Massive glutamine cyclization to pyroglutamic acid in human serum discovered using NMR spectroscopy

Characterisation of Tenebrio molitor Reared on Substrates Supplemented with Chestnut Shell

Tenebrio molitor larvae represent a sustainable protein source for food and feed. The aim of this study was to evaluate the supplementation of chestnut shell, a by-product of the agro-industrial chain, in growth substrates for T. molitor larvae rearing. Seven-week-old larvae were reared on three different growth substrates: the control group (CTRL) was fed wheat bran, treatment group one was fed wheat bran supplemented with 12.5% w/w chestnut shell (TRT1), and treatment group two was fed wheat bran supplemented with 25% w/w chestnut shell (TRT2). Larval weight, substrate consumption, and mortality were recorded weekly. After 14 days, insect meals were produced for bromatological and colorimetric analysis, and bacterial inhibition activity assay using a microdilution method. The amino acid profile of insects was determined using quantitative nuclear magnetic resonance spectroscopy. Our results showed a lower feed conversion ratio and higher larval survival rate % in TRT2 compared to CTRL (p < 0.05). Proteins and lipids of TRT2 were higher than other groups (p < 0.05). Important differences were observed in the amino acid profile of TRT1 and TRT2 compared to CTRL (p < 0.05). TRT1 and TRT2 showed higher E. coli inhibitory activity than CTRL (p < 0.05). In conclusion, chestnut shell supplementation improved the survival and functional characteristics of larvae and likely impacted the insects' metabolism.

Modeling blood metabolite homeostatic levels reduces sample heterogeneity across cohorts

Blood metabolite levels are affected by numerous factors, including preanalytical factors such as collection methods and geographical sites. These perturbations have caused deleterious consequences for many metabolomics studies and represent a major challenge in the metabolomics field. It is important to understand these factors and develop models to reduce their perturbations. However, to date, the lack of suitable mathematical models for blood metabolite levels under homeostasis has hindered progress. In this study, we develop quantitative models of blood metabolite levels in healthy adults based on multisite sample cohorts that mimic the current challenge. Five cohorts of samples obtained across four geographically distinct sites were investigated, focusing on approximately 50 metabolites that were quantified using 1H NMR spectroscopy. More than one-third of the variation in these metabolite profiles is due to cross-cohort variation. A dramatic reduction in the variation of metabolite levels (90%), especially their site-to-site variation (95%), was achieved by modeling each metabolite using demographic and clinical factors and especially other metabolites, as observed in the top principal components. The results also reveal that several metabolites contribute disproportionately to such variation, which could be explained by their association with biological pathways including biosynthesis and degradation. The study demonstrates an intriguing network effect of metabolites that can be utilized to better define homeostatic metabolite levels, which may have implications for improved health monitoring. As an example of the potential utility of the approach, we show that modeling gender-related metabolic differences retains the interesting variance while reducing unwanted (site-related) variance.

Interactions with microbial consortia have variable effects in organic carbon and production of exometabolites among genotypes of Populus trichocarpa

Poplar is a short-rotation woody crop frequently studied for its significance as a sustainable bioenergy source. The successful establishment of a poplar plantation partially depends on its rhizosphere-a dynamic zone governed by complex interactions between plant roots and a plethora of commensal, mutualistic, symbiotic, or pathogenic microbes that shape plant fitness. In an exploratory endeavor, we investigated the effects of a consortium consisting of ectomycorrhizal fungi and a beneficial Pseudomonas sp. strain GM41 on plant growth (including height, stem girth, leaf, and root growth) and as well as growth rate over time, across four Populus trichocarpa genotypes. Additionally, we compared the level of total organic carbon and plant exometabolite profiles across different poplar genotypes in the presence of the microbial consortium. These data revealed no significant difference in plant growth parameters between the treatments and the control across four different poplar genotypes at 7 weeks post-inoculation. However, total organic carbon and exometabolite profiles were significantly different between the genotypes and the treatments. These findings suggest that this microbial consortium has the potential to trigger early signaling responses in poplar, influencing its metabolism in ways crucial for later developmental processes and stress tolerance.

