Untargeted and stable isotope-assisted metabolomic analysis of MDA-MB-231 cells under hypoxia

Introduction

Hypoxia commonly occurs in cancers and is highly related with the occurrence, development and metastasis of cancer. Treatment of triple negative breast cancer remains challenge. Knowledge about the metabolic status of triple negative breast cancer cell lines in hypoxia is valuable for the understanding of molecular mechanisms of this tumor subtype to develop effective therapeutics.

Objectives

Comprehensively characterize the metabolic profiles of triple negative breast cancer cell line MDA-MB-231 in normoxia and hypoxia and the pathways involved in metabolic changes in hypoxia.

Methods

Differences in metabolic profiles affected pathways of MDA-MB-231 cells in normoxia and hypoxia were characterized using GC–MS based untargeted and stable isotope assisted metabolomic techniques.

Results

Thirty-three metabolites were significantly changed in hypoxia and nine pathways were involved. Hypoxia increased glycolysis, inhibited TCA cycle, pentose phosphate pathway and pyruvate carboxylation, while increased glutaminolysis in MDA-MB-231 cells.

Conclusion

The current results provide metabolic differences of MDA-MB-231 cells in normoxia and hypoxia conditions as well as the involved metabolic pathways, demonstrating the power of combined use of untargeted and stable isotope-assisted metabolomic methods in comprehensive metabolomic analysis.

     

The mTOR kinase inhibitor Everolimus decreases S6 kinase phosphorylation but fails to reduce mutant huntingtin levels in brain and is not neuroprotective in the R6/2 mouse model of Huntington's disease

Background

Huntington's disease (HD) is a progressive neurodegenerative disorder caused by a CAG repeat expansion within the huntingtin gene. Mutant huntingtin protein misfolds and accumulates within neurons where it mediates its toxic effects. Promoting mutant huntingtin clearance by activating macroautophagy is one approach for treating Huntington's disease (HD). In this study, we evaluated the mTOR kinase inhibitor and macroautophagy promoting drug everolimus in the R6/2 mouse model of HD.

Results

Everolimus decreased phosphorylation of the mTOR target protein S6 kinase indicating brain penetration. However, everolimus did not activate brain macroautophagy as measured by LC3B Western blot analysis. Everolimus protected against early declines in motor performance; however, we found no evidence for neuroprotection as determined by brain pathology. In muscle but not brain, everolimus significantly decreased soluble mutant huntingtin levels.

Conclusions

Our data suggests that beneficial behavioral effects of everolimus in R6/2 mice result primarily from effects on muscle. Even though everolimus significantly modulated its target brain S6 kinase, this did not decrease mutant huntingtin levels or provide neuroprotection.

     

Biosynthesis of glycerol phosphate is associated with long-term potentiation in hippocampal neurons

Introduction

Neurons have a very high energy requirement, and their metabolism is tightly regulated to ensure delivery of adequate substrate to sustain neuronal activity and neuroplastic changes. The mechanisms underlying the regulation of neuronal metabolism, however, are not completely clear.

Objective

The objective of this study was to investigate the central carbon metabolism in neurons, in order to identify the regulatory pathways governing neuronal anabolism and catabolism.

Methods

Here we first have applied MS-based endometabolomics to elucidate the metabolic dynamics in cultured hippocampal primary neurons. Using nanoLC-ESI-LTQ Orbitrap MS approach followed by statistical analysis, we measure the dynamics of uniformly labeled ¹³C-glucose entering neurons. We adapted the method by coupling offline patch-clamp setup with MS to confirm findings in vivo.

Results

According to non-parametric statistical analysis of metabolic dynamics, in cultured hippocampal neurons, the glycerol phosphate shuttle is active and correlates with the metabolic flux in the pentose phosphate pathway. In the hippocampus, glycerol-3-phosphate biosynthesis was activated in response to long-term potentiation together with the upregulation of glycolysis and the TCA cycle, but was inactive or silenced in basal conditions.

Conclusions

We identified the biosynthesis of glycerol-3-phosphate as a key regulator in mechanisms implicated in learning and memory. Notably, defects in enzymes linked with the glycerol phosphate shuttle have been implicated in neurological disorders and intellectual disability_. These results could improve our understanding of the general mechanisms of learning and memory and facilitate the development of novel therapies for metabolic disorders linked with intellectual disability.

