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.

     

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.

     

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.

     

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.

     

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.

     

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.

     

Strategy for automated metabolic profiling of glioma subtypes from ex-vivo HRMAS spectra

Introduction

Infiltrating gliomas are primary brain tumors that express significant biological and clinical heterogeneity in adults, which complicates their treatment and prognosis. Characterization of tumor subtypes using spectroscopic analysis may assist in predicting malignant transformation and quantification of response to therapy.

Study objective

To implement an automated algorithm for classification of metabolomic profiles for the classification of glioma pathological grades and the prediction of malignant progression using spectra obtained by high-resolution magic angle spinning (HR-MAS) spectroscopy of patient-derived tissue samples.

Methods

237 image-guided tissue samples were obtained from 152 patients who underwent surgery for newly diagnosed or recurrent glioma and analyzed via HR-MAS spectroscopy. Orthogonal projection to latent structures discriminant analysis was used as a classifier and the variable-influence-on-projection values were evaluated to identify signature spectral regions.

Results

The accuracy of classifiers developed for discriminating glioma subtypes was 68% for newly diagnosed grade II versus III samples; 86 and 92% for new and recurrent grade III versus IV, respectively; 95% for newly diagnosed grade II versus IV; and 88% for recurrent grade II versus IV lesions. Classifiers distinguished between samples from newly diagnosed vs. recurrent lesions with an accuracy of 78% for grade III and 99% for grade IV glioma.

Conclusion

Classifying metabolomic profiles for new and recurrent glioma without prior assumptions regarding spectral components identified candidate in vivo biomarkers for use in assessing changes that are likely to impact treatment decisions.

     

Investigation of altered urinary metabolomic profiles of invasive ductal carcinoma of breast using targeted and untargeted approaches

Introduction

Invasive ductal carcinoma (IDC) is a type of breast cancer, usually detected in advanced stages due to its asymptomatic nature which ultimately leads to low survival rate. Identification of urinary metabolic adaptations induced by IDC to understand the disease pathophysiology and monitor therapy response would be a helpful approach in clinical settings. Moreover, its non-invasive and cost effective strategy better suited to minimize apprehension among high risk population.

Objective

This study aims toward investigating the urinary metabolic alterations of IDC by targeted (LC-MRM/MS) and untargeted (GC–MS) approaches for the better understanding of the disease pathophysiology and monitoring therapy response.

Methods

Urinary metabolic alterations of IDC subjects (63) and control subjects (63) were explored by targeted (LC-MRM/MS) and untargeted (GC–MS) approaches. IDC specific urinary metabolomics signature was extracted by applying both univariate and multivariate statistical tools.

Results

Statistical analysis identified 39 urinary metabolites with the highest contribution to metabolomic alterations specific to IDC. Out of which, 19 metabolites were identified from targeted LC-MRM/MS analysis, while 20 were identified from the untargeted GC–MS analysis. Receiver operator characteristic (ROC) curve analysis evidenced 6 most discriminatory metabolites from each type of approach that could differentiate between IDC subjects and controls with higher sensitivity and specificity. Furthermore, metabolic pathway analysis depicted several dysregulated pathways in IDC including sugar, amino acid, nucleotide metabolism, TCA cycle etc.

Conclusions

Overall, this study provides valuable inputs regarding altered urinary metabolites which improved our knowledge on urinary metabolomic alterations induced by IDC. Moreover, this study identified several dysregulated metabolic pathways which offer further insight into the disease pathophysiology.

     

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.

     

Using urine metabolomics to understand the pathogenesis of infant respiratory syncytial virus (RSV) infection and its role in childhood wheezing

Background

Respiratory syncytial virus (RSV) infection in infants causes significant morbidity and is the strongest risk factor associated with asthma. Metabolites, which reflect the interactions between host cell and virus, provide an opportunity to identify the pathways that underlie severe infections and asthma development.

