ovarian cancer (HGSC). This fluid contains three-dimensional multicellular aggregates known as spheroids, which contribute to chemoresistance and are an accessible source of tumor material for proteomic-based biomarker discovery studies. Although heterogeneous ascitic spheroids can be generated from primary cell suspensions for ex vivo applications, they suffer from long generation times and reduced biological relevance. Here, we compare their ex vivo chemotherapy responses and proteomes to native spheroids that are collected directly from HGSC ascites, with the aim of assessing their suitability for proteomic-based chemoresponse prediction strategies that yield results within a clinically relevant time frame. We demonstrate that the chemoresponses of native spheroids better correlate with patients’ clinical treatment responses in 4 of 5 cases and that their proteomes uniquely segregate according to ex vivo carboplatin response along the first component. This pilot study suggests key proteins and biological pathways that may facilitate a global proteomic-based screening strategy for personalized HGSC treatment, with particular emphasis on extracellular matrix proteins. As such, native spheroids have the potential to progress the personalized treatment of HGSC patients with malignant ascites.
{"title":"Toward Proteomic-Based Prediction of Ex Vivo Platinum Sensitivity in Ovarian Cancer Ascitic Cellular Aggregates: A Pilot Study","authors":"Jack Scanlan, , , Parul Mittal, , , Noor A. Lokman, , , Martin K. Oehler, , , Peter Hoffmann, , and , Manuela Klingler-Hoffmann*, ","doi":"10.1021/acs.jproteome.5c00771","DOIUrl":"10.1021/acs.jproteome.5c00771","url":null,"abstract":"<p >The accumulation of malignant ascites in the peritoneal cavity is a hallmark of high-grade serous ovarian cancer (HGSC). This fluid contains three-dimensional multicellular aggregates known as spheroids, which contribute to chemoresistance and are an accessible source of tumor material for proteomic-based biomarker discovery studies. Although heterogeneous ascitic spheroids can be generated from primary cell suspensions for ex vivo applications, they suffer from long generation times and reduced biological relevance. Here, we compare their <i>ex vivo</i> chemotherapy responses and proteomes to native spheroids that are collected directly from HGSC ascites, with the aim of assessing their suitability for proteomic-based chemoresponse prediction strategies that yield results within a clinically relevant time frame. We demonstrate that the chemoresponses of native spheroids better correlate with patients’ clinical treatment responses in 4 of 5 cases and that their proteomes uniquely segregate according to <i>ex vivo</i> carboplatin response along the first component. This pilot study suggests key proteins and biological pathways that may facilitate a global proteomic-based screening strategy for personalized HGSC treatment, with particular emphasis on extracellular matrix proteins. As such, native spheroids have the potential to progress the personalized treatment of HGSC patients with malignant ascites.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":"25 2","pages":"828–841"},"PeriodicalIF":3.6,"publicationDate":"2025-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145814725","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}
Mitochondrial dysfunction induces numerous diseases, yet current proximity labeling methods require gene transfection and membrane potential-sensitive probes, limiting their use in hard-to-transfect cells and disease models. We developed TAG-PL (Tailored Antibody-Guided Proximity Labeling), a transfection-free approach for in-depth mapping of the mitochondrial proteome, achieving >90% specificity and identifying >450 mitochondrial proteins─more than the coverage of existing nontransfection methods. Applied to heat-stressed macrophages, TAG-PL revealed dynamic mitochondrial proteome remodeling, including antioxidant responses and metabolic shifts during heat stress. Notably, we discovered physical interactions between stress granules and mitochondria, identifying 10 interaction mediators (including MSRA and UBA1). These findings establish stress granules as regulatory hubs for organelle dynamics and immune responses. TAG-PL’s high performance and broad applicability across diverse sample types, particularly immune cells and tissues, make it a powerful tool for dissecting mitochondrial function in disease models without genetic manipulation.
