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

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.

GC/MS and 2D NMR-based approach to evaluate the chemical profile of hydroalcoholic extract from Agaricus blazei Murill and its anti-inflammatory effect on human neutrophils

ETHNOPHARMACOLOGICAL RELEVANCE

Agaricus blazei Murill (AbM) is one of the main mushrooms used for medicinal purposes. The use of AbM in the preparation of teas is widespread mainly in Asian countries, while in Brazil it is used as a functional food to combat inflammatory diseases and cancer.

AIM OF THE STUDY

The main focus of this study was the characterization of the chemical profile of the hydroalcoholic extract of Agaricus blazei Murill (AbE), as well as the evaluation of its cytotoxic and anti-inflammatory potential using human neutrophils.

MATERIALS AND METHODS

The extract was prepared by dynamic maceration using a mixture of ethanol and water (70/30, v v-1) as solvent. The chemical profile characterization was carried out by 2D NMR and GC-MS techniques. The cytotoxicity of AbE was evaluated through studies of hemolytic potential, cell viability and membrane integrity. The anti-inflammatory activity was analyzed by a PMA-induced neutrophil degranulation assay.

RESULTS

Chemical analysis of AbE revealed the presence of 28 metabolites in its composition, with mannitol as the major compound. AbE at 1-200 μg mL-1 and mannitol at 4-160 μg mL-1, showed low hemolytic and cytotoxic potential against human red blood cells and neutrophils. Furthermore, both were able to significantly reduce the release of myeloperoxidase.

CONCLUSIONS

These results indicate that AbE is a promising natural product to be incorporated into pharmaceutical dosage forms intended for the adjuvant treatment of inflammatory diseases.

Integrated plasma metabolomic and cytokine analysis reveals a distinct immunometabolic signature in atopic dermatitis

Importance

Disease models for atopic dermatitis (AD) have primarily focused on understanding underlying environmental, immunologic, and genetic etiologies. However, the role of metabolic mechanisms in AD remains understudied.

Objective

To investigate the circulating blood metabolomic and cytokine profile of AD as compared to healthy control patients.

Design

This study collected plasma from 20 atopic dermatitis with moderate-to-severe itch (score of ≥5 on the itch Numeric Rating Scale and IGA score ≥3) and 24 healthy control patients. Mass-spectrometry based metabolite data were compared between AD and healthy controls. Unsupervised and supervised machine learning algorithms and univariate analysis analyzed metabolic concentrations. Metabolite enrichment and pathway analyses were performed on metabolites with significant fold change between AD and healthy control patients. To investigate the correlation between metabolites levels and cytokines, Spearman's rank correlation coefficients were calculated between metabolites and cytokines.

Setting

Patients were recruited from the Johns Hopkins Itch Center and dermatology outpatient clinics in the Johns Hopkins Outpatient Center.

Participants

The study included 20 atopic dermatitis patients and 24 healthy control patients.

Main outcomes and measures

Fold changes of metabolites in AD vs healthy control plasma.

Results

In patients with AD, amino acids isoleucine, tyrosine, threonine, tryptophan, valine, methionine, and phenylalanine, the amino acid derivatives creatinine, indole-3-acrylic acid, acetyl-L-carnitine, L-carnitine, 2-hydroxycinnamic acid, N-acetylaspartic acid, and the fatty amide oleamide had greater than 2-fold decrease (all P-values<0.0001) compared to healthy controls. Enriched metabolites were involved in branched-chain amino acid (valine, leucine, and isoleucine) degradation, catecholamine biosynthesis, thyroid hormone synthesis, threonine metabolism, and branched and long-chain fatty acid metabolism. Dysregulated metabolites in AD were positively correlated cytokines TARC and MCP-4 and negatively correlated with IL-1a and CCL20.

Conclusions and relevance

Our study characterized novel dysregulated circulating plasma metabolites and metabolic pathways that may be involved in the pathogenesis of AD. These metabolic pathways serve as potential future biomarkers and therapeutic targets in the treatment of AD.