Objective

To study metabolic profile differences between infants with RSV infection, and human rhinovirus (HRV) infection, and healthy infants. To compare infant metabolic differences between children who do and do not wheeze.

Methods

In a term birth cohort, urine was collected while healthy and during acute viral respiratory infection with RSV and HRV. We used ¹H-NMR to identify urinary metabolites. Multivariate and univariate statistics were used to discriminate metabolic profiles of infants with either RSV ARI, or HRV ARI, and healthy infants. Multivariable logistic regression was used to assess the association of urine metabolites with 1st-, 2nd-, and 3rd-year recurrent wheezing.

Results

Several metabolites in nicotinate and nicotinamide metabolism pathways were down-regulated in infants with RSV infection compared to healthy controls. There were no significant differences in metabolite profiles between infants with RSV infection and infants with HRV Infection. Alanine was strongly associated with reduced risk of 1st-year wheezing (OR 0.18[0.0, 0.46]) and 2nd-year wheezing (OR 0.31[0.13, 0.73]), while 2-hydroxyisobutyric acid was associated with increased 3rd-year wheezing (OR 5.02[1.49, 16.93]) only among the RSV infected subset.

Conclusion

The metabolites associated with infant RSV infection and recurrent-wheezing are indicative of viral takeover of the cellular machinery and resources to enhance virulence, replication, and subversion of the host immune-response, highlighting metabolic pathways important in the pathogenesis of RSV infection and wheeze development.

     

Predicting ovarian cancer recurrence by plasma metabolic profiles before and after surgery

Background

Previous metabolomic studies have revealed that plasma metabolic signatures may predict epithelial ovarian cancer (EOC) recurrence. However, few studies have performed metabolic profiling of pre- and post-operative specimens to investigate EOC prognostic biomarkers.

Objective

The aims of our study were to compare the predictive performance of pre- and post-operative specimens and to create a better model for recurrence by combining biomarkers from both metabolic signatures.

Methods

Thirty-five paired plasma samples were collected from 35 EOC patients before and after surgery. The patients were followed-up until December, 2016 to obtain recurrence information. Metabolomics using rapid resolution liquid chromatography–mass spectrometry was performed to identify metabolic signatures related to EOC recurrence. The support vector machine model was employed to predict EOC recurrence using identified biomarkers.

Results

Global metabolomic profiles distinguished recurrent from non-recurrent EOC using both pre- and post-operative plasma. Ten common significant biomarkers, hydroxyphenyllactic acid, uric acid, creatinine, lysine, 3-(3,5-diiodo-4-hydroxyphenyl) lactate, phosphohydroxypyruvic acid, carnitine, coproporphyrinogen, l-beta-aspartyl-l-glutamic acid and 24,25-hydroxyvitamin D3, were identified as predictive biomarkers for EOC recurrence. The area under the receiver operating characteristic (AUC) values in pre- and post-operative plasma were 0.815 and 0.909, respectively; the AUC value after combining the two sets reached 0.964.

Conclusion

Plasma metabolomic analysis could be used to predict EOC recurrence. While post-operative biomarkers have a predictive advantage over pre-operative biomarkers, combining pre- and post-operative biomarkers showed the best predictive performance and has great potential for predicting recurrent EOC.

     

Serum metabolomics using ultra performance liquid chromatography coupled to mass spectrometry in lactating dairy cows following a single dose of sporidesmin

Introduction

Photosensitization is a common clinical sign in cows suffering from liver damage caused by the mycotoxin sporidesmin. This disease, called facial eczema (FE), is of major importance in New Zealand. Current techniques for diagnosing animals with subclinical sporidesmin-induced liver damage (i.e. without photosensitization) are nonspecific. In addition, little is known of the mechanisms involved in sporidesmin resistance, nor the early effects seen following low-dose sporidesmin intoxication.

Objective

The objective of this study was to identify individual metabolites or metabolic profiles that could be used as serum markers for early stage FE in lactating cows.

