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 prolifer...
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Autor*in:	Na Sun [verfasserIn] Yuchuan Zhang [verfasserIn] Jian Dong [verfasserIn] Geng Liu [verfasserIn] Zhenbin Liu [verfasserIn] Jiamin Wang [verfasserIn] Zilin Qiao [verfasserIn] Jiayou Zhang [verfasserIn] Kai Duan [verfasserIn] Xuanxuan Nian [verfasserIn] Zhongren Ma [verfasserIn] Xiaoming Yang [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	MDCK cells Cell proliferation Untargeted metabolomics Targeted metabolomics Tryptophan metabolism S-adenosylmethionine

Übergeordnetes Werk:	In: PeerJ - PeerJ Inc., 2013, 11, p e16077(2023)
Übergeordnetes Werk:	volume:11, p e16077 ; year:2023

Links:	Link aufrufen Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.7717/peerj.16077

Katalog-ID:	DOAJ095081461

Internformat


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520			\|a 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.
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allfields	10.7717/peerj.16077 doi (DE-627)DOAJ095081461 (DE-599)DOAJ030fca02d50a4350ba4763bfe68a4039 DE-627 ger DE-627 rakwb eng QH301-705.5 Na Sun verfasserin aut Metabolomics profiling reveals differences in proliferation between tumorigenic and non-tumorigenic Madin-Darby canine kidney (MDCK) cells 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. MDCK cells Cell proliferation Untargeted metabolomics Targeted metabolomics Tryptophan metabolism S-adenosylmethionine Medicine R Biology (General) Yuchuan Zhang verfasserin aut Jian Dong verfasserin aut Geng Liu verfasserin aut Zhenbin Liu verfasserin aut Jiamin Wang verfasserin aut Zilin Qiao verfasserin aut Jiayou Zhang verfasserin aut Kai Duan verfasserin aut Xuanxuan Nian verfasserin aut Zhongren Ma verfasserin aut Xiaoming Yang verfasserin aut In PeerJ PeerJ Inc., 2013 11, p e16077(2023) (DE-627)736558624 (DE-600)2703241-3 21678359 nnns volume:11, p e16077 year:2023 https://doi.org/10.7717/peerj.16077 kostenfrei https://doaj.org/article/030fca02d50a4350ba4763bfe68a4039 kostenfrei https://peerj.com/articles/16077.pdf kostenfrei https://peerj.com/articles/16077/ kostenfrei https://doaj.org/toc/2167-8359 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11, p e16077 2023
spelling	10.7717/peerj.16077 doi (DE-627)DOAJ095081461 (DE-599)DOAJ030fca02d50a4350ba4763bfe68a4039 DE-627 ger DE-627 rakwb eng QH301-705.5 Na Sun verfasserin aut Metabolomics profiling reveals differences in proliferation between tumorigenic and non-tumorigenic Madin-Darby canine kidney (MDCK) cells 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. MDCK cells Cell proliferation Untargeted metabolomics Targeted metabolomics Tryptophan metabolism S-adenosylmethionine Medicine R Biology (General) Yuchuan Zhang verfasserin aut Jian Dong verfasserin aut Geng Liu verfasserin aut Zhenbin Liu verfasserin aut Jiamin Wang verfasserin aut Zilin Qiao verfasserin aut Jiayou Zhang verfasserin aut Kai Duan verfasserin aut Xuanxuan Nian verfasserin aut Zhongren Ma verfasserin aut Xiaoming Yang verfasserin aut In PeerJ PeerJ Inc., 2013 11, p e16077(2023) (DE-627)736558624 (DE-600)2703241-3 21678359 nnns volume:11, p e16077 year:2023 https://doi.org/10.7717/peerj.16077 kostenfrei https://doaj.org/article/030fca02d50a4350ba4763bfe68a4039 kostenfrei https://peerj.com/articles/16077.pdf kostenfrei https://peerj.com/articles/16077/ kostenfrei https://doaj.org/toc/2167-8359 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11, p e16077 2023
