Metabolites — Open Access Journal

The Kulka resorcinol assay (Kulka, R.G., Biochemistry 1956, 63, 542–548) for ketoses has been widely used in the literature but suffers from two major disadvantages: (a) it employs large amounts of potentially harmful reagents for a general biology laboratory environment; and (b) in its original formulation, it is unsuited for modern high-throughput applications. Here, we have developed a modified Kulka assay, which contains a safer formulation, employing approx. 5.4 M HCl in 250 µL aliquots, and is suitable for use in high-throughput systems biology or enzymatic applications. The modified assay has been tested extensively for the measurement of two ketoses—fructose (a common substrate in cell growth experiments) and 1-deoxy-d-xylulose-5-phosphate (DXP), the product of the DXP-synthase reaction—which until now has only been assayable using time-consuming chromatographic methods or radioactivity. The Kulka microassay has a sensitivity of 0–250 nmol fructose or 0–500 nmol DXP. The assay is suitable for monitoring the consumption of fructose in bacterial growth experiments but is too insensitive to be used directly for the measurement of DXP in in vitro enzyme assays. However, we show that after concentration of the DXP-enzyme mix by butanol extraction, the Kulka resorcinol method can be used for enzyme assays. Full article

In a paradigm shift, cancer research efforts are being dedicated to the discovery of chemopreventive agents. The goal of this approach is to delay or prevent the progression of augmented cell division to established cancer. Research has focused on dietary supplements, drugs, and endogenous lipids that possess anti-inflammatory properties. We undertook a lipidomics analysis of potential endogenous anti-inflammatory/anti-proliferative lipids in human plasma. We performed high-resolution mass spectrometric lipidomics analyses of plasma samples from controls and patients with colorectal, kidney, pancreatic, glioblastoma, and breast cancers. We present evidence that endogenous very-long-chain dicarboxylic acids (VLCDCA) are anti-inflammatory lipids that possess chemopreventative properties. In a family of VLCDCAs, we characterized VLCDCA 28:4, which is decreased in the plasma of patients with colorectal, kidney, and pancreatic cancers. The structure of this biomarker was validated by derivatization strategies, synthesis of the analytical standard, and tandem mass spectrometry. Our data suggest that VLCDCA 28:4 may be a useful blood biomarker for a number of cancers and that resupplying this lipid, via a prodrug for example, may offer a new anti-inflammatory therapeutic strategy for delaying or preventing the progression of cancer and other inflammatory diseases. Full article

It has become increasingly important to qualitatively and quantitatively assess the volatile metabolites in a range of bodily fluids for use in monitoring health. There has been relatively little work on the quantitative analysis of compounds, particularly with respect to the effects of ethnicity or geographic location. A novel method for the quantification of compounds in stool using ¹³C labelled compounds as internal standards is presented. Using thermal desorption gas chromatography mass spectrometry, stool samples from 38 healthy volunteers were analysed. The ¹³C labelled compounds, acetone, ethyl butanoate, ethanoic acid, butanoic acid, 3-methylbutanoic acid, and indole, were added as internal standards. This process mimics the solubility characteristics of the compounds and thus the method was able to quantify the compounds within the solid stool. In total, 15 compounds were quantified: Dimethyl sulphide (26–25,626 ng/g), acetone (442–3006 ng/g), ethyl butanoate (39–2468 ng/g), ethyl 2-methylbutanoate (0.3–180 ng/g), dimethyl disulphide (35–1303 ng/g), 1-octen-3-one (12 ng/g), dimethyl trisulphide (10–410 ng/g), 1-octen-3-ol (0.4–58 ng/g), ethanoic acid (672–12,963 ng/g), butanoic acid (2493–11,553 ng/g), 3-methylbutanoic acid (64–8262 ng/g), pentanoic acid (88–21,886 ng/g), indole (290–5477 ng/g), and 3-methyl indole (37–3483 ng/g). Moreover, by altering the pH of the stool to pH 13 in conjunction with the addition of ¹³C trimethylamine, the method was successful in detecting and quantifying trimethylamine for the first time in stool samples (range 40–5312 ng/g). Statistical analysis revealed that samples from U.K. origin had five significantly different compounds (ethyl butanoate, 1-octen-3-ol, ethanoic acid, butanoic acid, pentanoic acid, and indole) from those of South American origin. However, there were no significant differences between vegetarian and omnivore samples. These findings are supported by pre-existing literature evidence. Moreover, we have tentatively identified 12 compounds previously not reported as having been found in stool. Full article