{"title":"TAG-PL: A Universal Proximity Labeling Platform for Mapping Mitochondrial Proteomes and Organelle Interactions under Stress","authors":"Enming Miao, , , Xuyang Yue, , , Zhixiong Tao, , , Hongqiang Qin*, , and , Mingliang Ye*, ","doi":"10.1021/acs.jproteome.5c00855","DOIUrl":"10.1021/acs.jproteome.5c00855","url":null,"abstract":"<p >Mitochondrial dysfunction induces numerous diseases, yet current proximity labeling methods require gene transfection and membrane potential-sensitive probes, limiting their use in hard-to-transfect cells and disease models. We developed TAG-PL (Tailored Antibody-Guided Proximity Labeling), a transfection-free approach for in-depth mapping of the mitochondrial proteome, achieving >90% specificity and identifying >450 mitochondrial proteins─more than the coverage of existing nontransfection methods. Applied to heat-stressed macrophages, TAG-PL revealed dynamic mitochondrial proteome remodeling, including antioxidant responses and metabolic shifts during heat stress. Notably, we discovered physical interactions between stress granules and mitochondria, identifying 10 interaction mediators (including MSRA and UBA1). These findings establish stress granules as regulatory hubs for organelle dynamics and immune responses. TAG-PL’s high performance and broad applicability across diverse sample types, particularly immune cells and tissues, make it a powerful tool for dissecting mitochondrial function in disease models without genetic manipulation.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":"25 2","pages":"966–977"},"PeriodicalIF":3.6,"publicationDate":"2025-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145808921","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}
Peroxynitrite is capable of inducing protein nitration, which alters protein structure and interferes with signaling pathways dependent on phosphorylation. This study aims to investigate the effects of peroxynitrite-driven nitration and phosphorylation on proteins in HEK293T cells. Through label-free quantitative mass spectrometry, we successfully identified over 5,000 proteins from 0.5 μg of cell extracts collected at five different time intervals (0, 2, 15, 30, and 60 min) after exposure to peroxynitrite. We found that protein expression profiles from 2 to 60 min were distinct from those at 0 min. LC-MS/MS was also applied to quantify and map the nitration and phosphorylation sites. Analysis of protein nitration and phosphorylation revealed distinct temporal profiles, suggesting that nitration may contribute to the altered phosphorylation of the same protein or its interacting proteins. This study provides valuable insights for further mechanistic studies in peroxynitrite-related pathways.
{"title":"Temporal Profiling of Peroxynitrite-Mediated Protein Nitration and Phosphorylation Using Proteomics Analysis","authors":"Yating Yao*, , , Shuang Wang, , , Jingyi Li, , , Xiaohua Wang, , and , Jinghua Yang*, ","doi":"10.1021/acs.jproteome.5c00417","DOIUrl":"10.1021/acs.jproteome.5c00417","url":null,"abstract":"<p >Peroxynitrite is capable of inducing protein nitration, which alters protein structure and interferes with signaling pathways dependent on phosphorylation. This study aims to investigate the effects of peroxynitrite-driven nitration and phosphorylation on proteins in HEK293T cells. Through label-free quantitative mass spectrometry, we successfully identified over 5,000 proteins from 0.5 μg of cell extracts collected at five different time intervals (0, 2, 15, 30, and 60 min) after exposure to peroxynitrite. We found that protein expression profiles from 2 to 60 min were distinct from those at 0 min. LC-MS/MS was also applied to quantify and map the nitration and phosphorylation sites. Analysis of protein nitration and phosphorylation revealed distinct temporal profiles, suggesting that nitration may contribute to the altered phosphorylation of the same protein or its interacting proteins. This study provides valuable insights for further mechanistic studies in peroxynitrite-related pathways.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":"25 2","pages":"607–617"},"PeriodicalIF":3.6,"publicationDate":"2025-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145808954","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}
Pub Date : 2025-12-22DOI: 10.1021/acs.jproteome.5c00872
Leander Roeland van der Hoeven, , , Maico Lechner, , , Cristina Hernandez-Rollan, , , Tanveer Singh Batth, , and , Jesper V. Olsen*,
This study presents a comparative analysis of three LysC endopeptidase homologues from Achromobacter lyticus (A. lyticus),Pseudomonas aeruginosa and Lysobacter enzymogenes for mass spectrometry-based proteomics. Utilizing a protein aggregation capture workflow with HeLa cell lysates, we assessed the enzymes’ cleavage specificity, digestion efficiency, and performance across various experimental conditions. Results showed that while all three LysC homologues exhibited high cleavage specificity at lysine residues, A. lyticus LysC outperformed the two others with superior peptide identification, digestion efficiency, and protein coverage, especially at shorter digestion times. Our experiments using a combination ofA. lyticusLysC and trypsin demonstrated the importance of employing LysC for significantly minimizing missed cleavage rates in tryptic digests, especially with regard to lysine-containing peptides. This study underscores A. lyticus LysC’s potential as an optimal choice for enhancing mass spectrometry-based proteomics.
