Metabolites — Open Access Journal

Emerging fusariotoxins, mainly enniatins (ENNs) and beauvericin (BEA), are secondary toxic metabolites produced by Fusarium spp. and are widely distributed contaminants of cereals and by-products. Mycotoxin contamination in these products supposes an important risk to feed supply security in the feed industry due to the common use of cereals in feed formulations. Hence, continuous monitoring of both raw materials and feed mixtures is highly recommended as stated by sanitary authorities. Therefore, an analytical procedure based on liquid chromatography tandem mass spectrometry and an acetonitrile-based extraction followed by a d-SPE (QuEChERS) step for the simultaneous determination of emerging Fusarium mycotoxins was in-house validated and successfully applied to raw materials (n=39) and feed manufactured with them (n=48). The analytical method was validated following the European guidelines and satisfactory results were obtained. Both raw materials and complete feedstuffs showed mycotoxin contamination at incidences of 18% and 92%, respectively. ENN B was the most commonly found mycotoxin in the analyzed samples at concentrations up to several tens of µg/kg. On the other hand, the co-occurrence of mycotoxins was observed in 47% of samples, ENN B and BEA being the most common combination. These results highlight the necessity to take a vigilant attitude to monitor the occurrence of contaminants in raw materials and feedstuffs throughout the manufacturing chain and storage. Full article

The field of metabolomics generally lacks standardized methods for the preparation of samples prior to analysis. This is especially true for metabolomics of reef-building corals, where the handful of studies that were published employ a range of sample preparation protocols. The utilization of metabolomics may prove essential in understanding coral biology in the face of increasing environmental threats, and an optimized method for preparing coral samples for metabolomics analysis would aid this cause. The current study evaluates three important steps during sample processing of stony corals: (i) metabolite extraction, (ii) metabolism preservation, and (iii) subsampling. Results indicate that a modified Bligh and Dyer extraction is more reproducible across multiple coral species compared to methyl tert-butyl ether and methanol extractions, while a methanol extraction is superior for feature detection. Additionally, few differences were detected between spectra from frozen or lyophilized coral samples. Finally, extraction of entire coral nubbins increased feature detection, but decreased throughput and was more susceptible to subsampling error compared to a novel tissue powder subsampling method. Overall, we recommend the use of a modified Bligh and Dyer extraction, lyophilized samples, and the analysis of brushed tissue powder for the preparation of reef-building coral samples for ¹H NMR metabolomics. Full article

Introduction: Parkinson’s disease (PD) is the second most common neurodegenerative disorder, without any widely available curative therapy. Metabolomics is a powerful tool which can be used to identify unexpected pathway-related disease progression and pathophysiological mechanisms. In this study, metabolomics in brain, plasma and liver was investigated in an experimental PD model, to discover small molecules that are associated with dopaminergic cell loss. Methods: Sprague Dawley (SD) rats were injected unilaterally with 6-hydroxydopamine (6-OHDA) or saline for the vehicle control group into the medial forebrain bundle (MFB) to induce loss of dopaminergic neurons in the substantia nigra pars compacta. Plasma, midbrain and liver samples were collected for metabolic profiling. Multivariate and univariate analyses revealed metabolites that were altered in the PD group. Results: In plasma, palmitic acid (q = 3.72 × 10⁻², FC = 1.81) and stearic acid (q = 3.84 × 10⁻², FC = 2.15), were found to be increased in the PD group. Palmitic acid (q = 3.5 × 10⁻²) and stearic acid (q = 2.7 × 10⁻²) correlated with test scores indicative of motor dysfunction. Monopalmitin (q = 4.8 × 10⁻², FC = −11.7), monostearin (q = 3.72 × 10⁻², FC = −15.1) and myo-inositol (q = 3.81 × 10⁻², FC = −3.32), were reduced in the midbrain. The liver did not have altered levels of these molecules. Conclusion: Our results show that saturated free fatty acids, their monoglycerides and myo-inositol metabolism in the midbrain and enteric circulation are associated with 6-OHDA-induced PD pathology. Full article

