Cell culture metabolomics: applications and future directions

Comparative Analysis of Breast Cancer Metabolomes Highlights Fascin's Central Role in Regulating Key Pathways Related to Disease Progression

Omics technologies provide useful tools for the identification of novel biomarkers in many diseases, including breast cancer, which is the most diagnosed cancer in women worldwide. We and others have reported a central role for the actin-bundling protein (fascin) in regulating breast cancer disease progression at different levels. However, whether fascin expression promotes metabolic molecules that could predict disease progression has not been fully elucidated. Here, fascin expression was manipulated via knockdown (fascinKD+NORF) and rescue (fascinKD+FORF) in the naturally fascin-positive (fascinpos+NORF) MDA-MB-231 breast cancer cells. Whether fascin dysregulates metabolic profiles that are associated with disease progression was assessed using untargeted metabolomics analyses via liquid chromatography-mass spectrometry. Overall, 12,226 metabolic features were detected in the tested cell pellets. Fascinpos+NORF cell pellets showed 2510 and 3804 significantly dysregulated metabolites compared to their fascinKD+NORF counterparts. Fascin rescue (fascinKD+FORF) revealed 2710 significantly dysregulated cellular metabolites compared to fascinKD+NORF counterparts. A total of 101 overlapped cellular metabolites between fascinKD+FORF and fascinpos+NORF were significantly dysregulated in the fascinKD+NORF cells. Analysis of the significantly dysregulated metabolites by fascin expression revealed their involvement in the metabolism of sphingolipid, phenylalanine, tyrosine, and tryptophan biosynthesis, and pantothenate and CoA biosynthesis, which are critical pathways for breast cancer progression. Our findings of fascin-mediated alteration of metabolic pathways could be used as putative poor prognostic biomarkers and highlight other underlying mechanisms of fascin contribution to breast cancer progression.

Cellular metabolomics study of the antitumor mechanism of Sijunzi decoction combined with mitomycin C

Mitomycin C (MMC) has an antitumor effect and is considered as a broad-spectrum antibiotic. Sijunzi Decoction (SJZD), a well-known ancient Chinese prescription, is widely used in the treatment of cancer when combined with chemotherapy drugs. Studies have shown that SJZD can be combined with other drugs to enhance the therapeutic effect against cancer and inhibit the toxicity of chemotherapy drugs, but the specific mechanism is not clear. Thus, we hope to further explore the antitumor mechanism of combined SJZD and MMC. 3-(4,5-Dimethyl-2-thiazolyl)-2, 5-diphenyl-2-H-tetrazolium bromide assay, flow cytometry, western blot, 1H NMR and HPLC-MS were used to study the mechanism at the cellular level. The results show that the combined administration can have a more significant effect on inhibiting the proliferation of cancer cells, promoting their apoptosis. Based on metabolomics, 38 biomarkers were found in the MMC group and 43 biomarkers were found in the combined administration group. Among them, 18 unique biomarkers were discovered in the combined administration group. Studies have shown that the antitumor mechanism of combined administration is related to amino acid metabolism, energy metabolism, lipid metabolism and nucleotide metabolism, among which amino acid metabolism is the most important. In addition, SJZD achieves the effect of toxin reduction and efficiency enhancement by improving the body's immunity and improving the oxidative stress environment.

NMR Metabolomics of Primary Ovarian Cancer Cells in Comparison to Established Cisplatin-Resistant and -Sensitive Cell Lines

Cancer cell lines are frequently used in metabolomics, such as in vitro tumor models. In particular, A2780 cells are commonly used as a model for ovarian cancer to evaluate the effects of drug treatment. Here, we compare the NMR metabolomics profiles of A2780 and cisplatin-resistant A2780 cells with those of cells derived from 10 patients with high-grade serous ovarian carcinoma (collected during primary cytoreduction before any chemotherapeutic treatment). Our analysis reveals a substantial similarity among all primary cells but significant differences between them and both A2780 and cisplatin-resistant A2780 cells. Notably, the patient-derived cells are closer to the resistant A2780 cells when considering the exo-metabolome, whereas they are essentially equidistant from A2780 and A2780-resistant cells in terms of the endo-metabolome. This behavior results from dissimilarities in the levels of several metabolites attributable to the differential modulation of underlying biochemical pathways. The patient-derived cells are those with the most pronounced glycolytic phenotype, whereas A2780-resistant cells mainly diverge from the others due to alterations in a few specific metabolites already known as markers of resistance.

Study on the Neuroprotective Effects of Eight Iridoid Components Using Cell Metabolomics

Iridoid components have been reported to have significant neuroprotective effects. However, it is not yet clear whether the efficacy and mechanisms of iridoid components with similar structures are also similar. This study aimed to compare the neuroprotective effects and mechanisms of eight iridoid components (catalpol (CAT), genipin (GE), geniposide (GEN), geniposidic acid (GPA), aucubin (AU), ajugol (AJU), rehmannioside C (RC), and rehmannioside D (RD)) based on corticosterone (CORT)-induced injury in PC12 cells. PC12 cells were randomly divided into a normal control group (NC), model group (M), positive drug group (FLX), and eight iridoid administration groups. Firstly, PC12 cells were induced with CORT to simulate neuronal injury. Then, the MTT method and flow cytometry were applied to evaluate the protective effects of eight iridoid components on PC12 cell damage. Thirdly, a cell metabolomics study based on ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry (UPLC-Q/TOF-MS) was performed to explore changes in relevant biomarkers and metabolic pathways following the intervention of administration. The MTT assay and flow cytometry analysis showed that the eight iridoid components can improve cell viability, inhibit cell apoptosis, reduce intracellular ROS levels, and elevate MMP levels. In the PCA score plots, the sample points of the treatment groups showed a trend towards approaching the NC group. Among them, AU, AJU, and RC had a weaker effect. There were 38 metabolites (19 metabolites each in positive and negative ion modes, respectively) identified as potential biomarkers during the experiment, among which 23 metabolites were common biomarkers of the eight iridoid groups. Pathway enrichment analysis revealed that the eight iridoid components regulated the metabolism mainly in relation to D-glutamine and D-glutamate metabolism, arginine biosynthesis, the TCA cycle, purine metabolism, and glutathione metabolism. In conclusion, the eight iridoid components could reverse an imbalanced metabolic state by regulating amino acid neurotransmitters, interfering with amino acid metabolism and energy metabolism, and harmonizing the level of oxidized substances to exhibit neuroprotective effects.

A Multi-Omics Approach Reveals Enrichment in Metabolites Involved in the Regulation of the Glutathione Pathway in LIN28B-Dependent Cancer Cells

The RNA-binding protein LIN28B, identified as an independent risk factor in high-risk neuroblastoma patients, is implicated in adverse treatment outcomes linked to metastasis and chemoresistance. Despite its clinical significance, the impact of LIN28B on neuroblastoma cell metabolism remains unexplored. This study employs a multi-omics approach, integrating transcriptome and metabolome data, to elucidate the global metabolic program associated with varying LIN28B expression levels over time. Our findings reveal that escalating LIN28B expression induces a significant metabolic rewiring in neuroblastoma cells. Specifically, LIN28B prompts a time-dependent increase in the release rate of metabolites related to the glutathione and aminoacyl-tRNA biosynthetic pathways, concomitant with a reduction in glucose uptake. These results underscore the pivotal role of LIN28B in governing neuroblastoma cell metabolism and suggest a potential disruption in the redox balance of LIN28B-bearing cells. This study offers valuable insights into the molecular mechanisms underlying LIN28B-associated adverse outcomes in neuroblastoma, paving the way for targeted therapeutic interventions.

