Evaluation and optimization of quantitative analysis of cofactors from yeast by liquid chromatography/mass spectrometry
- Authors
- Kim, Jungyeon; Jung, Inho; Cheong, Yu Eun; Kim, Kyoung Heon
- Issue Date
- 8-6월-2022
- Publisher
- ELSEVIER
- Keywords
- Cofactors; Liquid chromatography; mass spectrometry; Metabolome; Yeast; Saccharomyces cerevisiae
- Citation
- ANALYTICA CHIMICA ACTA, v.1211
- Indexed
- SCIE
SCOPUS
- Journal Title
- ANALYTICA CHIMICA ACTA
- Volume
- 1211
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/143406
- DOI
- 10.1016/j.aca.2022.339890
- ISSN
- 0003-2670
- Abstract
- Cofactors play pivotal roles in catabolism and anabolism in all living organisms. Many studies have investigated the concentration of cofactors in living organisms to understand their metabolic status, which can be used to produce valuable chemicals or to understand the pathophysiology of diseases. Among various analytical platforms, liquid chromatography/mass spectrometry (LC/MS) is the most frequently used method for the quantification of cofactors. Several studies have reported various analytical methods for cofactors using LC/MS. However, the lack of optimal LC/MS methods makes it challenging to analyze various cofactors simultaneously. In addition, the method of extracting cofactors from cells needs to be optimized because conventional protocols probably have low extraction efficiency, which makes it difficult to reflect the actual concentration of cofactors in cells. In this study, we systematically compared various analytical methods and suggested optimal methods for the analysis of cofactors using LC/MS. In addition, we systematically compared quenching methods and extraction solvents and suggested optimal methods for the extraction of cofactors from Saccharomyces cerevisiae. The optimized methods can be used as standard protocols for LC/MS analysis and the extraction of cofactors from S. cerevisiae.
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- Appears in
Collections - College of Life Sciences and Biotechnology > Division of Food Bioscience and Technology > 1. Journal Articles
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