     

PKM2 knockdown influences SREBP activation and lipid synthesis in bovine mammary-gland epithelial MAC-T cells

Objective

The purpose of the article is to evaluate the changes in lipid metabolism in bovine mammary-gland epithelial MAC-T cells after PKM2 knockdown.

Results

MAC-T cells stably expressing low levels of PKM2 were established with lentivirus-mediated small hairpin RNA. Although the knockdown of PKM2 had no effect on MAC-T cell growth, the reduced expression of PKM2 attenuated the mRNA and protein expression of key enzymes involved in sterol synthesis through the SREBP pathway.

Conclusions

The downregulation of PKM2 significantly influenced lipid synthesis in bovine mammary-gland epithelial MAC-T cells. These findings extend our understanding of the crosstalk between glycolysis and lipid metabolism in bovine mammary-gland epithelial cells.

     

Non-invasive urinary metabolomic profiling discriminates prostate cancer from benign prostatic hyperplasia

Introduction

Prostate cancer (PCa) is one of the most common malignancies in men worldwide. Serum prostate specific antigen (PSA) level has been extensively used as a biomarker to detect PCa. However, PSA is not cancer-specific and various non-malignant conditions, including benign prostatic hyperplasia (BPH), can cause a rise in PSA blood levels, thus leading to many false positive results.

Objectives

In this study, we evaluated the potential of urinary metabolomic profiling for discriminating PCa from BPH.

Methods

Urine samples from 64 PCa patients and 51 individuals diagnosed with BPH were analysed using ¹H nuclear magnetic resonance (¹H-NMR). Comparative analysis of urinary metabolomic profiles was carried out using multivariate and univariate statistical approaches.

Results

The urine metabolomic profile of PCa patients is characterised by increased concentrations of branched-chain amino acids (BCAA), glutamate and pseudouridine, and decreased concentrations of glycine, dimethylglycine, fumarate and 4-imidazole-acetate compared with individuals diagnosed with BPH.

Conclusion

PCa patients have a specific urinary metabolomic profile. The results of our study underscore the clinical potential of metabolomic profiling to uncover metabolic changes that could be useful to discriminate PCa from BPH in a clinical context.

     

Does centrifugation matter? Centrifugal force and spinning time alter the plasma metabolome

Background

Centrifugation is an indispensable procedure for plasma sample preparation, but applied conditions can vary between labs.

Aim

Determine whether routinely used plasma centrifugation protocols (1500×g 10 min; 3000×g 5 min) influence non-targeted metabolomic analyses.

Methods

Nuclear magnetic resonance spectroscopy (NMR) and High Resolution Mass Spectrometry (HRMS) data were evaluated with sparse partial least squares discriminant analyses and compared with cell count measurements.

Results

Besides significant differences in platelet count, we identified substantial alterations in NMR and HRMS data related to the different centrifugation protocols.

Conclusion

Already minor differences in plasma centrifugation can significantly influence metabolomic patterns and potentially bias metabolomics studies.

     

A methodology for elucidating regulatory mechanisms leading to changes in lipid profiles

Introduction

It is difficult to elucidate the metabolic and regulatory factors causing lipidome perturbations.

Objectives

This work simplifies this process.

Methods

A method has been developed to query an online holistic lipid metabolic network (of 7923 metabolites) to extract the pathways that connect the input list of lipids.

Results

The output enables pathway visualisation and the querying of other databases to identify potential regulators. When used to a study a plasma lipidome dataset of polycystic ovary syndrome, 14 enzymes were identified, of which 3 are linked to ELAVL1—an mRNA stabiliser.

Conclusion

This method provides a simplified approach to identifying potential regulators causing lipid-profile perturbations.

     

Binary similarity measures for fingerprint analysis of qualitative metabolomic profiles

Introduction

Contemporary metabolomic fingerprinting is based on multiple spectrometric and chromatographic signals, used either alone or combined with structural and chemical information of metabolic markers at the qualitative and semiquantitative level. However, signal shifting, convolution, and matrix effects may compromise metabolomic patterns. Recent increase in the use of qualitative metabolomic data, described by the presence (1) or absence (0) of particular metabolites, demonstrates great potential in the field of metabolomic profiling and fingerprint analysis.