Plant Heterotrophic Cultures: No Food, No Growth

Plant cells are capable of uptaking exogenous organic substances. This inherited trait allows the development of heterotrophic cell cultures in various plants. The most common of them are Nicotiana tabacum and Arabidopsis thaliana. Plant cells are widely used in academic studies and as factories for valuable substance production. The repertoire of compounds supporting the heterotrophic growth of plant cells is limited. The best growth of cultures is ensured by oligosaccharides and their cleavage products. Primarily, these are sucrose, raffinose, glucose and fructose. Other molecules such as glycerol, carbonic acids, starch, and mannitol have the ability to support growth occasionally, or in combination with another substrate. Culture growth is accompanied by processes of specialization, such as elongation growth. This determines the pattern of the carbon budget. Culture ageing is closely linked to substrate depletion, changes in medium composition, and cell physiological rearrangements. A lack of substrate leads to starvation, which results in a decrease in physiological activity and the mobilization of resources, and finally in the loss of viability. The cause of the instability of cultivated cells may be the non-optimal metabolism under cultural conditions or the insufficiency of internal regulation.

Metabolomics to Study Human Aging: A Review

In the last years, with the increase in the average life expectancy, the world's population is progressively aging, which entails social, health and economic problems. In this sense, the need to better understand the physiology of the aging process becomes an urgent need. Since the study of aging in humans is challenging, cellular and animal models are widely used as alternatives. Omics, namely metabolomics, have emerged in the study of aging, with the aim of biomarker discovering, which may help to uncomplicate this complex process. This paper aims to summarize different models used for aging studies with their advantages and limitations. Also, this review gathers the published articles referring to biomarkers of aging already discovered using metabolomics approaches, comparing the results obtained in the different studies. Finally, the most frequently used senescence biomarkers are described, along with their importance in understanding aging.

Fingerprinting and profiling in metabolomics of biosamples

This review focuses on metabolomics from an NMR point of view. It attempts to cover the broad scope of metabolomics and describes the NMR experiments that are most suitable for each sample type. It is addressed not only to NMR specialists, but to all researchers who wish to approach metabolomics with a clear idea of what they wish to achieve but not necessarily with a deep knowledge of NMR. For this reason, some technical parts may seem a bit naïve to the experts. The review starts by describing standard metabolomics procedures, which imply the use of a dedicated 600 MHz instrument and of four properly standardized 1D experiments. Standardization is a must if one wants to directly compare NMR results obtained in different labs. A brief mention is also made of standardized pre-analytical procedures, which are even more essential. Attention is paid to the distinction between fingerprinting and profiling, and the advantages and disadvantages of fingerprinting are clarified. This aspect is often not fully appreciated. Then profiling, and the associated problems of signal assignment and quantitation, are discussed. We also describe less conventional approaches, such as the use of different magnetic fields, the use of signal enhancement techniques to increase sensitivity, and the potential of field-shuttling NMR. A few examples of biomedical applications are also given, again with the focus on NMR techniques that are most suitable to achieve each particular goal, including a description of the most common heteronuclear experiments. Finally, the growing applications of metabolomics to foodstuffs are described.

Non-invasive biomarkers for mild cognitive impairment and Alzheimer's disease

Alzheimer's disease is the most common type of dementia in the elderly. It is a progressive degenerative disorder that may begin to develop up to 15 years before clinical symptoms appear. The identification of early biomarkers is crucial to enable a prompt diagnosis and to start effective interventions. In this work, we conducted a metabolomic study using proton Nuclear Magnetic Resonance (1H NMR) spectroscopy in serum samples from patients with neuropathologically confirmed Alzheimer's disease (AD, n = 51), mild cognitive impairment (MCI, n = 27), and cognitively healthy controls (HC, n = 50) to search for metabolites that could be used as biomarkers. Patients and controls underwent yearly clinical follow-ups for up to six years. MCI group included samples from three subgroups of subjects with different disease progression rates. The first subgroup included subjects that remained clinically stable at the MCI stage during the period of study (stable MCI, S-MCI, n = 9). The second subgroup accounted for subjects which were diagnosed with MCI at the moment of blood extraction, but progressed to clinical dementia in subsequent years (MCI-to-dementia, MCI-D, n = 14). The last subgroup was composed of subjects that had been diagnosed as dementia for the first time at the moment of sample collection (incipient dementia, Incp-D, n = 4). Partial Least Square Discriminant Analysis (PLS-DA) models were developed. Three models were obtained, one to discriminate between AD and HC samples with high sensitivity (93.75%) and specificity (94.75%), another model to discriminate between AD and MCI samples (100% sensitivity and 82.35% specificity), and a last model to discriminate HC and MCI with lower sensitivity and specificity (67% and 50%). Differences within the MCI group were further studied in an attempt to determine those MCI subjects that could develop AD-type dementia in the future. The relative concentration of metabolites, and metabolic pathways were studied. Alterations in the pathways of alanine, aspartate and glutamate metabolism, pantothenate and CoA biosynthesis, and beta-alanine metabolism, were found when HC and MCI- D patients were compared. In contrast, no pathway was found disturbed in the comparison of S-MCI with HC groups. These results highlight the potential of 1H NMR metabolomics to support the diagnosis of dementia in a less invasive way, and set a starting point for the study of potential biomarkers to identify MCI or HC subjects at risk of developing AD in the future.

Recent advances in the combination of organic solvent-free extraction, chemical standardization, antioxidant assay, and cell culture metabolomics for functional food and its by-product

Functional foods and their by-products contain a wide range of bioactive components with an array of health benefits and were proposed to improve public health, well-being, and others. To achieve a circular economy, the processing and extraction of flavonoids, phenolic compounds, and others from functional food and agri-food wastes will require the use of environmentally friendly, sustainable, and a low-cost solution. Extraction methods that can eliminate the use of organic solvents, suitable for use in the laboratory and production of extracts will be covered. This will include subcritical water extraction (SBE), pressurized hot water extraction (PHWE), supercritical fluid extraction (SFE), and others. Based on the selected analytical methods, the determination of the marker or bioactive compounds and chemical fingerprints will provide the control measures to identify the batch-to-batch variation of the composition of the functional food products obtained. The combination of chemical standardization with antioxidant assay, such as DPPH and ABTS+ will provide further information on the quality of the extracts. Lastly, to ascertain the biological and physiological relevance of the antioxidant properties of the target sample, treatment of the antioxidant compounds or extracts was carried out using cellular models, and validated using other experimental endpoints, such as metabolomics.

Paclitaxel Induces Neurotoxicity by Disrupting Tricarboxylic Acid Cycle Metabolic Balance in the Mouse Hippocampus

Objective

It is well known that paclitaxel (PTX)-induced neurotoxicity seriously affects the quality of life of patients and is the main reason for reducing the dose of chemotherapy or even stopping chemotherapy. The current data are limited, and further information is required for practice and verification. The aims of this study were to clarify the molecular mechanism underlying PTX-induced neurotoxicity by combining in vivo and in vitro metabolomics studies and provide new targets for the prevention and treatment of PTX-induced neurotoxicity.

