Zheng Li, Xiaohui Lu, Zhiyang Zhang, Shuoyang Yan, Yunli Yang
{"title":"利用多路复用表面增强拉曼散射读数的图案化纳米棒传感器阵列实现尿液挥发性代谢物的快速指纹识别和苯丙酮尿症的床旁诊断","authors":"Zheng Li, Xiaohui Lu, Zhiyang Zhang, Shuoyang Yan, Yunli Yang","doi":"10.1021/acs.analchem.4c02822","DOIUrl":null,"url":null,"abstract":"Phenylketonuria (PKU) is one of the most common genetic metabolic diseases, especially among newborns. Traditional clinical examination of newborn blood samples for PKU is invasive, laborious, and limited to hospitals and healthcare facilities. We reported herein a SERS-based sensor array with three thiophenolic nanoreceptors built on a patterned nanorod vertical array for rapid and inexpensive detection of characteristic volatile biomarkers indicative of PKU in the urine and accurate classification of newborn baby patients all performed on a hand-held SERS spectrophotometer. The well-ordered array was generated from the volatility-driven assembly of gold nanorods (AuNRs) into an upright and closely packed hexagonal configuration. The uniformly distributed nanowells between AuNRs offered an intense and aspect-ratio-dependent plasmonic field for the molecular enhancement of SERS outputs. The SERS-based detector was integrated into a test chip for regular monitoring of volatile phenylketone bodies in the spiked solution or patients’ urine within 5 min, allowing the quantification of a wide variety of normal or abnormal metabolites at their physiologically relevant concentration range. The detection limits for common biomarkers of PKU, including phenylpyruvic acid, 4-hydroxyphenylacetic acid, and phenylacetic acid, were at a few μM and well below the diagnostic thresholds. Moreover, the volatile headspace mixtures from a given urine sample could be fingerprinted by the sensor array and discriminated using machine-learning algorithms. Ultimately, the discrimination of baby patients among 26 cases of mild and classic PKU phenotypes and 17 cases of healthy volunteers could be realized with an overall accuracy of 97%. This hand-held SERS platform plays a pivotal role in advancing healthcare applications in quick screening of neonatal PKU through a facile urinary vapor test.","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"10 1","pages":""},"PeriodicalIF":6.7000,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Rapid Fingerprinting of Urinary Volatile Metabolites and Point-of-Care Diagnosis of Phenylketonuria on a Patterned Nanorod Sensor Array with Multiplexed Surface-Enhanced Raman Scattering Readouts\",\"authors\":\"Zheng Li, Xiaohui Lu, Zhiyang Zhang, Shuoyang Yan, Yunli Yang\",\"doi\":\"10.1021/acs.analchem.4c02822\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Phenylketonuria (PKU) is one of the most common genetic metabolic diseases, especially among newborns. Traditional clinical examination of newborn blood samples for PKU is invasive, laborious, and limited to hospitals and healthcare facilities. We reported herein a SERS-based sensor array with three thiophenolic nanoreceptors built on a patterned nanorod vertical array for rapid and inexpensive detection of characteristic volatile biomarkers indicative of PKU in the urine and accurate classification of newborn baby patients all performed on a hand-held SERS spectrophotometer. The well-ordered array was generated from the volatility-driven assembly of gold nanorods (AuNRs) into an upright and closely packed hexagonal configuration. The uniformly distributed nanowells between AuNRs offered an intense and aspect-ratio-dependent plasmonic field for the molecular enhancement of SERS outputs. The SERS-based detector was integrated into a test chip for regular monitoring of volatile phenylketone bodies in the spiked solution or patients’ urine within 5 min, allowing the quantification of a wide variety of normal or abnormal metabolites at their physiologically relevant concentration range. The detection limits for common biomarkers of PKU, including phenylpyruvic acid, 4-hydroxyphenylacetic acid, and phenylacetic acid, were at a few μM and well below the diagnostic thresholds. Moreover, the volatile headspace mixtures from a given urine sample could be fingerprinted by the sensor array and discriminated using machine-learning algorithms. Ultimately, the discrimination of baby patients among 26 cases of mild and classic PKU phenotypes and 17 cases of healthy volunteers could be realized with an overall accuracy of 97%. This hand-held SERS platform plays a pivotal role in advancing healthcare applications in quick screening of neonatal PKU through a facile urinary vapor test.\",\"PeriodicalId\":27,\"journal\":{\"name\":\"Analytical Chemistry\",\"volume\":\"10 1\",\"pages\":\"\"},\"PeriodicalIF\":6.7000,\"publicationDate\":\"2024-08-29\",\"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.4c02822\",\"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.4c02822","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, ANALYTICAL","Score":null,"Total":0}
Rapid Fingerprinting of Urinary Volatile Metabolites and Point-of-Care Diagnosis of Phenylketonuria on a Patterned Nanorod Sensor Array with Multiplexed Surface-Enhanced Raman Scattering Readouts
Phenylketonuria (PKU) is one of the most common genetic metabolic diseases, especially among newborns. Traditional clinical examination of newborn blood samples for PKU is invasive, laborious, and limited to hospitals and healthcare facilities. We reported herein a SERS-based sensor array with three thiophenolic nanoreceptors built on a patterned nanorod vertical array for rapid and inexpensive detection of characteristic volatile biomarkers indicative of PKU in the urine and accurate classification of newborn baby patients all performed on a hand-held SERS spectrophotometer. The well-ordered array was generated from the volatility-driven assembly of gold nanorods (AuNRs) into an upright and closely packed hexagonal configuration. The uniformly distributed nanowells between AuNRs offered an intense and aspect-ratio-dependent plasmonic field for the molecular enhancement of SERS outputs. The SERS-based detector was integrated into a test chip for regular monitoring of volatile phenylketone bodies in the spiked solution or patients’ urine within 5 min, allowing the quantification of a wide variety of normal or abnormal metabolites at their physiologically relevant concentration range. The detection limits for common biomarkers of PKU, including phenylpyruvic acid, 4-hydroxyphenylacetic acid, and phenylacetic acid, were at a few μM and well below the diagnostic thresholds. Moreover, the volatile headspace mixtures from a given urine sample could be fingerprinted by the sensor array and discriminated using machine-learning algorithms. Ultimately, the discrimination of baby patients among 26 cases of mild and classic PKU phenotypes and 17 cases of healthy volunteers could be realized with an overall accuracy of 97%. This hand-held SERS platform plays a pivotal role in advancing healthcare applications in quick screening of neonatal PKU through a facile urinary vapor test.
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.