Metabolic profiles in plasma of patients with herpes labialis based on GC-MS

OBJECTIVE

This study aims to compare the plasma metabolic profiles of patients with herpes labialis with healthy controls and identify the biomarkers of herpes labialis.

SUBJECTS AND METHODS

We collected 18 patients with herpes labialis and 20 healthy individuals. Plasma samples from both groups were analyzed using gas chromatography-mass spectrometry (GC-MS).

RESULTS

According to the principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA), we found that metabolic profiles had changed in patients with herpes labialis compared to the controls. By further selecting the different metabolites according to the variable importance in the projection (VIP) and p valve of t-tests, we found that acetic acid, pyroglutamic acid, alanine, ethanedioic acid, cyclohexaneacetic acid, pyruvic acid, d-mannose, phosphoric acid, l-amphetamine, and citric acid were decreased in patients with herpes labialis, while sedoheptulose and ethylamine were increased. Pathway analysis showed that herpes labialis may affect the amino acid and energy metabolism.

CONCLUSIONS

Our findings may contribute to elucidating the metabolic basis of herpes labialis and provide a new perspective for further research on the "Shang-Huo" state in traditional Chinese medicine (TCM).

Pyroglutamination-Induced Changes in the Physicochemical Features of a CXCR4 Chemokine Peptide: Kinetic and Structural Analysis

We investigate the physicochemical effects of pyroglutamination on the QHALTSV-NH2 peptide, a segment of cytosolic helix 8 of the human C-X-C chemokine G-protein-coupled receptor type 4 (CXCR4). This modification, resulting from the spontaneous conversion of glutamine to pyroglutamic acid, has significant impacts on the physicochemical features of peptides. Using a static approach, we compared the transformation in different conditions and experimentally found that the rate of product formation increases with temperature, underscoring the need for caution during laboratory experiments to prevent glutamine cyclization. Circular dichroism experiments revealed that the QHALTSV-NH2 segment plays a minor role in the structuration of H8 CXCR4; however, its pyroglutaminated analogue interacts differently with its chemical environment, showing increased susceptibility to solvent variations compared to the native form. The pyroglutaminated analogue exhibits altered behavior when interacting with lipid models, suggesting a significant impact on its interaction with cell membranes. A unique combination of atomic force microscopy and infrared nanospectroscopy revealed that pyroglutamination affects supramolecular self-assembly, leading to highly packed molecular arrangements and a crystalline structure. Moreover, the presence of pyroglumatic acid has been found to favor the formation of amyloidogenic aggregates. Our findings emphasize the importance of considering pyroglutamination in peptide synthesis and proteomics and its potential significance in amyloidosis.

Chemical Wastes in the Peptide Synthesis Process and Ways to Reduce Them

In recent decades, a growing interest has been observed among pharmaceutical companies in producing and selling 80 FDA-approved therapeutic peptides. However, there are many drawbacks to peptide synthesis at the academic and industrial scales, involving the use of large amounts of highly hazardous coupling reagents and solvents. This review focuses on hideous and observant wastes produced before, during, and after peptide synthesis and proposes some solutions to reduce them.

Microbiota and metabolites alterations in proximal and distal gastric cancer patients

Background

Globally, gastric cancer is the third most common cancer and the third leading cause of cancer death. Proximal and distal gastric cancers have distinct clinical and biological behaviors. The microbial composition and metabolic differences in proximal and distal gastric cancers have not been fully studied and discussed.

Methods

In this study, the gastric microbiome of 13 proximal gastric cancer tissues, 16 distal gastric cancer tissues, and their matched non-tumor tissues were characterized using 16S rRNA amplicon sequencing. Additionally, 10 proximal gastric cancer tissues, 11 distal gastric cancer tissues, and their matched non-tumor tissues were assessed by untargeted metabolomics.