Significant variation in organic acid components was detected in mature fruits of 101 apple accessions using high-performance liquid chromatography. The Malus species predominantly accumulated malic acid and citric acid, whereas wild fruits exhibited significantly higher levels of organic acid content than that in cultivated fruits. Differential accumulation patterns during fruit developmental stages was detected between malic acid and citric acid, thus suggesting a complex genetic regulation mechanism of organic acid metabolism in apple fruit. A highly positive correlation was detected between fruit total organic acid content with malic acid and citric acid content, thus suggesting that malic acid and citric acid are the principal determinants of apple fruit acidity. In contrast to malic acid, citric acid was predominantly detected in partial wild apples, while extremely low to undetectable concentrations of citric acid were observed in cultivated apple fruits; this is likely due to the genetic effects of parental characters. Our results provide vital information that could be useful for future studies on genetic analysis and improvement of organic acid accumulation in apple fruits. Full article

The aim of the present study was to assess the malodorous spoilages of Spanish-style green table olives through microbial and metabolite composition using current measuring techniques (e.g., high-throughput DNA sequencing, headspace solid-phase microextraction combined with gas chromatography-mass spectrometry). Under different alkaline and washing conditions, the spoilage fermentations were reproduced with Gordal and Manzanilla olive cultivars using a low salt concentration (71 g L⁻¹ NaCl) in the initial brine. The degradation of lactic acid and significant increases in volatile fatty acids and phenols were found in all the spoiled samples in comparison with the unspoiled control samples. According to high-throughput DNA sequencing, Cardiobacteriaceae and Ruminococcus were the dominant bacteria in the spoiled samples. PLS regression and Pearson’s correlation coefficient analyses revealed positive and negative correlations among microbial communities, metabolites, and sensory spoilage descriptors. Notably, the “zapatera” descriptor was significantly associated with Propionibacterium, which was positively correlated with acetic acid, propionic acid, succinic acid, and methyl propanoate; while the “butyric” descriptor exhibited a significant positive relationship with the genus Ruminococcus, which gave an almost significant correlation with propionic and butyric acids. Full article

Capturing a valid snapshot of the metabolome requires rapid quenching of enzyme activities. This is a crucial step in order to halt the constant flux of metabolism and high turnover rate of metabolites. Quenching with cold aqueous methanol is treated as a gold standard so far, however, reliability of metabolomics data obtained is in question due to potential problems connected to leakage of intracellular metabolites. Therefore, we investigated the influence of various parameters such as quenching solvents, methanol concentration, inclusion of buffer additives, quenching time and solvent to sample ratio on intracellular metabolite leakage from Chlamydomonas reinhardtii. We measured the recovery of twelve metabolite classes using gas chromatography mass spectrometry (GC-MS) in all possible fractions and established mass balance to trace the fate of metabolites during quenching treatments. Our data demonstrate significant loss of intracellular metabolites with the use of the conventional 60% methanol, and that an increase in methanol concentration or quenching time also resulted in higher leakage. Inclusion of various buffer additives showed 70 mM HEPES (4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid) to be suitable. In summary, we recommend quenching with 60% aqueous methanol supplemented with 70 mM HEPES (−40 °C) at 1:1 sample to quenching solvent ratio, as it resulted in higher recoveries for intracellular metabolites with subsequent reduction in the metabolite leakage for all metabolite classes. Full article