allfields_unstemmed	10.7717/peerj.16077 doi (DE-627)DOAJ095081461 (DE-599)DOAJ030fca02d50a4350ba4763bfe68a4039 DE-627 ger DE-627 rakwb eng QH301-705.5 Na Sun verfasserin aut Metabolomics profiling reveals differences in proliferation between tumorigenic and non-tumorigenic Madin-Darby canine kidney (MDCK) cells 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. MDCK cells Cell proliferation Untargeted metabolomics Targeted metabolomics Tryptophan metabolism S-adenosylmethionine Medicine R Biology (General) Yuchuan Zhang verfasserin aut Jian Dong verfasserin aut Geng Liu verfasserin aut Zhenbin Liu verfasserin aut Jiamin Wang verfasserin aut Zilin Qiao verfasserin aut Jiayou Zhang verfasserin aut Kai Duan verfasserin aut Xuanxuan Nian verfasserin aut Zhongren Ma verfasserin aut Xiaoming Yang verfasserin aut In PeerJ PeerJ Inc., 2013 11, p e16077(2023) (DE-627)736558624 (DE-600)2703241-3 21678359 nnns volume:11, p e16077 year:2023 https://doi.org/10.7717/peerj.16077 kostenfrei https://doaj.org/article/030fca02d50a4350ba4763bfe68a4039 kostenfrei https://peerj.com/articles/16077.pdf kostenfrei https://peerj.com/articles/16077/ kostenfrei https://doaj.org/toc/2167-8359 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11, p e16077 2023
allfieldsGer	10.7717/peerj.16077 doi (DE-627)DOAJ095081461 (DE-599)DOAJ030fca02d50a4350ba4763bfe68a4039 DE-627 ger DE-627 rakwb eng QH301-705.5 Na Sun verfasserin aut Metabolomics profiling reveals differences in proliferation between tumorigenic and non-tumorigenic Madin-Darby canine kidney (MDCK) cells 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. MDCK cells Cell proliferation Untargeted metabolomics Targeted metabolomics Tryptophan metabolism S-adenosylmethionine Medicine R Biology (General) Yuchuan Zhang verfasserin aut Jian Dong verfasserin aut Geng Liu verfasserin aut Zhenbin Liu verfasserin aut Jiamin Wang verfasserin aut Zilin Qiao verfasserin aut Jiayou Zhang verfasserin aut Kai Duan verfasserin aut Xuanxuan Nian verfasserin aut Zhongren Ma verfasserin aut Xiaoming Yang verfasserin aut In PeerJ PeerJ Inc., 2013 11, p e16077(2023) (DE-627)736558624 (DE-600)2703241-3 21678359 nnns volume:11, p e16077 year:2023 https://doi.org/10.7717/peerj.16077 kostenfrei https://doaj.org/article/030fca02d50a4350ba4763bfe68a4039 kostenfrei https://peerj.com/articles/16077.pdf kostenfrei https://peerj.com/articles/16077/ kostenfrei https://doaj.org/toc/2167-8359 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11, p e16077 2023
allfieldsSound	10.7717/peerj.16077 doi (DE-627)DOAJ095081461 (DE-599)DOAJ030fca02d50a4350ba4763bfe68a4039 DE-627 ger DE-627 rakwb eng QH301-705.5 Na Sun verfasserin aut Metabolomics profiling reveals differences in proliferation between tumorigenic and non-tumorigenic Madin-Darby canine kidney (MDCK) cells 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. MDCK cells Cell proliferation Untargeted metabolomics Targeted metabolomics Tryptophan metabolism S-adenosylmethionine Medicine R Biology (General) Yuchuan Zhang verfasserin aut Jian Dong verfasserin aut Geng Liu verfasserin aut Zhenbin Liu verfasserin aut Jiamin Wang verfasserin aut Zilin Qiao verfasserin aut Jiayou Zhang verfasserin aut Kai Duan verfasserin aut Xuanxuan Nian verfasserin aut Zhongren Ma verfasserin aut Xiaoming Yang verfasserin aut In PeerJ PeerJ Inc., 2013 11, p e16077(2023) (DE-627)736558624 (DE-600)2703241-3 21678359 nnns volume:11, p e16077 year:2023 https://doi.org/10.7717/peerj.16077 kostenfrei https://doaj.org/article/030fca02d50a4350ba4763bfe68a4039 kostenfrei https://peerj.com/articles/16077.pdf kostenfrei https://peerj.com/articles/16077/ kostenfrei https://doaj.org/toc/2167-8359 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11, p e16077 2023
language	English
source	In PeerJ 11, p e16077(2023) volume:11, p e16077 year:2023
sourceStr	In PeerJ 11, p e16077(2023) volume:11, p e16077 year:2023
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	MDCK cells Cell proliferation Untargeted metabolomics Targeted metabolomics Tryptophan metabolism S-adenosylmethionine Medicine R Biology (General)
isfreeaccess_bool	true
container_title	PeerJ