Results

There was no significant difference in microbial diversity and richness between the proximal and distal gastric cancer tissues. At the genus level, the abundance of Rikenellaceae_RC9_gut_group, Porphyromonas, Catonella, Proteus, Oribacterium, and Moraxella were significantly increased in Proximal T, whereas that of Methylobacterium_Methylorubrum was significantly increased in Distal T. The untargeted metabolomics analysis revealed 30 discriminative metabolites between Distal T and Distal N. In contrast, there were only 4 discriminative metabolites between Proximal T and Proximal N. In distal gastric cancer, different metabolites were scattered through multiple pathway, including the sphingolipid signaling pathway, arginine biosynthesis, protein digestion and absorption, alanine, aspartate and, glutamate metabolism, etc.In proximal gastric cancer, differential microbial metabolites were mainly related to hormone metabolism.

Conclusion

Methylobacterium-Methylorubrum was significantly increased in Distal T, positively correlated with cancer-promoting metabolites, and negatively correlated with cancer-inhibiting metabolites. Rikenellaceae_RC_gut_group was significantly increased in Proximal T and positively correlated with cancer-promoting metabolites. Further studies regarding the functions of the above-mentioned microorganisms and metabolites were warranted as the results may reveal the different mechanisms underlying the occurrence and development of proximal and distal gastric cancers and provide a basis for future treatments.

Importance

First, the differences in microbial composition and metabolites between the proximal and distal gastric cancers were described; then, the correlation between microbiota and metabolites was preliminarily discussed. These microbes and metabolites deserve further investigations as they may reveal the different mechanisms involved in the occurrence and development of proximal and distal gastric cancers and provide a basis for future treatments.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03650-x.

GC-MS Studies on the Conversion and Derivatization of γ-Glutamyl Peptides to Pyroglutamate (5-Oxo-Proline) Methyl Ester Pentafluoropropione Amide Derivatives

Glutathione (γ-L-glutamyl-L-cysteinyl-glycine, γ-Glu-Cys-Gly) is the most abundant intra-cellular dicarboxylic tripeptide with multiple physiological roles. In biological samples, glutathione exists in its reduced form GSH and in two stable oxidized forms, i.e., in its symmetric disulfide form GSSG and as S-glutathionyl residue in proteins. S-Glutathionylation is a post-translational modification, which is involved in several pathophysiological processes, including oxidative stress. The GSH-to-GSSG molar ratio is widely used as a measure of oxidative stress. γ-Glutamyl is the most characteristic structural moiety of GSH. We performed gas chromatography-mass spectrometry (GC-MS) studies for the development of a highly specific qualitative and quantitative method for γ-glutamyl peptides. We discovered intra-molecular conversion of GSH, GSSG, γ-Glu-Cys and of ophthalmic acid (OPH; γ-glutamyl-α-amino-n-butyryl-glycine) to pyroglutamate (pGlu; 5-oxo-proline, also known as pidolic acid) during their derivatization with 2 M HCl/CH₃OH (60 min, 80 °C). For GC-MS analysis, the methyl esters (Me) were further derivatized with pentafluoropropionic (PFP) anhydride in ethyl acetate (1:4, v/v; 30 min, 65 °C) to their PFP derivatives. At longer reaction times, pGlu is hydrolyzed to Glu. Internal standards were prepared by derivatizing GSH, GSSG, γ-Glu-Cys and OPH in 2 M HCl/CD₃OD. Quantification of the Me-PFP derivative of pGlu was performed in the electron-capture negative-ion chemical ionization (ECNICI) mode by selected-ion monitoring (SIM) of the mass-to-charge (m/z) ions 269 for unlabeled pGlu (d₀Me-PFP-pGlu) and m/z 272 for the in situ prepared deuterium-labeled pGlu (d₃Me-PFP-pGlu). Although not inherent to the analysis of small peptides, the present GC-MS method is useful to study several biochemical aspects of GSH. Using pentafluorobenzyl bromide (PFB-Br) as the derivatization reagent, we found that synthetic pGlu is converted in aqueous acetone (60 min, 50 °C) into its pentafluorobenzyl (PFB) ester (PFB-pGlu). This derivatization procedure is useful for the GC-MS analysis of free pGlu in the ECNICI mode. Quantitative analysis of PFB-pGlu by GC-MS requires the use of stable-isotope labeled analogs of pGlu as an internal standard.