Fibroblast phenylalanine concentration as a surrogate biomarker of cellular number

Metabolomics studies in human dermal fibroblasts can elucidate the biological mechanisms associated with some diseases, but several methodological issues that increase variability have been identified. We aimed to quantify the amino acid levels in cultured fibroblasts and to apply different sample-based normalization approaches. Forty-four skin biopsies from control subjects were collected. Amino acids were measured in fibroblasts supernatants by UPLC-MS/MS. Statistical supervised and unsupervised studies were used. Spearman's test showed that phenylalanine displayed the second highest correlation with the remaining amino acids (mean r = 0.8), whereas the total protein concentration from the cell pellet showed a mean of r = 0.67. The lowest percentage of variation was obtained when amino acids were normalized by phenylalanine values, with a mean of 42% vs 57% when normalized by total protein values. When amino acid levels were normalized by phenylalanine, Principal Component Analysis and clustering analyses identified different fibroblasts groups. In conclusion, phenylalanine may be a suitable biomarker to estimate cellular content in cultured fibroblasts.

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

Metabolic flux analysis (MFA) quantitatively describes cellular fluxes to understand metabolic phenotypes and functional behaviour after environmental and/or genetic perturbations. In the last decade, the application of stable isotopes became extremely important to determine and integrate in vivo measurements of metabolic reactions in systems biology. 13C-MFA is one of the most informative methods used to study central metabolism of biological systems. This review aims to outline the current experimental procedure adopted in 13C-MFA, starting from the preparation of cell cultures and labelled tracers to the quenching and extraction of metabolites and their subsequent analysis performed with very powerful software. Here, the limitations and advantages of nuclear magnetic resonance spectroscopy and mass spectrometry techniques used in carbon labelled experiments are elucidated by reviewing the most recent published papers. Furthermore, we summarise the most successful approaches used for computational modelling in flux analysis and the main application areas with a particular focus in metabolic engineering.

Cell Metabolomics Study on Synergistic anti-Hepatocellular Carcinoma Effect of Aidi Injection Combined with Doxorubicin

Hepatocellular carcinoma (HCC) is the sixth most common cancer worldwide and the second most common cause of cancer deaths. This study aimed to explore the inhibitory effect and mechanism of Aidi injection (ADI) combined with doxorubicin (DOX) in HCC treatment. The drug concentrations in combined threapy was determined by investigating the effect of various concentrations of ADI and DOX on the viability of H22 cells. The combination index (CI) was also calculated. A metabolomic strategy based on ultrahigh performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) platform was established to analyze the metabolites. As a result, the CI values were less than 1, indicating that the combination of ADI and DOX exerted a synergistic effect on HCC treatment. The combination of 40‰ ADI and 1 μmol/L DOX had the strongest inhibitory effect and was used for subsequent metabolomic analysis. A total of 19 metabolic markers were obtained in metabolomic analysis, including amino acids (L-glutamic acid, L-arginine, and L-tyrosine), organic acids (succinic acid and citric acid), adenosine, and hypoxanthine , etc. Compared with the treatment using DOX or ADI alone, the combined therapy further regulated the levels of metabolic markers in HCC, which may be the reason for the synergistic effect. Seven metabolic pathways were significantly enriched, including phenylalanine, tyrosine and tryptophan biosynthesis, D-glutamine and D-glutamate metabolism, alanine, aspartate and glutamate metabolism, phenylalanine metabolism, arginine biosynthesis, tricarboxylic acid (TCA) cycle, and purine metabolism. These findings demonstrated that ADI combined with DOX can effectively inhibit the viability of H22 cells, which may exert a synergistic anti-tumor effect by balancing the metabolism of amino acids and energy-related substances.

HepG2 as promising cell-based model for biosynthesis of long-term metabolites: Exemplified for metandienone

In order to detect the abuse of substances in sports, the knowledge of their metabolism is of undisputable importance. As in vivo administration of compounds faces ethical problems and might even not be applicable for nonapproved compounds, cell-based models might be a versatile tool for biotransformation studies. We coincubated HepG2 cells with metandienone and D₃ -epitestosterone for 14 days. Phase I and II metabolites were analyzed by high-performance liquid chromatography (HPLC)-tandem mass spectrometry and confirmed by gas chromatography-mass spectrometry (GC-MS). The metandienone metabolites formed by HepG2 cells were comparable with those renally excreted by humans. HepG2 cells also generated the two long-term metabolites 17β-hydroxymethyl-17α-methyl-18-nor-androst-1,4,13-trien-3-one and 17α-hydroxymethyl-17β-methyl-18-nor-androst-1,4,13-trien-3-one used in doping analyses, though in an inverse ratio compared with that observed in human urine. In conclusion, we showed that HepG2 cells are suitable as model for the investigation of biotransformation of androgens, especially for the anabolic androgenic steroid metandienone. They further proved to cover phase I and II metabolic pathways, which combined with a prolonged incubation time with metandienone resulted in the generation of its respective long-term metabolites known from in vivo metabolism. Moreover, we showed the usability of D₃ -epitestosterone as internal standard for the incubation. The method used herein appears to be suitable and advantageous compared with other models for the investigation of doping-relevant compounds, probably enabling the discovery of candidate metabolites for doping analyses.

