Literature DB >> 21533804

GC-TOFMS analysis of metabolites in adherent MDCK cells and a novel strategy for identifying intracellular metabolic markers for use as cell amount indicators in data normalization.

Bei Cao1, Jiye Aa, Guangji Wang, Xiaolan Wu, Linsheng Liu, Mengjie Li, Jian Shi, Xinwen Wang, Chunyan Zhao, Tian Zheng, Sheng Guo, Jinao Duan.   

Abstract

Cultured cell lines are useful models in biomedical research that characterize metabolic responses to various stimuli (e.g., pathogens, toxins, or drugs/chemicals) and explore the underlying mechanisms. However, data from cell metabolomic studies must be normalized to the amount of cells, which is dependent on diverse treatments. The currently used methods of cell counting and protein assay involve extra work and delay the quenching of intracellular metabolism. To develop a convenient, alternative approach, in this study, intracellular metabolites were extracted from a series amount of cultured adherent cells and profiled by gas chromatography-time-of-flight mass spectrometry (GC-TOFMS). The GC-TOFMS signal intensities for 11 intracellular markers present in two different cell lines showed good linearity with the protein content, with inositol and pantothenate most promising (correlation coefficient > 0.970). Despite the various amounts of cells, the data normalized to the metabolic markers and protein amounts showed similar effectiveness, resulted in better separation of the two cell lines, closer clustering within each group(cell line) on a principal components analysis scores plot, and had lower relative standard deviations for intracellular metabolites than those of the non-normalized data, suggesting that these markers were effective indicators of cell amounts and independent of cell lines.

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Year:  2011        PMID: 21533804     DOI: 10.1007/s00216-011-4981-8

Source DB:  PubMed          Journal:  Anal Bioanal Chem        ISSN: 1618-2642            Impact factor:   4.142


  10 in total

Review 1.  Experimental design and reporting standards for metabolomics studies of mammalian cell lines.

Authors:  Sarah Hayton; Garth L Maker; Ian Mullaney; Robert D Trengove
Journal:  Cell Mol Life Sci       Date:  2017-07-01       Impact factor: 9.261

2.  Measurement of DNA concentration as a normalization strategy for metabolomic data from adherent cell lines.

Authors:  Leslie P Silva; Philip L Lorenzi; Preeti Purwaha; Valeda Yong; David H Hawke; John N Weinstein
Journal:  Anal Chem       Date:  2013-10-02       Impact factor: 6.986

Review 3.  Towards quantitative mass spectrometry-based metabolomics in microbial and mammalian systems.

Authors:  Rahul Vijay Kapoore; Seetharaman Vaidyanathan
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2016-10-28       Impact factor: 4.226

4.  A comprehensive protocol for multiplatform metabolomics analysis in patient-derived skin fibroblasts.

Authors:  Jordan Wilkins; Dhananjay Sakrikar; Xuan-Mai Petterson; Ian R Lanza; Eugenia Trushina
Journal:  Metabolomics       Date:  2019-05-23       Impact factor: 4.290

5.  Reduced quenching and extraction time for mammalian cells using filtration and syringe extraction.

Authors:  Juan A Hernández Bort; Vinoth Shanmukam; Martin Pabst; Markus Windwarder; Laura Neumann; Ali Alchalabi; Guido Krebiehl; Gunda Koellensperger; Stephan Hann; Denise Sonntag; Friedrich Altmann; Christine Heel; Nicole Borth
Journal:  J Biotechnol       Date:  2014-04-29       Impact factor: 3.307

6.  Removing the bottlenecks of cell culture metabolomics: fast normalization procedure, correlation of metabolites to cell number, and impact of the cell harvesting method.

Authors:  Caroline Muschet; Gabriele Möller; Cornelia Prehn; Martin Hrabě de Angelis; Jerzy Adamski; Janina Tokarz
Journal:  Metabolomics       Date:  2016-09-15       Impact factor: 4.290

Review 7.  Metabolic flux analysis: a comprehensive review on sample preparation, analytical techniques, data analysis, computational modelling, and main application areas.

Authors:  Bruna de Falco; Francesco Giannino; Fabrizio Carteni; Stefano Mazzoleni; Dong-Hyun Kim
Journal:  RSC Adv       Date:  2022-09-07       Impact factor: 4.036

8.  Metabolomic approach to evaluating adriamycin pharmacodynamics and resistance in breast cancer cells.

Authors:  Bei Cao; Mengjie Li; Weibin Zha; Qijin Zhao; Rongrong Gu; Linsheng Liu; Jian Shi; Jun Zhou; Fang Zhou; Xiaolan Wu; Zimei Wu; Guangji Wang; Jiye Aa
Journal:  Metabolomics       Date:  2013-03-20       Impact factor: 4.290

9.  Modified Protocol of Harvesting, Extraction, and Normalization Approaches for Gas Chromatography Mass Spectrometry-Based Metabolomics Analysis of Adherent Cells Grown Under High Fetal Calf Serum Conditions.

Authors:  Raphaela Fritsche-Guenther; Anna Bauer; Yoann Gloaguen; Mario Lorenz; Jennifer A Kirwan
Journal:  Metabolites       Date:  2019-12-18

10.  The Synthetic Flavonoid Derivative GL-V9 Induces Apoptosis and Autophagy in Cutaneous Squamous Cell Carcinoma via Suppressing AKT-Regulated HK2 and mTOR Signals.

Authors:  Yejin Zhu; Mengdi Liu; Jingyue Yao; Qinglong Guo; Libin Wei
Journal:  Molecules       Date:  2020-10-30       Impact factor: 4.411

  10 in total

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