For people with Parkinson’s disease (PD), considered the most common neurodegenerative disease behind Alzheimer’s disease, accurate diagnosis is dependent on many factors; however, misdiagnosis is extremely common in the prodromal phases of the disease, when treatment is thought to be most effective. Currently, there are no robust biomarkers that aid in the early diagnosis of PD. Following previously reported work by our group, we accurately measured the concentrations of 18 bile acids in the serum of a prodromal mouse model of PD. We identified three bile acids at significantly different concentrations (p < 0.05) when mice representing a prodromal PD model were compared with controls. These include ω-murichoclic acid (MCAo), tauroursodeoxycholic acid (TUDCA) and ursodeoxycholic acid (UDCA). All were down-regulated in prodromal PD mice with TUDCA and UDCA at significantly lower levels (17-fold and 14-fold decrease, respectively). Using the concentration of three bile acids combined with logistic regression, we can discriminate between prodromal PD mice from control mice with high accuracy (AUC (95% CI) = 0.906 (0.777–1.000)) following cross validation. Our study highlights the need to investigate bile acids as potential biomarkers that predict PD and possibly reflect the progression of manifest PD. Full article

While progress has been made in discerning genetic associations with Parkinson’s disease (PD), identifying elusive environmental contributors necessitates the application of unconventional hypotheses and experimental strategies. Here, we provide an overview of studies that we conducted on a neurotoxic metabolite produced by a species of common soil bacteria, Streptomyces venezuelae (S. ven), indicating that the toxicity displayed by this bacterium causes stress in diverse cellular mechanisms, such as the ubiquitin proteasome system and mitochondrial homeostasis. This dysfunction eventually leads to age and dose-dependent neurodegeneration in the nematode Caenorhabditis elegans. Notably, dopaminergic neurons have heightened susceptibility, but all of the neuronal classes eventually degenerate following exposure. Toxicity further extends to human SH-SY5Y cells, which also degenerate following exposure. Additionally, the neurons of nematodes expressing heterologous aggregation-prone proteins display enhanced metabolite vulnerability. These mechanistic analyses collectively reveal a unique metabolomic fingerprint for this bacterially-derived neurotoxin. In considering that epidemiological distinctions in locales influence the incidence of PD, we surveyed soils from diverse regions of Alabama, and found that exposure to ~30% of isolated Streptomyces species caused worm dopaminergic neurons to die. In addition to aging, one of the few established contributors to PD appears to be a rural lifestyle, where exposure to soil on a regular basis might increase the risk of interaction with bacteria producing such toxins. Taken together, these data suggest that a novel toxicant within the Streptomyces genus might represent an environmental contributor to the progressive neurodegeneration that is associated with PD. Full article

Brain is a lipid-rich tissue, and fatty acids (FAs) play a crucial role in brain function, including neuronal cell growth and development. This study used GC-MS to survey all detectable FAs in the human parietal cortex (Brodmann area 7). These FAs were accurately quantified in 27 cognitively normal age-matched controls, 16 cases of moderate Alzheimer’s disease (AD), 30 severe AD, and 14 dementia with Lewy bodies (DLB). A total of 24 FA species were identified. Multiple comparison procedures, using stepdown permutation tests, noted higher levels of 13 FAs but the majority of changes were in moderate AD and DLB, rather than severe AD. Subjects with moderate AD and DLB pathology exhibited significantly higher levels of a number of FAs (13 FAs and 12 FAs, respectively). These included nervonic, lignoceric, cis-13,16-docosadienoic, arachidonic, cis-11,14,17-eicosatrienoic, erucic, behenic, α-linolenic, stearic, oleic, cis-10-heptanoic, and palmitic acids. The similarities between moderate AD and DLB were quite striking—arachidic acid was the only FA which was higher in moderate AD than control, and was not similarly affected in DLB. Furthermore, there were no significant differences between moderate AD and DLB. The associations between each FA and a number of variables, including diagnosis, age, gender, Aβ plaque load, tau load, and frontal tissue pH, were also investigated. To conclude, the development of AD or DLB pathology affects brain FA composition but, intriguingly, moderate AD neuropathology impacts this to a much greater extent. Post-mortem delay is a potential confounding factor, but the findings here suggest that there could be a more dynamic metabolic response in the earlier stages of the disease pathology. Full article

