<Superscript>13</Superscript>C-assisted metabolic flux analysis to investigate heterotrophic and mixotrophic metabolism in <Emphasis Type="Italic">Cupriavidus necator</Emphasis> H16

Introduction

Cupriavidus necator H16 is a gram-negative bacterium, capable of lithoautotrophic growth by utilizing hydrogen as an energy source and fixing carbon dioxide (CO₂) through Calvin–Benson–Bassham (CBB) cycle. The potential to utilize synthesis gas (Syngas) and the prospects of rerouting carbon from polyhydroxybutyrate synthesis to value-added compounds makes C. necator an excellent chassis for industrial application.

Objectives

In the context of lack of sufficient quantitative information of the metabolic pathways and to advance in rational metabolic engineering for optimized product synthesis in C. necator H16, we carried out a metabolic flux analysis based on steady-state ¹³C-labelling.

Methods

In this study, steady-state carbon labelling experiments, using either d-[1-¹³C]fructose or [1,2-¹³C]glycerol, were undertaken to investigate the carbon flux through the central carbon metabolism in C. necator H16 under heterotrophic and mixotrophic growth conditions, respectively.

Results

We found that the CBB cycle is active even under heterotrophic condition, and growth is indeed mixotrophic. While Entner–Doudoroff (ED) pathway is shown to be the major route for sugar degradation, tricarboxylic acid (TCA) cycle is highly active in mixotrophic condition. Enhanced flux is observed in reductive pentose phosphate pathway (redPPP) under the mixotrophic condition to supplement the precursor requirement for CBB cycle. The flux distribution was compared to the mRNA abundance of genes encoding enzymes involved in key enzymatic reactions of the central carbon metabolism.

Conclusion

This study leads the way to establishing ¹³C-based quantitative fluxomics for rational pathway engineering in C. necator H16.

     

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.

     

Multivariate strategy for the sample selection and integration of multi-batch data in metabolomics

Introduction

Availability of large cohorts of samples with related metadata provides scientists with extensive material for studies. At the same time, recent development of modern high-throughput ‘omics’ technologies, including metabolomics, has resulted in the potential for analysis of large sample sizes. Representative subset selection becomes critical for selection of samples from bigger cohorts and their division into analytical batches. This especially holds true when relative quantification of compound levels is used.

Objectives

We present a multivariate strategy for representative sample selection and integration of results from multi-batch experiments in metabolomics.

Methods

Multivariate characterization was applied for design of experiment based sample selection and subsequent subdivision into four analytical batches which were analyzed on different days by metabolomics profiling using gas-chromatography time-of-flight mass spectrometry (GC–TOF–MS). For each batch OPLS-DA^® was used and its p(corr) vectors were averaged to obtain combined metabolic profile. Jackknifed standard errors were used to calculate confidence intervals for each metabolite in the average p(corr) profile.

Results

A combined, representative metabolic profile describing differences between systemic lupus erythematosus (SLE) patients and controls was obtained and used for elucidation of metabolic pathways that could be disturbed in SLE.

Conclusion

Design of experiment based representative sample selection ensured diversity and minimized bias that could be introduced at this step. Combined metabolic profile enabled unified analysis and interpretation.

     

NMRProcFlow: a graphical and interactive tool dedicated to 1D spectra processing for NMR-based metabolomics

Introduction

Concerning NMR-based metabolomics, 1D spectra processing often requires an expert eye for disentangling the intertwined peaks.

Objectives

The objective of NMRProcFlow is to assist the expert in this task in the best way without requirement of programming skills.

Methods

NMRProcFlow was developed to be a graphical and interactive 1D NMR (¹H & ¹³C) spectra processing tool.

Results

NMRProcFlow (http://nmrprocflow.org), dedicated to metabolic fingerprinting and targeted metabolomics, covers all spectra processing steps including baseline correction, chemical shift calibration and alignment.

Conclusion

Biologists and NMR spectroscopists can easily interact and develop synergies by visualizing the NMR spectra along with their corresponding experimental-factor levels, thus setting a bridge between experimental design and subsequent statistical analyses.

     

Triterpenoid-rich loquat leaf extract induces growth inhibition and apoptosis of pancreatic cancer cells through altering key flux ratios of glucose metabolism

Introduction

Loquat leaf extract (LLE) is a mixture rich in terpenoids, and has broad biological activities including the inhibition of cancer cell growth. The exact metabolic mechanism of this growth inhibiting effect is not known.

Objectives

We investigated the cellular metabolic effect of LLE, and ursolic acid (UA) on pancreatic cancer cells using a ¹³C carbon tracing technology.

