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

Enantioselective toxicity effect and mechanisms of bifenthrin enantiomers on normal human hepatocytes

In recent decades, the toxicity of chiral pesticides to non-target organisms has attracted increasing attention. Cellular metabolic disorders are essential sensitive molecular initiating event for toxicological effects. BF is a typical chiral pesticide, and the liver is the main organ for BF accumulation. This study aimed to investigate the potential molecular mechanism of BF enantiomers' different toxic effects on L02 by a non-targeted metabolomic approach. Results revealed that the BF enantiomers exhibited different metabolic responses. In total, 51 and 36 differential metabolites were perturbed by 1S-cis-BF and 1R-cis-BF at the value of variable importance, respectively. When L02 were exposed to 1R-cis-BF, the significantly disturbed metabolic pathways were nicotinate and nicotinamide metabolism and pyrimidine metabolism. By comparison, more significantly perturbed metabolic pathways were received when the L02 were exposed to 1S-cis-BF, including glycine, serine and threonine metabolism, nicotinate and nicotinamide metabolism, arginine and proline metabolism, cysteine and methionine metabolism, glycerolipid metabolism, histidine metabolism, pyrimidine metabolism, amino sugar and nucleotide sugar metabolism and arginine biosynthesis. The results offer a new perspective in understanding the role of selective cytotoxicity of BF enantiomers, and help to evaluate the risk to human health at the enantiomeric level.

1H NMR spectroscopic characterisation of HepG2 cells as a model metabolic system for toxicology studies

The immortalised human hepatocellular HepG2 cell line is commonly used for toxicology studies as an alternative to animal testing due to its characteristic liver-distinctive functions. However, little is known about the baseline metabolic changes within these cells upon toxin exposure. We have applied 1H Nuclear Magnetic Resonance (NMR) spectroscopy to characterise the biochemical composition of HepG2 cells at baseline and post-exposure to hydrogen peroxide (H2O2). Metabolic profiles of live cells, cell extracts, and their spent media supernatants were obtained using 1H high-resolution magic angle spinning (HR-MAS) NMR and 1H NMR spectroscopic techniques. Orthogonal partial least squares discriminant analysis (O-PLS-DA) was used to characterise the metabolites that differed between the baseline and H2O2 treated groups. The results showed that H2O2 caused alterations to 10 metabolites, including acetate, glutamate, lipids, phosphocholine, and creatine in the live cells; 25 metabolites, including acetate, alanine, adenosine diphosphate (ADP), aspartate, citrate, creatine, glucose, glutamine, glutathione, and lactate in the cell extracts, and 22 metabolites, including acetate, alanine, formate, glucose, pyruvate, phenylalanine, threonine, tryptophan, tyrosine, and valine in the cell supernatants. At least 10 biochemical pathways associated with these metabolites were disrupted upon toxin exposure, including those involved in energy, lipid, and amino acid metabolism. Our findings illustrate the ability of NMR-based metabolic profiling of immortalised human cells to detect metabolic effects on central metabolism due to toxin exposure. The established data sets will enable more subtle biochemical changes in the HepG2 model cell system to be identified in future toxicity testing.

Thyroid cancer cell metabolism: A glance into cell culture system-based metabolomics approaches

Thyroid cancer is the most common malignancy of the endocrine system and the seventh most prevalent cancer in women worldwide. It is a complex and diverse disease characterized by heterogeneity, underscoring the importance of understanding the underlying metabolic alterations within tumor cells. Metabolomics technologies offer a powerful toolset to explore and identify endogenous and exogenous biochemical reaction products, providing crucial insights into the intricate metabolic pathways and processes within living cells. Metabolism plays a central role in cell function, making metabolomics a valuable reflection of a cell's phenotype. In the OMICs era, metabolomics analysis of cells brings numerous advantages over existing methods, propelling cell metabolomics as an emerging field with vast potential for investigating metabolic pathways and their perturbation in pathophysiological conditions. This review article aims to look into recent developments in applying metabolomics for characterizing and interpreting the cellular metabolome in thyroid cancer cell lines, exploring their unique metabolic characteristics. Understanding the metabolic alterations in tumor cells can lead to the identification of critical nodes in the metabolic network that could be targeted for therapeutic intervention.

Application and prospect of metabolomics in the early diagnosis of osteoporosis: a narrative review

This paper reviews the application of metabolomics in the early diagnosis of osteoporosis in recent years. The authors searched electronic databases for the keywords "metabolomics", "osteoporosis" and "biomarkers", then analyzed the relationship between functional markers and osteoporosis using categorical summarization. Lipid metabolism, amino acid metabolism and energy metabolism are closely related to osteoporosis development and can become early diagnostic markers of the condition. However, the existing studies in metabolomics suffer from varying application methods, difficulty in identifying isomers, small study cohorts and insufficient research on metabolic mechanisms. Consequently, it is important for future research to focus on broadening and standardizing the scope of the application of metabolomics. High-quality studies on a large scale should also be conducted while promoting the early diagnosis of osteoporosis in a more precise, comprehensive and sensitive manner.

Optimal LC-MS metabolomic profiling reveals emergent changes to monocyte metabolism in response to lipopolysaccharide

Introduction

Immunometabolism examines the links between immune cell function and metabolism. Dysregulation of immune cell metabolism is now an established feature of innate immune cell activation. Advances in liquid chromatography mass spectrometry (LC-MS) technologies have allowed discovery of unique insights into cellular metabolomics. Here we have studied and compared different sample preparation techniques and data normalisation methods described in the literature when applied to metabolomic profiling of human monocytes.