Methods

In the in vivo study, a PTX-induced neurotoxicity mouse model was established by intraperitoneal injection of PTX (6 mg/kg every three days) for two consecutive weeks. After verification by water maze tests and HE staining of pathological sections, hippocampal metabolites were measured and the differential metabolites and related metabolic pathways were identified by multivariate statistical analysis. In the in vitro study, we investigated the effects of PTX on mouse hippocampal neuron cells, assessing the concentration and time of administration by MTT assays. After modeling, the relevant metabolites in the TCA cycle were quantified by targeted metabolomics using stable isotope labeling. Finally, the key enzymes of the TCA cycle in tissues and cells were verified by RT-PCR.

Results

Administration of PTX to model mice resulted in neurological damage, shown by both water-maze tests and hippocampal tissue sections. Twenty-four metabolites and five associated metabolic pathways were found to differ significantly between the hippocampal tissues of the model and control groups. These included metabolites and pathways related to the TCA cycle and pyruvate metabolism. Metabolomics analysis using stable isotope labeling showed significant changes in metabolites associated with the TCA cycle compared with the control group (P < 0.05). Finally, RT-PCR verified that the expression of key enzymes in the TCA cycle was changed to different degrees in both hippocampal tissues and cells.

Conclusion

Our results showed that PTX neurotoxicity in hippocampal tissue and neuron cells was associated with inhibition of the TCA cycle. This inhibition leads to brain insufficiency and impaired metabolism, resulting in various neurotoxic symptoms.

The effects of two cytotoxic gold(i) carbene compounds on the metabolism of A2780 ovarian cancer cells: mechanistic inferences through NMR analysis

NMR metabolomics is a powerful tool to characterise the changes in cancer cell metabolism elicited by anticancer drugs. Here, the large metabolic alterations produced by two cytotoxic gold carbene compounds in A2780 ovarian cancer cells are described and discussed in comparison to auranofin, in the frame of the available mechanistic knowledge.

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.

Closing the gap between in vivo and in vitro omics: using QA/QC to strengthen ex vivo NMR metabolomics

Metabolomics aims to achieve a global quantitation of the pool of metabolites within a biological system. Importantly, metabolite concentrations serve as a sensitive marker of both genomic and phenotypic changes in response to both internal and external stimuli. NMR spectroscopy greatly aids in the understanding of both in vitro and in vivo physiological systems and in the identification of diagnostic and therapeutic biomarkers. Accordingly, NMR is widely utilized in metabolomics and fluxomics studies due to its limited requirements for sample preparation and chromatography, its non-destructive and quantitative nature, its utility in the structural elucidation of unknown compounds, and, importantly, its versatility in the analysis of in vitro, in vivo, and ex vivo samples. This review provides an overview of the strengths and limitations of in vitro and in vivo experiments for translational research and discusses how ex vivo studies may overcome these weaknesses to facilitate the extrapolation of in vitro insights to an in vivo system. The application of NMR-based metabolomics to ex vivo samples, tissues, and biofluids can provide essential information that is close to a living system (in vivo) with sensitivity and resolution comparable to those of in vitro studies. The success of this extrapolation process is critically dependent on high-quality and reproducible data. Thus, the incorporation of robust quality assurance and quality control checks into the experimental design and execution of NMR-based metabolomics experiments will ensure the successful extrapolation of ex vivo studies to benefit translational medicine.

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.

Metabolomic Analysis of Human Astrocytes in Lipotoxic Condition: Potential Biomarker Identification by Machine Learning Modeling

The association between neurodegenerative diseases (NDs) and obesity has been well studied in recent years. Obesity is a syndrome of multifactorial etiology characterized by an excessive accumulation and release of fatty acids (FA) in adipose and non-adipose tissue. An excess of FA generates a metabolic condition known as lipotoxicity, which triggers pathological cellular and molecular responses, causing dysregulation of homeostasis and a decrease in cell viability. This condition is a hallmark of NDs, and astrocytes are particularly sensitive to it, given their crucial role in energy production and oxidative stress management in the brain. However, analyzing cellular mechanisms associated with these conditions represents a challenge. In this regard, metabolomics is an approach that allows biochemical analysis from the comprehensive perspective of cell physiology. This technique allows cellular metabolic profiles to be determined in different biological contexts, such as those of NDs and specific metabolic insults, including lipotoxicity. Since data provided by metabolomics can be complex and difficult to interpret, alternative data analysis techniques such as machine learning (ML) have grown exponentially in areas related to omics data. Here, we developed an ML model yielding a 93% area under the receiving operating characteristic (ROC) curve, with sensibility and specificity values of 80% and 93%, respectively. This study aimed to analyze the metabolomic profiles of human astrocytes under lipotoxic conditions to provide powerful insights, such as potential biomarkers for scenarios of lipotoxicity induced by palmitic acid (PA). In this work, we propose that dysregulation in seleno-amino acid metabolism, urea cycle, and glutamate metabolism pathways are major triggers in astrocyte lipotoxic scenarios, while increased metabolites such as alanine, adenosine, and glutamate are suggested as potential biomarkers, which, to our knowledge, have not been identified in human astrocytes and are proposed as candidates for further research and validation.

Metabolic Profiling of CHO Cells during the Production of Biotherapeutics

As indicated by an ever-increasing number of FDA approvals, biotherapeutics constitute powerful tools for the treatment of various diseases, with monoclonal antibodies (mAbs) accounting for more than 50% of newly approved drugs between 2014 and 2018 (Walsh, 2018). The pharmaceutical industry has made great progress in developing reliable and efficient bioproduction processes to meet the demand for recombinant mAbs. Mammalian cell lines are preferred for the production of functional, complex recombinant proteins including mAbs, with Chinese hamster ovary (CHO) cells being used in most instances. Despite significant advances in cell growth control for biologics manufacturing, cellular responses to environmental changes need to be understood in order to further improve productivity. Metabolomics offers a promising approach for developing suitable strategies to unlock the full potential of cellular production. This review summarizes key findings on catabolism and anabolism for each phase of cell growth (exponential growth, the stationary phase and decline) with a focus on the principal metabolic pathways (glycolysis, the pentose phosphate pathway and the tricarboxylic acid cycle) and the families of biomolecules that impact these circuities (nucleotides, amino acids, lipids and energy-rich metabolites).

The Long-Term Culture of Human Fibroblasts Reveals a Spectroscopic Signature of Senescence

Aging is a complex process which leads to progressive loss of fitness/capability/ability, increasing susceptibility to disease and, ultimately, death. Regardless of the organism, there are some features common to aging, namely, the loss of proteostasis and cell senescence. Mammalian cell lines have been used as models to study the aging process, in particular, cell senescence. Thus, the aim of this study was to characterize the senescence-associated metabolic profile of a long-term culture of human fibroblasts using Fourier Transform Infrared and Nuclear Magnetic Resonance spectroscopy. We sub-cultivated fibroblasts from a newborn donor from passage 4 to passage 17 and the results showed deep changes in the spectroscopic profile of cells over time. Late passage cells were characterized by a decrease in the length of fatty acid chains, triglycerides and cholesterol and an increase in lipid unsaturation. We also found an increase in the content of intermolecular β-sheets, possibly indicating an increase in protein aggregation levels in cells of later passages. Metabolic profiling by NMR showed increased levels of extracellular lactate, phosphocholine and glycine in cells at later passages. This study suggests that spectroscopy approaches can be successfully used to study changes concomitant with cell senescence and validate the use of human fibroblasts as a model to monitor the aging process.