Objectives

The aim of this study is a comprehensive evaluation of binary similarity measures for the elucidation of patterns among samples of different botanical origin and various metabolomic profiles.

Methods

Nine qualitative metabolomic data sets covering a wide range of natural products and metabolomic profiles were applied to assess 44 binary similarity measures for the fingerprinting of plant extracts and natural products. The measures were analyzed by the novel sum of ranking differences method (SRD), searching for the most promising candidates.

Results

Baroni-Urbani–Buser (BUB) and Hawkins–Dotson (HD) similarity coefficients were selected as the best measures by SRD and analysis of variance (ANOVA), while Dice (Di1), Yule, Russel-Rao, and Consonni-Todeschini 3 ranked the worst. ANOVA revealed that concordantly and intermediately symmetric similarity coefficients are better candidates for metabolomic fingerprinting than the asymmetric and correlation based ones. The fingerprint analysis based on the BUB and HD coefficients and qualitative metabolomic data performed equally well as the quantitative metabolomic profile analysis.

Conclusion

Fingerprint analysis based on the qualitative metabolomic profiles and binary similarity measures proved to be a reliable way in finding the same/similar patterns in metabolomic data as that extracted from quantitative data.

     

A metabolomics guided exploration of marine natural product chemical space

Introduction

Natural products from culture collections have enormous impact in advancing discovery programs for metabolites of biotechnological importance. These discovery efforts rely on the metabolomic characterization of strain collections.

Objective

Many emerging approaches compare metabolomic profiles of such collections, but few enable the analysis and prioritization of thousands of samples from diverse organisms while delivering chemistry specific read outs.

Method

In this work we utilize untargeted LC–MS/MS based metabolomics together with molecular networking to inventory the chemistries associated with 1000 marine microorganisms.

Result

This approach annotated 76 molecular families (a spectral match rate of 28 %), including clinically and biotechnologically important molecules such as valinomycin, actinomycin D, and desferrioxamine E. Targeting a molecular family produced primarily by one microorganism led to the isolation and structure elucidation of two new molecules designated maridric acids A and B.

Conclusion

Molecular networking guided exploration of large culture collections allows for rapid dereplication of know molecules and can highlight producers of uniques metabolites. These methods, together with large culture collections and growing databases, allow for data driven strain prioritization with a focus on novel chemistries.

     

Identifying metabolic elements that contribute to productivity of 1-propanol bioproduction using metabolomic analysis

Introduction

Previously constructed Escherichia coli strains that produce 1-propanol use the native threonine pathway, or a heterologous citramalate pathway. However, based on the energy and cofactor requirements of each pathway, a combination of the two pathways produces synergistic effects that increase the theoretical maximum yield with a simultaneous unexplained increase in productivity.

Objective

Identification of key factors that contribute to synergistic effect leading to 1-propanol yield and productivity improvement in E. coli with native threonine pathway and heterologous citramalate pathway.

Method

A combination of snapshot metabolomic profiling and dynamic metabolic turnover analysis were used to identify system-wide perturbations that contribute to the productivity improvement.

Result and Conclusion

In the presence of both pathways, increased glucose consumption and elevated levels of glycolytic intermediates are attributed to an elevated phosphoenolpyruvate (PEP)/pyruvate ratio that is known to increase the function of the native phosphotransferase. Turnover analysis of nitrogen containing byproducts reveals that ammonia assimilation, required for the threonine pathway, is streamlined when provided with an NAD(P)H surplus in the presence of the citramalate pathway. Our study illustrates the application of metabolomics in identification of factors that alter cellular physiology for improvement of 1-propanol bioproduction.

     

Crop metabolomics: from diagnostics to assisted breeding

Background

Until recently, plant metabolomics have provided a deep understanding on the metabolic regulation in individual plants as experimental units. The application of these techniques to agricultural systems subjected to more complex interactions is a step towards the implementation of translational metabolomics in crop breeding.

Aim of Review

We present here a review paper discussing advances in the knowledge reached in the last years derived from the application of metabolomic techniques that evolved from biomarker discovery to improve crop yield and quality.

