Evaluation of extraction processes for intracellular metabolite profiling of mammalian cells: matching extraction approaches to cell type and metabolite targets

In this study we report on the optimisation of the technologies for generation of a global metabolomics profile for intracellular metabolites in Chinese hamster ovary (CHO) cells. We evaluated the effectiveness of a range of different extraction methods applied to CHO cells which had been quenched using a previously optimised approach. The extraction methods tested included cold methanol, hot ethanol, acid, alkali and methanol/chloroform plus combinations of these. The extraction of metabolites using two 100% methanol extractions followed by a final water extraction recovered the largest range of metabolites. For the majority of metabolites, extracts generated in this manner exhibited the greatest recovery with high reproducibility. Therefore, this was the best extraction method for attaining a global metabolic profile from a single sample. However, another parallel extraction method (e.g. alkali) may also be required to maximise the range of metabolites recovered (e.g. non-polar metabolites).

[1]  D. Kell,et al.  Analysis of the metabolic footprint and tissue metabolome of placental villous explants cultured at different oxygen tensions reveals novel redox biomarkers. , 2008, Placenta.

[2]  Udo Reichl,et al.  Simultaneous extraction of several metabolites of energy metabolism and related substances in mammalian cells: optimization using experimental design. , 2008, Analytical biochemistry.

[3]  Michael Butler,et al.  Animal cell cultures: recent achievements and perspectives in the production of biopharmaceuticals , 2005, Applied Microbiology and Biotechnology.

[4]  Balázs Papp,et al.  Evaluation of predicted network modules in yeast metabolism using NMR-based metabolite profiling. , 2007, Genome research.

[5]  Royston Goodacre,et al.  Effective quenching processes for physiologically valid metabolite profiling of suspension cultured Mammalian cells. , 2009, Analytical chemistry.

[6]  Klaus Maier,et al.  Identification of metabolic fluxes in hepatic cells from transient 13C‐labeling experiments: Part II. Flux estimation , 2008, Biotechnology and bioengineering.

[7]  D. Kell,et al.  High-throughput classification of yeast mutants for functional genomics using metabolic footprinting , 2003, Nature Biotechnology.

[8]  Mohamed Al-Rubeai,et al.  Metabolic characterization of a hyper-productive state in an antibody producing NS0 myeloma cell line. , 2009, Metabolic engineering.

[9]  D. Kell,et al.  Detection and Identification of Novel Metabolomic Biomarkers in Preeclampsia , 2008, Reproductive Sciences.

[10]  T. Ferenci,et al.  Global metabolite analysis: the influence of extraction methodology on metabolome profiles of Escherichia coli. , 2003, Analytical biochemistry.

[11]  J. François,et al.  Sampling techniques and comparative extraction procedures for quantitative determination of intra- a , 1998 .

[12]  E. Smid,et al.  Comparison of quenching and extraction methodologies for metabolome analysis of Lactobacillus plantarum , 2007, Microbial cell factories.

[13]  C. Chassagnole,et al.  Dynamic modeling of the central carbon metabolism of Escherichia coli. , 2002, Biotechnology and bioengineering.

[14]  T. Ferenci,et al.  Assessing the effect of reactive oxygen species on Escherichia coli using a metabolome approach. , 1999, Redox report : communications in free radical research.

[15]  Jae Sung Cho,et al.  Global physiological understanding and metabolic engineering of microorganisms based on omics studies , 2005, Applied Microbiology and Biotechnology.

[16]  M. Reuss,et al.  In vivo analysis of glucose-induced fast changes in yeast adenine nucleotide pool applying a rapid sampling technique. , 1993, Analytical biochemistry.

[17]  U. Hofmann,et al.  Identification of metabolic fluxes in hepatic cells from transient 13C‐labeling experiments: Part I. Experimental observations , 2008, Biotechnology and bioengineering.

[18]  Andrew J Racher,et al.  Antibody production. , 2006, Advanced drug delivery reviews.

[19]  J. Rabinowitz,et al.  Absolute quantitation of intracellular metabolite concentrations by an isotope ratio-based approach , 2008, Nature Protocols.

[20]  M. Viant,et al.  High-throughput tissue extraction protocol for NMR- and MS-based metabolomics. , 2008, Analytical biochemistry.

[21]  J. François,et al.  A rapid and reliable method for metabolite extraction in yeast using boiling buffered ethanol , 1997, Yeast.

[22]  John T. Wei,et al.  Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression , 2009, Nature.

[23]  R. Goodacre,et al.  Global Metabolic Profiling of Escherichia Coli Cultures: an Evaluation of Methods for Quenching and Extraction of Intracellular Metabolites , 2022 .

[24]  O. Fiehn Metabolomics – the link between genotypes and phenotypes , 2004, Plant Molecular Biology.

[25]  F. Zimmermann,et al.  A partial defect in carbon catabolite repression in mutants of Saccharomyces cerevisiae with reduced hexose phosphyorylation , 1977, Molecular and General Genetics MGG.

[26]  Theodore E. Cohn,et al.  Detection and identification , 1985 .

[27]  A. Fiechter,et al.  Rapid sampling of yeast cells and automated assays of adenylate, citrate, pyruvate and glucose-6-phosphate pools. , 1974, Analytical biochemistry.

[28]  J. W. Allwood,et al.  1H NMR, GC-EI-TOFMS, and data set correlation for fruit metabolomics: application to spatial metabolite analysis in melon. , 2009, Analytical chemistry.

[29]  T. Ferenci,et al.  Effect of Slow Growth on Metabolism of Escherichia coli, as Revealed by Global Metabolite Pool (“Metabolome”) Analysis , 1998, Journal of bacteriology.

[30]  D. Ekman,et al.  A direct cell quenching method for cell-culture based metabolomics , 2009, Metabolomics.

[31]  Nigel W. Hardy,et al.  Proposed minimum reporting standards for chemical analysis , 2007, Metabolomics.

[32]  Royston Goodacre,et al.  Metabolomics: Current technologies and future trends , 2006, Proteomics.

[33]  Ningning Ma,et al.  A single nutrient feed supports both chemically defined NS0 and CHO fed‐batch processes: Improved productivity and lactate metabolism , 2009, Biotechnology progress.

[34]  Cécile Cabasson,et al.  Quantitative metabolic profiles of tomato flesh and seeds during fruit development: complementary analysis with ANN and PCA , 2007, Metabolomics.

[35]  R. Goodacre Metabolomics of a superorganism. , 2007, The Journal of nutrition.