Understanding Inborn Errors of Metabolism through Metabolomics

Inborn errors of metabolism (IEMs) are rare diseases caused by a defect in a single enzyme, co-factor, or transport protein. For most IEMs, no effective treatment is available and the exact disease mechanism is unknown. The application of metabolomics and, more specifically, tracer metabolomics in IEM research can help to elucidate these disease mechanisms and hence direct novel therapeutic interventions. In this review, we will describe the different approaches to metabolomics in IEM research. We will discuss the strengths and weaknesses of the different sample types that can be used (biofluids, tissues or cells from model organisms; modified cell lines; and patient fibroblasts) and when each of them is appropriate to use.

Protective Mechanism of Gandou Decoction in a Copper-Laden Hepatolenticular Degeneration Model: In Vitro Pharmacology and Cell Metabolomics

Gandou decoction (GDD) is a classic prescription for the treatment of hepatolenticular degeneration (HLD) in China; however, the liver-protecting mechanism of this prescription needs further evaluation. In the present study, we explored the protective mechanisms of GDD in a copper-laden HLD model using integrated pharmacology and cellular metabolomics in vitro. The results revealed that GDD could significantly promote copper excretion in copper-laden HLD model cells and improve the ultrastructural changes in hepatocytes. In addition, GDD could decrease the extent of lipid peroxidation, levels of reactive oxygen species, and the release rate of lactate dehydrogenase while increasing the activity of superoxide dismutase and the ratio of glutathione to oxidized glutathione in the copper-laden HLD model cells. On conducting statistical analysis of significant metabolic changes, 47 biomarkers and 30 related metabolic pathways were screened as pharmacological reactions induced by GDD in HLD model cells. d-glutamate and d-glutamine metabolic pathways showed the highest importance and significance among the 30 metabolic pathways, and the differential expression levels of the glutamine synthetase (GS) and the renal type and liver type GLS (GLS1 and GLS2) proteins were verified by Western blotting. Collectively, our data established the underlying mechanism of GDD therapy, such as the promotion of copper excretion and improvement in oxidative stress by regulating the expressions of GS, GLS1, and GLS2 protein to protect hepatocytes from injury.

Comprehending Cardiac Dysfunction by Oxidative Stress: Untargeted Metabolomics of In Vitro Samples

Cardiovascular diseases (CVDs) are noncommunicable diseases known for their complex etiology and high mortality rate. Oxidative stress (OS), a condition in which the release of free radical exceeds endogenous antioxidant capacity, is pivotal in CVC, such as myocardial infarction, ischemia/reperfusion, and heart failure. Due to the lack of information about the implications of OS on cardiovascular conditions, several methodologies have been applied to investigate the causes and consequences, and to find new ways of diagnosis and treatment as well. In the present study, cardiac dysfunction was evaluated by analyzing cells’ alterations with untargeted metabolomics, after simulation of an oxidative stress condition using hydrogen peroxide (H₂O₂) in H9c2 myocytes. Optimizations of H₂O₂ concentration, cell exposure, and cell recovery times were performed through MTT assays. Intracellular metabolites were analyzed right after the oxidative stress (oxidative stress group) and after 48 h of cell recovery (recovery group) by ultra-high-performance liquid chromatography coupled to mass spectrometry (UHPLC-MS) in positive and negative ESI ionization mode. Significant alterations were found in pathways such as “alanine, aspartate and glutamate metabolism”, “glycolysis”, and “glutathione metabolism”, mostly with increased metabolites (upregulated). Furthermore, our results indicated that the LC-MS method is effective for studying metabolism in cardiomyocytes and generated excellent fit (R²Y > 0.987) and predictability (Q² > 0.84) values.

Metabolic response of Lactobacillus acidophilus exposed to amoxicillin

Drug-induced diarrhea is a common adverse drug reaction, especially the one caused by the widespread use of antibiotics. The reduction of probiotics is one reason for intestinal disorders induced by an oral antibiotic. However, the intrinsic mechanism of drug-induced diarrhea is still unknown. In this study, we used metabolomics methods to explore the effects of the classic oral antibiotic, amoxicillin, on the growth and metabolism of Lactobacillus acidophilus, while scanning electron microscopy (SEM) and 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assays were employed to evaluate changes in cell activity and morphology. The results showed that cell viability gradually decreased, while the degree of cell wall rupture increased, with increasing amoxicillin concentrations. A non-targeted metabolomics analysis identified 13 potential biomarkers associated with 9 metabolic pathways. The data showed that arginine and proline metabolism, nicotinate and nicotinamide metabolism, pyrimidine metabolism, glycine, serine and threonine metabolism, beta-alanine metabolism, glycerolipid metabolism, tryptophan metabolism, steroid hormone biosynthesis, and histidine metabolism may be involved in the different effects exerted by amoxicillin on L. acidophilus. This study provides potential targets for screening probiotics regulators and lays a theoretical foundation for the elucidation of their mechanisms.

Lipidomics reveals the dysregulated ceramide metabolism in oxidized low-density lipoprotein-induced macrophage-derived foam cell

Atherosclerosis (AS) is associated with increasing lipid peroxidation. Oxidative modification of low-density lipoproteins (ox-LDL) is one most important factors contributing to the pathogenesis and clinical features of AS. The lipid composition influenced by ox-LDL is not known clearly. In this work, a UHPLC/Orbitrap MS-based lipidomics approach integrated pathway analysis was performed to advance understanding of the lipid composition and feature pathway in an ox-LDL-induced foamy macrophage cell. In the lipid metabolic profiling, 196 lipid species from 15 (sub)classes were identified. Lipid profiling indicated that increasing ox-LDL caused lipid metabolic alternations, manifesting as phospholipids being down-regulated and sphingolipids being up-regulated. Pathway analysis explored glycerophospholipid and sphingolipid metabolism, which was involved in atherogenic changes. Notably, dysregulated ceramide metabolism was a typical feature of foamy cell formation. qRT-PCR analysis was conducted to explore the differentially expressed genes. It indicated that ceramide metabolic balance might be disordered, performing higher synthesis and lower hydrolysis, with the ratio of SMPD1/SGMS2 being significantly up-regulated (p < 0.05) in the ox-LDL induced group. Our work offers a comprehensive understanding of macrophage-derived foam cells and screen feature pathways associated with foamy cell formation, which provides a reference for the clinic diagnosis of AS and drug interventions.

Synthesis of Silver Nanoparticles from the Polysaccharide of Farfarae Flos and Uncovering Its Anticancer Mechanism Based on the Cell Metabolomic Approach

In this study, the polysaccharide of Farfarae Flos (FFP) was utilized as a reducing agent to the green synthesis of FFP@AgNPs, and the anticancer activity was evaluated using the HT29 cells. The results showed that the FFP@AgNPs could significantly decrease proliferation ability, inhibit migration, and promote cell apoptosis of HT29 cells, which suggested that the FFP@AgNPs showed significant, strong cytotoxicity against HT29 cells. The cell metabolomic analysis coupled with the heatmap showed an obvious metabolome difference for the cells with and without FFP@AgNPs treatment, which was related to 51 differential metabolites. Four metabolic pathways were determined as the key pathways, and the representative functional metabolites and metabolic pathways were validated in vitro. Nicotinic acid (NA) was revealed as the key metabolite relating with the effect of FFP@AgNPs, and it was interesting that NA supplementation could inhibit the proliferation ability of HT29 cells in vitro, lead to mitochondrial dysfunction, reduce intracellular ATP, and damage the integrity of the cell membrane, which exhibited a similar effect as FFP@AgNPs. In conclusion, this study not only revealed the anticancer mechanism of FFP@AgNPs against the HT29 cells but also provided the important reference that NA shows a potential role in the development of a therapy for colorectal cancer.