Gestational trophoblastic disease (GTD) is a group of highly aggressive, rare tumors. Human chorionic gonadotropin is a common biomarker used in the diagnosis and monitoring of GTD. To improve our knowledge of the pathology of GTD, we performed protein-peptide profiling on the urine of patients affected with gestational trophoblastic neoplasm (GTN). We analyzed urinesamples from patients diagnosed with GTN (n = 26) and from healthy pregnant and non-pregnant controls (n = 17) using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS).Ions were examined in a linear mode over a m/z range of 1000–10,000. All GTN urine samples were analyzed before and after treatment and compared with those of the controls. The statistical analyses included multivariate classification algorithms as well as ROC curves. Urine sample analyses revealed there were significant differences in the composition of the ions between the evaluated groups. Comparing the pre-treatment and group with the pregnant controls, we identified two discriminatory proteins: hemoglobin subunit α (m/z = 1951.81) and complement C4A (m/z = 1895.43). Then, comparing urine samples from the post-treatment cases with those from the non-pregnant controls, we identified the peptides uromodulin fragments (m/z = 1682.34 and 1913.54) and complement C4A (m/z = 1895.43). Full article

Analysis of microscopic specimens has emerged as a useful analytical application in metabolomics because of its capacity for characterizing a highly homogenous sample with a specific interest. The undeviating analysis helps to unfold the hidden activities in a bulk specimen and contributes to the understanding of the fundamental metabolisms in life. In NMR spectroscopy, micro(µ)-probe technology is well-established and -adopted to the microscopic level of biofluids. However, this is quite the contrary with specimens such as tissue, cell and organism. This is due to the substantial difficulty of developing a sufficient µ-size magic-angle spinning (MAS) probe for sub-milligram specimens with the capability of high-quality data acquisition. It was not until 2012; a µMAS probe had emerged and shown promises to µg analysis; since, a continuous advancement has been made striving for the possibility of µMAS to be an effective NMR spectroscopic analysis. Herein, the mini-review highlights the progress of µMAS development—from an impossible scenario to an attainable solution—and describes a few demonstrative metabolic profiling studies. The review will also discuss the current challenges in µMAS NMR analysis and its potential to metabolomics. Full article

Genome-scale metabolic models (GEMs) are manually curated repositories describing the metabolic capabilities of an organism. GEMs have been successfully used in different research areas, ranging from systems medicine to biotechnology. However, the different naming conventions (namespaces) of databases used to build GEMs limit model reusability and prevent the integration of existing models. This problem is known in the GEM community, but its extent has not been analyzed in depth. In this study, we investigate the name ambiguity and the multiplicity of non-systematic identifiers and we highlight the (in)consistency in their use in 11 biochemical databases of biochemical reactions and the problems that arise when mapping between different namespaces and databases. We found that such inconsistencies can be as high as 83.1%, thus emphasizing the need for strategies to deal with these issues. Currently, manual verification of the mappings appears to be the only solution to remove inconsistencies when combining models. Finally, we discuss several possible approaches to facilitate (future) unambiguous mapping. Full article

Cerebral palsy (CP) is one of the most common causes of motor disability in childhood, with complex and heterogeneous etiopathophysiology and clinical presentation. Understanding the metabolic processes associated with the disease may aid in the discovery of preventive measures and therapy. Tissue samples (caudate nucleus) were obtained from post-mortem CP cases (n = 9) and age- and gender-matched control subjects (n = 11). We employed a targeted metabolomics approach using both ¹H NMR and direct injection liquid chromatography-tandem mass spectrometry (DI/LC-MS/MS). We accurately identified and quantified 55 metabolites using ¹H NMR and 186 using DI/LC-MS/MS. Among the 222 detected metabolites, 27 showed significant concentration changes between CP cases and controls. Glycerophospholipids and urea were the most commonly selected metabolites used to develop predictive models capable of discriminating between CP and controls. Metabolomics enrichment analysis identified folate, propanoate, and androgen/estrogen metabolism as the top three significantly perturbed pathways. We report for the first time the metabolomic profiling of post-mortem brain tissue from patients who died from cerebral palsy. These findings could help to further investigate the complex etiopathophysiology of CP while identifying predictive, central biomarkers of CP. Full article