authorswithroles_txt_mv	Na Sun @@aut@@ Yuchuan Zhang @@aut@@ Jian Dong @@aut@@ Geng Liu @@aut@@ Zhenbin Liu @@aut@@ Jiamin Wang @@aut@@ Zilin Qiao @@aut@@ Jiayou Zhang @@aut@@ Kai Duan @@aut@@ Xuanxuan Nian @@aut@@ Zhongren Ma @@aut@@ Xiaoming Yang @@aut@@
publishDateDaySort_date	2023-01-01T00:00:00Z
hierarchy_top_id	736558624
id	DOAJ095081461
language_de	englisch
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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. 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callnumber-first	Q - Science
author	Na Sun
spellingShingle	Na Sun misc QH301-705.5 misc MDCK cells misc Cell proliferation misc Untargeted metabolomics misc Targeted metabolomics misc Tryptophan metabolism misc S-adenosylmethionine misc Medicine misc R misc Biology (General) Metabolomics profiling reveals differences in proliferation between tumorigenic and non-tumorigenic Madin-Darby canine kidney (MDCK) cells
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topic_title	QH301-705.5 Metabolomics profiling reveals differences in proliferation between tumorigenic and non-tumorigenic Madin-Darby canine kidney (MDCK) cells MDCK cells Cell proliferation Untargeted metabolomics Targeted metabolomics Tryptophan metabolism S-adenosylmethionine
topic	misc QH301-705.5 misc MDCK cells misc Cell proliferation misc Untargeted metabolomics misc Targeted metabolomics misc Tryptophan metabolism misc S-adenosylmethionine misc Medicine misc R misc Biology (General)
topic_unstemmed	misc QH301-705.5 misc MDCK cells misc Cell proliferation misc Untargeted metabolomics misc Targeted metabolomics misc Tryptophan metabolism misc S-adenosylmethionine misc Medicine misc R misc Biology (General)
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title	Metabolomics profiling reveals differences in proliferation between tumorigenic and non-tumorigenic Madin-Darby canine kidney (MDCK) cells
ctrlnum	(DE-627)DOAJ095081461 (DE-599)DOAJ030fca02d50a4350ba4763bfe68a4039
title_full	Metabolomics profiling reveals differences in proliferation between tumorigenic and non-tumorigenic Madin-Darby canine kidney (MDCK) cells
author_sort	Na Sun
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author_browse	Na Sun Yuchuan Zhang Jian Dong Geng Liu Zhenbin Liu Jiamin Wang Zilin Qiao Jiayou Zhang Kai Duan Xuanxuan Nian Zhongren Ma Xiaoming Yang
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title_sort	metabolomics profiling reveals differences in proliferation between tumorigenic and non-tumorigenic madin-darby canine kidney (mdck) cells
callnumber	QH301-705.5
title_auth	Metabolomics profiling reveals differences in proliferation between tumorigenic and non-tumorigenic Madin-Darby canine kidney (MDCK) cells
abstract	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.
abstractGer	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.
abstract_unstemmed	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.
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title_short	Metabolomics profiling reveals differences in proliferation between tumorigenic and non-tumorigenic Madin-Darby canine kidney (MDCK) cells
url	https://doi.org/10.7717/peerj.16077 https://doaj.org/article/030fca02d50a4350ba4763bfe68a4039 https://peerj.com/articles/16077.pdf https://peerj.com/articles/16077/ https://doaj.org/toc/2167-8359
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author2	Yuchuan Zhang Jian Dong Geng Liu Zhenbin Liu Jiamin Wang Zilin Qiao Jiayou Zhang Kai Duan Xuanxuan Nian Zhongren Ma Xiaoming Yang
author2Str	Yuchuan Zhang Jian Dong Geng Liu Zhenbin Liu Jiamin Wang Zilin Qiao Jiayou Zhang Kai Duan Xuanxuan Nian Zhongren Ma Xiaoming Yang
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up_date	2024-07-04T01:50:09.307Z
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Metabolomics profiling reveals differences in proliferation between tumorigenic and non-tumorigenic Madin-Darby canine kidney (MDCK) cells

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