Toxicometabolomics: Small Molecules to Answer Big Toxicological Questions

Given the high biological impact of classical and emerging toxicants, a sensitive and comprehensive assessment of the hazards and risks of these substances to organisms is urgently needed. In this sense, toxicometabolomics emerged as a new and growing field in life sciences, which use metabolomics to provide new sets of susceptibility, exposure, and/or effects biomarkers; and to characterize in detail the metabolic responses and altered biological pathways that various stressful stimuli cause in many organisms. The present review focuses on the analytical platforms and the typical workflow employed in toxicometabolomic studies, and gives an overview of recent exploratory research that applied metabolomics in various areas of toxicology.

A novel strategy based on targeted cellular metabolomics for quantitatively evaluating anti-aging effect and screening effective extracts of Erzhi Wan

The complexity of ingredients in traditional Chinese medicine (TCM) makes it challenging to clarify its efficacy in an acceptable and scientific approach. The present study was aimed to use quantification results from targeted cellular metabolomics to evaluate anti-aging efficacy of a famous Chinese medicine formula, Erzhi Wan (EZW), and screen possible effective extracts, depending on the developed strategy integrating multivariate receiver operating characteristic (ROC) curve and analytic hierarchy process (AHP). In this study, senescent NRK cells induced by D-galactose were treated with drug-containing serum of EZW and four kinds of extracts (petroleum ether, ethyl acetate, butanol and water). Intermediates of two major metabolic pathways for energy synthesis, tricarboxylic acid (TCA) cycle and glycolysis, were accurately quantified by GC-MS/MS to identify discriminate metabolites for clarifying therapeutic mechanism of EZW based on multivariate statistical analysis. Senescent and non-senescent cells were successfully distinguished using these metabolites by ROC curve analysis. Next, these metabolites were used as evaluation indexes to quantitatively reflect different effect of EZW and its extracts, according to the role of them in distinguishing groups and in conjunction with AHP. In vitro detection of senescence-associated β-galactosidase (SA-β-gal) activity was used to verify the reliability of evaluation results. The reversal after treatment of drug-containing serum of EZW and extracts was observed, and the petroleum ether extract might be the potential active extract responsible for the major anti-aging effect of EZW, which was in agreement with in vitro experiments. Altogether, metabolomics was a powerful approach for evaluation efficacy and elucidation action mechanisms of TCM. The integrated evaluation strategy in this paper with properties of high practicality, feasibility and effectivity was expected to provide a new insight into comprehensive and quantitative efficacy evaluation.

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

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

Live monitoring of cellular metabolism and mitochondrial respiration in 3D cell culture system using NMR spectroscopy

Background: Because of the interplay between mitochondrial respiration and cellular metabolism, the simultaneous monitoring of both cellular processes provides important insights for the understanding of biological processes. NMR flow systems provide a unique window into the metabolome of cultured cells. Simplified bioreactor construction based on commercially available flow systems increase the practicability and reproducibility of bioreactor studies using standard NMR spectrometers. We therefore aim at establishing a reproducible NMR bioreactor system for metabolic ¹H-NMR investigations of small molecules and concurrent oxygenation determination by ¹⁹F-NMR, with in depth description and validation by accompanying measures. Methods: We demonstrate a detailed and standardized workflow for the preparation and transfer of collagen based 3D cell culture of high cell density for perfused investigation in a 5 mm NMR tube. Self-constructed gas mixing station enables 5% CO₂ atmosphere for physiological pH in carbon based medium and is perfused by HPLC pump. Results & Discussion: Implemented perfused bioreactor allows detection of perfusion rate dependent metabolite content. We show interleaved dynamic profiling of 26 metabolites and mitochondrial respiration. During constant perfusion, sequential injection of rotenone/oligomycin and 2-deoxy-glucose indicated immediate activation and deactivation of glycolytic rate and full inhibition of oxygen consumption. We show sensitivity to detect substrate degradation rates of major mitochondrial fuel pathways and were able to simultaneously measure cellular oxygen consumption.

We show sensitivity to detect substrate degradation rates of major mitochondrial fuel pathways and feasibility to simultaneously measure cellular oxygen consumption combining a commercially available flow tube system with a standard 5 mm NMR probe.

In vivo characterization of physiological and metabolic changes related to isocitrate dehydrogenase 1 mutation expcression by multiparametric MRI and MRS in a rat model with orthotopically grafted human-derived glioblastoma cell lines

The physiological mechanism induced by the isocitrate dehydrogenase 1 (IDH1) mutation, associated with better treatment response in gliomas, remains unknown. The aim of this preclinical study was to characterize the IDH1 mutation through in vivo multiparametric MRI and MRS. Multiparametric MRI, including the measurement of blood flow, vascularity, oxygenation, permeability, and in vivo MRS, was performed on a 4.7 T animal MRI system in rat brains grafted with human-derived glioblastoma U87 cell lines expressing or not the IDH1 mutation by the CRISPR/Cas9 method, and secondarily characterized with additional ex vivo HR-MAS and histological analyses. In univariate analyses, compared with IDH1-, IDH1+ tumors exhibited higher vascular density (p < 0.01) and better perfusion (p = 0.02 for cerebral blood flow), but lower vessel permeability (p < 0.01 for time to peak (TTP), p = 0.04 for contrast enhancement) and decreased T1 map values (p = 0.02). Using linear discriminant analysis, vascular density and TTP values were found to be independent MRI parameters for characterizing the IDH1 mutation (p < 0.01). In vivo MRS and ex vivo HR-MAS analysis showed lower metabolites of tumor aggressiveness for IDH1+ tumors (p < 0.01). Overall, the IDH1 mutation exhibited a higher vascularity on MRI, a lower permeability, and a less aggressive metabolic profile. These MRI features may prove helpful to better pinpoint the physiological mechanisms induced by this mutation.

Glioblastoma Metabolomics-In Vitro Studies

In 2016, the WHO introduced new guidelines for the diagnosis of brain gliomas based on new genomic markers. The addition of these new markers to the pre-existing diagnostic methods provided a new level of precision for the diagnosis of glioma and the prediction of treatment effectiveness. Yet, despite this new classification tool, glioblastoma (GBM), a grade IV glioma, continues to have one of the highest mortality rates among central nervous system tumors. Metabolomics is a particularly promising tool for the analysis of GBM tumors and potential methods of treating them, as it is the only "omics" approach that is capable of providing a metabolic signature of a tumor's phenotype. With careful experimental design, cell cultures can be a useful matrix in GBM metabolomics, as they ensure stable conditions and, under proper conditions, are capable of capturing different tumor phenotypes. This paper reviews in vitro metabolomic profiling studies of high-grade gliomas, with a particular focus on sample-preparation techniques, crucial metabolites identified, cell culture conditions, in vitro-in vivo extrapolation, and pharmacometabolomics. Ultimately, this review aims to elucidate potential future directions for in vitro GBM metabolomics.