Evaluation of metabolomics behavior of human colon cancer HT29 cell lines treated with ionic liquid graviola fruit pulp extract

ETHNOPHARMACOLOGICAL RELEVANCE

Medicinal plants have been used by indigenous people across the world for centuries to help individuals preserve their wellbeing and cure diseases. Annona muricata L. (Graviola) which is belonging to the Annonaceae family has been traditionally used due to its medicinal abilities including antimicrobial, anti-inflammatory, antioxidant and cancer cell growth inhibition. Graviola is claimed to be a potential antitumor due to its selective cytotoxicity against several cancer cell lines. However, the metabolic mechanism information underlying the anticancer activity remains limited.

AIM OF THE STUDY

This study aimed to investigate the effect of ionic liquid-Graviola fruit pulp extract (IL-GPE) on the metabolomics behavior of colon cancer (HT29) by using an untargeted GC-TOFMS-based metabolic profiling.

MATERIALS AND METHODS

Multivariate data analysis was used to determine the metabolic profiling, and the ingenuity pathway analysis (IPA) was used to predict the altered canonical pathways after treating the HT29 cells with crude IL-GPE and Taxol (positive control).

RESULTS

The principal components analysis (PCA) identified 44 metabolites with the most reliable factor loading, and the cluster analysis (CA) separated three groups of metabolites: metabolites specific to the non-treated HT29 cells, metabolites specific to the treated HT29 cells with the crude IL-GPE and metabolites specific to Taxol treatment. Pathway analysis of metabolomic profiles revealed an alteration of many metabolic pathways, including amino acid metabolism, aerobic glycolysis, urea cycle and ketone bodies metabolism that contribute to energy metabolism and cancer cell proliferation.

CONCLUSION

The crude IL-GPE can be one of the promising anticancer agents due to its selective inhibition of energy metabolism and cancer cell proliferation.

Applying metabolomics to veterinary pharmacology and therapeutics

Metabolomics is the large-scale study of low-molecular-weight substances in a biological system in a given physiological state at a given time point. Metabolomics can be applied to identify predictors of inter-individual variability in drug response, provide clinicians with data useful for decision-making processes in drug selection, and inform about the pharmacokinetics and pharmacodynamics of a drug. It is, therefore, an exceptional approach for gaining new understanding effects in the field of comparative veterinary pharmacology. However, the incorporation of metabolomics into veterinary pharmacology and toxicology is not yet widespread, and this is probably, at least in part, a result of its highly multidisciplinary nature. This article reviews the potential applications of metabolomics in veterinary pharmacology and therapeutics. It integrates key concepts for designing metabolomics studies and analyzing and interpreting metabolomics data, providing solid foundations for applying metabolomics to the study of drugs in all veterinary species.

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

Cutaneous squamous-cell carcinoma (cSCC) is one of most common type of non-black skin cancer. The malignancy degree and the death risk of cSCC patients are significantly higher than basal cell carcinoma patients. GL-V9 is a synthesized flavonoid derived from natural active ingredient wogonin and shows potent growth inhibitory effects in liver and breast cancer cells. In this study, we investigated the anti-cSCC effect and the underlying mechanism of GL-V9. The results showed that GL-V9 induced both apoptosis and autophagy in human cSCC cell line A431 cells, and prevented the growth progression of chemical induced primary skin cancer in mice. Metabolomics assay showed that GL-V9 potentially affected mitochondrial function, inhibiting glucose metabolism and Warburg effect. Further mechanism studies demonstrated that AKT played important roles in the anti-cSCC effect of GL-V9. On one hand, GL-V9 suppressed AKT-modulated mitochondrial localization of HK2 and promoted the protein degradation of HK2, resulting in cell apoptosis and glycolytic inhibition. On the other hand, GL-V9 induced autophagy via inhibiting Akt/mTOR pathway. Interestingly, though the autophagy induced by GL-V9 potentially antagonized its effect of apoptosis induction, the anti-cSCC effect of GL-V9 was not diluted. All above, our studies suggest that GL-V9 is a potent candidate for cSCC treatment.