Methods

Results are presented from a 59-day sporidesmin challenge in Friesian-cross dairy cows. Serum metabolite profiles were obtained using reversed phase ultra-performance liquid chromatography (UPLC) electrospray ionization mass spectrometry (MS) and UPLC tandem MS. Multivariate and time series analyses were used to assess the data.

Results

Statistical analysis, both with and without the temporal component, could distinguish the profiles of animals with clinical signs from the others, but not those affected subclinically. An increase in the concentrations of a combination of taurine- and glycine-conjugated secondary bile acids (BAs) was the most likely cause of the separation. This is the first time that MS methods have been applied to FE and that bile acids changes have been detected in cattle exposed to sporidesmin.

Conclusions

It is well known that BA concentrations increase during cholestasis due to damage to bile ducts and leakage of the bile. This is the first study to investigate metabolomic changes in serum following a sporidesmin challenge. Further work to establish the significance of the elevation of individual BAs concentrations in the serum of early-stage sporidesmin-poisoned cows is necessary.

     

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.

     

Metabolic risks at birth of neonates exposed in utero to HIV-antiretroviral therapy relative to unexposed neonates: an NMR metabolomics study of cord blood

Introduction

Antiretroviral therapy (ART) for HIV-infected pregnant women is highly effective in preventing mother-to-child transmission (PMTCT) of the virus, but deleterious metabolic and mitochondrial observations in infants born to HIV-infected women treated with ART during pregnancy are periodically reported.

Objectives

This study addresses the concern of HIV-ART-induced metabolic perturbations through a metabolomics study of cord blood collected during transitional neonatal hypoglycaemia following birth from newborns either exposed or unexposed to fetal HIV-ART.

Methods

Proton magnetic resonance spectra from cord blood of 11 in utero HIV-ART-exposed and 14 unexposed newborns, as well as serum from 8 control infants, generated 114 spectral bins which were used to identify significant metabolites by means of univariate and multivariate statistical analyses.

Results

The metabolite profiles differed significantly between that from the unexposed newborns and that from infants—interpreted to characterize the state of transitional neonatal hypoglycaemia (low glucose and high lactic acid and ketone bodies). Quantitative analysis of potential ATP generation showed no meaningful difference in the global metabolite profiles of HIV-ART-exposed and unexposed neonates, but Volcano plot analysis, affirmed by odds ratios, indicated that exposure to HIV-ART affected the plasma 3-hydroxybutyric acid and hypoxanthine concentrations.

Conclusions

The metabolite profile for transitional neonatal hypoglycaemia indicated that HIV-ART did not compromise the exposed neonates to the energy stress of allostasis experienced at birth. Increased hypoxanthine and 3-hydroxybutyric acid indicates metabolic stress at birth in some of the newborns exposed to HIV-ART and raises a concern about unrecognized prolonged allostasis with potential neurological consequences for these infants.

     

Metabolic characterization of hepatitis B virus-related liver cirrhosis using NMR-based serum metabolomics

Introduction

Liver cirrhosis (LC) is an advanced liver disease that can develop into hepatocellular carcinoma. Hepatitis B virus (HBV) infection is one of the main causes of LC. Therefore, there is an urgent need for developing a new method to monitor the progression of HBV-related LC (HBV-LC).

Objectives

In this study, we attempted to examine serum metabolic changes in healthy individuals as well as patients with HBV and HBV-LC. Furthermore, potential metabolite biomarkers were identified to evaluate patients progressed from health to HBV-LC.

Methods

Metabolic profiles in the serum of healthy individuals as well as patients with HBV and HBV-LC were detected using an NMR-based metabolomic approach. Univariate and multivariate analyses were conducted to analyze serum metabolic changes during HBV-LC progression. Moreover, potential metabolite biomarkers were explored by receiver operating characteristic curve analysis.