Key Scientific Concepts of Review

Translational metabolomics applied to crop breeding programs.

     

Intracellular trafficking of planar cell polarity proteins

Background

Planar cell polarity (PCP) is a phenomenon in which epithelial cells are polarized along the plane of a tissue. PCP is critical for a variety of developmental processes and is regulated by a set of evolutionarily conserved PCP signaling proteins. Many of the PCP proteins adopt characteristic asymmetric localizations on the opposing cellular boundaries. Currently, the molecular mechanisms that establish and maintain this PCP asymmetry remain largely unclear. Newly synthesized integral PCP proteins are transported along the secretory transport pathway to the plasma membranes. Once delivered to the plasma membranes, PCP proteins undergo endocytosis. Recent studies reveal insights into the intracellular trafficking of PCP proteins, suggesting that intracellular trafficking of PCP proteins contributes to establishing the PCP asymmetry.

Objective

To understand the intracellular trafficking of planar cell polarity proteins in the secretory transport pathway and endocytic transport pathway.

Methods

This review summarizes our current understanding of the intracellular trafficking of PCP proteins. We highlights the molecular mechanisms that regulate sorting of PCP proteins into transport vesicles and how the intracellular trafficking process regulates the asymmetric localizations of PCP proteins.

Results

Current studies reveal novel insights into the molecular mechanisms mediating intracellular trafficking of PCP proteins. This process is critical for delivering newly synthesized PCP proteins to their specific destinations, removing the unstable or mislocalized PCP proteins from the plasma membranes and preserving tissue polarity during proliferation of mammalian skin cells.

Conclusion

Understanding how PCP proteins are delivered in the secretory and endocytic transport pathway will provide mechanistic insights into how the asymmetric localizations of PCP proteins are established and maintained.

     

TIGAR cooperated with glycolysis to inhibit the apoptosis of leukemia cells and associated with poor prognosis in patients with cytogenetically normal acute myeloid leukemia

Background

Cancer cells show increased glycolysis and take advantage of this metabolic pathway to generate ATP. The TP53-induced glycolysis and apoptosis regulator (TIGAR) inhibits aerobic glycolysis and protects tumor cells from intracellular reactive oxygen species (ROS)-associated apoptosis. However, the function of TIGAR in glycolysis and survival of acute myeloid leukemia cells remains unclear.

Methods

We analyzed TIGAR expression in cytogenetically normal (CN-) AML patients and the correlations with clinical and biological parameters. In vivo and in vitro, we tested whether glycolysis may induce TIGAR expression and evaluated the combination effect of glycolysis inhibitor and TIGAR knockdown on human leukemia cell proliferation.

Results

High TIGAR expression was an independent predictor of poor survival and high incidence of relapse in adult patients with CN-AML. TIGAR also showed high expression in multiple human leukemia cell lines and knockdown of TIGAR activated glycolysis through PFKFB3 upregulation in human leukemia cells. Knockdown of TIGAR inhibited the proliferation of human leukemia cells and sensitized leukemia cells to glycolysis inhibitor both in vitro and in vivo. Furthermore, TIGAR knockdown in combination with glycolysis inhibitor 2-DG led leukemia cells to apoptosis. In addition, the p53 activator Nutlin-3α showed a significant combinational effect with TIGAR knockdown in leukemia cells. However, TIGAR expression and its anti-apoptotic effects were uncoupled from overexpression of exogenous p53 in leukemia cells.

Conclusions

TIGAR might be a predictor of poor survival and high incidence of relapse in AML patients, and the combination of TIGAR inhibitors with anti-glycolytic agents may be novel therapies for the future clinical use in AML patients.

     

A systematic review of metabolomics biomarkers for Bisphenol A exposure

Introduction

Bisphenol A (BPA), 2,2-bis(4-hydroxyphenyl) propane, a common industrial chemical which has extremely huge production worldwide, is ubiquitous in the environment. Human have high risk of exposing to BPA and the health problems caused by BPA exposure have aroused public concern. However, the biomarkers for BPA exposure are lacking. As a rapidly developing subject, metabolomics has accumulated a large amount of valuable data in various fields. The secondary application of published metabolomics data could be a very promising field for generating novel biomarkers whilst further understanding of toxicity mechanisms.