Methods

Primary monocytes stimulated with lipopolysaccharide (LPS) for four hours was used as a study model. Monocytes (n=24) were freshly isolated from whole blood and stimulated for four hours with lipopolysaccharide (LPS). A methanol-based extraction protocol was developed and metabolomic profiling carried out using a Hydrophilic Interaction Liquid Chromatography (HILIC) LC-MS method. Data analysis pipelines used both targeted and untargeted approaches, and over 40 different data normalisation techniques to account for technical and biological variation were examined. Cytokine levels in supernatants were measured by ELISA.

Results

This method provided broad coverage of the monocyte metabolome. The most efficient and consistent normalisation method was measurement of residual protein in the metabolite fraction, which was further validated and optimised using a commercial kit. Alterations to the monocyte metabolome in response to LPS can be detected as early as four hours post stimulation. Broad and profound changes in monocyte metabolism were seen, in line with increased cytokine production. Elevated levels of amino acids and Krebs cycle metabolites were noted and decreases in aspartate and β-alanine are also reported for the first time. In the untargeted analysis, 154 metabolite entities were significantly altered compared to unstimulated cells. Pathway analysis revealed the most prominent changes occurred to (phospho-) inositol metabolism, glycolysis, and the pentose phosphate pathway.

Discussion

These data report the emergent changes to monocyte metabolism in response to LPS, in line with reports from later time points. A number of these metabolites are reported to alter inflammatory gene expression, which may facilitate the increases in cytokine production. Further validation is needed to confirm the link between metabolic activation and upregulation of inflammatory responses.

Identification of biomarkers associated with the feed efficiency by metabolomics profiling: results from the broiler lines divergent for high or low abdominal fat content

Background

Improving feed efficiency (FE) is one of the main objectives in broiler breeding. It is difficult to directly measure FE traits, and breeders hence have been trying to identify biomarkers for the indirect selection and improvement of FE traits. Metabolome is the "bridge" between genome and phenome. The metabolites may potentially account for more of the phenotypic variation and can suitably serve as biomarkers for selecting FE traits. This study aimed to identify plasma metabolite markers for selecting high-FE broilers. A total of 441 birds from Northeast Agricultural University broiler lines divergently selected for abdominal fat content were used to analyze plasma metabolome and estimate the genetic parameters of differentially expressed metabolites.

Results

The results identified 124 differentially expressed plasma metabolites (P < 0.05) between the lean line (high-FE birds) and the fat line (low-FE birds). Among these differentially expressed plasma metabolites, 44 were found to have higher positive or negative genetic correlations with FE traits (|r_g| ≥ 0.30). Of these 44 metabolites, 14 were found to display moderate to high heritability estimates (h² ≥ 0.20). However, among the 14 metabolites, 4 metabolites whose physiological functions have not been reported were excluded. Ultimately, 10 metabolites were suggested to serve as the potential biomarkers for breeding the high-FE broilers. Based on the physiological functions of these metabolites, reducing inflammatory and improving immunity were proposed to improve FE and increase production efficiency.

Conclusions

According to the pipeline for the selection of the metabolite markers established in this study, it was suggested that 10 metabolites including 7-ketocholesterol, dimethyl sulfone, epsilon-(gamma-glutamyl)-lysine, gamma-glutamyltyrosine, 2-oxoadipic acid, L-homoarginine, testosterone, adenosine 5'-monophosphate, adrenic acid, and calcitriol could be used as the potential biomarkers for breeding the "food-saving broilers".

Therapeutic Effects of Salvianolic Acid B on Angiotensin II-Induced Atrial Fibrosis by Regulating Atrium Metabolism via Targeting AMPK/FoxO1/miR-148a-3p Axis

The present study highlights the effects of salvianolic acid B (Sal B) on angiotensin II (Ang II)-activated atrial fibroblasts as well as the associated potential mechanism from the metabonomics perspective. Metabolic profile analysis performed an optimal separation of the Ang II and control group, indicating a recovery impact of Sal B on Ang II-activated fibroblasts (FBs). We found that metabolite levels in the Ang II + Sal B group were reversed to normal. Moreover, 23 significant metabolites were identified. Metabolic network analysis indicated that these metabolites participated in purine metabolism and FoxO signaling pathway. We found that Sal B activated AMP-activated protein kinase (AMPK) phosphorylation, which further promoted FoxO1 activation and increased miR-148a-3p level. We further verified that Sal B modulate the abnormal AMP, phosphocreatine, glutathione (GSH), and reactive oxygen species (ROS) production in Ang II-stimulated FBs. Collectively, Sal B can protect the Ang II-activated FBs from fibrosis and oxidative stress via AMPK/FoxO1/miRNA-148a-3p axis.

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.

Metabolomics in asthma: A platform for discovery

Asthma, characterized by airway hyperresponsiveness, inflammation and remodeling, is a chronic airway disease with complex etiology. Severe asthma is characterized by frequent exacerbations and poor therapeutic response to conventional asthma therapy. A clear understanding of cellular and molecular mechanisms of asthma is critical for the discovery of novel targets for optimal therapeutic control of asthma. Metabolomics is emerging as a powerful tool to elucidate novel disease mechanisms in a variety of diseases. In this review, we summarize the current status of knowledge in asthma metabolomics at systemic and cellular levels. The findings demonstrate that various metabolic pathways, related to energy metabolism, macromolecular biosynthesis and redox signaling, are differentially modulated in asthma. Airway smooth muscle cell plays pivotal roles in asthma by contributing to airway hyperreactivity, inflammatory mediator release and remodeling. We posit that metabolomic profiling of airway structural cells, including airway smooth muscle cells, will shed light on molecular mechanisms of asthma and airway hyperresponsiveness and help identify novel therapeutic targets.