Fast and ergonomic extraction of adherent mammalian cells for NMR-based metabolomics studies

Cellular metabolomics has become key to elucidate mechanistic aspects in various fields such as cancerology or pharmacology, and is rapidly becoming a standard phenotyping tool accessible to the broad biological community. Acquisition of reliable spectroscopic datasets, such as nuclear magnetic resonance (NMR) spectra, to characterize biological systems depends on the elaboration of robust methods for cellular metabolites extraction. Previous studies have addressed many issues raised by these protocols, however with little pondering on ergonomic and practical aspects of the methods that impact their scalability, reproducibility and hence their suitability to high-throughput studies or their use by non-metabolomics experts. Here, we optimize a fast and ergonomic protocol for extraction of metabolites from adherent mammalian cells for NMR metabolomics studies. The proposed extraction protocol, including cell washing, metabolism quenching and actual extraction of intracellular metabolites, was first optimized on HeLa cells. Efficiency of the protocol, in its globality and for the different individual steps, was assessed by NMR quantification of 27 metabolites from cellular extracts. We show that a single PBS wash provides a seemly compromise between contamination from growth medium and leakage of intracellular metabolites. In HeLa cells, extraction using pure methanol, without cell scraping, recovered a higher amount of intracellular metabolites than the reference methanol/water/chloroform method with cell scraping, with yields varying across metabolite classes. Optimized and reference protocols were further tested on eight cell lines of miscellaneous nature, and inter-operator reproducibility was demonstrated. Our results stress the need for tailored extraction protocols and show that fast protocols minimizing time-consuming steps, without compromising extraction yields, are suitable for high-throughput metabolomics studies. Graphical abstract.

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

A gas chromatography mass spectrometry (GC-MS) metabolomics protocol was modified for quenching, harvesting, and extraction of metabolites from adherent cells grown under high (20%) fetal calf serum conditions. The reproducibility of using either 50% or 80% methanol for quenching of cells was compared for sample harvest. To investigate the efficiency and reproducibility of intracellular metabolite extraction, different volumes and ratios of chloroform were tested. Additionally, we compared the use of total protein amount versus cell mass as normalization parameters. We demonstrate that the method involving 50% methanol as quenching buffer followed by an extraction step using an equal ratio of methanol:chloroform:water (1:1:1, v/v/v) followed by the collection of 6 mL polar phase for GC-MS measurement was superior to the other methods tested. Especially for large sample sets, its comparative ease of measurement leads us to recommend normalization to protein amount for the investigation of intracellular metabolites of adherent human cells grown under high (or standard) fetal calf serum conditions. To avoid bias, care should be taken beforehand to ensure that the ratio of total protein to cell number are consistent among the groups tested. For this reason, it may not be suitable where culture conditions or cell types have very different protein outputs (e.g., hypoxia vs. normoxia). The full modified protocol is available in the Supplementary Materials.

Evaluation and optimization of sample pretreatment for GC/MS-based metabolomics in embryonic zebrafish

Metabolomics tactics have been applied in the research associated with embryonic zebrafish. However, the report regarding the evaluation of impacts of sample pretreatment on metabolomics results from zebrafish embryos is limited. In the present study, different data normalization approaches, extraction solvents, and extraction strategies for off-line derivatization gas chromatography coupled with mass spectrometry-based metabolomics analysis of zebrafish eleutheroembryos were evaluated and optimized. The results showed that, when 4-chlorophenylalanine normalization, sample homogenization and pure methanol combined with ultrasonic extraction were conducted, better repeatabilities, higher signals and broader coverages of detected metabolites can be achieved. The recovery and standard deviation of most standards were in the range of 82%-121% and 6.6%-12%, respectively, while the relative standard deviation of major detected metabolites ranged from 5.4% to 19%, indicating good extraction efficiencies and method precision. Under the developed method, 87 important endogenous metabolites such as citric acid and hypoxanthine were identified by universal databases or standards among 270 extracted metabolites, which consisted of sugars, amines, amino acids, nucleotides, fatty acids, and sterols. Therefore, the results could provide a proper pretreatment protocol for the analysis of wide-coverage metabolome in embryonic zebrafish. In addition, this study highlights the impact of normalization and extraction methods on the data quality of metabolomics analysis.

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

INTRODUCTION

Patient-derived skin fibroblasts offer a unique translational model to study molecular mechanisms of multiple human diseases. Metabolomics profiling allows to track changes in a broad range of metabolites and interconnected metabolic pathways that could inform on molecular mechanisms involved in disease development and progression, and on the efficacy of therapeutic interventions. Therefore, it is important to establish standardized protocols for metabolomics analysis in human skin fibroblasts for rigorous and reliable metabolic assessment.