To explore novel methods for the analysis of metabolomics data, we compared the ability of Partial Least Squares Discriminant Analysis (PLS-DA) and Bayesian networks (BN) to build predictive plasma metabolite models of age three asthma status in 411 three year olds (n = 59 cases and 352 controls) from the Vitamin D Antenatal Asthma Reduction Trial (VDAART) study. The standard PLS-DA approach had impressive accuracy for the prediction of age three asthma with an Area Under the Curve Convex Hull (AUCCH) of 81%. However, a permutation test indicated the possibility of overfitting. In contrast, a predictive Bayesian network including 42 metabolites had a significantly higher AUCCH of 92.1% (p for difference < 0.001), with no evidence that this accuracy was due to overfitting. Both models provided biologically informative insights into asthma; in particular, a role for dysregulated arginine metabolism and several exogenous metabolites that deserve further investigation as potential causative agents. As the BN model outperformed the PLS-DA model in both accuracy and decreased risk of overfitting, it may therefore represent a viable alternative to typical analytical approaches for the investigation of metabolomics data. Full article

Metabolomics is the identification and quantification of all or specified metabolites in a living system under a specific condition or disease. Metabolomics in cirrhosis can be used in diagnosing complications, determining prognosis and assessment of response to therapy. In this review, we summarized representative applications of metabolomics in cirrhosis and significant metabolites associated with cirrhosis and its complications. Full article

The goal of this study is to map the metabolic pathways of poorly understood bacterial phytopathogen, Xanthomonas oryzae (Xoo) BXO43 fed with plant mimicking media XOM2 containing glutamate, methionine and either 40% [¹³C₅] xylose or 40% [¹³C₆] glucose. The metabolic networks mapped using the KEGG mapper and the mass isotopomer fragments of proteinogenic amino acids derived from GC-MS provided insights into the activities of Xoo central metabolic pathways. The average ¹³C in histidine, aspartate and other amino acids confirmed the activities of PPP, the TCA cycle and amino acid biosynthetic routes, respectively. The similar labelling patterns of amino acids (His, Ala, Ser, Val and Gly) from glucose and xylose feeding experiments suggests that PPP would be the main metabolic route in Xoo. Owing to the lack of annotated gene phosphoglucoisomerase in BXO43, the ¹³C incorporation in alanine could not be attributed to the competing pathways and hence warrants additional positional labelling experiments. The negligible presence of ¹³C incorporation in methionine brings into question its potential role in metabolism and pathogenicity. The extent of the average ¹³C labelling in several amino acids highlighted the contribution of pre-existing pools that need to be accounted for in ¹³C-flux analysis studies. This study provided the first qualitative insights into central carbon metabolic pathway activities in Xoo. Full article

Currently, the energy required to produce biofuel from algae is 1.38 times the energy available from the fuel. Current methods do not deliver scalable, commercially viable cell wall disruption, which creates a bottleneck on downstream processing. This is primarily due to the methods depositing energy within the water as opposed to within the algae. This study investigates ultraviolet B (UVB) as a disruption method for the green algae Chlamydomonas reinhardtii, Dunaliella salina and Micractinium inermum to enhance solvent lipid extraction. After 232 seconds of UVB exposure at 1.5 W/cm², cultures of C. reinhardtii (culture density 0.7 mg/mL) showed 90% disruption, measured using cell counting, correlating to an energy consumption of 5.6 MJ/L algae. Small-scale laboratory tests on C. reinhardtii showed bead beating achieving 45.3 mg/L fatty acid methyl esters (FAME) and UV irradiation achieving 79.9 mg/L (lipids solvent extracted and converted to FAME for measurement). The alga M. inermum required a larger dosage of UVB due to its thicker cell wall, achieving a FAME yield of 226 mg/L, compared with 208 mg/L for bead beating. This indicates that UV disruption had a higher efficiency when used for solvent lipid extraction. This study serves as a proof of concept for UV irradiation as a method for algal cell disruption. Full article