Effect of serum sample storage temperature on metabolomic and proteomic biomarkers

Prospective biomarker studies can be used to identify biomarkers predictive of disease onset. However, if serum biomarkers are measured years after their collection, the storage conditions might affect analyte concentrations. Few data exists concerning which metabolites and proteins are affected by storage at − 20 °C vs − 80 °C. Our objectives were to document analytes affected by storage of serum samples at − 20 °C vs − 80 °C, and to identify those indicative of the storage temperature. We utilized liquid chromatography tandem mass spectrometry and Luminex to quantify 300 analytes from serum samples of 16 Finnish individuals with type 1 diabetes, with split-aliquot samples stored at − 80 °C and − 20 °C for a median of 4.2 years. Results were validated in 315 Finnish and 916 Scottish individuals with type 1 diabetes, stored at − 20 °C and at − 80 °C, respectively. After quality control, we analysed 193 metabolites and proteins of which 120 were apparently unaffected and 15 clearly susceptible to storage at − 20 °C vs − 80 °C. Further, we identified serum glutamate/glutamine ratio greater than 0.20 as a biomarker of storage at − 20 °C vs − 80 °C. The results provide a catalogue of analytes unaffected and affected by storage at − 20 °C vs − 80 °C and biomarkers indicative of sub-optimal storage.

Chiral secondary amino acids, their importance, and methods of analysis

Naturally occurring secondary amino acids, with proline as the main representative, contain an alpha-imino group in a cycle that is typically four-, five-, and six-membered. The unique ring structure exhibits exceptional properties-conformational rigidity, chemical stability, and specific roles in protein structure and folding. Many proline analogues have been used as valuable compounds for the study of metabolism of both prokaryotic and eukaryotic cells and for the synthesis of compounds with desired biological, pharmaceutical, or industrial properties. The D-forms of secondary amino acids play different roles in living organisms than the L-forms. They have different metabolic pathways, biological, physiological, and pharmacological effects, they can be indicators of changes and also serve as biomarkers of diseases. In the scientific literature, the number of articles examining D-amino acids in biological samples is increasing. The review summarises information on the occurrence and importance of D- and L-secondary amino acids-azetidic acid, proline, hydroxyprolines, pipecolic, nipecotic, hydroxypipecolic acids and related peptides containing these D-AAs, as well as the main analytical methods (mostly chromatographic) used for their enantiomeric determination in different matrices (biological samples, plants, food, water, and soil).

A Pilot Study on the 1H-NMR Serum Metabolic Profile of Takotsubo Patients Reveals Systemic Response to Oxidative Stress

Takotsubo syndrome (TTS) presents as an acute coronary syndrome characterized by severe left ventricular (LV) dysfunction and non-obstructive coronary artery disease that typically shows spontaneous recovery within days or weeks. The mechanisms behind TTS are mainly related to beta-adrenergic overstimulation and acute endogenous catecholamine surge, both of which could increase oxidative status that may induce further deterioration of cardiac function. Although several studies reported evidence of inflammation and oxidative stress overload in myocardial tissue of TTS models, systemic biochemical evidence of augmented oxidant activity in patients with TTS is lacking. In this study, serum samples of ten TTS patients and ten controls have been analyzed using ¹H-NMR spectroscopy. The results of this pilot study show a marked alteration in the systemic metabolic profile of TTS patients, mainly characterized by significant elevation of ketone bodies, 2-hydroxybutyrate, acetyl-L-carnitine, and glutamate levels, in contrast with a decrease of several amino acid levels. The overall metabolic fingerprint reflects a systemic response to oxidative stress caused by the stressor that triggered the syndrome’s onset.