Intracellular and extracellular untargeted metabolomics reveal the effect of acute uranium exposure in HK-2 cells

Uranium exposure poses a serious threat to the health of occupational populations and the public. Although metabolomics is a promising research approach to study the toxicological mechanisms of uranium exposure, in vitro studies using human cells are scarce. Applying cultured cell metabolomics, we exhaustively analyzed the intracellular and extracellular differential metabolites upon uranium exposure and characterized the possible biological effects of uranium exposure on human kidney cells. Uranium exposure significantly induced disturbance in the amino acid biosynthesis and linoleic acid metabolism of the cells. Cells exposed to uranium produce excessive amounts of arachidonic acid, which has the potential to cause oxidative stress and damage cells. The results provide new evidence for an oxidative stress mechanism of uranium-induced renal cell injury. Cell metabolomics has proven to be a useful diagnostic tool to study the molecular mechanisms of uranium poisoning.

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.

DNA-DAPI Interaction-Based Method for Cell Proliferation Rate Evaluation in 3D Structures

Effective cell number monitoring throughout the three-dimensional (3D) scaffold is a key factor in tissue engineering. There are many methods developed to evaluate cell number in 2D environments; however, they often encounter limitations in 3D. Therefore, there is a demand for reliable methods to measure cell proliferation in 3D surroundings. Here, we report a novel technique for the DNA content-based evaluation of cell proliferation using DNA-binding dye DAPI. We demonstrated the method's compatibility with four different cell cultures: cancer lines MCF-7 and MH-22a, embryonic fibroblast cell line Swiss 3T3, and primary mesenchymal stem cell culture isolated from rat's incisors. The DAPI based method was able to successfully evaluate cell proliferation in 2D, 2.5D, and 3D environments. Even though the proposed method does not discriminate between viable and dead cells, it might give a convenient snapshot of the cell number at a given time point. This should help to more reliably evaluate various processes proceeding in 2.5D and 3D cultures.

Comprehensive Metabolomic Analysis Reveals Dynamic Metabolic Reprogramming in Hep3B Cells with Aflatoxin B1 Exposure

Hepatitis B virus (HBV) infection and aflatoxin B1 (AFB1) exposure have been recognized as independent risk factors for the occurrence and development of hepatocellular carcinoma (HCC), but their combined impacts and the potential metabolic mechanisms remain poorly characterized. Here, a comprehensive non-targeted metabolomic study was performed following AFB1 exposed to Hep3B cells at two different doses: 16 μM and 32 μM. The metabolites were identified and quantified by an ultra-performance liquid chromatography-mass spectrometry (UPLC-MS)-based strategy. A total of 2679 metabolites were identified, and 392 differential metabolites were quantified among three groups. Pathway analysis indicated that dynamic metabolic reprogramming was induced by AFB1 and various pathways changed significantly, including purine and pyrimidine metabolism, hexosamine pathway and sialylation, fatty acid synthesis and oxidation, glycerophospholipid metabolism, tricarboxylic acid (TCA) cycle, glycolysis, and amino acid metabolism. To the best of our knowledge, the alteration of purine and pyrimidine metabolism and decrease of hexosamine pathways and sialylation with AFB1 exposure have not been reported. The results indicated that our metabolomic strategy is powerful to investigate the metabolome change of any stimulates due to its high sensitivity, high resolution, rapid separation, and good metabolome coverage. Besides, these findings provide an overview of the metabolic mechanisms of the AFB1 combined with HBV and new insight into the toxicological mechanism of AFB1. Thus, targeting these metabolic pathways may be an approach to prevent carcinogen-induced cancer, and these findings may provide potential drug targets for therapeutic intervention.

Unraveling the Extracellular Metabolism of Immortalized Hippocampal Neurons Under Normal Growth Conditions

Metabolomic profiling of cell lines has shown many potential applications and advantages compared to animal models and human subjects, and an accurate cellular metabolite analysis is critical to understanding both the intracellular and extracellular environments in cell culture. This study provides a fast protocol to investigate in vitro metabolites of immortalized hippocampal neurons HN9.10e with minimal perturbation of the cell system using a targeted approach. HN9.10e neurons represent a reliable model of one of the most vulnerable regions of the central nervous system. Here, the assessment of their extracellular metabolic profile was performed by studying the cell culture medium before and after cell growth under standard conditions. The targeted analysis was performed by a direct, easy, high-throughput reversed-phase liquid chromatography with diode array detector (RP-HPLC-DAD) method and by headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) for the study of volatile organic compounds (VOCs). The analysis of six different batches of cells has allowed to investigate the metabolic reproducibility of neuronal cells and to describe the metabolic "starting" conditions that are mandatory for a well-grounded interpretation of the results of any following cellular treatment. An accurate study of the metabolic profile of the HN9.10e cell line has never been performed before, and it could represent a quality parameter before any other targeting assay or further exploration.