Methods

MIA PaCa-2 cells were cultured in medium containing [1, 2 ¹³C₂]-glucose in the presence of either LLE (50 µg/ml), UA (50 µM), or metformin (1 mM). The mass isotopomer distribution of glucose, lactate, ribose, glutamate and palmitate in medium was determined. Based on the mass isotopomer distribution in metabolites we were able to determine individual ¹³C enrichment (∑M?×?n) and the minimum fraction of new synthesis?(1-M0) in each metabolite. Several flux ratios of energy metabolic pathways were calculated from the mass isotopomer ratios of these metabolites.

Results

We found that tumor viability was suppressed by LLE and UA in a dose dependent manner, and the tumor-inhibiting effect was associated with the changes in oxidative/non-oxidative pentose (Ox/Non-ox) and pyruvate dehydrogenase/isocitrate dehydrogenase (PDH/ICDH) flux ratios resulting in decreased new syntheses of ribose and fatty acids.

Conclusion

Metabolic homeostasis (balance of fluxes) in cancer cells is maintained through the regulation of metabolic fluxes by oncogenes and tumor-suppressor genes. Treatment of MIA PaCa-2 cells by LLE, UA and metformin likely altered key metabolic flux ratios affecting metabolic homeostasis required for energy and macromolecular production in tumor growth.

     

A metabolomics approach to uncover effects of different exercise modalities in type 1 diabetes

Introduction

Exercise-associated metabolism in type 1 diabetes (T1D) remains under-studied due to the complex interplay between exogenous insulin, counter-regulatory hormones and insulin-sensitivity.

Objective

To identify the metabolic differences induced by two exercise modalities in T1D using ultra high-performance liquid chromatography coupled to high-resolution mass spectrometry (UHPLC–HRMS) based metabolomics.

Methods

Twelve T1D adults performed intermittent high-intensity (IHE) and continuous-moderate-intensity (CONT) exercise. Serum samples were analysed by UHPLC–HRMS.

Results

Metabolic profiling of IHE and CONT highlighted exercise-induced changes in purine and acylcarnitine metabolism.

Conclusion

IHE may increase beta-oxidation through higher ATP-turnover. UHPLC–HRMS based metabolomics as a data-driven approach without an a priori hypothesis may help uncover distinctive metabolic effects during exercise in T1D.Clinical trial registration number is www.clinicaltrials.gov: NCT02068638.

     

Extraction of natural products from bark of <Emphasis Type="Italic">Betula pendula</Emphasis> using ionic liquids

Introduction

Aqueous–methanol mixtures have successfully been applied to extract a broad range of metabolites from plant tissue. However, a certain amount of material remains insoluble.

Objectives

To enlarge the metabolic compendium, two ionic liquids were selected to extract the methanol insoluble part of trunk from Betula pendula.

Methods

The extracted compounds were analyzed by LC/MS and GC/MS.

Results

The results show that 1-butyl-3-methylimidazolium acetate (IL-Ac) predominantly resulted in fatty acids, whereas 1-ethyl-3-methylimidazolium tosylate (IL-Tos) mostly yielded phenolic structures. Interestingly, bark yielded more ionic liquid soluble metabolites compared to interior wood.

Conclusion

From this one can conclude that the application of ionic liquids may expand the metabolic snapshot.

     

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.

     

Metabolomic profiling of maternal hair suggests rapid development of intrahepatic cholestasis of pregnancy

Introduction

Intrahepatic cholestasis of pregnancy (ICP) is a common maternal liver disease; development can result in devastating consequences, including sudden fetal death and stillbirth. Currently, recognition of ICP only occurs following onset of clinical symptoms.

Objective

Investigate the maternal hair metabolome for predictive biomarkers of ICP.

Methods

The maternal hair metabolome (gestational age of sampling between 17 and 41 weeks) of 38 Chinese women with ICP and 46 pregnant controls was analysed using gas chromatography–mass spectrometry.

Results

Of 105 metabolites detected in hair, none were significantly associated with ICP.

Conclusion

Hair samples represent accumulative environmental exposure over time. Samples collected at the onset of ICP did not reveal any metabolic shifts, suggesting rapid development of the disease.

     

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.

     

Quantitative analysis of tetrahydrofolate metabolites from <Emphasis Type="Italic">clostridium autoethanogenum</Emphasis>

Introduction

Quantification of tetrahydrofolates (THFs), important metabolites in the Wood–Ljungdahl pathway (WLP) of acetogens, is challenging given their sensitivity to oxygen.

Objective

To develop a simple anaerobic protocol to enable reliable THFs quantification from bioreactors.