Nuclear Magnetic Resonance Spectroscopy in Clinical Metabolomics and Personalized Medicine: Current Challenges and Perspectives

Personalized medicine is probably the most promising area being developed in modern medicine. This approach attempts to optimize the therapies and the patient care based on the individual patient characteristics. Its success highly depends on the way the characterization of the disease and its evolution, the patient’s classification, its follow-up and the treatment could be optimized. Thus, personalized medicine must combine innovative tools to measure, integrate and model data. Towards this goal, clinical metabolomics appears as ideally suited to obtain relevant information. Indeed, the metabolomics signature brings crucial insight to stratify patients according to their responses to a pathology and/or a treatment, to provide prognostic and diagnostic biomarkers, and to improve therapeutic outcomes. However, the translation of metabolomics from laboratory studies to clinical practice remains a subsequent challenge. Nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS) are the two key platforms for the measurement of the metabolome. NMR has several advantages and features that are essential in clinical metabolomics. Indeed, NMR spectroscopy is inherently very robust, reproducible, unbiased, quantitative, informative at the structural molecular level, requires little sample preparation and reduced data processing. NMR is also well adapted to the measurement of large cohorts, to multi-sites and to longitudinal studies. This review focus on the potential of NMR in the context of clinical metabolomics and personalized medicine. Starting with the current status of NMR-based metabolomics at the clinical level and highlighting its strengths, weaknesses and challenges, this article also explores how, far from the initial “opposition” or “competition”, NMR and MS have been integrated and have demonstrated a great complementarity, in terms of sample classification and biomarker identification. Finally, a perspective discussion provides insight into the current methodological developments that could significantly raise NMR as a more resolutive, sensitive and accessible tool for clinical applications and point-of-care diagnosis. Thanks to these advances, NMR has a strong potential to join the other analytical tools currently used in clinical settings.

Metabonomic study of the intervention effects of Parthenolide on anti-thyroid cancer activity

Thyroid cancer is the most common endocrine malignant tumor in the world, and its incidence is increasing. Although the mortality rate of thyroid cancer is low, its persistence/recurrence rate is high. In addition, some patients with thyroid cancer fail to respond to radiation. Therefore, it is urgent need to develop a novel treatment for thyroid cancer. Parthenolide (PTL), a traditional Chinese medicine Tanacetum parthenium extract, has shown encouraging effects in anti-tumor, anti-inflammatory and anti-malaria. However, it is unclear whether PTL has an anti-thyroid cancer effect and its possible mechanism of action. In the recent years, metabonomics has been widely used in tumors research to explore the pharmacological mechanism of drugs, but few studies used metabonomics to investigate the pharmacological effects of PTL in thyroid tumors. In order to comprehensively reveal the mechanism and effects of PTL on anti-thyroid tumors, metabonomics combined cell biological research methods were conducted. The results showed that PTL promote apoptosis of thyroid cancer cells (TPC-1) in a concentration-dependent manner. The metabolic differences between the PTL group and the control group were compared by metabonomics, and 31 potential metabolites were identified. These metabolites were mainly involved in the tricarboxylic acid cycle, amino acid metabolism, choline metabolism and lipid metabolism. These results implied that PTL may inhibit the proliferation and development of thyroid carcinoma by accelerating oxidation emergency response, inhibiting adenosine triphosphate (ATP) synthesis and metabolic imbalance. The results of this study revealed that PTL can be an effective and potential drug for the treatment of thyroid cancer.

Regional metabolic signatures in the Ndufs4(KO) mouse brain implicate defective glutamate/α-ketoglutarate metabolism in mitochondrial disease

Leigh Syndrome (LS) is a mitochondrial disorder defined by progressive focal neurodegenerative lesions in specific regions of the brain. Defects in NDUFS4, a subunit of complex I of the mitochondrial electron transport chain, cause LS in humans; the Ndufs4 knockout mouse (Ndufs4(KO)) closely resembles the human disease. Here, we probed brain region-specific molecular signatures in pre-symptomatic Ndufs4(KO) to identify factors which underlie focal neurodegeneration. Metabolomics revealed that free amino acid concentrations are broadly different by region, and glucose metabolites are increased in a manner dependent on both region and genotype. We then tested the impact of the mTOR inhibitor rapamycin, which dramatically attenuates LS in Ndufs4(KO), on region specific metabolism. Our data revealed that loss of Ndufs4 drives pathogenic changes to CNS glutamine/glutamate/α-ketoglutarate metabolism which are rescued by mTOR inhibition Finally, restriction of the Ndufs4 deletion to pre-synaptic glutamatergic neurons recapitulated the whole-body knockout. Together, our findings are consistent with mTOR inhibition alleviating disease by increasing availability of α-ketoglutarate, which is both an efficient mitochondrial complex I substrate in Ndufs4(KO) and an important metabolite related to neurotransmitter metabolism in glutamatergic neurons.

