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Metabolomics profiling reveals differences in proliferation between tumorigenic and non-tumorigenic Madin-Darby canine kidney (MDCK) cells
BACKGROUND: Madin-Darby canine kidney (MDCK) cells are a cellular matrix in the production of influenza vaccines. The proliferation rate of MDCK cells is one of the critical factors that determine the vaccine production cycle. It is yet to be determined if there is a correlation between cell prolife...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10517658/ https://www.ncbi.nlm.nih.gov/pubmed/37744241 http://dx.doi.org/10.7717/peerj.16077 |
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author | Sun, Na Zhang, Yuchuan Dong, Jian Liu, Geng Liu, Zhenbin Wang, Jiamin Qiao, Zilin Zhang, Jiayou Duan, Kai Nian, Xuanxuan Ma, Zhongren Yang, Xiaoming |
author_facet | Sun, Na Zhang, Yuchuan Dong, Jian Liu, Geng Liu, Zhenbin Wang, Jiamin Qiao, Zilin Zhang, Jiayou Duan, Kai Nian, Xuanxuan Ma, Zhongren Yang, Xiaoming |
author_sort | Sun, Na |
collection | PubMed |
description | BACKGROUND: Madin-Darby canine kidney (MDCK) cells are a cellular matrix in the production of influenza vaccines. The proliferation rate of MDCK cells is one of the critical factors that determine the vaccine production cycle. It is yet to be determined if there is a correlation between cell proliferation and alterations in metabolic levels. This study aimed to explore the metabolic differences between MDCK cells with varying proliferative capabilities through the use of both untargeted and targeted metabolomics. METHODS: To investigate the metabolic discrepancies between adherent cell groups (MDCK-M60 and MDCK-CL23) and suspension cell groups (MDCK-XF04 and MDCK-XF06), untargeted and targeted metabolomics were used. Utilizing RT-qPCR analysis, the mRNA expressions of key metabolites enzymes were identified. RESULTS: An untargeted metabolomics study demonstrated the presence of 81 metabolites between MDCK-M60 and MDCK-CL23 cells, which were mainly affected by six pathways. An analysis of MDCK-XF04 and MDCK-XF06 cells revealed a total of 113 potential metabolites, the majority of which were impacted by ten pathways. Targeted metabolomics revealed a decrease in the levels of choline, tryptophan, and tyrosine in MDCK-CL23 cells, which was in accordance with the results of untargeted metabolomics. Additionally, MDCK-XF06 cells experienced a decrease in 5’-methylthioadenosine and tryptophan, while S-adenosylhomocysteine, kynurenine, 11Z-eicosenoic acid, 3-phosphoglycerate, glucose 6-phosphate, and phosphoenolpyruvic acid concentrations were increased. The mRNA levels of MAT1A, MAT2B, IDO1, and IDO2 in the two cell groups were all increased, suggesting that S-adenosylmethionine and tryptophan may have a significant role in cell metabolism. CONCLUSIONS: This research examines the effect of metabolite fluctuations on cell proliferation, thus offering a potential way to improve the rate of MDCK cell growth. |
format | Online Article Text |
id | pubmed-10517658 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-105176582023-09-24 Metabolomics profiling reveals differences in proliferation between tumorigenic and non-tumorigenic Madin-Darby canine kidney (MDCK) cells Sun, Na Zhang, Yuchuan Dong, Jian Liu, Geng Liu, Zhenbin Wang, Jiamin Qiao, Zilin Zhang, Jiayou Duan, Kai Nian, Xuanxuan Ma, Zhongren Yang, Xiaoming PeerJ Bioinformatics BACKGROUND: Madin-Darby canine kidney (MDCK) cells are a cellular matrix in the production of influenza vaccines. The proliferation rate of MDCK cells is one of the critical factors that determine the vaccine production cycle. It is yet to be determined if there is a correlation between cell proliferation and alterations in metabolic levels. This study aimed to explore the metabolic differences between MDCK cells with varying proliferative capabilities through the use of both untargeted and targeted metabolomics. METHODS: To investigate the metabolic discrepancies between adherent cell groups (MDCK-M60 and MDCK-CL23) and suspension cell groups (MDCK-XF04 and MDCK-XF06), untargeted and targeted metabolomics were used. Utilizing RT-qPCR analysis, the mRNA expressions of key metabolites enzymes were identified. RESULTS: An untargeted metabolomics study demonstrated the presence of 81 metabolites between MDCK-M60 and MDCK-CL23 cells, which were mainly affected by six pathways. An analysis of MDCK-XF04 and MDCK-XF06 cells revealed a total of 113 potential metabolites, the majority of which were impacted by ten pathways. Targeted metabolomics revealed a decrease in the levels of choline, tryptophan, and tyrosine in MDCK-CL23 cells, which was in accordance with the results of untargeted metabolomics. Additionally, MDCK-XF06 cells experienced a decrease in 5’-methylthioadenosine and tryptophan, while S-adenosylhomocysteine, kynurenine, 11Z-eicosenoic acid, 3-phosphoglycerate, glucose 6-phosphate, and phosphoenolpyruvic acid concentrations were increased. The mRNA levels of MAT1A, MAT2B, IDO1, and IDO2 in the two cell groups were all increased, suggesting that S-adenosylmethionine and tryptophan may have a significant role in cell metabolism. CONCLUSIONS: This research examines the effect of metabolite fluctuations on cell proliferation, thus offering a potential way to improve the rate of MDCK cell growth. PeerJ Inc. 2023-09-20 /pmc/articles/PMC10517658/ /pubmed/37744241 http://dx.doi.org/10.7717/peerj.16077 Text en ©2023 Sun et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Bioinformatics Sun, Na Zhang, Yuchuan Dong, Jian Liu, Geng Liu, Zhenbin Wang, Jiamin Qiao, Zilin Zhang, Jiayou Duan, Kai Nian, Xuanxuan Ma, Zhongren Yang, Xiaoming Metabolomics profiling reveals differences in proliferation between tumorigenic and non-tumorigenic Madin-Darby canine kidney (MDCK) cells |
title | Metabolomics profiling reveals differences in proliferation between tumorigenic and non-tumorigenic Madin-Darby canine kidney (MDCK) cells |
title_full | Metabolomics profiling reveals differences in proliferation between tumorigenic and non-tumorigenic Madin-Darby canine kidney (MDCK) cells |
title_fullStr | Metabolomics profiling reveals differences in proliferation between tumorigenic and non-tumorigenic Madin-Darby canine kidney (MDCK) cells |
title_full_unstemmed | Metabolomics profiling reveals differences in proliferation between tumorigenic and non-tumorigenic Madin-Darby canine kidney (MDCK) cells |
title_short | Metabolomics profiling reveals differences in proliferation between tumorigenic and non-tumorigenic Madin-Darby canine kidney (MDCK) cells |
title_sort | metabolomics profiling reveals differences in proliferation between tumorigenic and non-tumorigenic madin-darby canine kidney (mdck) cells |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10517658/ https://www.ncbi.nlm.nih.gov/pubmed/37744241 http://dx.doi.org/10.7717/peerj.16077 |
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