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

Comparison of Various Extraction Approaches for Optimized Preparation of Intracellular Metabolites from Human Mesenchymal Stem Cells and Fibroblasts for NMR-Based Study

Metabolomics has proven to be a sensitive tool for monitoring biochemical processes in cell culture. It enables multi-analysis, clarifying the correlation between numerous metabolic pathways. Together with other analysis, it thus provides a global view of a cell's physiological state. A comprehensive analysis of molecular changes is also required in the case of mesenchymal stem cells (MSCs), which currently represent an essential portion of cells used in regenerative medicine. Reproducibility and correct measurement are closely connected to careful metabolite extraction, and sample preparation is always a critical point. Our study aimed to compare the efficiencies of four harvesting and six extraction methods. Several organic reagents (methanol, ethanol, acetonitrile, methanol-chloroform, MTBE) and harvesting approaches (trypsinization vs. scraping) were tested. We used untargeted nuclear magnetic resonance spectroscopy (NMR) to determine the most efficient method for the extraction of metabolites from human adherent cells, specifically human dermal fibroblasts adult (HDFa) and dental pulp stem cells (DPSCs). A comprehensive dataset of 29 identified and quantified metabolites were determined to possess statistically significant differences in the abundances of several metabolites when the cells were detached mechanically to organic solvent compared to when applying enzymes mainly in the classes of amino acids and peptides for both types of cells. Direct scraping to organic solvent is a method that yields higher abundances of determined metabolites. Extraction with the use of different polar reagents, 50% and 80% methanol, or acetonitrile, mostly showed the same quality. For both HDFa and DPSC cells, the MTBE method, methanol-chloroform, and 80% ethanol extractions showed higher extraction efficiency for the most identified and quantified metabolites Thus, preparation procedures provided a cell sample processing protocol that focuses on maximizing extraction yield. Our approach may be useful for large-scale comparative metabolomic studies of human mesenchymal stem cell samples.

Development of metabolome extraction strategy for metabolite profiling of skin tissue

INTRODUCTION

Changes in skin phenotypic characteristics are based on skin tissue. The study of the metabolic changes in skin tissue can help understand the causes of skin diseases and identify effective therapeutic interventions.

OBJECTIVES

We aimed to establish and optimize a non-targeted skin metabolome extraction system for skin tissue metabolomics with high metabolite coverage, recovery, and reproducibility using gas chromatography/mass spectrometry.

METHODS

The metabolites in skin tissues were extracted using eleven different extraction systems, which were designed using reagents with different polarities based on sequential solid-liquid extraction employing a two-step strategy and analyzed using gas chromatograph/mass spectrometry. The extraction efficiency of diverse solvents was evaluated by coefficient of variation (CV), multivariate analysis, metabolites coverage, and relative peak area analysis.

RESULTS

We identified 119 metabolites and the metabolite profiles differed significantly between the eleven extraction systems. Metabolites with high abundances in the organic extraction systems, followed by aqueous extraction, were involved in the biosynthesis of unsaturated fatty acids, while metabolites with high abundances in the aqueous extraction systems, followed by organic extraction, were involved in amino sugar and nucleotide sugar metabolism, and glycerolipid metabolism. MeOH/chloroform-H2O and MeOH/H2O-chloroform were the extraction systems that yielded the highest number of metabolites, while MeOH/acetonitrile (ACN)-H2O and ACN/H2O-IPA exhibited superior metabolite recoveries.

CONCLUSION

Our results demonstrated that our research facilitates the selection of an appropriate metabolite extraction approach based on the experimental purpose for the metabolomics study of skin tissue.

A systematic evaluation of quenching and extraction procedures for quantitative metabolome profiling of HeLa carcinoma cell under 2D and 3D cell culture conditions

Metabolic reprogramming has been coined as a hallmark of cancer, accompanied by which the alterations in metabolite levels have profound effects on gene expression, cellular differentiation, and the tumor environment. Yet a systematic evaluation of quenching and extraction procedures for quantitative metabolome profiling of tumor cells is currently lacking. To achieve this, this study is aimed at establishing an unbiased and leakage-free metabolome preparation protocol for HeLa carcinoma cell. We evaluated 12 combinations of quenching and extraction methods from three quenchers (liquid nitrogen, -40°C 50% methanol, 0.5°C normal saline) and four extractants (-80°C 80% methanol, 0.5°C methanol/chloroform/water [1:1:1 v/v/v], 0.5°C 50% acetonitrile, 75°C 70% ethanol) for global metabolite profiling of adherent HeLa carcinoma cells. Based on the isotope dilution mass spectrometry (IDMS) method, gas/liquid chromatography in tandem with mass spectrometry was used to quantitatively determine 43 metabolites including sugar phosphates, organic acids, amino acids (AAs), adenosine nucleotides, and coenzymes involved in central carbon metabolism. The results showed that the total amount of the intracellular metabolites in cell extracts obtained using different sample preparation procedures with the IDMS method ranged from 21.51 to 295.33 nmol per million cells. Among 12 combinations, cells that washed twice with phosphate buffered saline (PBS), quenched with liquid nitrogen, and then extracted with 50% acetonitrile were found to be the most optimal method to acquire intracellular metabolites with high efficiency of metabolic arrest and minimal loss during sample preparation. In addition, the same conclusion was drawn as these 12 combinations were applied to obtain quantitative metabolome data from three-dimensional (3D) tumor spheroids. Furthermore, a case study was carried out to evaluate the effect of doxorubicin (DOX) on both adherent cells and 3D tumor spheroids using quantitative metabolite profiling. Pathway enrichment analysis using targeted metabolomics data showed that DOX exposure would significantly affect AA metabolism-related pathways, which might be related to the mitigation of redox stress. Strikingly, our data suggested that compared to two-dimensional (2D) cells the increased intracellular glutamine level in 3D cells benefited replenishing the tricarboxylic acid (TCA) cycle when the glycolysis was limited after dosing with DOX. Taken together, this study provides a well-established quenching and extraction protocol for quantitative metabolome profiling of HeLa carcinoma cell under 2D and 3D cell culture conditions. Based on this, quantitative time-resolved metabolite data can serve to the generation of hypotheses on metabolic reprogramming to reveal its important role in tumor development and treatment.