Analysis of low-molecular-weight metabolites in stomach cancer cells by a simplified and inexpensive GC/MS metabolomics method

GC/MS coupled metabolomics analysis, using a simplified and much less expensive silylation process with trimethylsilyl cyanide (TMSCN), was conducted to investigate metabolic abnormalities in stomach cancer cells. Under optimized conditions for derivatization by TMSCN and methanol extraction, 228 metabolites were detected using GC/MS spectrometry analysis, and 89 metabolites were identified using standard compounds and the NIST database. Ten metabolite levels were found to be lower in stomach cancer cells relative to normal cells. Among those ten metabolites, four metabolites-ribose, proline, pyroglutamic acid, and glucose-were known to be linked to cancers. In particular, pyroglutamic acid level showed a drastic reduction of 22-fold in stomach cancer cells. Since glutamine and glutamic acid are known to undergo cyclization to pyroglutamic acid, the 22-fold reduction might be the actual reduction in the levels of glutamine and/or glutamic acid-both known to be cancer-related. Hence, the marked reduction in pyroglutamic acid level might serve as a biomarker to aid early detection of stomach cancer. Graphical abstract.

Elusive π-helical peptide foldamers spotted by chiroptical studies

A series of oligomers containing alternate l-Ala and pGlu (pyroglutamic acid) both in the L and D form have been prepared and conformationally investigated by X-ray, NMR, UV/ECD, IR/VCD and molecular modelling. X-ray diffraction analysis was possible for the shortest oligomers LL-1 and LD-1. Molecular dynamics simulations of the oligomers demonstrated that the energy landscapes of the LL-series are broad. In contrast, the energy landscapes of the LD-series are characterized by well-defined minima corresponding to specific conformational structures. A single well-defined minimum exists in the energy landscape of the largest oligomer LD-8, corresponding to a precise conformation, characterized by i + 5 →i N-HO[double bond, length as m-dash]C hydrogen bonds, typical of a π-helix. ECD and VCD spectra were measured to identify the chiroptical profiles of the oligomers. The most striking element in the ECD spectra of the LD-series is their exceptionally strong intensity, which confirms that these polypeptides attain a high degree of helical order. VCD spectra for the LD-series are well reproduced by frequency calculations when π-helix folds are employed as input structures, suggesting that a symmetrical VCD couplet around 1720 cm^-1 can be taken as the VCD signature of π-helices.

Metabolome and proteome changes in skeletal muscle and blood of pre-weaning calves fed leucine and threonine supplemented diets

In pre-weaning calves, both leucine and threonine play important roles in growth and muscle metabolism. In this study, metabolomics, proteomics and clinical chemistry were used to assess the effects of leucine and threonine supplementation added to milk replacer on 14 newborn Holstein male calves: 7 were fed a control diet (Ctrl) and 7 were fed the Ctrl diet supplemented with 0.3% leucine and 0.3% threonine (LT) from 5.6 days of age to 53.6 days. At this time, blood and semitendinosus muscle biopsies were collected for analysis. Integrated metabolomics and proteomics showed that branched-chain amino acids (BCAA) degradation and mitochondrial oxidative metabolism (citrate cycle and respiratory chain) were the main activated pathways in muscle because of the supplementation. BCAA derivatives and metabolites related to lipid mobilization showed the major changes. The deleterious effects of activated oxidative phosphorylation were balanced by the upregulation of antioxidant proteins. An increase in protein synthesis was indicated by elevated aminoacyl-tRNA biosynthesis and increased S6 ribosomal protein phosphorylation in skeletal muscle. In conclusion, LT group showed greater BCAA availability and mitochondrial oxidative activity; as the muscle cells undergo greater aerobic metabolism, antioxidant defenses were activated to compensate for possible cell damage. Data are available via ProteomeXchange (PXD016098). SIGNIFICANCE: Leucine and threonine are essential amino acids for the pre-weaning calf, being of high importance for growth. In this study, we found that leucine and threonine supplementation of milk replacer to feed pre-weaning calves led to differences in the proteome, metabolome and clinical chemistry analytes in skeletal muscle and plasma, albeit no differences in productive performance were recorded. This study extends our understanding on the metabolism in dairy calves and helps optimizing their nutritional status.

