A rapid, simple and sensitive microfluidic chip electrophoresis mass spectrometry method for monitoring amino acids in cell culture media

Silva, Meire Ribeiro da; Zaborowska, Izabela; Carillo, Sara; Bones, Jonathan

doi:10.1016/j.chroma.2021.462336

Cited by 16 publications

(6 citation statements)

References 32 publications

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“…In the regular mode, the determinants were tyrosine, arginine, and glutamine. The abundance of amino acids was reported to be related to cell viability 59 , as an excess amount was reported to accumulate toxic metabolites 60 . Metabolisms of the three amino acids were found to produce ammonia, 4-hydroxyphenylpyruvate, and dimethylarginine 61 , which are toxic to cells 62 , 63 and cause growth inhibition 64 or cell apoptosis 65 , 66 .…”

Section: Discussionmentioning

confidence: 99%

Employing active learning in the optimization of culture medium for mammalian cells

2023

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Medium optimization is a crucial step during cell culture for biopharmaceutics and regenerative medicine; however, this step remains challenging, as both media and cells are highly complex systems. Here, we addressed this issue by employing active learning. Specifically, we introduced machine learning to cell culture experiments to optimize culture medium. The cell line HeLa-S3 and the gradient-boosting decision tree algorithm were used to find optimized media as pilot studies. To acquire the training data, cell culture was performed in a large variety of medium combinations. The cellular NAD(P)H abundance, represented as A450, was used to indicate the goodness of culture media. In active learning, regular and time-saving modes were developed using culture data at 168 h and 96 h, respectively. Both modes successfully fine-tuned 29 components to generate a medium for improved cell culture. Intriguingly, the two modes provided different predictions for the concentrations of vitamins and amino acids, and a significant decrease was commonly predicted for fetal bovine serum (FBS) compared to the commercial medium. In addition, active learning-assisted medium optimization significantly increased the cellular concentration of NAD(P)H, an active chemical with a constant abundance in living cells. Our study demonstrated the efficiency and practicality of active learning for medium optimization and provided valuable information for employing machine learning technology in cell biology experiments.

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Section: Discussionmentioning

confidence: 99%

Employing active learning in the optimization of culture medium for mammalian cells

2023

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“…In the regular mode, tyrosine, arginine, and glutamine were the determinants. The abundance of amino acids was related to cell viability 60 , as the excess amount could accumulate toxic metabolites 61 . Metabolisms of the three amino acids produced ammonia, 4-Hydroxyphenylpyruvate, and dimethylarginine 62 , which were toxic to cells 63, 64 and caused growth inhibition 65 or cell apoptosis 66, 67 .…”

Section: Discussionmentioning

confidence: 99%

Employing active learning in the optimization of culture medium for mammalian cells

Hashizume

Ozawa

Ying

2022

Preprint

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Medium optimization is a crucial step of cell culture for biopharmaceutics and regeneration medicine. It remains challenging, as both media and cells are highly complex systems. To address the issue, we tried active learning to fine-tune the culture medium by combining the high-throughput assay and machine learning. As a pilot study, the cell line HeLa-S3 and the gradient-boosting decision tree algorithm were used. The regular and time-saving approaches were developed, and both successfully fine-tuned 29 components to achieve improved cell culture than the original medium. The fine-tuned media showed a significant decrease in fetal bovine serum and the differentiation in vitamins and amino acids. Unexpectedly, the medium optimization raised the cellular NAD(P)H abundance but not the cell concentration owing to the conventional method used for cell culture assay. Our study demonstrated the efficiency of active learning for medium optimization and provided valuable hints for employing machine learning in cell culture.

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“…With the introduction of microfluidic chips CE‐MS [207], 16 AAs were separated in 3 min. The migration time repeatability of AAs was very stable, with RSD values below 1.0%.…”

Section: Approaches Without Derivatizationmentioning

confidence: 99%

“…Based on real samples, depletion analysis of AAs in cell growth media was performed in less than 3 min, and baseline separations of isomers were achieved. The signal-to-noise ratio had increased by an average of 28 times compared to previous studies, and the peak height by a factor of 2.6 compared to previous studies.With the introduction of microfluidic chips CE-MS[207], 16 AAs were separated in 3 min. The migration time repeatability of AAs was very stable, with RSD values below 1.0%.…”

mentioning

confidence: 99%

Overview of chromatographic and electrophoretic methods for the determination of branched‐chain amino acids

Yin

Adams

Schepdael

2023

J of Separation Science

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The significance of branched‐chain amino acids in diseases was clearly shown over the years. This review aims to describe the available techniques for their analytical determination. The article provides examples of the use of various analytical methods. The methods are divided into two categories: derivatization and non‐derivatization approaches. Separation is achieved through different chromatography or capillary electrophoresis techniques and can be combined with different detectors such as flame ionization, ultraviolet, fluorescence, and mass spectrometry. It compares the application of various derivatization reagents or detection as such for different detectors.

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A rapid, simple and sensitive microfluidic chip electrophoresis mass spectrometry method for monitoring amino acids in cell culture media

Cited by 16 publications

References 32 publications

Employing active learning in the optimization of culture medium for mammalian cells

Employing active learning in the optimization of culture medium for mammalian cells

Employing active learning in the optimization of culture medium for mammalian cells

Overview of chromatographic and electrophoretic methods for the determination of branched‐chain amino acids

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