Objectives

To summarize the published literature on the use of metabolomics as a tool to study BPA exposure and provide a systematic perspectives of current research on biomarkers screening of BPA exposure.

Methods

We conducted a systematic search of MEDLINE (PubMed) up to the end of June 25, 2017 with the key term combinations of ‘metabolomics’, ‘metabonomics’, ‘mass spectrometry’, ‘nuclear magnetic spectroscopy’, ‘metabolic profiling’ and ‘amino acid profile’ combined with ‘BPA exposure’. Additional articles were identified through searching the reference lists from included studies.

Results

This systematic review included 15 articles. Intermediates of glycolysis, Krebs cycle, β oxidation of long chain fatty acids, pentose phosphate pathway, nucleoside metabolism, branched chain amino acid metabolism, aromatic amino acids metabolism, sulfur-containing amino acids metabolism were significantly changed after BPA exposure, suggesting BPA had a highly complex toxic effects on organism which was consistent with existing studies. The biomarkers most consistently associated with BPA exposure were lactate and choline.

Conclusion

Existing metabolomics studies of BPA exposure present heterogeneous findings regarding metabolite profile characteristics. We need more evidence from target metabolomics and epidemiological studies to further examine the reliability of these biomarkers which link to low, environmentally relevant, exposure of BPA in human body.

     

High-throughput extraction and quantification method for targeted metabolomics in murine tissues

Introduction

Global metabolomics analyses using body fluids provide valuable results for the understanding and prediction of diseases. However, the mechanism of a disease is often tissue-based and it is advantageous to analyze metabolomic changes directly in the tissue. Metabolomics from tissue samples faces many challenges like tissue collection, homogenization, and metabolite extraction.

Objectives

We aimed to establish a metabolite extraction protocol optimized for tissue metabolite quantification by the targeted metabolomics AbsoluteIDQ? p180 Kit (Biocrates). The extraction method should be non-selective, applicable to different kinds and amounts of tissues, monophasic, reproducible, and amenable to high throughput.

Methods

We quantified metabolites in samples of eleven murine tissues after extraction with three solvents (methanol, phosphate buffer, ethanol/phosphate buffer mixture) in two tissue to solvent ratios and analyzed the extraction yield, ionization efficiency, and reproducibility.

Results

We found methanol and ethanol/phosphate buffer to be superior to phosphate buffer in regard to extraction yield, reproducibility, and ionization efficiency for all metabolites measured. Phosphate buffer, however, outperformed both organic solvents for amino acids and biogenic amines but yielded unsatisfactory results for lipids. The observed matrix effects of tissue extracts were smaller or in a similar range compared to those of human plasma.

Conclusion

We provide for each murine tissue type an optimized high-throughput metabolite extraction protocol, which yields the best results for extraction, reproducibility, and quantification of metabolites in the p180 kit. Although the performance of the extraction protocol was monitored by the p180 kit, the protocol can be applicable to other targeted metabolomics assays.

     

Chilling slows anaerobic metabolism to improve anoxia tolerance of insects

Background

Insects are renowned for their ability to survive anoxia. Anoxia tolerance may be enhanced during chilling through metabolic suppression.

Aims

Here, the metabolomic response of insects to anoxia, both with and without chilling, for different durations (12–36 h) was examined to assess the potential cross-tolerance mechanisms.

Results

Chilling during anoxia (cold anoxia) significantly improved survival relative to anoxia at warmer temperatures. Reduced intermediate metabolites and increased lactic acid, indicating a switch to anaerobic metabolism, were characteristic of larvae in anoxia.

Conclusions

Anoxia tolerance was correlated survival improvements after cold anoxia were correlated with a reduction in anaerobic metabolism.

     

Metabolomics of the human aqueous humor

Introduction

The optical elements of the eye—cornea, lens, and vitreous humor—are avascular tissues, and their nutrition and waste removal are provided by aqueous humor (AH). The AH production occurs through the active secretion and the passive diffusion/ultrafiltration of blood plasma. The comparison of the metabolomic profiles of AH and plasma is important for understanding of the mechanisms of biochemical processes and metabolite transport taking place in vivo in ocular tissues.