Metabolic Abnormalities in Patients with Chronic Disorders of Consciousness

The vegetative state (VS) and minimally conscious state (MCS) are two major types of chronic disorders of consciousness (DoC). The assessment of these two consciousness states generally relies on the Coma Recovery Scale-Revised (CRS-R) score, but a high misdiagnosis rate limits the generalized use of this score. To identify metabolites in human plasma that can accurately distinguish VS from MCS patients, comprehensive plasma metabolic profiles were obtained with targeted metabolomics analysis and untargeted and targeted lipidomics analysis. Univariate and multivariate analyses were used to assess the significance of differences. Compared with healthy controls (HCs), the DoC groups, Emerged from Minimally Conscious State (EMCS) group and Alzheimer’s disease (AD) group had significantly different metabolic profiles. Purine metabolism pathway differed the most between the DoC (MCS and VS) and HC groups. In this pathway, adenosine, ADP, and AMP, which are the derived products of ATP degradation, were decreased in the MCS and VS groups compared to healthy controls. More importantly, we identified certain lipids for which the levels were enriched in the VS or MCS groups. Specifically, phosphatidylcholine, (38:5)-H (PC(38:5)-H), and arachidonic acid (AA) differed substantially between the VS and MCS groups and may be used to distinguish these two groups of patients. Together, our findings suggest that metabolic profiling is significantly altered in patients with chronic DoC.

Considerations for using isolated cell systems to understand cardiac metabolism and biology

Changes in myocardial metabolic activity are fundamentally linked to cardiac health and remodeling. Primary cardiomyocytes, induced pluripotent stem cell-derived cardiomyocytes, and transformed cardiomyocyte cell lines are common models used to understand how (patho)physiological conditions or stimuli contribute to changes in cardiac metabolism. These cell models are helpful also for defining metabolic mechanisms of cardiac dysfunction and remodeling. Although technical advances have improved our capacity to measure cardiomyocyte metabolism, there is often heterogeneity in metabolic assay protocols and cell models, which could hinder data interpretation and discernment of the mechanisms of cardiac (patho)physiology. In this review, we discuss considerations for integrating cardiomyocyte cell models with techniques that have become relatively common in the field, such as respirometry and extracellular flux analysis. Furthermore, we provide overviews of metabolic assays that complement XF analyses and that provide information on not only catabolic pathway activity, but biosynthetic pathway activity and redox status as well. Cultivating a more widespread understanding of the advantages and limitations of metabolic measurements in cardiomyocyte cell models will continue to be essential for the development of coherent metabolic mechanisms of cardiac health and pathophysiology.

Development of an LC-MS Targeted Metabolomics Methodology to Study Proline Metabolism in Mammalian Cell Cultures

A growing interest in metabolomics studies of cultured cells requires development not only untargeted methods capable of fingerprinting the complete metabolite profile but also targeted methods enabling the precise and accurate determination of a selected group of metabolites. Proline metabolism affects many crucial processes at the cellular level, including collagen biosynthesis, redox balance, energetic processes as well as intracellular signaling. The study aimed to develop a robust and easy-to-use targeted metabolomics method for the determination of the intracellular level of proline and the other two amino acids closely related to proline metabolism: glutamic acid and arginine. The method employs hydrophilic interaction liquid chromatography followed by high-resolution, accurate-mass mass spectrometry for reliable detection and quantification of the target metabolites in cell lysates. The sample preparation consisted of quenching by the addition of ice-cold methanol and subsequent cell scraping into a quenching solution. The method validation showed acceptable linearity (r > 0.995), precision (%RSD < 15%), and accuracy (88.5–108.5%). Pilot research using HaCaT spontaneously immortalized human keratinocytes in a model for wound healing was performed, indicating the usefulness of the method in studies of disturbances in proline metabolism. The developed method addresses the need to determine the intracellular concentration of three key amino acids and can be used routinely in targeted mammalian cell culture metabolomics research.

Metabolomic Approaches to Study Chemical Exposure-Related Metabolism Alterations in Mammalian Cell Cultures

Biological organisms are constantly exposed to an immense repertoire of molecules that cover environmental or food-derived molecules and drugs, triggering a continuous flow of stimuli-dependent adaptations. The diversity of these chemicals as well as their concentrations contribute to the multiplicity of induced effects, including activation, stimulation, or inhibition of physiological processes and toxicity. Metabolism, as the foremost phenotype and manifestation of life, has proven to be immensely sensitive and highly adaptive to chemical stimuli. Therefore, studying the effect of endo- or xenobiotics over cellular metabolism delivers valuable knowledge to apprehend potential cellular activity of individual molecules and evaluate their acute or chronic benefits and toxicity. The development of modern metabolomics technologies such as mass spectrometry or nuclear magnetic resonance spectroscopy now offers unprecedented solutions for the rapid and efficient determination of metabolic profiles of cells and more complex biological systems. Combined with the availability of well-established cell culture techniques, these analytical methods appear perfectly suited to determine the biological activity and estimate the positive and negative effects of chemicals in a variety of cell types and models, even at hardly detectable concentrations. Metabolic phenotypes can be estimated from studying intracellular metabolites at homeostasis in vivo, while in vitro cell cultures provide additional access to metabolites exchanged with growth media. This article discusses analytical solutions available for metabolic phenotyping of cell culture metabolism as well as the general metabolomics workflow suitable for testing the biological activity of molecular compounds. We emphasize how metabolic profiling of cell supernatants and intracellular extracts can deliver valuable and complementary insights for evaluating the effects of xenobiotics on cellular metabolism. We note that the concepts and methods discussed primarily for xenobiotics exposure are widely applicable to drug testing in general, including endobiotics that cover active metabolites, nutrients, peptides and proteins, cytokines, hormones, vitamins, etc.

Cell metabolomics to study the function mechanism of Cyperus rotundus L. on triple-negative breast cancer cells

BACKGROUND

Triple-negative breast cancer (TNBC) is a kind of malignant tumor with higher recurrence and metastasis rate. According to historical records, the dry rhizomes Cyperus rotundus L. could be ground into powder and mixed with ginger juice and wine for external application for breast cancer. We studied the effect of the ethanol extract of Cyperus rotundus L. (EECR) on TNBC cells and found its' apoptosis-inducing effect with a dose-relationship. But the function mechanism of EECR on TNBC is still mysterious. Hence, the present research aimed to detect its function mechanism at the small molecule level through ultra-high performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry (UPLC-Q-TOF-MS/MS) metabolomics.