The β-carbonic anhydrase (CA, EC 4.2.1.1) from the pathogenic protozoan Entamoeba histolytica, EhiCA, was investigated for its activation with a panel of natural and non-natural amino acids and amines. EhiCA was potently activated by D-His, D-Phe, D-DOPA, L- and D-Trp, L- and D-Tyr, 4-amino-L-Tyr, histamine and serotonin, with K_As ranging between 1.07 and 10.1 µM. The best activator was D-Tyr (K_A of 1.07 µM). L-Phe, L-DOPA, L-adrenaline, L-Asn, L-Asp, L-Glu and L-Gln showed medium potency activation, with K_As of 16.5–25.6 µM. Some heterocyclic- alkyl amines, such as 2-pyridyl-methyl/ethyl-amine and 4-(2-aminoethyl)-morpholine, were devoid of EhiCA activating properties with K_As > 100 µM. As CA activators have poorly been investigated for their interaction with protozoan CAs, our study may be relevant for an improved understanding of the role of this enzyme in the life cycle of E. histolytica. Full article

Nonalcoholic fatty liver disease (NAFLD) is a common cause ofhepatic abnormalities worldwide. Nonalcoholic steatohepatitis (NASH) is part of the spectrum of NAFLD and leads to progressive liver disease, such as cirrhosis and hepatocellular carcinoma. In NASH patient, fibrosis represents the major predictor of liver-related mortality; therefore, it is important to have an early and accurate diagnosis of NASH. The current gold standard for the diagnosis of NASH is still liver biopsy. The development of biomarkers able to predict disease severity, prognosis, as well as response to therapy without the need for a biopsy is the focus of most up-to-dategenomic, transcriptomic, proteomic, and metabolomic research. In the future, patients might be diagnosed andtreated according to theirmolecular signatures. In this short review, we discuss how information from genomics, proteomics, and metabolomics contribute to the understanding of NAFLD pathogenesis. Full article

The common potato, Solanum tuberosum L., is the fourth most important agricultural crop worldwide. Until recently, vegetative propagation by tubers has been the main method of potato cultivation. A shift of interest to sexual potato reproduction by true botanical seeds is due to the appearance of a new hybrid seed breeding strategy whose successful application for many crop species has been supported by male sterility. This investigation was focused on the study of differences in the metabolite profiles of anthers at the mature pollen stage from male-fertile and male-sterile genotypes of S. tuberosum. Application of gas chromatography coupled with a mass spectrometry method allowed detection of metabolic profiles for 192 compounds. Further data analysis with several libraries fully identified 75 metabolites; a similar amount was defined up to the classes. Metabolic profiles in the anthers of fertile genotypes were significantly distinguished from male-sterile ones by the accumulation of carbohydrates, while the anthers of sterile genotypes contained a higher amount of amino acids. In comparison with male-fertile plants, male-sterile genotypes had undeveloped pollen grain characters; i.e., smaller grain size, a thicker exine, “permanent tetrads” that failed to disintegrate into microspores, and the absence of pollen apertures that might be due to a disorder in the metabolism of carbohydrates and fatty acids. Full article

Background: Thyroid cancer is the most common endocrine malignancy, with papillary thyroid carcinoma (PTC) being the most common (85–90%) among all the different types of thyroid carcinomas. Cancer cells show metabolic alterations and, due to their rapid proliferation, an accumulation of reactive oxygen species, playing a fundamental role in cancer development and progression. Currently, the crosstalk among thyrocytes metabolism, redox balance and oncogenic mutations remain poorly characterized. The aim of this study was to investigate the interplay among metabolic alterations, redox homeostasis and oncogenic mutations in PTC-derived cells. Methods: Metabolic and redox profile, glutamate-cysteine ligase, glutaminase-1 and metabolic transporters were evaluated in PTC-derived cell lines with distinguished genetic background (TPC-1, K1 and B-CPAP), as well as in an immortalized thyroid cell line (Nthy-ori3-1) selected as control. Results: PTC-derived cells, particularly B-CPAP cells, harboring BRAF, TP53 and human telomerase reverse transcriptase (hTERT) mutation, displayed an increase of metabolites and transporters involved in energetic pathways. Furthermore, all PTC-derived cells showed altered redox homeostasis, as reported by the decreased antioxidant ratios, as well as the increased levels of intracellular oxidant species. Conclusion: Our findings confirmed the pivotal role of the metabolism and redox state regulation in the PTC biology. Particularly, the most perturbed metabolic phenotypes were found in B-CPAP cells, which are characterized by the most aggressive genetic background. Full article

