NMR metabolomics for evaluating passage number and harvesting effects on mammalian cell metabolome
The variation in the extracellular metabolites of RAW 264.7 cells obtained from different passage numbers (passage 9, 12 and 14) was examined. The impact of different harvesting protocols (trypsinization and scraping) on recovery of intracellular metabolites was then assessed. The similarity and var...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2019
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| Online Access: | http://psasir.upm.edu.my/id/eprint/81480/ http://psasir.upm.edu.my/id/eprint/81480/1/NMR.pdf |
| _version_ | 1848859114452549632 |
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| author | Abdul Hamid, Nur Ashikin Abas, Faridah Maulidiani, M. Ismail, Intan Safinar Chau, Ling Tham Swarup, Sanjay Umashankar, Shivshankar |
| author_facet | Abdul Hamid, Nur Ashikin Abas, Faridah Maulidiani, M. Ismail, Intan Safinar Chau, Ling Tham Swarup, Sanjay Umashankar, Shivshankar |
| author_sort | Abdul Hamid, Nur Ashikin |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | The variation in the extracellular metabolites of RAW 264.7 cells obtained from different passage numbers (passage 9, 12 and 14) was examined. The impact of different harvesting protocols (trypsinization and scraping) on recovery of intracellular metabolites was then assessed. The similarity and variation in the cell metabolome was investigated using 1H NMR metabolic profiling modeled using multivariate data analysis. The characterization and quantification of metabolites was performed to determine the passage-related and harvesting-dependent effects on impacted metabolic networks. The trypsinized RAW cells from lower passages gave higher intensities of most identified metabolites, including asparagine, serine and tryptophan. Principal component analysis revealed variation between cells from different passages and harvesting methods, as indicated by the formation of clusters in score plot. Analysis of S-plots revealed metabolites that acted as biomarkers in discriminating cells from different passages including acetate, serine, lactate and choline. Meanwhile lactate, glutamine and pyruvate served as biomarkers for differentiating trypsinized and scraped cells. In passage-dependent effects, glycolysis and TCA cycle were influential, whereas glycerophospholipid metabolism was affected by the harvesting method. Overall, it is proposed that typsinized RAW cells from lower passage numbers are more appropriate when conducting experiments related to NMR metabolomics. |
| first_indexed | 2025-11-15T12:24:12Z |
| format | Article |
| id | upm-81480 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T12:24:12Z |
| publishDate | 2019 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-814802021-06-12T23:43:30Z http://psasir.upm.edu.my/id/eprint/81480/ NMR metabolomics for evaluating passage number and harvesting effects on mammalian cell metabolome Abdul Hamid, Nur Ashikin Abas, Faridah Maulidiani, M. Ismail, Intan Safinar Chau, Ling Tham Swarup, Sanjay Umashankar, Shivshankar The variation in the extracellular metabolites of RAW 264.7 cells obtained from different passage numbers (passage 9, 12 and 14) was examined. The impact of different harvesting protocols (trypsinization and scraping) on recovery of intracellular metabolites was then assessed. The similarity and variation in the cell metabolome was investigated using 1H NMR metabolic profiling modeled using multivariate data analysis. The characterization and quantification of metabolites was performed to determine the passage-related and harvesting-dependent effects on impacted metabolic networks. The trypsinized RAW cells from lower passages gave higher intensities of most identified metabolites, including asparagine, serine and tryptophan. Principal component analysis revealed variation between cells from different passages and harvesting methods, as indicated by the formation of clusters in score plot. Analysis of S-plots revealed metabolites that acted as biomarkers in discriminating cells from different passages including acetate, serine, lactate and choline. Meanwhile lactate, glutamine and pyruvate served as biomarkers for differentiating trypsinized and scraped cells. In passage-dependent effects, glycolysis and TCA cycle were influential, whereas glycerophospholipid metabolism was affected by the harvesting method. Overall, it is proposed that typsinized RAW cells from lower passage numbers are more appropriate when conducting experiments related to NMR metabolomics. Elsevier 2019-07 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/81480/1/NMR.pdf Abdul Hamid, Nur Ashikin and Abas, Faridah and Maulidiani, M. and Ismail, Intan Safinar and Chau, Ling Tham and Swarup, Sanjay and Umashankar, Shivshankar (2019) NMR metabolomics for evaluating passage number and harvesting effects on mammalian cell metabolome. Analytical Biochemistry, 576. pp. 20-32. ISSN 0003-2697; ESSN: 1096-0309 https://www.sciencedirect.com/science/article/pii/S000326971831217X 10.1016/j.ab.2019.04.001 |
| spellingShingle | Abdul Hamid, Nur Ashikin Abas, Faridah Maulidiani, M. Ismail, Intan Safinar Chau, Ling Tham Swarup, Sanjay Umashankar, Shivshankar NMR metabolomics for evaluating passage number and harvesting effects on mammalian cell metabolome |
| title | NMR metabolomics for evaluating passage number and harvesting effects on mammalian cell metabolome |
| title_full | NMR metabolomics for evaluating passage number and harvesting effects on mammalian cell metabolome |
| title_fullStr | NMR metabolomics for evaluating passage number and harvesting effects on mammalian cell metabolome |
| title_full_unstemmed | NMR metabolomics for evaluating passage number and harvesting effects on mammalian cell metabolome |
| title_short | NMR metabolomics for evaluating passage number and harvesting effects on mammalian cell metabolome |
| title_sort | nmr metabolomics for evaluating passage number and harvesting effects on mammalian cell metabolome |
| url | http://psasir.upm.edu.my/id/eprint/81480/ http://psasir.upm.edu.my/id/eprint/81480/ http://psasir.upm.edu.my/id/eprint/81480/ http://psasir.upm.edu.my/id/eprint/81480/1/NMR.pdf |