Cell metabolomics analyses revealed a role of altered fatty acid oxidation in neurotoxicity pattern difference between nab-paclitaxel and solvent-based paclitaxel

Peripheral neuropathy (PN) is a dose-limiting, painful adverse reaction associated with the use of paclitaxel. This common side effect was often partially attributed to the solvent used for solubilization of the highly hydrophobic drug substance. Therefore, the development of alternative formulations thrived, which included that of Abraxane® containing nanoparticle albumin-bound paclitaxel (nab-paclitaxel). However, studies demonstrated inconsistent conclusions regarding the mitigation of PN in comparison with the traditional formulation. The mass spectrometry-based cell metabolomics approach was used in the present study to explore the potentially associated mechanisms. Although no significant difference in the effects on cell viability was observed, fold changes in carnitine, several acylcarnitines and long-chain fatty acid(s) were significantly different between treatment groups in differentiated and undifferentiated SH-SY5Y cells. The most prominent difference observed was the significant increase of octanoylcarnitine in cells treated with solvent-based paclitaxel, which was found to be associated with significant decrease of medium-chain acyl-CoA dehydrogenase (MCAD). The findings suggested the potential role of altered fatty acid oxidation in the different neurotoxicity patterns observed, which may be a possible target for therapeutic interventions worth further investigation.

Differences in Fatty Acid Oxidation between Nab-Paclitaxel- and Solvent-Based Paclitaxel-Treated A549 Cells Based on Metabolomics

The pharmacokinetics, safety, and anticancer efficacy profiles of nanoparticle albumin-bound (nab)-paclitaxel formulations are superior to those of solvent-based paclitaxel formulations. The aims of the present study were to study the effects of nab-paclitaxel and solvent-based paclitaxel formulations on the metabolic profiles of the model cell line (A549) and attempt to elucidate the associated metabolic pathways. A mass spectrometry-based cell metabolomics approach and viability evaluation were used to explore the potential difference. Western blotting was utilized to measure the levels of relevant proteins, and carnitine palmitoyltransferase 1 (CPT1) activities were quantified. Fold changes normalized to controls in levels of carnitine and several acylcarnitines were significantly different (p < 0.05) between A549 cells treated with nab-paclitaxel and those treated with solvent-based paclitaxel. Relative to the controls, there were also significant fold change differences in palmitic and linoleic acid levels in the cell lysates, mitochondrial CPT1 activities, and mitochondrial medium-chain acyl-CoA dehydrogenase (MCAD) protein levels in the A549 cells subjected to the nab-paclitaxel and solvent-based paclitaxel formulations. Results suggested that the two formulations differentially modulated fatty acid oxidation in the A549 cells. While cell viability results did not reveal significant differences, the findings implied that a mass spectrometry-based cell metabolomics approach could be a sensitive tool to explore the differences caused by formulation changes without using animals. Since uncertainties of products containing nanomaterials warrant holistic screening to address safety concerns, the aforementioned approach may be of regulatory importance and is worth further investigation.

Development of a prototype device for near real-time surface-enhanced Raman scattering monitoring of biological samples

With the fast growth of bioanalytical surface-enhanced Raman scattering (SERS), analytical methods have had to adapt to the complex nature of biological samples. In particular, interfering species and protein adsorption onto the SERS substrates have been addressed by sample preparation steps, such as precipitation or extraction, and by smart SERS substrate functionalisation. These additional handling steps however result in irreversible sample alteration, which in turn prevents sample monitoring over time. A new methodology, that enables near real-time, non-invasive and non-destructive SERS monitoring of biological samples, is therefore proposed. It combines solid SERS substrates, benefitting from liquid immersion resistance for extended periods of time, with an original protein filtering device and an on-field detection by means of a handheld Raman analyser. The protein removal device aims at avoiding protein surface fouling on the SERS substrate. It consists of an ultracentrifugation membrane fixed under a cell culture insert for multi-well plates. The inside of the insert is dedicated to containing biological samples. The solid SERS substrate and a simple medium, without any protein, are placed under the insert. By carefully selecting the membrane molecular weight cutoff, selective diffusion of small analytes through the device could be achieved whereas larger proteins were retained inside the insert. Non-invasive SERS spectral acquisition was then carried out through the bottom of the multi-well plate. The diffusion of a SERS probe, 2-mercaptopyridine, and of a neurotransmitter having a less intense SERS signal, serotonin, were first successfully monitored with the device. Then, the latter was applied to distinguish between subclones of cancerous cells through differences in metabolite production. This promising methodology showed a high level of versatility, together with the capability to reduce cellular stress and contamination hazards.

Novel Insights into Mice Multi-Organ Metabolism upon Exposure to a Potential Anticancer Pd(II)-Agent

Pd(II)-compounds are presently regarded as promising anticancer drugs, as an alternative to Pt(II)-based drugs (e.g., cisplatin), which typically trigger severe side-effects and acquired resistance. Dinuclear Pd(II) complexes with biogenic polyamines such as spermine (Pd₂Spm) have exhibited particularly beneficial cytotoxic properties, hence unveiling the importance of understanding their impact on organism metabolism. The present study reports the first nuclear magnetic resonance (NMR)-based metabolomics study to assess the in vivo impact of Pd₂Spm on the metabolism of healthy mice, to identify metabolic markers with possible relation to biotoxicity/side-effects and their dynamics. The changes in the metabolic profiles of both aqueous and lipophilic extracts of mice kidney, liver, and breast tissues were evaluated, as a function of drug-exposure time, using cisplatin as a reference drug. A putative interpretation was advanced for the metabolic deviations specifically triggered by Pd₂Spm, this compound generally inducing faster metabolic response and recovery to control levels for all organs tested, compared to cisplatin (except for kidney lipid metabolism). These results constitute encouraging preliminary metabolic data suggestive of potential lower negative effects of Pd₂Spm administration.

UPLC-orbitrap-MS-based metabolic profiling of HaCaT cells exposed to withanolides extracted from Datura metel.L: Insights from an untargeted metabolomics

In recent decades, more and more attention to the withanolides extracted from Datura metel.L has been paid due to their anti-psoriatic effects. Withanolides have also been reported to exhibit anti-inflammatory and anti-proliferative properties. Thus, withanolides have been considered as a promising candidate of anti-psoriatic drug. The aim of this study was to investigated the metabolic network of HaCaT cells after exposure to withanolides to identify anti-psoriatic mechanism induced by withanolides on skin cells. In this experiment, our results demonstrated that exposure to withanolides at concentrations beyond 50 μg/mL inhibited cell proliferation and induced cell apoptosis in a dose-dependent manner. In addition, withanolides-induced reactive oxygen species (ROS) generation and mitochondrial depolarization in HaCaT cells. In this research, ultra-high performance liquid chromatography coupled with orbitrap mass spectrometry (UPLC-orbitrap-MS) method was applied to profile metabolite changes in HaCaT cells exposed to withanolides. In total, significant variations in 38 differential metabolites were identified between withanolides exposure and untreated groups. The exposure of HaCaT cells to withanolides at the dose of 200 μg/mL for 24 h was revealed by the disturbance of energy metabolism, amino acid metabolism, lipid metabolism and nucleic acid metabolism. UPLC-orbitrap-MS-based cell metabolomics provided a comprehensive method for the identification of withanolides' anti-psoriasis mechanisms in vitro. And above metabolic disorders also reflected potential therapeutic targets for treating psoriasis.