{"title":"Comparative Analysis of Lysine-Specific Peptidases for Optimizing Proteomics Workflows","authors":"Leander Roeland van der Hoeven, , , Maico Lechner, , , Cristina Hernandez-Rollan, , , Tanveer Singh Batth, , and , Jesper V. Olsen*, ","doi":"10.1021/acs.jproteome.5c00872","DOIUrl":"10.1021/acs.jproteome.5c00872","url":null,"abstract":"<p >This study presents a comparative analysis of three LysC endopeptidase homologues from <i>Achromobacter lyticus</i> (<i>A. lyticus</i>),<i>Pseudomonas aeruginosa</i> and <i>Lysobacter enzymogenes</i> for mass spectrometry-based proteomics. Utilizing a protein aggregation capture workflow with HeLa cell lysates, we assessed the enzymes’ cleavage specificity, digestion efficiency, and performance across various experimental conditions. Results showed that while all three LysC homologues exhibited high cleavage specificity at lysine residues, <i>A. lyticus</i> LysC outperformed the two others with superior peptide identification, digestion efficiency, and protein coverage, especially at shorter digestion times. Our experiments using a combination of<i>A. lyticus</i>LysC and trypsin demonstrated the importance of employing LysC for significantly minimizing missed cleavage rates in tryptic digests, especially with regard to lysine-containing peptides. This study underscores <i>A. lyticus</i> LysC’s potential as an optimal choice for enhancing mass spectrometry-based proteomics.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":"25 2","pages":"1176–1183"},"PeriodicalIF":3.6,"publicationDate":"2025-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.jproteome.5c00872","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145802712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Bacillus subtilis is a Gram-positive bacterium widely used in biotechnology due to its efficient secretion systems. Among these, the twin-arginine (Tat) pathway facilitates the export of fully folded cofactor-containing proteins across the cytoplasmic membrane. The TatAyCy translocase, which is expressed constitutively, is key to this process. Previous studies showed that this translocase not only consists of the TatAy and TatCy subunits, but that it also recruits the LiaH protein upon overexpression. Presumably, the recruitment of LiaH represents an intrinsic protective mechanism against the potentially detrimental effects of facilitating the membrane passage of large, fully folded proteins. However, to date the full spectrum of physiological consequences of protein translocation via TatAyCy has remained elusive. In this study, we employed a 14N/15N metabolic labeling approach combined with subcellular fractionation to quantitatively analyze proteomic changes in the cytoplasm, membrane, and extracellular milieu upon TatAyCy overexpression. Our findings show that high-level TatAyCy expression leads to a prolonged vegetative state and disrupts key cellular processes, including genetic competence, motility, chemotaxis, and biofilm formation. Notably, arginine metabolism emerges as a central factor in the cellular adaptation to TatAyCy-induced stress.
{"title":"Physiological Consequences of Overexpression of a Twin-Arginine Translocase in Bacillus subtilis Revealed by 14N/15N Labeling","authors":"Margarita Bernal-Cabas, , , Minia Antelo-Varela, , , Bimal Prajapati, , , Tobias Schilling, , , Marina López-Álvarez, , , Stefano Grasso, , , Sandra Maaβ, , , Andreas Otto, , , Girbe Buist, , , Dörte Becher, , and , Jan Maarten van Dijl*, ","doi":"10.1021/acs.jproteome.5c00787","DOIUrl":"10.1021/acs.jproteome.5c00787","url":null,"abstract":"<p ><i>Bacillus subtilis</i> is a Gram-positive bacterium widely used in biotechnology due to its efficient secretion systems. Among these, the twin-arginine (Tat) pathway facilitates the export of fully folded cofactor-containing proteins across the cytoplasmic membrane. The TatAyCy translocase, which is expressed constitutively, is key to this process. Previous studies showed that this translocase not only consists of the TatAy and TatCy subunits, but that it also recruits the LiaH protein upon overexpression. Presumably, the recruitment of LiaH represents an intrinsic protective mechanism against the potentially detrimental effects of facilitating the membrane passage of large, fully folded proteins. However, to date the full spectrum of physiological consequences of protein translocation via TatAyCy has remained elusive. In this study, we employed a <sup>14</sup>N/<sup>15</sup>N metabolic labeling approach combined with subcellular fractionation to quantitatively analyze proteomic changes in the cytoplasm, membrane, and extracellular milieu upon TatAyCy overexpression. Our findings show that high-level TatAyCy expression leads to a prolonged vegetative state and disrupts key cellular processes, including genetic competence, motility, chemotaxis, and biofilm formation. Notably, arginine metabolism emerges as a central factor in the cellular adaptation to TatAyCy-induced stress.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":"25 2","pages":"852–868"},"PeriodicalIF":3.6,"publicationDate":"2025-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145802646","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}