There is growing interest in the metabolic interplay between the gut microbiome and host metabolism. Taxonomic and functional profiling of the gut microbiome by next-generation sequencing (NGS) has unveiled substantial richness and diversity. However, the mechanisms underlying interactions between diet, gut microbiome and host metabolism are still poorly understood. Genome-scale metabolic modeling (GSMM) is an emerging approach that has been increasingly applied to infer diet–microbiome, microbe–microbe and host–microbe interactions under physiological conditions. GSMM can, for example, be applied to estimate the metabolic capabilities of microbes in the gut. Here, we discuss how meta-omics datasets such as shotgun metagenomics, can be processed and integrated to develop large-scale, condition-specific, personalized microbiota models in healthy and disease states. Furthermore, we summarize various tools and resources available for metagenomic data processing and GSMM, highlighting the experimental approaches needed to validate the model predictions. Full article

We used nuclear magnetic spectroscopy (NMR) to evaluate the metabolic impacts of crude oil, Corexit 5900A, a dispersant, and a crude oil Corexit 5900A mixture exposure on skeletal muscle, heart, and liver physiology of hatchling loggerhead sea turtles (Caretta caretta). Tissue samples were obtained from 22 seven-day-old hatchlings after a four day cutaneous exposure to environmentally relevant concentrations of crude oil, Corexit 5900A, a combination of crude oil and Corexit 9500A, or a seawater control. We identified 38 metabolites in the aqueous extracts of the liver, and 30 metabolites in both the skeletal and heart muscle aqueous extracts, including organic acids/osmolytes, energy compounds, amino acids, ketone bodies, nucleosides, and nucleotides. Skeletal muscle lactate, creatines, and taurine concentrations were significantly lower in hatchlings exposed to crude oil than in control hatchlings. Lactate, taurine, and cholines appeared to be the basis of some variation in hatchling heart samples, and liver inosine, uracil, and uridine appeared to be influenced by Corexit and crude oil exposure. Observed decreases in concentrations of lactate and creatines may reflect energy depletion in skeletal muscle of oil-exposed animals, while decreased taurine concentrations in these animals may reflect higher oxidative stress. Full article

High performance liquid chromatography (HPLC) is a frequently used technique in carotenoid research. So far, however, little attention has been paid to the fact that many of the organic solvents used in HPLC separation of highly apolar C₄₀ carotenoids impose a significant threat to both health (especially for women) and the general laboratory environment. Here, we developed a solvent combination capable of allowing high-resolution HPLC separation of the C₄₀ carotenoid, spirilloxanthin, and all of its biosynthetic precursors beginning with phytoene, using relatively safe, environmentally friendly solvents. We show that separation of spirilloxanthin and its precursors anhydrorhodovibrin and lycopene using modern ultra-high performance chromatography (UHPLC) poses particular problems for apolar carotenoid separation, due to the long residence times in the sample delivery system, which facilitates carotenoid aggregation. We resolved these problems by developing the solvent delivery combination acetone/acetonitrile/isopropanol/methanol (65/30/5/2 (v/v/v/v)), which allows excellent column separation using the safe isocratic solvent system methanol/tetrahydrofuran (98/2 (v/v)). We also demonstrate that the development strategy for optimizing a solvent system for carotenoid separation can be well-described by the use of the average dielectric constant of the total sample delivery solvent, and present a formal method for analysis of the efficiency of separation. Full article

High resolution magic-angle spinning (HR-MAS) nuclear magnetic resonance (NMR) spectroscopy is increasingly used for profiling of breast cancer tissue, delivering quantitative information for approximately 40 metabolites. One unique advantage of the method is that it can be used to analyse intact tissue, thereby requiring only minimal sample preparation. Importantly, since the method is non-destructive, it allows further investigations of the same specimen using for instance transcriptomics. Here, we discuss technical aspects critical for a successful analysis—including sample handling, measurement conditions, pulse sequences for one- and two dimensional analysis, and quantification methods—and summarize available studies, with a focus on significant associations of metabolite levels with clinically relevant parameters. Full article