Comparative metabolomics of MCF-7 breast cancer cells using different extraction solvents assessed by mass spectroscopy

Metabolic profiling of cancer cells can play a vital role in revealing the molecular bases of cancer development and progression. In this study, gas chromatography coupled with mass spectrometry (GC-MS) was employed for the determination of signatures found in ER+/PR+ breast cancer cells derived from MCF-7 using different extraction solvents including: A, formic acid in water; B, ammonium hydroxide in water; C, ethyl acetate; D, methanol: water (1:1, v/v); and E, acetonitrile: water (1:1, v/v). The greatest extraction rate and diversity of metabolites occurs with extraction solvents A and E. Extraction solvent D showed moderate extraction efficiency, whereas extraction solvent B and C showed inferior metabolite diversity. Metabolite set enrichment analysis (MSEA) results showed energy production pathways to be key in MCF-7 cell lines. This study showed that mass spectrometry could identify key metabolites associated with cancers. The highest enriched pathways were related to energy production as well as Warburg effect pathways, which may shed light on how energy metabolism has been hijacked to encourage tumour progression and eventually metastasis in breast cancer.

A Novel Metabolic Signature To Predict the Requirement of Dialysis or Renal Transplantation in Patients with Chronic Kidney Disease

Identification of chronic kidney disease patients at risk of progressing to end-stage renal disease (ESRD) is essential for treatment decision-making and clinical trial design. Here, we explored whether proton nuclear magnetic resonance (NMR) spectroscopy of blood plasma improves the currently best performing kidney failure risk equation, the so-called Tangri score. Our study cohort comprised 4640 participants from the German Chronic Kidney Disease (GCKD) study, of whom 185 (3.99%) progressed over a mean observation time of 3.70 ± 0.88 years to ESRD requiring either dialysis or transplantation. The original four-variable Tangri risk equation yielded a C statistic of 0.863 (95% CI, 0.831-0.900). Upon inclusion of NMR features by state-of-the-art machine learning methods, the C statistic improved to 0.875 (95% CI, 0.850-0.911), thereby outperforming the Tangri score in 94 out of 100 subsampling rounds. Of the 24 NMR features included in the model, creatinine, high-density lipoprotein, valine, acetyl groups of glycoproteins, and Ca²⁺-EDTA carried the highest weights. In conclusion, proton NMR-based plasma fingerprinting improved markedly the detection of patients at risk of developing ESRD, thus enabling enhanced patient treatment.

Metabolic Labeling of Cultured Mammalian Cells for Stable Isotope-Resolved Metabolomics: Practical Aspects of Tissue Culture and Sample Extraction

Stable isotope-resolved metabolomics (SIRM) methods are used increasingly by cancer researchers to probe metabolic pathways and identify vulnerabilities in cancer cells. Analytical and computational advances are being made constantly, but tissue culture and sample extraction procedures are often variable and not elaborated in the literature. This chapter discusses basic aspects of tissue culture practices as they relate to the use of stable isotope tracers and provides a detailed metabolic labeling and metabolite extraction procedure designed to maximize the amount of information that can be obtained from a single tracer experiment.

NMR metabolomics of cerebrospinal fluid differentiates inflammatory diseases of the central nervous system

BACKGROUND

Myriad infectious and noninfectious causes of encephalomyelitis (EM) have similar clinical manifestations, presenting serious challenges to diagnosis and treatment. Metabolomics of cerebrospinal fluid (CSF) was explored as a method of differentiating among neurological diseases causing EM using a single CSF sample.