Atypical antipsychotics (AAPs) are a class of medications associated with significant metabolic side effects, including insulin resistance. The aim of this study was to analyze the skeletal muscle lipidome of patients on AAPs, compared to mood stabilizers, to further understand the molecular changes underlying AAP treatment and side effects. Bipolar patients on AAPs or mood stabilizers underwent a fasting muscle biopsy and assessment of insulin sensitivity. A lipidomic analysis of total fatty acids (TFAs), phosphatidylcholines (PCs) and ceramides (CERs) was performed on the muscle biopsies, then lipid species were compared between treatment groups, and correlation analyses were performed with insulin sensitivity. TFAs and PCs were decreased and CERs were increased in the AAP group relative to those in the mood stabilizer group (FDR q-value <0.05). A larger number of TFAs and PCs were positively correlated with insulin sensitivity in the AAP group compared to those in the mood stabilizer group. In contrast, a larger number of CERs were negatively correlated with insulin sensitivity in the AAP group compared to that in the mood stabilizer group. The findings here suggest that AAPs are associated with changes in the lipid profiles of human skeletal muscle when compared to mood stabilizers and that these changes correlate with insulin sensitivity. Full article

Rice (Oryza sativa L.) processing yields ~60 million metric tons of bran annually. Rice genes producing bran metabolites of nutritional and human health importance were assessed across 17 diverse cultivars from seven countries using non-targeted metabolomics, and resulted in 378–430 metabolites. Gambiaka cultivar had the highest number and Njavara had the lowest number of metabolites. The 71 rice bran compounds of significant variation by cultivar included 21 amino acids, seven carbohydrates, two metabolites from cofactors and vitamins, 33 lipids, six nucleotides, and two secondary metabolites. Tryptophan, α-ketoglutarate, γ-tocopherol/β-tocopherol, and γ-tocotrienol are examples of bran metabolites with extensive cultivar variation and genetic information. Thirty-four rice bran components that varied between cultivars linked to 535 putative biosynthetic genes using to the OryzaCyc 4.0, Plant Metabolic Network database. Rice genes responsible for bran composition with animal and human health importance is available for rice breeding programs to utilize in crop improvement. Full article

Microdialysis (MD) can provide continuous information about tissue composition. To assess in critically ill patients adipose tissue metabolic patterns, the relationships between metabolic patterns and blood cytokine concentration associations of adipose tissue energy metabolism and clinical outcome we studied 203 mechanically ventilated general intensive care unit (ICU) patients. Upon ICU admission an MD catheter was inserted into the subcutaneous adipose tissue of the upper thigh to measure lactate (L), glucose, pyruvate (P), and glycerol. Serum concentrations of IL-10, IL-6, IL-8, and TNF-α were determined within 48 h from ICU admission. Mitochondrial dysfunction was defined as L/P ratio >30 and pyruvate ≥70 μmol/L, ischemia as L/P ratio >30 and pyruvate <70 μmol/L and no ischemia/no mitochondrial dysfunction (i.e., aerobic metabolism) was as L/P ratio ≤30. Metabolism was aerobic in 74% of patients. In 13% of patients there was biochemical evidence of ischemia and in 13% of patients of mitochondrial dysfunction. Mitochondrial dysfunction was associated with poor outcome. In conclusion, MD showed that about two thirds of critically ill patients have normal aerobic adipose tissue metabolism. Mitochondrial dysfunction was not common but was associated with poor outcome. Identifying subgroups of critically ill patients is crucial as different treatment strategies may improve survival. Full article