Objectives

The work is aimed at the determination of concentrations of a wide range of most abundant metabolites in the human AH, the comparison of the metabolomic profiles of AH and serum, and the analysis of the post-mortem metabolomic changes in these two biological fluids.

Methods

The quantitative metabolomic profiling was carried out with the use of two independent methods—high-frequency ¹H NMR spectroscopy and HPLC with high-resolution ESI-MS detection.

Results

The concentrations of 71 most abundant metabolites in blood serum and AH from living patients and human cadavers have been measured. It has been found that the level of ascorbate in AH is by two orders of magnitude higher than that in serum; the levels of other metabolites are either similar to that in serum, or differ from that by a factor of 2–5. The post-mortem metabolomic composition of both serum and AH undergoes rapid and strong changes.

Conclusion

The differences between the metabolomic profiles of AH and serum for majority of metabolites can be attributed to the metabolic activity of the ocular tissues leading to the lack or excess of some metabolites, while the high concentration of ascorbate in AH demonstrates the activity of ascorbate-specific pumps at the blood-aqueous border. The post-mortem metabolomic changes are caused by the disruption of the major biochemical cycles and cell lysis. These changes should be taken into account in the analysis of disease-induced changes in post-mortem samples of the ocular tissues.

     

Quantitative metabolomic analysis of the human cornea and aqueous humor

Introduction

Cornea is the outermost part of the eye supplied mostly by aqueous humor (AH). Therefore, the comparison of the metabolomic compositions of AH and cornea may help to determine which compounds are produced inside the cornea, and which penetrate into cornea from AH for intra-corneal consumption. Keratoconus (KC) is the most common form of the cornea dystrophy, and the analysis of KC corneas can unravel the metabolomic changes occurring in AH and cornea of KC patients.

Objectives

The work is aimed at the determination of concentrations of a wide range of metabolites in the human cornea and AH, the comparison of the metabolomic profiles of cornea and AH, and the comparison of the metabolomic compositions of samples taken from KC patients and normal donors (post-mortem).

Methods

The quantitative metabolomic profiling was carried out with the use of two independent methods—high-frequency ¹H NMR spectroscopy and HPLC with high-resolution ESI-MS detection.

Results

The concentrations of 71 most abundant metabolites in cornea and AH from keratoconus patients and from human cadavers have been measured. It is found that the concentrations of purines and organic acids in cornea are significantly higher than in AH. The KC corneas are characterized by the enhanced levels of acetate and citrate, and also by low values of GSH/GSSG ratios.

Conclusion

A significant difference in the metabolomic compositions of the human AH and cornea has been revealed. The concentrations of glucose and some amino acids in cornea are significantly lower than in AH, indicating their fast consumption inside the cornea. The high levels of organic acids, purines and GSH in cornea should be attributed to their production in the cornea. The enhanced levels of acetate and citrate as well as the low values of GSH/GSSG ratios in KC corneas are the indicators of the oxidative stress.

     

Applications of metabolomics in the study and management of preeclampsia: a review of the literature

Introduction

Preeclampsia represents a major public health burden worldwide, but predictive and diagnostic biomarkers are lacking. Metabolomics is emerging as a valuable approach to generating novel biomarkers whilst increasing the mechanistic understanding of this complex condition.

Objectives

To summarize the published literature on the use of metabolomics as a tool to study preeclampsia.

Methods

PubMed and Web of Science were searched for articles that performed metabolomic profiling of human biosamples using either Mass-spectrometry or Nuclear Magnetic Resonance based approaches and which included preeclampsia as a primary endpoint.

Results

Twenty-eight studies investigating the metabolome of preeclampsia in a variety of biospecimens were identified. Individual metabolite and metabolite profiles were reported to have discriminatory ability to distinguish preeclamptic from normal pregnancies, both prior to and post diagnosis. Lipids and carnitines were among the most commonly reported metabolites. Further work and validation studies are required to demonstrate the utility of such metabolites as preeclampsia biomarkers.

Conclusion

Metabolomic-based biomarkers of preeclampsia have yet to be integrated into routine clinical practice. However, metabolomic profiling is becoming increasingly popular in the study of preeclampsia and is likely to be a valuable tool to better understand the pathophysiology of this disorder and to better classify its subtypes, particularly when integrated with other omic data.