METHODS

The CCK-8 assay and the Annexin V-FITC/PI assay were applied to test the effect of EECR on MDA-MB-231 cells and MDA-MB 468 cells at various concentrations of 0, 200, 400, and 600 μg/ml. UPLC-Q-TOF-MS/MS based metabolomics was used between the control group and the EECR treatment groups. Multivariate statistical analysis was used to visualize the apoptosis-inducing action of EECR and filtrate significantly changed metabolites.

RESULTS

The apoptosis-inducing action was confirmed and forty-nine significantly changed metabolites (VIP > 1, p < 0.05, and FC > 1.2 or FC < 0.8) were identified after the interference of EECR. The level of significant differential metabolites between control group, middle dose group, and high dose group were compared and found that which supported the apoptosis-inducing action with dose-dependence.

CONCLUSION

By means of metabolism, we have detected the mechanism of EECR inducing apoptosis of TNBC cells at the level of small molecule metabolites and found that EECR impacted the energy metabolism of TNBC cells. In addition, we concluded that EECR induced apoptosis by breaking the balance between ATP-production and ATP-consumption: arresting the pathways of Carbohydrate metabolism such as Central carbon metabolism in cancer, aerobic glycolysis, and Amino sugar and nucleotide sugar metabolism, whereas accelerating the pathways of ATP-consumption including Amino Acids metabolism, Fatty acid metabolism, Riboflavin metabolism and Purine metabolism. Although further study is still needed, EECR has great potential in the clinical treatment of TNBC with fewer toxic and side effects.

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.

Effects of harvesting and extraction methods on metabolite recovery from adherently growing mammalian cells

With the wide application of cell metabolomics in many research areas, there is a need to develop an effective procedure for adherent mammalian cell metabolomics that allows for accurate determination of intracellular metabolite levels and easy comparison between multiple studies of a similar application. Here we aimed to compare the efficiencies of different cell harvesting methods and metabolite extraction methods in sample preparation procedures, and to provide a cell sample processing protocol which focuses on maximizing metabolite recovery ranging from polar to lipidic ones. A systematical evaluation of 4 cell harvesting methods and 4 extraction methods was conducted based on human hepatoma HepG2 cells. The impact of different methods on the recoveries of 11 different categories of metabolites was further investigated. The water disruption sample harvesting method provided superior performance to the other 3 harvesting methods, trypsinization, scraping in phosphate buffered saline, and direct solvent scraping, with respect to the recoveries of polar metabolites and lipids. Among the 4 extraction methods, the novel two-phase solvent system extraction method with both methyl tert-butyl ether (MTBE) and 75% 9 : 1 methanol : chloroform showed an absolute advantage with high extraction efficiency for global metabolomics. We showed a metabolite-specific impact of the harvesting method and extraction method on metabolite concentrations. The water disruption sample collection combined with novel two-phase solvent system extraction enabled simultaneous profiling of lipids and metabolites with mixed polarity for sample preparation. Our approach may open up new perspectives toward large-scale comprehensive metabolomic analyses of adherent mammalian cell samples.

The effect of polysaccharides from Cibotium barometz on enhancing temozolomide-induced glutathione exhausted in human glioblastoma U87 cells, as revealed by 1H NMR metabolomics analysis

Glioblastoma (GBM) is the most malignant central nervous system tumor, with poor prognosis. Temozolomide (TMZ) has been used as a first-line drug for the treatment of GBM for over a decade, but its treatment benefits are limited by acquired resistance. Polysaccharides from Cibotium barometz (CBPs) are polysaccharides purified from the root of Cibotium barometz (L.) J. Sm., possessing sensitizing activity. The purpose of this study was to investigate the anti-cancer effect of CBP from different processing methods on U87 cells using a ¹H NMR-based metabolic approach, complemented with qRT-PCR and flow cytometry, to identify potential markers and discover the targets to explore the underlying mechanism. Cibotium barometz is usually processed under sand heating in clinical applications. Polysaccharides from both the processed (PCBP) and raw (RCBP) C. barometz were prepared, and the effect on enhancing the sensitivity to TMZ was investigated in vitro. CBP can significantly increase the toxicity of TMZ to the U87 cell line, promote apoptosis, enhance cell cycle changes, and arrest cells in S phase, and RCBP demonstrated better activity. Multivariate statistical analyses, such as principal component analysis (PCA) and orthogonal projection to latent structure with discriminant analysis (OPLS-DA), were used to identify metabolic biomarkers, and 12 metabolites in the cell extract samples were clearly identified as altered after RCBP exposure. NMR-based cell metabolomics provided a holistic method for the identification of CBP's apoptosis-enhancing mechanisms and the exploration of its potential applications in preclinical and clinical studies.

