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

Abstract

IntroductionAlthough cultured cells are nowadays regularly analyzed by metabolomics technologies, some issues in study setup and data processing are still not resolved to complete satisfaction: a suitable harvesting method for adherent cells, a fast and robust method for data normalization, and the proof that metabolite levels can be normalized to cell number.ObjectivesWe intended to develop a fast method for normalization of cell culture metabolomics samples, to analyze how metabolite levels correlate with cell numbers, and to elucidate the impact of the kind of harvesting on measured metabolite profiles.MethodsWe cultured four different human cell lines and used them to develop a fluorescence-based method for DNA quantification. Further, we assessed the correlation between metabolite levels and cell numbers and focused on the impact of the harvesting method (scraping or trypsinization) on the metabolite profile.ResultsWe developed a fast, sensitive and robust fluorescence-based method for DNA quantification showing excellent linear correlation between fluorescence intensities and cell numbers for all cell lines. Furthermore, 82–97 % of the measured intracellular metabolites displayed linear correlation between metabolite concentrations and cell numbers. We observed differences in amino acids, biogenic amines, and lipid levels between trypsinized and scraped cells.ConclusionWe offer a fast, robust, and validated normalization method for cell culture metabolomics samples and demonstrate the eligibility of the normalization of metabolomics data to the cell number. We show a cell line and metabolite-specific impact of the harvesting method on metabolite concentrations.Electronic supplementary materialThe online version of this article (doi:10.1007/s11306-016-1104-8) contains supplementary material, which is available to authorized users.

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

“…As we were interested in analyzing only the polar metabolites in this study, it was excluded from the test solvents. We also looked at whether cell mass or total protein represented a better normalization strategy, since cell count cannot easily be used for adherent cells harvested for a metabolomics approach [32].…”

Correlation guided Network Integration (CoNI) reveals novel genetic regulators of hepatic metabolism

“…Cells were cultured in DMEM supplemented with 10% fetal bovine serum and antibiotics (penicillin 100 IU/ml and streptomycin 100 μg/ml) in 5% CO 2 at 37 °C. At 70–80% confluence, cells were transfected with five different human SMARTpool On Target plus siRNA clones (L-006727-00, L-021435-02, L-009511-00, L-020477-02, L-016272-01; Dharmacon, Lafayette, USA) or ON-TARGETplus Non-targeting Pool (D-001810-10) using DharmaFECT #4 (Dharmacon) for 48 hours and subjected to metabolite extraction in an ice-cold 80/20 (v/v) methanol/water mixture as described previously [33]. Cells were homogenized using the Precellys24 homogenizer twice for 25 s at 5,500 rpm and 0-3°C, with 5s pause intervals in between.…”

“…To normalize the obtained metabolomics data from cell homogenates for differences in cell numbers, the DNA content was determined using fluorochrome Hoechst 33342 (ThermoFisher Scientific, Schwerte, Germany) and a GloMax Multi Detection System (Promega, Mannheim, Germany) from a small aliquot taken before the final centrifugation step, as previously described [33]. The DNA content for one replicate of the Cobll1 KD was too low, thus this sample was excluded from all downstream analysis, resulting in n=5 Cobll1 KD replicates.…”

Hochdurchsatz‐Metabolomik mit 1D‐NMR

“…Bei Zellen kann man voraussetzen, dass eine Zunahme der Zellzahl mit einer linearen Zunahme der Metabolitensignale einhergeht. Die Datennormalisierung wird hier meist anhand der Zellzahl durchgeführt . Daneben sind auch die Gesamt‐DNA oder das Gesamtprotein als Referenz möglich .…”

“…Die Datennormalisierung wird hier meist anhand der Zellzahl durchgeführt . Daneben sind auch die Gesamt‐DNA oder das Gesamtprotein als Referenz möglich . Nach dem gleichen Prinzip wird für Gewebe eine Normalisierung nach dem Gewicht der Probe empfohlen .…”