OBJECTIVES

We aimed to develop an optimized protocol for concurrent measure of the concentration of amino acids, acylcarnitines, and components of the tricarboxylic acid (TCA) cycle in human skin fibroblasts using gas (GC) and liquid chromatography (LC) coupled with mass spectrometry (MS).

METHODS

The suitability of four different methods of cell harvesting on the recovery of amino acids, acylcarnitines, and TCA cycle metabolites was established using GC/MS and LC/MS analytical platforms. For each method, metabolite stability was determined after 48 h, 2 weeks and 1 month of storage at - 80 °C.

RESULTS

Harvesting cells in 80% methanol solution allowed the best recovery and preservation of metabolites. Storage of samples in 80% methanol up to 1  month at - 80 °C did not significantly impact metabolite concentrations.

CONCLUSION

We developed a robust workflow for metabolomics analysis in human skin fibroblasts suitable for a high-throughput multiplatform analysis. This method allows a direct side-by-side comparison of metabolic changes in samples collected at different time that could be used for studies in large patient cohorts.

Sample Preparation and Reporting Standards for Metabolomics of Adherent Mammalian Cells

Metabolomics is an analytical technique that investigates the small molecules present within a biological system. Metabolomics of cultured cells allows profiling of the metabolic chemicals involved in a cell type-specific system and the response of that metabolome to external challenges, such as change in environment or exposure to drugs or toxins. The numerous benefits of in vitro metabolomics include a much greater control of external variables and reduced ethical concerns. There is potential for metabolomics of mammalian cells to uncover new information on mechanisms of action for drugs or toxins or to provide a more sensitive, human-specific early risk assessment in drug development or toxicology investigations. One way to achieve stronger biological outcomes from metabolomic data is via the use of these mammalian cultured cell models, particularly in a high-throughput context. With the sensitivity and quantity of data that metabolomics is able to provide, it is important to ensure that the sampling techniques have minimal interference when it comes to interpretation of any observed shifts in the metabolite profile. Here we describe a sampling procedure designed to ensure that the effects seen in metabolomic analyses are explained fully by the experimental factor and not other routine culture-specific activities.

The influence of culture media upon observed cell secretome metabolite profiles: The balance between cell viability and data interpretability

The application of metabolomics to investigating the cell secretome has garnered popularity owing to the method's large-scale data output, biochemical insight, and prospects for novel target compound discovery. However, there are no standardized protocols for the use of cell growth media, a factor that can exert profound effects upon the detected metabolites, and thus in the interpretability of the resulting data. Herein, we applied a liquid chromatography-high resolution mass spectrometry-based metabolomics approach to examine the influence of 5 different media combinations upon the obtained secretome of two phenotypically different cell lines: human embryonic kidney cells (HEK293) and L6 rat muscle cells. These media combinations were, M1: Medium 199, M2: Medium 199 + 2% fetal bovine serum (FBS), M3: Dulbecco's Modified Eagle's Medium (DMEM), M4: DMEM + 2% FBS and M5: Krebs-Henseleit Modified Buffer (KHB). The effect of incubation (37 °C) vs. refrigeration (4 °C) on DMEM medium over a 24 h period was also investigated. Results were validated for a selected panel of 5 metabolites measured from an additional cell culture experiment. Metabolomics identified a total of 53 polar metabolites that exhibited differential patterns on a cell type- and medium-specific basis. We observed that choice of media was the primary contributor to the secreted metabolite profile detected. The addition of FBS resulted in unique detected metabolites, compared to media-only controls (M199 and DMEM alone). Glutamine and pyroglutamate were more abundant in incubated relative to refrigerated DMEM medium. The overall metabolic pattern of the metabolites from the targeted approach matched with that exhibited across M1-M5 of the metabolomics experiment, and aided in further identifying the presence of compounds that were below the limit of detection in metabolomics. Based upon these findings, we highlight the following considerations in designing a cell secretome-based metabolite profiling experiment: (1) multiple media combinations (with and without FBS) should be tested for each cell line to be investigated; (2) cell-free media combinations should be plated separately, and incubated/treated in the same experimental conditions as the cells; and (3) a compromise between cell death and metabolite detection should be identified in order to avoid batch-specific contributions from FBS supplementation.

