Yiqing Cao, Shuai Liao, Chunhui Deng, Haotian Qin, Yan Li
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By utilizing two distinct but synergistic affinity mechanisms-the immune affinity between CD63 aptamer and exosomal CD63 proteins, and hydrophobic interactions between the DSPE and the exosomal lipids-pH-BiAN can enable efficient and specific exosome separation. Moreover, during the urine exosome capture procedure, the pH-BiAN outperforms conventional solid exosome separation materials by remaining soluble in the urine sample, significantly enhancing mass transfer and contact efficiency. After exosome capture, pH-BiAN can quickly aggregate and convert to solid upon pH adjustment, allowing for easy centrifugation separation. Afterwards, multiple machine learning models were established by combining liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS) untargeted metabolomics for isolated exosomes, and the clinical accuracy of the training and test sets was more than 0.919, which could well distinguish early osteoarthritis patients from healthy people.</p>","PeriodicalId":435,"journal":{"name":"Talanta","volume":"283 ","pages":"127144"},"PeriodicalIF":5.6000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A pH-responsive phase-transition bi-affinity nanopolymer-assisted exosome metabolomics for early screening of osteoarthritis.\",\"authors\":\"Yiqing Cao, Shuai Liao, Chunhui Deng, Haotian Qin, Yan Li\",\"doi\":\"10.1016/j.talanta.2024.127144\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Exosomes, emerging as ideal non-invasive biomarkers for disease diagnosis and monitoring, have seldom been explored based on metabolite levels. In this study, we designed and synthesized a pH-responsive phase-transition bifunctional affinity nanopolymer (pH-BiAN) that could efficiently and homogeneously separate exosomes from urine. Specifically, poly-4-vinylpyridine (P4VP) was chosen as the pH-responsive polymer and simultaneously modified with two exosome-affinity components CD63 aptamer and distearoyl phosphoethanolamine (DSPE) through a one-step amide reaction at room temperature. By utilizing two distinct but synergistic affinity mechanisms-the immune affinity between CD63 aptamer and exosomal CD63 proteins, and hydrophobic interactions between the DSPE and the exosomal lipids-pH-BiAN can enable efficient and specific exosome separation. Moreover, during the urine exosome capture procedure, the pH-BiAN outperforms conventional solid exosome separation materials by remaining soluble in the urine sample, significantly enhancing mass transfer and contact efficiency. After exosome capture, pH-BiAN can quickly aggregate and convert to solid upon pH adjustment, allowing for easy centrifugation separation. 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A pH-responsive phase-transition bi-affinity nanopolymer-assisted exosome metabolomics for early screening of osteoarthritis.
Exosomes, emerging as ideal non-invasive biomarkers for disease diagnosis and monitoring, have seldom been explored based on metabolite levels. In this study, we designed and synthesized a pH-responsive phase-transition bifunctional affinity nanopolymer (pH-BiAN) that could efficiently and homogeneously separate exosomes from urine. Specifically, poly-4-vinylpyridine (P4VP) was chosen as the pH-responsive polymer and simultaneously modified with two exosome-affinity components CD63 aptamer and distearoyl phosphoethanolamine (DSPE) through a one-step amide reaction at room temperature. By utilizing two distinct but synergistic affinity mechanisms-the immune affinity between CD63 aptamer and exosomal CD63 proteins, and hydrophobic interactions between the DSPE and the exosomal lipids-pH-BiAN can enable efficient and specific exosome separation. Moreover, during the urine exosome capture procedure, the pH-BiAN outperforms conventional solid exosome separation materials by remaining soluble in the urine sample, significantly enhancing mass transfer and contact efficiency. After exosome capture, pH-BiAN can quickly aggregate and convert to solid upon pH adjustment, allowing for easy centrifugation separation. Afterwards, multiple machine learning models were established by combining liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS) untargeted metabolomics for isolated exosomes, and the clinical accuracy of the training and test sets was more than 0.919, which could well distinguish early osteoarthritis patients from healthy people.
期刊介绍:
Talanta provides a forum for the publication of original research papers, short communications, and critical reviews in all branches of pure and applied analytical chemistry. Papers are evaluated based on established guidelines, including the fundamental nature of the study, scientific novelty, substantial improvement or advantage over existing technology or methods, and demonstrated analytical applicability. Original research papers on fundamental studies, and on novel sensor and instrumentation developments, are encouraged. Novel or improved applications in areas such as clinical and biological chemistry, environmental analysis, geochemistry, materials science and engineering, and analytical platforms for omics development are welcome.
Analytical performance of methods should be determined, including interference and matrix effects, and methods should be validated by comparison with a standard method, or analysis of a certified reference material. Simple spiking recoveries may not be sufficient. The developed method should especially comprise information on selectivity, sensitivity, detection limits, accuracy, and reliability. However, applying official validation or robustness studies to a routine method or technique does not necessarily constitute novelty. Proper statistical treatment of the data should be provided. Relevant literature should be cited, including related publications by the authors, and authors should discuss how their proposed methodology compares with previously reported methods.