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Automatic 1D (1)H NMR Metabolite Quantification for Bioreactor Monitoring

High-throughput metabolomics can be used to optimize cell growth for enhanced production or for monitoring cell health in bioreactors. It has applications in cell and gene therapies, vaccines, biologics, and bioprocessing. NMR metabolomics is a method that allows for fast and reliable experimentatio...

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Autores principales: Wang, Roy Chih Chung, Campbell, David A., Green, James R., Čuperlović-Culf, Miroslava
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8001003/
https://www.ncbi.nlm.nih.gov/pubmed/33803350
http://dx.doi.org/10.3390/metabo11030157
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author Wang, Roy Chih Chung
Campbell, David A.
Green, James R.
Čuperlović-Culf, Miroslava
author_facet Wang, Roy Chih Chung
Campbell, David A.
Green, James R.
Čuperlović-Culf, Miroslava
author_sort Wang, Roy Chih Chung
collection PubMed
description High-throughput metabolomics can be used to optimize cell growth for enhanced production or for monitoring cell health in bioreactors. It has applications in cell and gene therapies, vaccines, biologics, and bioprocessing. NMR metabolomics is a method that allows for fast and reliable experimentation, requires only minimal sample preparation, and can be set up to take online measurements of cell media for bioreactor monitoring. This type of application requires a fully automated metabolite quantification method that can be linked with high-throughput measurements. In this review, we discuss the quantifier requirements in this type of application, the existing methods for NMR metabolomics quantification, and the performance of three existing quantifiers in the context of NMR metabolomics for bioreactor monitoring.
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spelling pubmed-80010032021-03-28 Automatic 1D (1)H NMR Metabolite Quantification for Bioreactor Monitoring Wang, Roy Chih Chung Campbell, David A. Green, James R. Čuperlović-Culf, Miroslava Metabolites Review High-throughput metabolomics can be used to optimize cell growth for enhanced production or for monitoring cell health in bioreactors. It has applications in cell and gene therapies, vaccines, biologics, and bioprocessing. NMR metabolomics is a method that allows for fast and reliable experimentation, requires only minimal sample preparation, and can be set up to take online measurements of cell media for bioreactor monitoring. This type of application requires a fully automated metabolite quantification method that can be linked with high-throughput measurements. In this review, we discuss the quantifier requirements in this type of application, the existing methods for NMR metabolomics quantification, and the performance of three existing quantifiers in the context of NMR metabolomics for bioreactor monitoring. MDPI 2021-03-09 /pmc/articles/PMC8001003/ /pubmed/33803350 http://dx.doi.org/10.3390/metabo11030157 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ).
spellingShingle Review
Wang, Roy Chih Chung
Campbell, David A.
Green, James R.
Čuperlović-Culf, Miroslava
Automatic 1D (1)H NMR Metabolite Quantification for Bioreactor Monitoring
title Automatic 1D (1)H NMR Metabolite Quantification for Bioreactor Monitoring
title_full Automatic 1D (1)H NMR Metabolite Quantification for Bioreactor Monitoring
title_fullStr Automatic 1D (1)H NMR Metabolite Quantification for Bioreactor Monitoring
title_full_unstemmed Automatic 1D (1)H NMR Metabolite Quantification for Bioreactor Monitoring
title_short Automatic 1D (1)H NMR Metabolite Quantification for Bioreactor Monitoring
title_sort automatic 1d (1)h nmr metabolite quantification for bioreactor monitoring
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8001003/
https://www.ncbi.nlm.nih.gov/pubmed/33803350
http://dx.doi.org/10.3390/metabo11030157
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