Methods

Anaerobic cultures were mixed with anaerobic acetonitrile for extraction. Targeted LC–MS/MS was used for quantification.

Results

Tetrahydrofolates can only be quantified if sampled anaerobically. THF levels showed a strong correlation to acetyl-CoA, the end product of the WLP.

Conclusion

Our method is useful for relative quantification of THFs across different growth conditions. Absolute quantification of THFs requires the use of labelled standards.

     

Insights into gemcitabine resistance and the potential for therapeutic monitoring

Introduction

Gemcitabine is an important component of pancreatic cancer clinical management. Unfortunately, acquired gemcitabine resistance is widespread and there are limitations to predicting and monitoring therapeutic outcomes.

Objective

To investigate the potential of metabolomics to differentiate pancreatic cancer cells that develops resistance or respond to gemcitabine treatment.

Results

We applied 1D ¹H and 2D ¹H–¹³C HSQC NMR methods to profile the metabolic signature of pancreatic cancer cells. ¹³C₆-glucose labeling identified 30 key metabolites uniquely altered between wild-type and gemcitabine-resistant cells upon gemcitabine treatment. Gemcitabine resistance was observed to reprogram glucose metabolism and to enhance the pyrimidine synthesis pathway. Myo-inositol, taurine, glycerophosphocholine and creatinine phosphate exhibited a “binary switch” in response to gemcitabine treatment and acquired resistance.

Conclusion

Metabolic differences between naïve and resistant pancreatic cancer cells and, accordingly, their unique responses to gemcitabine treatment were revealed, which may be useful in the clinical setting for monitoring a patient’s therapeutic response.

     

Metabolomics analysis of liver reveals profile disruption in bovines upon steroid treatment

Introduction

The surveillance of illegal anabolic practices in bovine meat production is necessary to guarantee consumers’ health. Screening strategies based on the recognition of indirect biological effects are considered by the community as promising tools to overcome some limitations of classical analytical methods and might therefore concur to ensure safer food for the consumer.

Objectives

The present work aims at characterizing the metabolic profile induced in liver by administration of anabolic steroids, and at identifying potential disturbances in the hepatic metabolism.

Methods

A total of 32 liver samples, 16 from untreated bulls and 16 from bulls treated with an ear implant (Revalor-XS^®) containing trenbolone acetate (200 mg) and β-estradiol (40 mg), were analyzed following a LC–MS-based metabolomic analysis combining RP and HILIC chromatographic separations. Different multivariate statistical tools were applied to the datasets to select common metabolites that may be considered as potential markers based on their significant changes in concentrations after administration of sexual steroids.

Results

Eight candidate markers were identified. Moreover, a subset of four markers was also validated by a different laboratory that performed the same analysis using an independent instrumental and elaboration platform, confirming the robustness of the results achieved.

Conclusion

This study was performed mimicking experimental conditions that may be used during a potential misuse practice. It is promising in the objective of setting up an analytical strategy to highlight sexual steroids abuse in livestock animals.

     

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.

     

Anti-hyperglycemic effect of loquat leaf extract is associated with the redistribution of glucose carbon to its metabolites: a <Superscript>13</Superscript>C-tracing study in HepG2 cells

Introduction

Loquat leaf extract (LLE) is commonly used in China for a variety of ailments including diabetes. Several recent reports implicate LLE and a sesquiterpene glycoside, one of its components, as being an anti-hyperglycemic agent. However, the underlying mechanism of action of this anti-hyperglycemic agent has not been reported.

Objective

We have conducted a tracer-based metabolomics study to investigate the effects of sesquiterpene and loquat extract on the balance of flux of central glucose metabolism in HepG2 cells and to compare with those of “insulin sensitizers”, metformin and rosiglitazone.

Methods

Human hepatoma HepG2 cells in confluence culture were incubated in Dulbecco’s modified Eagle’s medium containing 50% [1, 2 ¹³C₂]-glucose in the presence of rosiglitazone, metformin, LLE or pure sesquiterpene. Cells were harvested in 48 h. Mass isotopomers of metabolites (glycogen, ribose, deoxyribose, glutamate and palmitate) were determined.

Results

¹³C labeling in metabolic intermediates were summarized in a mass isotopomer matrix. Treatment with loquat extract/sesquiterpene, metformin and rosiglitazone each produced distinctive mass isotopomer patterns reflecting disparate effects on the contribution of glucose to various metabolites production, and on several metabolic flux ratios. The overall effect of LLE and sesquiterpene on glucose metabolism is clearly different from those of the known “insulin sensitizers”.