Duchenne muscular dystrophy (DMD) is a musculoskeletal disorder that causes severe morbidity and reduced lifespan. Individuals with DMD have an X-linked mutation that impairs their ability to produce functional dystrophin protein in muscle. No cure exists for this disease and the few therapies that are available do not dramatically delay disease progression. Thus, there is a need to better understand the mechanisms underlying DMD which may ultimately lead to improved treatment options. The muscular dystrophy (MDX) mouse model is frequently used to explore DMD disease traits. Though some studies of metabolism in dystrophic mice exist, few have characterized metabolic profiles of supporting cells in the diseased environment. Using nontargeted metabolomics we characterized metabolic alterations in muscle satellite cells (SCs) and serum of MDX mice. Additionally, live-cell imaging revealed MDX-derived adipose progenitor cell (APC) defects. Finally, metabolomic studies revealed a striking elevation of acylcarnitines in MDX APCs, which we show can inhibit APC proliferation. Together, these studies highlight widespread metabolic alterations in multiple progenitor cell types and serum from MDX mice and implicate dystrophy-associated metabolite imbalances in APCs as a potential contributor to adipose tissue disequilibrium in DMD. Full article

According to Coldiretti, Italy still continues to hold the European Quality record in extra virgin olive oils with origin designation and protected geographical indication (PDO and PGI). To date, 46 Italian brands are recognized by the European Union: 42 PDO and 4 PGI (Tuscan PGI, Calabria PGI; Tuscia PGI and PGI Sicily). Specific regulations, introduced for these quality marks, include the designation of both the geographical areas and the plant varieties contributing to the composition of the olive oil. However, the PDO and PGI assessment procedures are currently based essentially on farmer declarations. Tuscan PGI extra virgin olive oil is one of the best known Italian trademarks around the world. Tuscan PGI varietal platform is rather wide including 31 specific olive cultivars which should account for at least 95% of the product. On the other hand, while the characteristics of other popular Italian extra virgin olive oils (EVOOs) cultivars from specific geographical areas have been extensively studied (such as those of Coratina based blends from Apulia), little is still known about Tuscan PGI EVOO constituents. In this work, we performed, for the first time, a large-scale analysis of Tuscan PGI monocultivar olive oils by ¹H NMR spectroscopy and multivariate statistical analyses (MVA). After genetic characterization of 217 leaf samples from 24 selected geographical areas, distributed all over the Tuscany, a number of 202 micro-milled oil samples including 10 PGI cultivars, was studied. The results of the present work confirmed the need of monocultivar genetically certified EVOO samples for the construction of ¹H-NMR-metabolic profiles databases suitable for cultivar and/or geographical origin assessment. Such specific PGI EVOOs databases could be profitably used to justify the high added value of the product and the sustainability of the related supply chain. Full article

Despite the significant advantages of metabolomic biomarkers, no diagnostic tests based on metabolomics have been introduced to clinical use. There are many reasons for this, centered around substantial obstacles in developing clinically useful metabolomic biomarkers. Most significant is the need for interdisciplinary teams with expertise in metabolomics, analysis of complex clinical and metabolomic data, and clinical care. Importantly, the clinical need must precede biomarker discovery, and the experimental design for discovery and validation must reflect the purpose of the biomarker. Standard operating procedures for procuring and handling samples must be developed from the beginning, to ensure experimental integrity. Assay design is another challenge, as there is not much precedent informing this. Another obstacle is that it is not yet clear how to protect any intellectual property related to metabolomic biomarkers. Viewing a metabolomic biomarker as a natural phenomenon would inhibit patent protection and potentially stifle commercial interest. However, demonstrating that a metabolomic biomarker is actually a derivative of a natural phenomenon that requires innovation would enhance investment in this field. Finally, effective knowledge translation strategies must be implemented, which will require engagement with end users (clinicians and lab physicians), patient advocate groups, policy makers, and payer organizations. Addressing each of these issues comprises the framework for introducing a metabolomic biomarker to practice. Full article