Previous studies have shown that metabolomics can be a useful tool to better understand the mechanisms of carcinogenesis; however, alterations in biochemical pathways that lead to bladder cancer (BC) development have hitherto not been fully investigated. In this study, gas chromatography-mass spectrometry (GC-MS)-based metabolomics was applied to unveil the metabolic alterations between low-grade and high-grade BC cultured cell lines. Multivariable analysis revealed a panel of metabolites responsible for the separation between the two tumorigenic cell lines. Significantly lower levels of fatty acids, including myristic, palmitic, and palmitoleic acids, were found in high-grade versus low-grade BC cells. Furthermore, significantly altered levels of some amino acids were observed between low- and high-grade BC, namely glycine, leucine, methionine, valine, and aspartic acid. This study successfully demonstrated the potential of metabolomic analysis to discriminate BC cells according to tumor aggressiveness. Moreover, these findings suggest that bladder tumorigenic cell lines of different grades disclose distinct metabolic profiles, mainly affecting fatty acid biosynthesis and amino acid metabolism to compensate for higher energetic needs. Full article

Coffee drinking has been associated with a lower risk of certain chronic diseases and overall mortality. Its effects on disease risk may vary according to the type of coffee brew consumed and its chemical composition. We characterized variations in the chemical profiles of 76 coffee brew samples representing different brew methods, roast levels, bean species, and caffeine types, either prepared or purchased from outlets in Rockville, Maryland, United States of America. Samples were profiled using liquid chromatography coupled with high-resolution mass spectrometry, and the main sources of chemical variability identified by the principal component partial R-square multivariable regression were found to be brew methods (R_partial² = 36%). A principal component analysis (PCA) was run on 18 identified coffee compounds after normalization for total signal intensity. The three first principal components were driven by roasting intensity (41% variance), type of coffee beans (29%), and caffeine (8%). These variations were mainly explained by hydroxycinnamoyl esters and diketopiperazines (roasting), N-caffeoyltryptophan, N-p-coumaroyltryptophan, feruloylquinic acids, and theophylline (coffee bean variety) and theobromine (decaffeination). Instant coffees differed from all coffee brews by high contents of diketopiperazines, suggesting a higher roast of the extracted beans. These variations will be important to consider for understanding the effects of different coffee brews on disease risk. Full article

Nuclear magnetic resonance (NMR) spectroscopy is a powerful tool for the non-targeted metabolomics of intact biofluids and even living organisms. However, spectral overlap can limit the information that can be obtained from 1D 1H NMR. For example, magnetic susceptibility broadening in living organisms prevents any metabolic information being extracted from solution-state 1D 1H NMR. Conversely, the additional spectral dispersion afforded by 2D 1H-13C NMR allows a wide range of metabolites to be assigned in-vivo in 13C enriched organisms, as well as a greater depth of information for biofluids in general. As such, 2D 1H-13C NMR is becoming more and more popular for routine metabolic screening of very complex samples. Despite this, there are only a very limited number of statistical software packages that can handle 2D NMR datasets for chemometric analysis. In comparison, a wide range of commercial and free tools are available for analysis of 1D NMR datasets. Overtime, it is likely more software solutions will evolve that can handle 2D NMR directly. In the meantime, this application note offers a simple alternative solution that converts 2D 1H-13C Heteronuclear Single Quantum Correlation (HSQC) data into a 1D “spikelet” format that preserves not only the 2D spectral information, but also the 2D dispersion. The approach allows 2D NMR data to be converted into a standard 1D Bruker format that can be read by software packages that can only handle 1D NMR data. This application note uses data from Daphnia magna (water fleas) in-vivo to demonstrate how to generate and interpret the converted 1D spikelet data from 2D datasets, including the code to perform the conversion on Bruker spectrometers. Full article

In Proton Nuclear Magnetic Resonance (¹H-NMR) spectroscopy, the signals assignment procedure is normally conducted by visual inspection of the spectra, by taking advantage of the innate predisposition of human eye for pattern recognition. In the case of untargeted metabolomics investigations on food and body fluids, the complexity of the spectra may lead the user to overlook signals, independently from their biological relevance. Here, we describe a four steps procedure that is designed to guide signals assignment task by visual inspection. The procedure can be employed whenever an experimental plan allows for the application of a univariate statistical analysis on a point-by-point basis, which is commonly the case. By comparing, as a proof of concept, ¹H-NMR spectra of vaginal fluids of healthy and bacterial vaginosis (BV) affected women, we show that the procedure is also readily usable by non-experts in three particularly challenging cases: overlapping multiplets, poorly aligned signals, and signals with very poor signal-to-noise ratio. The paper is accompanied by the necessary codes and examples written in R computational language to allow the interested user gaining a hands-on impression of the procedure’s strengths and weaknesses. Full article