Results

Serum metabolic changes were closely associated with the progression of HBV-LC, mainly involving energy metabolism, protein metabolism, lipid metabolism and microbial metabolism. Serum histidine was identified as a potential biomarker for HBV patients. Acetate, formate, pyruvate and glutamine in the serum were identified as a potential biomarker panel for patients progressed from HBV to HBV-LC. In addition, phenylalanine, unsaturated lipid, n-acetylglycoprotein and acetone in the serum could be considered as a potential common biomarkers panel for these patients.

Conclusion

NMR-based serum metabolomic approach could be a promising tool to monitor the progression of liver disease. Different metabolites may reflect different stages of liver disease.

     

Alterations in lipid,amino acid,and energy metabolism distinguish Crohn’s disease from ulcerative colitis and control subjects by serum metabolomic profiling

Introduction

Biomarkers are needed in inflammatory bowel disease (IBD) to help define disease activity and identify underlying pathogenic mechanisms. We hypothesized that serum metabolomics, which produces unique metabolite profiles, can aid in this search.

Objectives

The aim of this study was to characterize serum metabolomic profiles in patients with IBD, and to assess for differences between patients with ulcerative colitis (UC), Crohn’s disease (CD), and non-IBD subjects.

Methods

Serum samples from 20 UC, 20 CD, and 20 non-IBD control subjects were obtained along with patient characteristics, including medication use and clinical disease activity. Non-targeted metabolomic profiling was performed using ultra-high performance liquid chromatography/mass spectrometry (UPLC-MS/MS) optimized for basic or acidic species and hydrophilic interaction liquid chromatography (HILIC/UPLC-MS/MS).

Results

In total, 671 metabolites were identified. Comparing IBD and control subjects revealed 173 significantly altered metabolites (27 increased and 146 decreased). The majority of the alterations occurred in lipid-, amino acid-, and energy-related metabolites. Comparing only CD and control subjects revealed 286 significantly altered metabolites (54 increased and 232 decreased), whereas comparing UC and control subjects revealed only five significantly altered metabolites (all decreased). Hierarchal clustering using significant metabolites separated CD from UC and control subjects.

Conclusions

We demonstrate that a number of lipid-, amino acid-, and tricarboxylic acid cycle-related metabolites were significantly altered in IBD patients, more specifically in CD. Therefore, alterations in lipid and amino acid metabolism and energy homeostasis may play a key role in the pathogenesis of CD.

     

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.

     

Effect of everolimus on the glucose metabolic pathway in mouse skeletal muscle cells (C2C12)

Introduction

Everolimus selectively inhibits mammalian target of rapamycin complex 1 (mTORC1) and exerts an antineoplastic effect. Metabolic disturbance has emerged as a common and unique side effect of everolimus.

Objectives

We used targeted metabolomic analysis to investigate the effects of everolimus on the intracellular glycometabolic pathway.

Methods

Mouse skeletal muscle cells (C2C12) were exposed to everolimus for 48 h, and changes in intracellular metabolites were determined by capillary electrophoresis time-of-flight mass spectrometry. mRNA abundance, protein expression and activity were measured for enzymes involved in glycometabolism and related pathways.

Results

Both extracellular and intracellular glucose levels increased with exposure to everolimus. Most intracellular glycometabolites were decreased by everolimus, including those involved in glycolysis and the pentose phosphate pathway, whereas no changes were observed in the tricarboxylic acid cycle. Everolimus suppressed mRNA expression of enzymes related to glycolysis, downstream of mTOR signaling enzymes and adenosine 5′-monophosphate protein kinases. The activity of key enzymes involved in glycolysis and the pentose phosphate pathway were decreased by everolimus. These results show that everolimus impairs glucose utilization in intracellular metabolism.

Conclusions

The present metabolomic analysis indicates that everolimus impairs glucose metabolism in muscle cells by lowering the activities of glycolysis and the pentose phosphate pathway.