Uncovering the Effect of Passage Number on HT29 Cell Line Based on the Cell Metabolomic Approach

The passage number is an important factor when designing the cell line-based experiment. Although HT29 cells were widely used in the laboratory for colorectal cancer studies, the impact of cell passage number on the HT29 cells was still unknown. In this study, phenotypic assay and metabolomic approach were applied to analyze the systemic effects of passage numbers (passage 4, 10, and 16) on the HT29 cells. The results showed that the increased cell passage number affected the cell cycle distribution and also decreased the proliferation and migration ability of HT29 cells. The metabolomic analysis coupled with heatmap and hierarchical cluster analysis showed obvious metabolome difference among the cells with different passage numbers, which was related with 61 differential metabolites. Three metabolic pathways were determined as the key pathways, and arginine participated in two of them. In addition, it was found that arginine supplementation could inhibit the proliferation ability of HT29 cells in vitro, and a synergistic effect existed between arginine and cisplatin. In conclusion, this study not only revealed the influence of passage numbers on the HT29 cell but also provided an important reference that arginine has the potential role to be developed as the cisplatin therapeutic adjuvant.

Convergence of Plasma Metabolomics and Proteomics Analysis to Discover Signatures of High-Grade Serous Ovarian Cancer

Simple Summary

In-time diagnosing ovarian cancer, intractable cancer that has no symptoms can increase the survival of women. The aim of this study was to discover biomarkers from liquid biopsy samples using multi-omics approach, metabolomics and proteomics for the diagnosis of ovarian cancer. To verify our biomarker candidates, we conducted comparative analysis with other previous published studies. Despite the limitations of non-invasive samples, our findings are able to discover emerging properties through the interplay between metabolites and proteins and mechanism-based biomarkers through integrated protein and metabolite analysis.

Abstract

The 5-year survival rate in the early and late stages of ovarian cancer differs by 63%. In addition, a liquid biopsy is necessary because there are no symptoms in the early stage and tissue collection is difficult without using invasive methods. Therefore, there is a need for biomarkers to achieve this goal. In this study, we found blood-based metabolite or protein biomarker candidates for the diagnosis of ovarian cancer in the 20 clinical samples (10 ovarian cancer patients and 10 healthy control subjects). Plasma metabolites and proteins were measured and quantified using mass spectrometry in ovarian cancer patients and control groups. We identified the differential abundant biomolecules (34 metabolites and 197 proteins) and statistically integrated molecules of different dimensions to better understand ovarian cancer signal transduction and to identify novel biological mechanisms. In addition, the biomarker reliability was verified through comparison with existing research results. Integrated analysis of metabolome and proteome identified emerging properties difficult to grasp with the single omics approach, more reliably interpreted the cancer signaling pathway, and explored new drug targets. Especially, through this analysis, proteins (PPCS, PMP2, and TUBB) and metabolites (L-carnitine and PC-O (30:0)) related to the carnitine system involved in cancer plasticity were identified.

Mass Spectrometry-Based Metabolic Fingerprinting Contributes to Unveil the Role of RSUME in Renal Cell Carcinoma Cell Metabolism

Clear cell renal cell carcinoma (ccRCC) is a heterogeneous disease with 50-80% patients exhibiting mutations in the von Hippel-Lindau (VHL) gene. RSUME (RWD domain (termed after three major RWD-containing proteins: RING finger-containing proteins, WD-repeat-containing proteins, and yeast DEAD (DEXD)-like helicases)-containing protein small ubiquitin-related modifier (SUMO) enhancer) acts as a negative regulator of VHL function in normoxia. A discovery-based metabolomics approach was developed by means of ultraperformance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (MS) for fingerprinting the endometabolome of a human ccRCC cell line 786-O and three other transformed cell systems (n = 102) with different expressions of RSUME and VHL. Cross-validated orthogonal projection to latent structures discriminant analysis models were built on positive, negative, and a combination of positive- and negative-ion mode MS data sets. Discriminant feature panels selected by an iterative multivariate classification allowed differentiating cells with different expressions of RSUME and VHL. Fifteen identified discriminant metabolites with level 1, including glutathione, butyrylcarnitine, and acetylcarnitine, contributed to understand the role of RSUME in ccRCC. Altered pathways associated with the RSUME expression were validated by biological and bioinformatics analyses. Combined results showed that in the absence of VHL, RSUME is involved in the downregulation of the antioxidant defense system, whereas in the presence of VHL, it acts in rerouting energy-related pathways, negatively modulating the lipid utilization, and positively modulating the fatty acid synthesis, which may promote deposition in droplets.

NMR-based metabolomic analysis for the effects of Huiyang Shengji extract on rat diabetic skin ulcers

ETHNOPHARMACOLOGICAL RELEVANCE

Huiyang Shengji formula (HSF) is a compound Chinese herbal medicine prescription, and has long been used for treating chronic non-healing wounds.

AIM OF THE STUDY

The purpose of this study was to provide new insight into molecular mechanisms of healing effects of the HSF treatments.

MATERIALS AND METHODS

We established a rat diabetic skin ulcer (DSU) model, and assessed healing effects of four HSF treatments on DSUs by calculating wound healing rates and immunohistochemical detection of the expressions of angiogenesis-related factors in the model rats (Mod) relative to normal rats (Nor), including Huiyang extract (HE), Shengji extract (SE), Huiyang Shengji extract (HSE) and HSE associated with acupuncture (Ac-HSE). We then performed NMR-based metabolomic analyses on skin tissues of the Nor, Mod, HSE-treated, Ac-HSE-treated rats to address metabolic mechanisms underlying these effects.

RESULTS

These treatments up-regulated expressions of two angiogenesis-related factors VEGF and CD31, and improved efficacy of healing DSUs, in which HSE and Ac-HSE exhibited the most significant effects. Compared with Mod, HSE and Ac-HSE groups shared four characteristic metabolites (lactate, histidine, succinate and acetate) and four significantly altered metabolic pathways with Nor. Both HSE and Ac-HSE treatments could partly reverse the metabolically disordered pathological state of DSUs to the normal state. They might improve wound healing through promoting glucose metabolism, BCAAs metabolism, and enhancing antioxidant capacity and angiogenesis in DSU tissues. Ac-HSE significantly enhanced wound healing rates compared to HSE, potentially owing to significant capacities of enhancing anti-oxidation and angiogenesis and interfering three more metabolic pathways.

CONCLUSIONS

This work provides a mechanistic understanding of the healing effects of the HSE and Ac-HSE treatments on DSUs, is of benefit to improvements of the HSF treatments for clinically healing chronic non-healing wounds.

Insights in Osteosarcoma by Proton Nuclear Magnetic Resonance Serum Metabonomics

Pediatric osteosarcoma outcomes have improved over the last decades; however, patients who do not achieve a full resection of the tumor, even after aggressive chemotherapy, have the worst prognosis. At a genetic level, osteosarcoma presents many alterations, but there is scarce information on alterations at metabolomic levels. Therefore, an untargeted nuclear magnetic resonance metabonomic approach was used to reveal blood serum alterations, when samples were taken from 21 patients with osteosarcoma aged from 12–20 (18, 86%) to 43 (3, 14%) years before any anticancer therapy were collected. The results showed that metabolites differed greatly between osteosarcoma and healthy control serum samples, especially in lipids, aromatic amino acids (phenylalanine and tyrosine), and histidine concentrations. Besides, most of the loading plots point to protons of the fatty acyls (-CH₃ and -CH₂-) from very-low- and low-density lipoproteins and cholesterol, as crucial metabolites for discrimination of the patients with osteosarcoma from the healthy samples. The relevance of blood lipids in osteosarcoma was highlighted when analyzed together with the somatic mutations disclosed in tumor samples from the same cohort of patients, where six genes linked to the cholesterol metabolism were found being altered too. The high consistency of the discrimination between osteosarcoma and healthy control blood serum suggests that nuclear magnetic resonance could be successfully applied for osteosarcoma diagnostic and prognostic purposes, which could ameliorate the clinical efficacy of therapy.