Conclusion

Our study demonstrates the utility of isotopomer matrix in summarizing metabolic actions of LLE on the balance of fluxes occurring within the central glucose metabolism in HepG2 cells. ¹³C carbon tracing (tracer-based metabolomics) is a useful systems biology tool to elucidate glucose metabolic pathways affected by diabetes and its treatment.

     

Characterization of ankylosing spondylitis and rheumatoid arthritis using <Superscript>1</Superscript>H NMR-based metabolomics of human fecal extracts

Introduction

The differences in fecal metabolome between ankylosing spondylitis (AS)/rheumatoid arthritis (RA) patients and healthy individuals could be the reason for an autoimmune disorder.

Objectives

The study explored the fecal metabolome difference between AS/RA patients and healthy controls to clarify human immune disturbance.

Methods

Fecal samples from 109 individuals (healthy controls 34, AS 40, and RA 35) were analyzed by ¹H NMR spectroscopy. Data were analyzed with principal component analysis (PCA) and orthogonal projection to latent structure discriminant (OPLS-DA) analysis.

Results

Significant differences in the fecal metabolic profiles could distinguish AS/RA patients from healthy controls but could not distinguish between AS and RA patients. The significantly decreased metabolites in AS/RA patients were butyrate, propionate, methionine, and hypoxanthine. Significantly increased metabolites in AS/RA patients were taurine, methanol, fumarate, and tryptophan.

Conclusion

The metabolome variations in feces indicated AS and RA were two homologous diseases that could not be distinguished by ¹H NMR metabolomics.

     

Metabolic response of porcine colon explants to in vitro infection by <Emphasis Type="Italic">Brachyspira hyodysenteriae</Emphasis>: a leap into disease pathophysiology

Introduction

Swine dysentery caused by Brachyspira hyodysenteriae is a production limiting disease in pig farming. Currently antimicrobial therapy is the only treatment and control method available.

Objective

The aim of this study was to characterize the metabolic response of porcine colon explants to infection by B. hyodysenteriae.

Methods

Porcine colon explants exposed to B. hyodysenteriae were analyzed for histopathological, metabolic and pro-inflammatory gene expression changes.

Results

Significant epithelial necrosis, increased levels of l-citrulline and IL-1α were observed on explants infected with B. hyodysenteriae.

Conclusions

The spirochete induces necrosis in vitro likely through an inflammatory process mediated by IL-1α and NO.

     

Monitoring cancer prognosis,diagnosis and treatment efficacy using metabolomics and lipidomics

Introduction

Cellular metabolism is altered during cancer initiation and progression, which allows cancer cells to increase anabolic synthesis, avoid apoptosis and adapt to low nutrient and oxygen availability. The metabolic nature of cancer enables patient cancer status to be monitored by metabolomics and lipidomics. Additionally, monitoring metabolic status of patients or biological models can be used to greater understand the action of anticancer therapeutics.

Objectives

Discuss how metabolomics and lipidomics can be used to (i) identify metabolic biomarkers of cancer and (ii) understand the mechanism-of-action of anticancer therapies. Discuss considerations that can maximize the clinical value of metabolic cancer biomarkers including case–control, prognostic and longitudinal study designs.

Methods

A literature search of the current relevant primary research was performed.

Results

Metabolomics and lipidomics can identify metabolic signatures that associate with cancer diagnosis, prognosis and disease progression. Discriminatory metabolites were most commonly linked to lipid or energy metabolism. Case–control studies outnumbered prognostic and longitudinal approaches. Prognostic studies were able to correlate metabolic features with future cancer risk, whereas longitudinal studies were most effective for studying cancer progression. Metabolomics and lipidomics can help to understand the mechanism-of-action of anticancer therapeutics and mechanisms of drug resistance.

Conclusion

Metabolomics and lipidomics can be used to identify biomarkers associated with cancer and to better understand anticancer therapies.

     

How the chemical features of molecules may have addressed the settlement of metabolic steps

Introduction

While the evolutionary adaptation of enzymes to their own substrates is a well assessed and rationalized field, how molecules have been originally selected in order to initiate and assemble convenient metabolic pathways is a fascinating, but still debated argument.

Objectives

Aim of the present study is to give a rationale for the preferential selection of specific molecules to generate metabolic pathways.

Methods

The comparison of structural features of molecules, through an inductive methodological approach, offer a reading key to cautiously propose a determining factor for their metabolic recruitment.

Results

Starting with some commonplaces occurring in the structural representation of relevant carbohydrates, such as glucose, fructose and ribose, arguments are presented in associating stable structural determinants of these molecules and their peculiar occurrence in metabolic pathways.

Conclusions

Among other possible factors, the reliability of the structural asset of a molecule may be relevant or its selection among structurally and, a priori, functionally similar molecules.