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

Metabolomics is an analytical technique that investigates the small biochemical molecules present within a biological sample isolated from a plant, animal, or cultured cells. It can be an extremely powerful tool in elucidating the specific metabolic changes within a biological system in response to an environmental challenge such as disease, infection, drugs, or toxins. A historically difficult step in the metabolomics pipeline is in data interpretation to a meaningful biological context, for such high-variability biological samples and in untargeted metabolomics studies that are hypothesis-generating by design. One way to achieve stronger biological context of metabolomic data is via the use of cultured cell models, particularly for mammalian biological systems. The benefits of in vitro metabolomics include a much greater control of external variables and no ethical concerns. The current concerns are with inconsistencies in experimental procedures and level of reporting standards between different studies. This review discusses some of these discrepancies between recent studies, such as metabolite extraction and data normalisation. The aim of this review is to highlight the importance of a standardised experimental approach to any cultured cell metabolomics study and suggests an example procedure fully inclusive of information that should be disclosed in regard to the cell type/s used and their culture conditions. Metabolomics of cultured cells has the potential to uncover previously unknown information about cell biology, functions and response mechanisms, and so the accurate biological interpretation of the data produced and its ability to be compared to other studies should be considered vitally important.

Quantitative NMR analysis of intra- and extracellular metabolism of mammalian cells: A tutorial

Metabolomics analysis of body fluids as well as cells is depended on many factors. While several well-accepted standard operating procedures for the analysis of body fluids are available, the NMR based quantitative analysis of cellular metabolites is less well standardized. Experimental designs depend on the cell type, the quenching protocol and the applied post-acquisition workflow. Here, we provide a tutorial for the quantitative description of the metabolic phenotype of mammalian cells using NMR spectroscopy. We discuss all key steps of the process, starting from the selection of the appropriate culture medium, quenching techniques to arrest metabolism in a reproducible manner, the extraction of the intracellular components and the profiling of the culture medium. NMR data acquisition and methods for both qualitative and quantitative analysis are also provided. The suggested methods cover experiments for adherent cells and cells in suspension. We ultimately describe the application of the discussed workflow to a thyroid cancer cell line. Although this tutorial focuses on mammalian cells, the given guidelines and procedures may be adjusted for the analysis of other cell types.

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

Metabolome analyses are a suite of analytical approaches that enable us to capture changes in the metabolome (small molecular weight components, typically less than 1500 Da) in biological systems. Mass spectrometry (MS) has been widely used for this purpose. The key challenge here is to be able to capture changes in a reproducible and reliant manner that is representative of the events that take place in vivo Typically, the analysis is carried out in vitro, by isolating the system and extracting the metabolome. MS-based approaches enable us to capture metabolomic changes with high sensitivity and resolution. When developing the technique for different biological systems, there are similarities in challenges and differences that are specific to the system under investigation. Here, we review some of the challenges in capturing quantitative changes in the metabolome with MS based approaches, primarily in microbial and mammalian systems.This article is part of the themed issue 'Quantitative mass spectrometry'.

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

INTRODUCTION

Although 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.

OBJECTIVES

We 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.

METHODS

We 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.

RESULTS

We 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.

CONCLUSION

We 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.

Sample normalization methods in quantitative metabolomics

To reveal metabolomic changes caused by a biological event in quantitative metabolomics, it is critical to use an analytical tool that can perform accurate and precise quantification to examine the true concentration differences of individual metabolites found in different samples. A number of steps are involved in metabolomic analysis including pre-analytical work (e.g., sample collection and storage), analytical work (e.g., sample analysis) and data analysis (e.g., feature extraction and quantification). Each one of them can influence the quantitative results significantly and thus should be performed with great care. Among them, the total sample amount or concentration of metabolites can be significantly different from one sample to another. Thus, it is critical to reduce or eliminate the effect of total sample amount variation on quantification of individual metabolites. In this review, we describe the importance of sample normalization in the analytical workflow with a focus on mass spectrometry (MS)-based platforms, discuss a number of methods recently reported in the literature and comment on their applicability in real world metabolomics applications. Sample normalization has been sometimes ignored in metabolomics, partially due to the lack of a convenient means of performing sample normalization. We show that several methods are now available and sample normalization should be performed in quantitative metabolomics where the analyzed samples have significant variations in total sample amounts.