A global metabolomic insight into the oxidative stress and membrane damage of copper oxide nanoparticles and microparticles on microalga Chlorella vulgaris

To compare aquatic organisms' responses to the toxicity of copper oxide (CuO) nanoparticles (NPs) with those of CuO microparticles (MPs) and copper (Cu) ions, a global metabolomics approach was employed to investigate the changes of both polar and nonpolar metabolites in microalga Chlorella vulgaris after 5-day exposure to CuO NPs and MPs (1 and 10 mg/L), as well as the corresponding dissolved Cu ions (0.08 and 0.8 mg/L). Unchanged growth, slight reactive oxygen species production, and significant membrane damage (at 10 mg/L CuO particles) in C. vulgaris were demonstrated. A total of 75 differentiated metabolites were identified. Most metabolic pathways perturbed after CuO NPs exposure were shared by those after CuO MPs and Cu ions exposure, including accumulation of chlorophyll intermediates (max. 2.4-5.2 fold), membrane lipids remodeling for membrane protection (decrease of phosphatidylethanolamines (min. 0.6 fold) and phosphatidylcholines (min. 0.2-0.7 fold), as well as increase of phosphatidic acids (max. 1.5-2.9 fold), phosphatidylglycerols (max. 2.2-2.3 fold), monogalactosyldiacylglycerols (max. 1.2-1.4 fold), digalactosylmonoacylglycerols (max. 1.9-3.8 fold), diacylglycerols (max. 1.4 fold), lysophospholipids (max. 1.8-3.0 fold), and fatty acids (max. 3.0-6.2 fold)), perturbation of glutathione metabolism induced by oxidative stress, and accumulation of osmoregulants (max. 1.3-2.6 fold) to counteract osmotic stress. The only difference between metabolic responses to particles and those to ions was the accumulation of fatty acids oxidation products: particles caused higher fold changes (particles/ions ratio 1.9-3.0) at 1 mg/L and lower fold changes (particles/ions ratio 0.4-0.7) at 10 mg/L compared with ions. Compared with microparticles, there was no nanoparticle-specific pathway perturbed. These results confirm the predominant role of dissolved Cu ions on the toxicity of CuO NPs and MPs, and also reveal particle-specific toxicity from a metabolomics perspective.

From Samples to Insights into Metabolism: Uncovering Biologically Relevant Information in LC-HRMS Metabolomics Data

Untargeted metabolomics (including lipidomics) is a holistic approach to biomarker discovery and mechanistic insights into disease onset and progression, and response to intervention. Each step of the analytical and statistical pipeline is crucial for the generation of high-quality, robust data. Metabolite identification remains the bottleneck in these studies; therefore, confidence in the data produced is paramount in order to maximize the biological output. Here, we outline the key steps of the metabolomics workflow and provide details on important parameters and considerations. Studies should be designed carefully to ensure appropriate statistical power and adequate controls. Subsequent sample handling and preparation should avoid the introduction of bias, which can significantly affect downstream data interpretation. It is not possible to cover the entire metabolome with a single platform; therefore, the analytical platform should reflect the biological sample under investigation and the question(s) under consideration. The large, complex datasets produced need to be pre-processed in order to extract meaningful information. Finally, the most time-consuming steps are metabolite identification, as well as metabolic pathway and network analysis. Here we discuss some widely used tools and the pitfalls of each step of the workflow, with the ultimate aim of guiding the reader towards the most efficient pipeline for their metabolomics studies.

Chronic kidney disease: Biomarker diagnosis to therapeutic targets

Chronic kidney disease (CKD), characterized as renal dysfunction, is recognized as a major public health problem with high morbidity and mortality worldwide. Unfortunately, there are no obvious clinical symptoms in early stage disease until severe damage has occurred. Further complicating early diagnosis and treatment is the lack of sensitive and specific biomarkers. As such, novel biomarkers are urgently needed. Metabolomics has shown an increasing potential for identifying underlying disease mechanisms, facilitating clinical diagnosis and developing pharmaceutical treatments for CKD. Recent advances in metabolomics revealed that CKD was closely associated with the dysregulation of numerous metabolites, such as amino acids, lipids, nucleotides and glycoses, that might be exploited as potential biomarkers. In this review, we summarize recent metabolomic applications based on animal model studies and in patients with CKD and highlight several biomarkers that may play important roles in diagnosis, intervention and development of new therapeutic strategies.

Decoding the Metabolome and Lipidome of Child Malnutrition by Mass Spectrometric Techniques: Present Status and Future Perspectives

Child malnutrition (CM) is a global public health problem. It contributes to poor health in one in four children under five years worldwide and causes serious health problems in children, including stunted, wasted, and overweight growth. These serious public health issues lead to a higher chance of living in poverty in adulthood. Malnutrition is related with reduced economic productivity and increases the serious national and international burden. Currently, there is no meaningful therapeutic intervention of CM, and the use of different therapeutic foods has shown poor outcomes among supplemented malnourished children. The role of metabolites and lipids has been extensively recognized as early determinants of child health, but their contribution in CM and its pathobiology are poorly understood. This perspective provides a most recent update on these aspects. After briefly introducing the disciplines of metabolomics and lipidomics, we describe a mass spectrometry-based metabolic workflow for analysis of both metabolites and lipids and summarize several recent applications of metabolomics and lipidomics in CM. Finally, we discuss the future directions of the field toward the development of meaningful interventions for CM through metabolomics and lipidomics advances.

Exposure of HepaRG Cells to Sodium Saccharin Underpins the Importance of Including Non-Hepatotoxic Compounds When Investigating Toxicological Modes of Action Using Metabolomics

Metabolites represent the most downstream information of the cellular organisation. Hence, metabolomics experiments are extremely valuable to unravel the endogenous pathways involved in a toxicological mode of action. However, every external stimulus can introduce alterations in the cell homeostasis, thereby obscuring the involved endogenous pathways, biasing the interpretation of the results. Here we report on sodium saccharin, which is considered to be not hepatotoxic and therefore can serve as a reference compound to detect metabolic alterations that are not related to liver toxicity. Exposure of HepaRG cells to high levels of sodium saccharin (>10 mM) induced cell death, probably due to an increase in the osmotic pressure. Yet, a low number (n = 15) of significantly altered metabolites were also observed in the lipidome, including a slight decrease in phospholipids and an increase in triacylglycerols, upon daily exposure to 5 mM sodium saccharin for 72 h. The observation that a non-hepatotoxic compound can affect the metabolome underpins the importance of correct experimental design and data interpretation when investigating toxicological modes of action via metabolomics.