A Comparison of Solvent-Based Extraction Methods to Assess the Central Carbon Metabolites in Mouse Bone and Muscle

The identification of endogenous metabolites has great potential for understanding the underlying tissue processes occurring in either a homeostatic or a diseased state. The application of gas chromatography-mass spectrometry (GC-MS)-based metabolomics on musculoskeletal tissue samples has gained traction. However, limited comparison studies exist evaluating the sensitivity, reproducibility, and robustness of the various existing extraction protocols for musculoskeletal tissues. Here, we evaluated polar metabolite extraction from bone and muscle of mouse origin. The extraction methods compared were (1) modified Bligh-Dyer (mBD), (2) low chloroform (CHCl3)-modified Bligh-Dyer (mBD-low), and (3) modified Matyash (mMat). In particular, the central carbon metabolites (CCM) appear to be relevant for musculoskeletal regeneration, given their role in energy metabolism. However, the sensitivity, reproducibility, and robustness of these methods for detecting targeted polar CCM remains unknown. Overall, the extraction of metabolites using the mBD, mBD-low, and mMat methods appears sufficiently robust and reproducible for bone, with the mBD method slightly bettering the mBD-low and mMat methods. Furthermore, mBD, mBD-low, and mMat were sufficiently sensitive in detecting polar metabolites extracted from mouse muscle; however, they lacked repeatability. This study highlights the need for a re-thinking, towards a tissue-specific optimization of methods for metabolite extractions, ensuring sufficient sensitivity, repeatability, and robustness.

Comparative Proteomic and Metabolomic Analysis of Human Osteoblasts, Differentiated from Dental Pulp Stem Cells, Hinted Crucial Signaling Pathways Promoting Osteogenesis

Population aging has been a global trend for the last decades, which increases the pressure to develop new cell-based or drug-based therapies, including those that may cure bone diseases. To understand molecular processes that underlie bone development and turnover, we followed osteogenic differentiation of human dental pulp stem cells (DPSCs) using a specific induction medium. The differentiation process imitating in vivo osteogenesis is triggered by various signaling pathways and is associated with massive proteome and metabolome changes. Proteome was profiled by ultrahigh-performance liquid chromatography and comprehensively quantified by ion mobility-enhanced mass spectrometry. From 2667 reproducibly quantified and identified proteins, 432 were differentially abundant by strict statistic criteria. Metabolome profiling was carried out by nuclear magnetic resonance. From 27 detected metabolites, 8 were differentially accumulated. KEGG and MetaboAnalyst hinted metabolic pathways that may be involved in the osteogenic process. Enrichment analysis of differentially abundant proteins highlighted PPAR, FoxO, JAK-STAT, IL-17 signaling pathways, biosynthesis of thyroid hormones and steroids, mineral absorption, and fatty acid metabolism as processes with prominent impact on osteoinduction. In parallel, metabolomic data showed that aminoacyl-tRNA biosynthesis, as well as specific amino acids, likely promote osteodifferentiation. Targeted immunoassays validated and complemented omic results. Our data underlined the complexity of the osteogenic mechanism. Finally, we proposed promising targets for future validation in patient samples, a step toward the treatment of bone defects.

Exploratory Metabolomic Analysis Based on Reversed-Phase Liquid Chromatography-Mass Spectrometry to Study an In Vitro Model of Hypoxia-Induced Metabolic Alterations in HK-2 Cells

Oxygen deficiency in cells, tissues, and organs can not only prevent the proper development of biological functions but it can also lead to several diseases and disorders. In this sense, the kidney deserves special attention since hypoxia can be considered an important factor in the pathophysiology of both acute kidney injury and chronic kidney disease. To provide better knowledge to unveil the molecular mechanisms involved, new studies are necessary. In this sense, this work aims to study, for the first time, an in vitro model of hypoxia-induced metabolic alterations in human proximal tubular HK-2 cells because renal proximal tubules are particularly susceptible to hypoxia. Different groups of cells, cultivated under control and hypoxia conditions at 0.5, 5, 24, and 48 h, were investigated using untargeted metabolomic approaches based on reversed-phase liquid chromatography–mass spectrometry. Both intracellular and extracellular fluids were studied to obtain a large metabolite coverage. On the other hand, multivariate and univariate analyses were carried out to find the differences among the cell groups and to select the most relevant variables. The molecular features identified as affected metabolites were mainly amino acids and Amadori compounds. Insights about their biological relevance are also provided.