Analytical methodology for metabolomics study of adherent mammalian cells using NMR, GC-MS and LC-HRMS

We developed a methodology for the analysis of intracellular metabolites using nuclear magnetic resonance spectrometry (NMR), gas-chromatography coupled with mass spectrometry (GC-MS), and liquid chromatography coupled with high resolution mass spectrometry (LC-HRMS). The main steps for analysis of adherent cells in order to recover the widest possible range of intracellular compounds are blocking metabolic activity by quenching and extraction of intracellular metabolites. We explored three protocols to quench NSC-34 cell metabolism and four different extraction methods, analyzed by NMR. On the basis of the number of metabolites extracted and their relative standard deviation (RSD) analyzed by NMR, the most reproducible protocol [quenching by MeOH at -40 °C and extraction with CH2Cl2/MeOH/H2O (3:3:2)] was used to obtain intracellular media to be analyzed by GC-MS and LC-HRMS. GC-MS analysis was optimized by three oximation procedures followed by silylation derivatization and these were compared to silylation alone. Using reversed-phase liquid chromatography (C18), four different gradients for LC-MS were compared. The analytical protocols were determined to establish the reliability and suitability of sample treatments required to achieve the correct biological analysis of untargeted mammalian cell metabolomics.

Metabolomics of adherent mammalian cells by capillary electrophoresis-mass spectrometry: HT-29 cells as case study

In this work, the optimization of an effective protocol for cell metabolomics is described with special emphasis in the sample preparation and subsequent analysis of intracellular metabolites from adherent mammalian cells by capillary electrophoresis-mass spectrometry. As case study, colon cancer HT-29 cells, a human cell model to investigate colon cancer, are employed. The feasibility of the whole method for cell metabolomics is demonstrated via a fast and sensitive profiling of the intracellular metabolites HT-29 cells by capillary electrophoresis-time-of-flight mass spectrometry (CE-TOF MS). The suitability of this methodology is further corroborated through the examination of the metabolic changes in the polyamines pathway produced in colon cancer HT-29 cells by difluoromethylornithine (DFMO), a known potent ornithine decarboxylase inhibitor. The selection of the optimum extraction conditions allowed a higher sample volume injection that led to an increase in CE-TOF MS sensitivity. Following a non-targeted metabolomics approach, 10 metabolites (namely, putrescine, ornithine, gamma-aminobutyric acid (GABA), oxidized and reduced glutathione, 5'-deoxy-5'-(methylthio)adenosine, N-acetylputrescine, cysteinyl-glycine, spermidine and an unknown compound) were found to be significantly altered by DFMO (p<0.05) in HT-29 cells. In addition to the effect of DFMO on polyamine metabolism, minor modifications of other metabolic pathways (e.g., related to intracellular thiol redox state) were observed.

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

In order to preserve the in vivo metabolite levels of cells, a quenching protocol must be quickly executed to avoid degradation of labile metabolites either chemically or biologically. In the case of mammalian cell cultures cultivated in complex media, a wash step previous to quenching is necessary to avoid contamination of the cell pellet with extracellular metabolites, which could distort the real intracellular concentration of metabolites. This is typically achieved either by one or multiple centrifugation/wash steps which delay the time until quenching (even harsh centrifugation requires several minutes for processing until the cells are quenched) or filtration. In this article, we describe and evaluate a two-step optimized protocol based on fast filtration by use of a vacuum pump for quenching and subsequent extraction of intracellular metabolites from CHO (Chinese hamster ovary) suspension cells, which uses commercially available components. The method allows transfer of washed cells into liquid nitrogen within 10-15s of sampling and recovers the entire extraction solution volume. It also has the advantage to remove residual filter filaments in the final sample, thus preventing damage to separation columns during subsequent MS analysis. Relative to other methods currently used in the literature, the resulting energy charge of intracellular adenosine nucleotides was increased to 0.94 compared to 0.90 with cold PBS quenching or 0.82 with cold methanol/AMBIC quenching.

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

Metabolomics is a rapidly advancing field, and much of our understanding of the subject has come from research on cell lines. However, the results and interpretation of such studies depend on appropriate normalization of the data; ineffective or poorly chosen normalization methods can lead to frankly erroneous conclusions. That is a recurrent challenge because robust, reliable methods for normalization of data from cells have not been established. In this study, we have compared several methods for normalization of metabolomic data from cell extracts. Total protein concentration, cell count, and DNA concentration exhibited strong linear correlations with seeded cell number, but DNA concentration was found to be the most generally useful method for the following reasons: (1) DNA concentration showed the greatest consistency across a range of cell numbers; (2) DNA concentration was the closest to proportional with cell number; (3) DNA samples could be collected from the same dish as the metabolites; and (4) cell lines that grew in clumps were difficult to count accurately. We therefore conclude that DNA concentration is a widely applicable method for normalizing metabolomic data from adherent cell lines.