Influence of Drying Method on NMR-Based Metabolic Profiling of Human Cell Lines

Metabolic profiling of cell line and tissue extracts involves sample processing that includes a drying step prior to re-dissolving the cell or tissue extracts in a buffer for analysis by GC/LC-MS or NMR. Two of the most commonly used drying techniques are centrifugal evaporation under vacuum (SpeedVac) and lyophilization. Here, NMR spectroscopy was used to determine how the metabolic profiles of hydrophilic extracts of three human pancreatic cancer cell lines, MiaPaCa-2, Panc-1 and AsPC-1, were influenced by the choice of drying technique. In each of the three cell lines, 40-50 metabolites were identified as having statistically significant differences in abundance in redissolved extract samples depending on the drying technique used during sample preparation. In addition to these differences, some metabolites were only present in the lyophilized samples, for example, n-methyl-α-aminoisobutyric acid, n-methylnicotimamide, sarcosine and 3-hydroxyisovaleric acid, whereas some metabolites were only present in SpeedVac dried samples, for example, trimethylamine. This research demonstrates that the choice of drying technique used during the preparation of samples of human cell lines or tissue extracts can significantly influence the observed metabolome, making it important to carefully consider the selection of a drying method prior to preparation of such samples for metabolic profiling.

Aryl hydrocarbon receptor activation mediates kidney disease and renal cell carcinoma

The aryl hydrocarbon receptor (AhR) is a well-known ligand-activated cytoplasmic transcription factor that contributes to cellular responses against environmental toxins and carcinogens. AhR is activated by a range of structurally diverse compounds from the environment, microbiome, natural products, and host metabolism, suggesting that AhR possesses a rather promiscuous ligand binding site. Increasing studies have indicated that AhR can be activated by a variety of endogenous ligands and induce the expression of a battery of genes. AhR regulates a variety of physiopathological events, including cell proliferation, differentiation, apoptosis, adhesion and migration. These new roles have expanded our understanding of the AhR signalling pathways and endogenous metabolites interacting with AhR under homeostatic and pathological conditions. Recent studies have demonstrated that AhR is linked to cardiovascular disease (CVD), chronic kidney disease (CKD) and renal cell carcinoma (RCC). In this review, we summarize gut microbiota-derived ligands inducing AhR activity in patients with CKD, CVD, diabetic nephropathy and RCC that may provide a new diagnostic and prognostic approach for complex renal damage. We further highlight polyphenols from natural products as AhR agonists or antagonists that regulate AhR activity. A better understanding of structurally diverse polyphenols and AhR biological activities would allow us to illuminate their molecular mechanism and discover potential therapeutic strategies targeting AhR activation.

Non-Targeted UHPLC-Q-TOF/MS-Based Metabolomics Reveals a Metabolic Shift from Glucose to Glutamine in CPB Cells during ISKNV Infection Cycle

Infectious spleen and kidney necrosis virus (ISKNV) has caused serious economic losses in the cultured mandarin fish (Siniperca chuatsi) industry in China. Host metabolism alteration induced by disease infection may be the core problem of pathogenesis. However, to date, little is known about the disease-induced fish metabolism changes. In this study, we first reported ISKNV, the fish virus, induced metabolism alteration. The metabolomics profiles of Chinese perch brain cells (CPB) post-ISKNV infection at progressive time points were analyzed using the UHPLC-Q-TOF/MS technique. A total of 98 differential metabolites were identified. In the samples harvested at 24 hours post-infection (hpi; the early stage of ISKNV infection), 49 differential metabolites were identified comparing with control cells, including 31 up-regulated and 18 down-regulated metabolites. And in the samples harvested at 72 hpi (the late stage of ISKNV infection), 49 differential metabolites were identified comparing with control cells, including 27 up-regulated and 22 down-regulated metabolites. These differential metabolites were involved in many pathways related with viral pathogenesis. Further analysis on the major differential metabolites related to glucose metabolism and amino acid metabolism revealed that both glucose metabolism and glutamine metabolism were altered and a metabolic shift was determined from glucose to glutamine during ISKNV infection cycle. In ISKNV-infected cells, CPB cells prefer to utilize glucose for ISKNV replication at the early stage of infection, while they prefer to utilize glutamine to synthetize lipid for ISKNV maturation at the late stage of infection. These findings may improve the understanding of the interaction between ISKNV and host, as well as provide a new insight for elucidating the ISKNV pathogenic mechanism.

Discrimination of Different Parts of Saffron by Metabolomic-Based Ultra-Performance Liquid Chromatography Coupled with High-Definition Mass Spectrometry

In this study, the metabolite profiling of three different parts of Crocus sativus L. was measured by using ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTof-MS/MS). Multivariate statistical analysis was used to distinguish among the samples from different parts. A total of 54 compounds were identified in tepals, stigmas and stamens by UPLC-QTof-MS/MS. The results stated that chemical characteristics of saffron were obviously diverse in terms of the parts of flower. Through analysis, coniferin and crocin-2 were special components in stigmas when compared to tepals and stamens. The content of flavonoids was high in tepals when compared with the stigmas. The tepal of saffron may processed as a source of flavonoids in the future. The research provided the basis for the theory that only the stigma can be used as medicine.

