{"title":"工业生物过程监测中高通量代谢物分析的定量1H NMR优化。","authors":"Yingting Shi, Yuxiang Wan, Yiru Wang, Kerui Fang, Jiayu Yang, Yuting Lu, Xinyuan Xie, Jianyang Pan, Dong Gao, Haibin Wang, Haibin Qu","doi":"10.1007/s00216-025-05845-9","DOIUrl":null,"url":null,"abstract":"<p><p>Quantitative <sup>1</sup>H NMR (<sup>1</sup>H qNMR) is an ideal tool for bioprocess monitoring because it can comprehensively detect and quantify diverse metabolites that significantly influence bioprocess performance. However, the long experiment time associated with the <sup>1</sup>H qNMR, due to the long longitudinal relaxation time (T1) of some metabolites, does not meet the requirements for high-throughput analysis. We developed a high-throughput <sup>1</sup>H qNMR method for bioprocess analysis using a short relaxation delay (D1) to reduce analytical time and a correction factor (k) to compensate for incomplete relaxation. A total of 27 metabolites were quantified using spectral deconvolution via a peak fitting algorithm and MCR-ALS. Methodological validation results indicated that the precision and accuracy of the developed qNMR method were consistently high across different D1 values, with LOQs ranging from 0.008 to 0.13 mM and LODs ranging from 0.024 to 0.38 mM. Notably, a longer D1 value generally resulted in lower LODs and LOQs for most metabolites. A D1 value of 4 s was optimal for balancing analysis time and performance. The method is broadly applicable for bioprocess monitoring and control, offering valuable guidance for optimizing CHO cell culture processes and improving yield.</p>","PeriodicalId":462,"journal":{"name":"Analytical and Bioanalytical Chemistry","volume":" ","pages":""},"PeriodicalIF":3.8000,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Quantitative <sup>1</sup>H NMR optimization for high-throughput metabolite analysis in industrial bioprocess monitoring.\",\"authors\":\"Yingting Shi, Yuxiang Wan, Yiru Wang, Kerui Fang, Jiayu Yang, Yuting Lu, Xinyuan Xie, Jianyang Pan, Dong Gao, Haibin Wang, Haibin Qu\",\"doi\":\"10.1007/s00216-025-05845-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Quantitative <sup>1</sup>H NMR (<sup>1</sup>H qNMR) is an ideal tool for bioprocess monitoring because it can comprehensively detect and quantify diverse metabolites that significantly influence bioprocess performance. However, the long experiment time associated with the <sup>1</sup>H qNMR, due to the long longitudinal relaxation time (T1) of some metabolites, does not meet the requirements for high-throughput analysis. We developed a high-throughput <sup>1</sup>H qNMR method for bioprocess analysis using a short relaxation delay (D1) to reduce analytical time and a correction factor (k) to compensate for incomplete relaxation. A total of 27 metabolites were quantified using spectral deconvolution via a peak fitting algorithm and MCR-ALS. Methodological validation results indicated that the precision and accuracy of the developed qNMR method were consistently high across different D1 values, with LOQs ranging from 0.008 to 0.13 mM and LODs ranging from 0.024 to 0.38 mM. Notably, a longer D1 value generally resulted in lower LODs and LOQs for most metabolites. A D1 value of 4 s was optimal for balancing analysis time and performance. The method is broadly applicable for bioprocess monitoring and control, offering valuable guidance for optimizing CHO cell culture processes and improving yield.</p>\",\"PeriodicalId\":462,\"journal\":{\"name\":\"Analytical and Bioanalytical Chemistry\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":3.8000,\"publicationDate\":\"2025-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Analytical and Bioanalytical Chemistry\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://doi.org/10.1007/s00216-025-05845-9\",\"RegionNum\":2,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOCHEMICAL RESEARCH METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Analytical and Bioanalytical Chemistry","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1007/s00216-025-05845-9","RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
Quantitative 1H NMR optimization for high-throughput metabolite analysis in industrial bioprocess monitoring.
Quantitative 1H NMR (1H qNMR) is an ideal tool for bioprocess monitoring because it can comprehensively detect and quantify diverse metabolites that significantly influence bioprocess performance. However, the long experiment time associated with the 1H qNMR, due to the long longitudinal relaxation time (T1) of some metabolites, does not meet the requirements for high-throughput analysis. We developed a high-throughput 1H qNMR method for bioprocess analysis using a short relaxation delay (D1) to reduce analytical time and a correction factor (k) to compensate for incomplete relaxation. A total of 27 metabolites were quantified using spectral deconvolution via a peak fitting algorithm and MCR-ALS. Methodological validation results indicated that the precision and accuracy of the developed qNMR method were consistently high across different D1 values, with LOQs ranging from 0.008 to 0.13 mM and LODs ranging from 0.024 to 0.38 mM. Notably, a longer D1 value generally resulted in lower LODs and LOQs for most metabolites. A D1 value of 4 s was optimal for balancing analysis time and performance. The method is broadly applicable for bioprocess monitoring and control, offering valuable guidance for optimizing CHO cell culture processes and improving yield.
期刊介绍:
Analytical and Bioanalytical Chemistry’s mission is the rapid publication of excellent and high-impact research articles on fundamental and applied topics of analytical and bioanalytical measurement science. Its scope is broad, and ranges from novel measurement platforms and their characterization to multidisciplinary approaches that effectively address important scientific problems. The Editors encourage submissions presenting innovative analytical research in concept, instrumentation, methods, and/or applications, including: mass spectrometry, spectroscopy, and electroanalysis; advanced separations; analytical strategies in “-omics” and imaging, bioanalysis, and sampling; miniaturized devices, medical diagnostics, sensors; analytical characterization of nano- and biomaterials; chemometrics and advanced data analysis.