Dumei Ma, Yongqi Wang, Jiacheng Ye, Chao Xin, Chuan-Fan Ding, Yinghua Yan
{"title":"利用mof衍生的双金属纳米立方杂交纳米片精确检测碳青霉烯耐药和高致病性肺炎克雷伯菌","authors":"Dumei Ma, Yongqi Wang, Jiacheng Ye, Chao Xin, Chuan-Fan Ding, Yinghua Yan","doi":"10.1021/acs.analchem.5c00509","DOIUrl":null,"url":null,"abstract":"Carbapenem resistance and hypervirulence represent two distinct evolutionary pathways in <i>Klebsiella pneumoniae</i>, posing significant challenges in clinical settings. Of particular concern are convergent strains that combine both traits, complicating timely diagnosis and treatment. Herein, we present a novel MOF-derived bimetallic nanocube hybrid nanosheet (denoted Pt-G@Cu<sub>5</sub>Zn<sub>8</sub>C@Au) designed to enhance laser desorption/ionization mass spectrometry (LDI-MS) in distinguishing convergent strains from other variants. The novel material, synthesized through the pyrolysis of pristine MOFs, features uniformly distributed Cu and Zn synergistic metal sites within the carbon matrix, addressing critical limitations of current nanomatrices for in situ extraction of metabolic fingerprints from microbial cells, such as limited sensitivity (e.g., amorphous silicon, TiO<sub>2</sub>, and metal nanoparticles) or relatively weak conductivity and stability (MOF-based materials). Utilizing this advanced matrix, the metabolic fingerprints of 248 <i>K. pneumoniae</i> isolates were rapidly extracted, identifying 23 top VIP-score peaks as potential biomarkers for differentiating convergent strains from their variants. Combined with machine learning, the prediction model achieved 100% accuracy in distinguishing convergent strains from carbapenem-sensitive isolates (CS_cKP) or hypervirulent isolates (hvKP) using the SVM model, while achieving 78.26% accuracy in differentiating them from carbapenem-resistant isolates (CR_cKP) with the KNN/NB models. These findings highlight the high accuracy and efficacy of our assay in distinguishing convergent strains from their variants.","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"44 1","pages":""},"PeriodicalIF":6.7000,"publicationDate":"2025-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Precise Detection of Carbapenem-Resistant and Hypervirulent Klebsiella pneumoniae Using MOF-Derived Bimetallic Nanocube Hybrid Nanosheet\",\"authors\":\"Dumei Ma, Yongqi Wang, Jiacheng Ye, Chao Xin, Chuan-Fan Ding, Yinghua Yan\",\"doi\":\"10.1021/acs.analchem.5c00509\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Carbapenem resistance and hypervirulence represent two distinct evolutionary pathways in <i>Klebsiella pneumoniae</i>, posing significant challenges in clinical settings. Of particular concern are convergent strains that combine both traits, complicating timely diagnosis and treatment. Herein, we present a novel MOF-derived bimetallic nanocube hybrid nanosheet (denoted Pt-G@Cu<sub>5</sub>Zn<sub>8</sub>C@Au) designed to enhance laser desorption/ionization mass spectrometry (LDI-MS) in distinguishing convergent strains from other variants. The novel material, synthesized through the pyrolysis of pristine MOFs, features uniformly distributed Cu and Zn synergistic metal sites within the carbon matrix, addressing critical limitations of current nanomatrices for in situ extraction of metabolic fingerprints from microbial cells, such as limited sensitivity (e.g., amorphous silicon, TiO<sub>2</sub>, and metal nanoparticles) or relatively weak conductivity and stability (MOF-based materials). Utilizing this advanced matrix, the metabolic fingerprints of 248 <i>K. pneumoniae</i> isolates were rapidly extracted, identifying 23 top VIP-score peaks as potential biomarkers for differentiating convergent strains from their variants. Combined with machine learning, the prediction model achieved 100% accuracy in distinguishing convergent strains from carbapenem-sensitive isolates (CS_cKP) or hypervirulent isolates (hvKP) using the SVM model, while achieving 78.26% accuracy in differentiating them from carbapenem-resistant isolates (CR_cKP) with the KNN/NB models. These findings highlight the high accuracy and efficacy of our assay in distinguishing convergent strains from their variants.\",\"PeriodicalId\":27,\"journal\":{\"name\":\"Analytical Chemistry\",\"volume\":\"44 1\",\"pages\":\"\"},\"PeriodicalIF\":6.7000,\"publicationDate\":\"2025-05-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Analytical Chemistry\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://doi.org/10.1021/acs.analchem.5c00509\",\"RegionNum\":1,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, ANALYTICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Analytical Chemistry","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1021/acs.analchem.5c00509","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, ANALYTICAL","Score":null,"Total":0}
Precise Detection of Carbapenem-Resistant and Hypervirulent Klebsiella pneumoniae Using MOF-Derived Bimetallic Nanocube Hybrid Nanosheet
Carbapenem resistance and hypervirulence represent two distinct evolutionary pathways in Klebsiella pneumoniae, posing significant challenges in clinical settings. Of particular concern are convergent strains that combine both traits, complicating timely diagnosis and treatment. Herein, we present a novel MOF-derived bimetallic nanocube hybrid nanosheet (denoted Pt-G@Cu5Zn8C@Au) designed to enhance laser desorption/ionization mass spectrometry (LDI-MS) in distinguishing convergent strains from other variants. The novel material, synthesized through the pyrolysis of pristine MOFs, features uniformly distributed Cu and Zn synergistic metal sites within the carbon matrix, addressing critical limitations of current nanomatrices for in situ extraction of metabolic fingerprints from microbial cells, such as limited sensitivity (e.g., amorphous silicon, TiO2, and metal nanoparticles) or relatively weak conductivity and stability (MOF-based materials). Utilizing this advanced matrix, the metabolic fingerprints of 248 K. pneumoniae isolates were rapidly extracted, identifying 23 top VIP-score peaks as potential biomarkers for differentiating convergent strains from their variants. Combined with machine learning, the prediction model achieved 100% accuracy in distinguishing convergent strains from carbapenem-sensitive isolates (CS_cKP) or hypervirulent isolates (hvKP) using the SVM model, while achieving 78.26% accuracy in differentiating them from carbapenem-resistant isolates (CR_cKP) with the KNN/NB models. These findings highlight the high accuracy and efficacy of our assay in distinguishing convergent strains from their variants.
期刊介绍:
Analytical Chemistry, a peer-reviewed research journal, focuses on disseminating new and original knowledge across all branches of analytical chemistry. Fundamental articles may explore general principles of chemical measurement science and need not directly address existing or potential analytical methodology. They can be entirely theoretical or report experimental results. Contributions may cover various phases of analytical operations, including sampling, bioanalysis, electrochemistry, mass spectrometry, microscale and nanoscale systems, environmental analysis, separations, spectroscopy, chemical reactions and selectivity, instrumentation, imaging, surface analysis, and data processing. Papers discussing known analytical methods should present a significant, original application of the method, a notable improvement, or results on an important analyte.