Unique mechanistic insights into the beneficial effects of angiotensin-(1-7) on the prevention of cardiac fibrosis: A metabolomic analysis of primary cardiac fibroblasts

BACKGROUND

Cell metabolic pathways are highly conserved among species and change rapidly in response to drug stimulation. Therefore, we explore the effects of angiotensin-(1-7) in a primary cell model of cardiac fibrosis established in angiotensin II-stimulated cardiac fibroblasts via metabolomics analysis and further clarify the potential protective mechanism of angiotensin-(1-7).

METHODS AND RESULTS

After exposing cardiac fibroblasts to angiotensin II and/or angiotensin-(1-7), 172 metabolites in these cells were quantified and identified by gas chromatography-mass spectrometry. The data were subsequently analyzed by orthogonal partial least squares discriminant analysis to shortlist biochemically significant metabolites associated with the antifibrotic action of angiotensin-(1-7). Seven significant metabolites were identified: 10,13-dimethyltetradecanoic acid, arachidonic acid, aspartic acid, docosahexaenoic acid (DHA), glutathione, palmitelaidic acid, and pyroglutamic acid. By metabolic network analysis, we found that these metabolites were involved in six metabolic pathways, including arachidonic acid metabolism, leukotriene metabolism, and the γ-glutamyl cycle. Since these metabolic pathways are related to calcium balance and oxidative stress, we further verified that angiotensin-(1-7) suppressed the abnormal extracellular calcium influx and excessive accumulation of intracellular reactive oxygen species (ROS) in angiotensin II-stimulated cardiac fibroblasts. Furthermore, we found that angiotensin-(1-7) suppressed the abnormal calcium- and ROS-dependent activation of calcium/calmodulin-dependent protein kinase II delta (CaMKIIδ), the increased expression of CaMKIIδ-related proteins (NADPH oxidase 4 (Nox4), cellular communication network factor 2 (CTGF), and p-ERK1/2), and excessive collagen deposition in vitro and in vivo.

CONCLUSIONS

Angiotensin-(1-7) can ameliorate the angiotensin II-stimulated metabolic perturbations associated with cardiac fibroblast activation. These metabolic changes indicate that modulation of calcium- and ROS-dependent activation of CaMKIIδ mediates the activity of angiotensin-(1-7) against cardiac fibrosis. Moreover, pyroglutamic acid and arachidonic acid may be potential biomarkers for monitoring the antifibrotic action of angiotensin-(1-7).

Novel strategies for clinical investigation and biomarker discovery: a guide to applied metabolomics

Metabolomics is an emerging technology that is increasing both in basic science and in human applications, providing a physiological snapshot. It has been highlighted as one of the most wide ranging and reliable tools for the investigation of physiological status, the discovery of new biomarkers and the analysis of metabolic pathways. Metabolomics uses innovative mass spectrometry (MS) allied to chromatography or nuclear magnetic resonance (NMR). The recent advances in bioinformatics, databases and statistics, have provided a unique perception of metabolites interaction and the dynamics of metabolic pathways at a system level. In this context, several studies have applied metabolomics in physiology- and disease-related works. The application of metabolomics includes, physiological and metabolic evaluation/monitoring, individual response to different exercise, nutritional interventions, pathological processes, responses to pharmacological interventions, biomarker discovery and monitoring for distinct aspects, such as: physiological capacity, fatigue/recovery and aging among other applications. For metabolomic analyses, despite huge improvements in the field, several complex methodological steps must be taken into consideration. In this regard, the present article aims to summarize the novel aspects of metabolomics and provide a guide for metabolomics for professionals related to physiologist and medical applications.

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 General Explanation Method with NMR Spectroscopy Enables the Identification of Metabolite Profiles Specific for Normal and Tumor Cell Lines

Machine learning models in metabolomics, despite their great prediction accuracy, are still not widely adopted owing to the lack of an efficient explanation for their predictions. In this study, we propose the use of the general explanation method to explain the predictions of a machine learning model to gain detailed insight into metabolic differences between biological systems. The method was tested on a dataset of 1 H NMR spectra acquired on normal lung and mesothelial cell lines and their tumor counterparts. Initially, the random forests and artificial neural network models were applied to the dataset, and excellent prediction accuracy was achieved. The predictions of the models were explained with the general explanation method, which enabled identification of discriminating metabolic concentration differences between individual cell lines and enabled the construction of their specific metabolic concentration profiles. This intuitive and robust method holds great promise for in-depth understanding of the mechanisms that underline phenotypes as well as for biomarker discovery in complex diseases.

Omics research project on prospective cohort studies from the Tohoku Medical Megabank Project

Population-based prospective cohort studies are indispensable for modern medical research as they provide important knowledge on the influences of many kinds of genetic and environmental factors on the cause of disease. Although traditional cohort studies are mainly conducted using questionnaires and physical examinations, modern cohort studies incorporate omics and genomic approaches to obtain comprehensive physical information, including genetic information. Here, we report the design and midterm results of multi-omics analysis on population-based prospective cohort studies from the Tohoku Medical Megabank (TMM) Project. We have incorporated genomic and metabolomic studies in the TMM cohort study as both metabolome and genome analyses are suitable for high-throughput analysis of large-scale cohort samples. Moreover, an association study between the metabolome and genome show that metabolites are an important intermediate phenotype connecting genetic and lifestyle factors to physical and pathologic phenotypes. We apply our metabolome and genome analyses to large-scale cohort samples in the following studies.