Xiangyu Pan, Zeying Zhang*, Yang Yun, Xu Zhang, Yali Sun, Zixuan Zhang, Huadong Wang, Xu Yang, Zhiyu Tan, Yaqi Yang, Hongfei Xie, Bogdan Bogdanov, Georgii Zmaga, Pavel Senyushkin, Xuemei Wei, Yanlin Song* and Meng Su*,
{"title":"机器学习辅助高通量鉴定和定量印制异链蛋白质生物标记物。","authors":"Xiangyu Pan, Zeying Zhang*, Yang Yun, Xu Zhang, Yali Sun, Zixuan Zhang, Huadong Wang, Xu Yang, Zhiyu Tan, Yaqi Yang, Hongfei Xie, Bogdan Bogdanov, Georgii Zmaga, Pavel Senyushkin, Xuemei Wei, Yanlin Song* and Meng Su*, ","doi":"10.1021/jacs.4c04460","DOIUrl":null,"url":null,"abstract":"<p >Advanced in vitro diagnosis technologies are highly desirable in early detection, prognosis, and progression monitoring of diseases. Here, we engineer a multiplex protein biosensing strategy based on the tunable liquid confinement self-assembly of multi-material heterochains, which show improved sensitivity, throughput, and accuracy compared to standard ELISA kits. By controlling the material combination and the number of ligand nanoparticles (NPs), we observe robust near-field enhancement as well as both strong electromagnetic resonance in polymer–semiconductor heterochains. In particular, their optical signals show a linear response to the coordination number of the semiconductor NPs in a wide range. Accordingly, a visible nanophotonic biosensor is developed by functionalizing antibodies on central polymer chains that can identify target proteins attached to semiconductor NPs. This allows for the specific detection of multiple protein biomarkers from healthy people and pancreatic cancer patients in one step with an ultralow detection limit (1 pg/mL). Furthermore, rapid and high-throughput quantification of protein expression levels in diverse clinical samples such as buffer, urine, and serum is achieved by combining a neural network algorithm, with an average accuracy of 97.3%. This work demonstrates that the heterochain-based biosensor is an exemplary candidate for constructing next-generation diagnostic tools and suitable for many clinical settings.</p>","PeriodicalId":49,"journal":{"name":"Journal of the American Chemical Society","volume":null,"pages":null},"PeriodicalIF":14.4000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Machine Learning-Assisted High-Throughput Identification and Quantification of Protein Biomarkers with Printed Heterochains\",\"authors\":\"Xiangyu Pan, Zeying Zhang*, Yang Yun, Xu Zhang, Yali Sun, Zixuan Zhang, Huadong Wang, Xu Yang, Zhiyu Tan, Yaqi Yang, Hongfei Xie, Bogdan Bogdanov, Georgii Zmaga, Pavel Senyushkin, Xuemei Wei, Yanlin Song* and Meng Su*, \",\"doi\":\"10.1021/jacs.4c04460\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p >Advanced in vitro diagnosis technologies are highly desirable in early detection, prognosis, and progression monitoring of diseases. Here, we engineer a multiplex protein biosensing strategy based on the tunable liquid confinement self-assembly of multi-material heterochains, which show improved sensitivity, throughput, and accuracy compared to standard ELISA kits. By controlling the material combination and the number of ligand nanoparticles (NPs), we observe robust near-field enhancement as well as both strong electromagnetic resonance in polymer–semiconductor heterochains. In particular, their optical signals show a linear response to the coordination number of the semiconductor NPs in a wide range. Accordingly, a visible nanophotonic biosensor is developed by functionalizing antibodies on central polymer chains that can identify target proteins attached to semiconductor NPs. This allows for the specific detection of multiple protein biomarkers from healthy people and pancreatic cancer patients in one step with an ultralow detection limit (1 pg/mL). Furthermore, rapid and high-throughput quantification of protein expression levels in diverse clinical samples such as buffer, urine, and serum is achieved by combining a neural network algorithm, with an average accuracy of 97.3%. 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Machine Learning-Assisted High-Throughput Identification and Quantification of Protein Biomarkers with Printed Heterochains
Advanced in vitro diagnosis technologies are highly desirable in early detection, prognosis, and progression monitoring of diseases. Here, we engineer a multiplex protein biosensing strategy based on the tunable liquid confinement self-assembly of multi-material heterochains, which show improved sensitivity, throughput, and accuracy compared to standard ELISA kits. By controlling the material combination and the number of ligand nanoparticles (NPs), we observe robust near-field enhancement as well as both strong electromagnetic resonance in polymer–semiconductor heterochains. In particular, their optical signals show a linear response to the coordination number of the semiconductor NPs in a wide range. Accordingly, a visible nanophotonic biosensor is developed by functionalizing antibodies on central polymer chains that can identify target proteins attached to semiconductor NPs. This allows for the specific detection of multiple protein biomarkers from healthy people and pancreatic cancer patients in one step with an ultralow detection limit (1 pg/mL). Furthermore, rapid and high-throughput quantification of protein expression levels in diverse clinical samples such as buffer, urine, and serum is achieved by combining a neural network algorithm, with an average accuracy of 97.3%. This work demonstrates that the heterochain-based biosensor is an exemplary candidate for constructing next-generation diagnostic tools and suitable for many clinical settings.
期刊介绍:
The flagship journal of the American Chemical Society, known as the Journal of the American Chemical Society (JACS), has been a prestigious publication since its establishment in 1879. It holds a preeminent position in the field of chemistry and related interdisciplinary sciences. JACS is committed to disseminating cutting-edge research papers, covering a wide range of topics, and encompasses approximately 19,000 pages of Articles, Communications, and Perspectives annually. With a weekly publication frequency, JACS plays a vital role in advancing the field of chemistry by providing essential research.