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.

Aspirin Modifies Inflammatory Mediators and Metabolomic Profiles and Contributes to the Suppression of Obesity-Associated Breast Cancer Cell Growth

Breast cancer is the most common cancer among women. Adiposity generally accompanies immune cell infiltration and cytokine secretion, which is ideal for tumor development. Aspirin is a chemopreventive agent against several types of cancer. The aim of this study was to investigate whether aspirin inhibits the growth of 4T1 breast cancer cells by inhibiting the inflammatory response and regulating the metabolomic profile of 3T3-L1 adipocytes. 3T3-L1 adipocyte-conditioned medium (Ad-CM) was used to mimic the obese adipose tissue microenvironment in 4T1 cells. The results revealed that aspirin inhibited macrophage chemoattractant protein (MCP-1), interleukin (IL-6), IL-1β, and plasminogen activator inhibitor (PAI-1) production in 3T3-L1 adipocytes stimulated by tumor necrosis factor-alpha (TNF-α) and lipopolysaccharide (LPS). In the obesity-associated model, Ad-CM significantly promoted 4T1 cell growth and migration, which were attenuated after aspirin treatment. The results of metabolic analyses using Ad-CM showed that amino acid metabolites and oxidative stress were increased in mature 3T3-L1 adipocytes compared to those in fibroblasts. Aspirin treatment modified metabolites involved in suppressing lipogenesis, oxidative stress, and neoplastic formation. In the relative fatty acid quantitation analysis of Ad-CM, aspirin diminished fatty acid contents of C16:1, C18:1, C18:2, C20:4, and C24:1. This study is the first to show that aspirin modifies the metabolomics and fatty acid composition of 3T3-L1 adipocytes and inhibits obesity-associated inflammation that contributes to obesity-related breast cancer cell growth and migration.

Proteomics and metabolomics - Current and future perspectives in clinical andrology

Proteomics and metabolomics are emerging as promising tools to investigate the molecular mechanisms associated with male infertility. Proteins and metabolites play a pivotal role in regulating the molecular pathways associated with physiological functions of spermatozoa. Semen analysis, physical examination and laboratory work up cannot identify the etiology of infertility in 30%-40% of cases, which are classified as idiopathic. Therefore, the application of proteomics and metabolomics in the field of andrology will aid to overcome the limitations of the standard semen analysis. Understanding the molecular pathways associated with male infertility will help in planning ad hoc treatments, contributing to the clinical management of infertile patients. In this review, proteomics and metabolomics studies on spermatozoa and seminal plasma are discussed with a focus on molecular biomarkers associated with male infertility-related conditions.

Metabolomic characterization of colorectal cancer cell lines highlighting stage-specific alterations during cancer progression

Introduction: Metabolomic studies on various colorectal cancer (CRC) cell lines have improved our understanding of the biochemical events underlying the disease. However, the metabolic profile dynamics associated with different stages of CRC progression is still lacking. Such information can provide further insights into the pathophysiology and progression of the disease that will prove useful in identifying specific targets for drug designing and therapeutics. Thus, our study aims to characterize the metabolite profiles in the established cell lines corresponding to different stages of CRC. Methods: Metabolite profiling of normal colon cell lines (CCD 841 CoN) and CRC cell lines corresponding to different stages, i.e., SW 1116 (stage A), HT 29 and SW 480 (stage B), HCT 15 and DLD-1 (stage C), and HCT 116 (stage D), was carried out using liquid chromatography-mass spectrometry (LC-MS). Mass Profiler Professional and Metaboanalyst 4.0 software were used for statistical and pathway analysis. METLIN database was used for the identification of metabolites. Results: We identified 72 differential metabolites compared between CRC cell lines of all the stages and normal colon cells. Principle component analysis and partial least squares discriminant analysis score plot were used to segregate normal and CRC cells, as well as CRC cells in different stages of the disease. Variable importance in projection score identified unique differential metabolites in CRC cells of the different stages. We identified 7 differential metabolites unique to stage A, 3 in stage B, 5 in stage C, and 5 in stage D. Conclusion: This study highlights the differential metabolite profiling in CRC cell lines corresponding to different stages. The identification of the differential metabolites in CRC cells at individual stages will lead to a better understanding of the pathophysiology of CRC development and progression and, hence, its application in treatment strategies.

Bigdata analytics identifies metabolic inhibitors and promoters for productivity improvement and optimization of monoclonal antibody (mAb) production process

Recent advances in metabolite quantification and identification have enabled new research into the detection and control of titer inhibitors and promoters. This paper presents a bigdata analytics study to identify both inhibitors and promoters using multivariate data analysis of metabolomics data. By applying multi-way partial least squares (PLS) model to metabolite data from four fed-batch bioreactor conditions where feed formulation and selection agent concentrations varied, metabolites which exhibited the most significant impact on titer during cultivation were ranked from highest to lowest. The model outputs were then constrained to reduce the number of statistically relevant inhibitors or promoters to the top ten, which were used to conduct metabolic pathway analysis. Furthermore, a method is presented for identifying amino acids that prevent the accumulation of the inhibitors and/or enhance the formation of promoters during production. Finally, the metabolomics and pathway analysis results were integrated and validated with transcriptomics data to characterize metabolic changes occurring among different growth conditions. From these results, new feeding strategies were implemented which resulted in increased fed-batch production titer. Methodology from this work could be applied to future process optimization strategies for biotherapeutic production.

Malignancy Grade-Dependent Mapping of Metabolic Landscapes in Human Urothelial Bladder Cancer: Identification of Novel, Diagnostic, and Druggable Biomarkers

Background: Urothelial bladder cancer (UBC) is one of the cancers with the highest mortality rate and prevalence worldwide; however, the clinical management of the disease remains challenging. Metabolomics has emerged as a powerful tool with beneficial applications in cancer biology and thus can provide new insights on the underlying mechanisms of UBC progression and/or reveal novel diagnostic and therapeutic schemes. Methods: A collection of four human UBC cell lines that critically reflect the different malignancy grades of UBC was employed; RT4 (grade I), RT112 (grade II), T24 (grade III), and TCCSUP (grade IV). They were examined using Nuclear Magnetic Resonance, Mass Spectrometry, and advanced statistical approaches, with the goal of creating new metabolic profiles that are mechanistically associated with UBC progression toward metastasis. Results: Distinct metabolic profiles were observed for each cell line group, with T24 (grade III) cells exhibiting the most abundant metabolite contents. AMP and creatine phosphate were highly increased in the T24 cell line compared to the RT4 (grade I) cell line, indicating the major energetic transformation to which UBC cells are being subjected during metastasis. Thymosin β4 and β10 were also profiled with grade-specific patterns of expression, strongly suggesting the importance of actin-cytoskeleton dynamics for UBC advancement to metastatic and drug-tolerant forms. Conclusions: The present study unveils a novel and putatively druggable metabolic signature that holds strong promise for early diagnosis and the successful chemotherapy of UBC disease.

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.