GC/TOFMS analysis of metabolites in serum and urine reveals metabolic perturbation of TCA cycle in db/db mice involved in diabetic nephropathy

Early diagnosis of diabetic nephropathy (DN) is difficult although it is of crucial importance to prevent its development. To probe potential markers and the underlying mechanism of DN, an animal model of DN, the db/db mice, was used and serum and urine metabolites were profiled using gas chromatography/time-of-flight mass spectrometry. Metabolic patterns were evaluated based on serum and urine data. Principal component analysis of the data revealed an obvious metabonomic difference between db/db mice and controls, and db/db mice showed distinctly different metabolic patterns during the progression from diabetes to early, medium, and later DN. The identified metabolites discriminating between db/db mice and controls suggested that db/db mice have perturbations in the tricarboxylic acid cycle (TCA, citrate, malate, succinate, and aconitate), lipid metabolism, glycolysis, and amino acid turnover. The db/db mice were characterized by acidic urine, high TCA intermediates in serum at week 6 and a sharp decline thereafter, and gradual elevation of free fatty acids in the serum. The sharp drop of serum TCA intermediates from week 6 to 8 indicated the downregulated glycolysis and insulin resistance. However, urinary TCA intermediates did not decrease in parallel with those in the serum from week 6 to 10, and an increased portion of TCA intermediates in the serum was excreted into the urine at 8, 10, and 12 wk than at 6 wk, indicating kidney dysfunction occurred. The relative abundances of TCA intermediates in urine relative to those in serum were suggested as an index of renal damage.

Mammalian cell metabolomics: experimental design and sample preparation

Metabolomics represents the global assessment of metabolites in a biological sample and reports the closest information to the phenotype of the biological system under study. Mammalian cell metabolomics has emerged as a promising tool with potential applications in many biotechnology and research areas. Metabolomics workflow includes experimental design, sampling, sample processing, metabolite analysis, and data processing. Given their influence on metabolite content and biological interpretation of data, a good experimental design and the appropriate choice of a sample processing method are prerequisites for success in any metabolomic study. The use of mammalian cells in the metabolomics field involves harder sample processing methods, including metabolism quenching and metabolite extraction, as compared to the use of body fluids, although such critical issues are frequently overlooked. This review aims to overview the common experimental procedures used in mammalian cell metabolomics based on mass spectrometry, by placing special emphasis on discussing sample preparation approaches, although other aspects, such as cell metabolomics applications, culture systems, cellular models, analytical platforms, and data analysis, are also briefly covered. This review intends to be a helpful tool to assist researchers in addressing decisions when planning a metabolomics study involving the use of mammalian cells.

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

Continuous exposure of breast cancer cells to adriamycin induces high expression of P-gp and multiple drug resistance. However, the biochemical process and the underlying mechanisms for the gradually induced resistance are not clear. To explore the underlying mechanism and evaluate the anti-tumor effect and resistance of adriamycin, the drug-sensitive MCF-7S and the drug-resistant MCF-7Adr breast cancer cells were used and treated with adriamycin, and the intracellular metabolites were profiled using gas chromatography mass spectrometry. Principal components analysis of the data revealed that the two cell lines showed distinctly different metabolic responses to adriamycin. Adriamycin exposure significantly altered metabolic pattern of MCF-7S cells, which gradually became similar to the pattern of MCF-7Adr, indicating that metabolic shifts were involved in adriamycin resistance. Many intracellular metabolites involved in various metabolic pathways were significantly modulated by adriamycin treatment in the drug-sensitive MCF-7S cells, but were much less affected in the drug-resistant MCF-7Adr cells. Adriamycin treatment markedly depressed the biosynthesis of proteins, purines, pyrimidines and glutathione, and glycolysis, while it enhanced glycerol metabolism of MCF-7S cells. The elevated glycerol metabolism and down-regulated glutathione biosynthesis suggested an increased reactive oxygen species (ROS) generation and a weakened ability to balance ROS, respectively. Further studies revealed that adriamycin increased ROS and up-regulated P-gp in MCF-7S cells, which could be reversed by N-acetylcysteine treatment. It is suggested that adriamycin resistance is involved in slowed metabolism and aggravated oxidative stress. Assessment of cellular metabolomics and metabolic markers may be used to evaluate anti-tumor effects and to screen for candidate anti-tumor agents.