METHODOLOGY/PRINCIPAL FINDINGS

1H NMR metabolomics was applied to CSF samples from 27 patients with a laboratory-confirmed disease, including Lyme disease or West Nile Virus meningoencephalitis, multiple sclerosis, rabies, or Histoplasma meningitis, and 25 controls. Cluster analyses distinguished samples by infection status and moderately by pathogen, with shared and differentiating metabolite patterns observed among diseases. CART analysis predicted infection status with 100% sensitivity and 93% specificity.

CONCLUSIONS/SIGNIFICANCE

These preliminary results suggest the potential utility of CSF metabolomics as a rapid screening test to enhance diagnostic accuracies and improve patient outcomes.

Comparison of sequential derivatization with concurrent methods for GC/MS-based metabolomics

The gas chromatography/mass spectrometry (GC/MS)-based metabolomics requires a two-step derivatization procedure consisting of oximation and silylation. However, due to the incomplete derivatization and degeneration of the metabolites, good repeatability is difficult to obtain during the batch derivatization, as the time between completing the derivatization process and GC analysis differs from sample to sample. In this research, we successfully obtained good repeatability for the peak areas of 52 selected metabolites by sequential derivatization and interval injection, in which the oximation and silylation times were maintained at constant values. In addition, the derivatization times and amount of reagents employed were varied to confirm that the optimal derivatization conditions differed for the various metabolites. In conventional batch derivatization, six metabolites, viz. glutamine, glutamic acid, histidine, alanine, asparagine, and tryptophan, exhibited fluctuations in their peak areas. Indeed, we found that for all six metabolites these differences originated from the silylation process, while the variations for glutamine and glutamic acid were related to the oximation process.

Prediction of platinum-based chemotherapy efficacy in lung cancer based on LC-MS metabolomics approach

Lung cancer is the common cause of cancer-related death worldwide. Platinum-based chemotherapy is the cornerstone of treatment for lung cancer. Platinum sensitivity is a major possibility for effective cancer treatment. In this study, several potential biomarkers were identified for evaluating and predicting the response to platinum-based chemotherapy. LC-MS-based metabolomics was performed on plasma samples from 43 lung cancer patients with different chemotherapy efficacy. By combing multivariate statistical analysis, pathway analysis with correlation analysis, 8 potential biomarkers were significantly associated with platinum chemotherapy response. Moreover, a prediction model with these biomarkers involved in citric acid cycle, glutamate metabolism and amino acid metabolism, showed 100% sensitivity and 100% specificity for predicting chemotherapy response in a validation set. Interestingly, 2-hydroxyglutaric acid (2-HG) as an oncometabolite accumulated in lung cancer was remarkably elevated in the partial response (PR) patients. Collectively, our findings implicated that metabolomics can serve as a potential tool to select lung cancer patients that are more likely to benefit from the platinum-based treatment.

NMR-Guided Mass Spectrometry for Absolute Quantitation of Human Blood Metabolites

Broad-based, targeted metabolite profiling using mass spectrometry (MS) has become a major platform used in the field of metabolomics for a variety of applications. However, quantitative MS analysis is challenging owing to numerous factors including (1) the need for, ideally, isotope-labeled internal standards for each metabolite, (2) the fact that such standards may be unavailable or prohibitively costly, (3) the need to maintain the standards' concentrations close to those of the target metabolites, and (4) the alternative use of time-consuming calibration curves for each target metabolite. Here, we introduce a new method in which metabolites from a single serum specimen are quantified on the basis of a recently developed NMR method [ Nagana Gowda et al. Anal. Chem. 2015 , 87 , 706 ] and then used as references for absolute metabolite quantitation using MS. The MS concentrations of 30 metabolites thus derived for test serum samples exhibited excellent correlations with the NMR ones (R² > 0.99) with a median CV of 3.2%. This NMR-guided-MS quantitation approach is simple and easy to implement and offers new avenues for the routine quantification of blood metabolites using MS. The demonstration that NMR and MS data can be compared and correlated when using identical sample preparations allows improved opportunities to exploit their combined strengths for biomarker discovery and unknown-metabolite identification. Intriguingly, however, metabolites including glutamine, pyroglutamic acid, glucose, and sarcosine correlated poorly with NMR data because of stability issues in their MS analyses or weak or overlapping signals. Such information is potentially important for improving biomarker discovery and biological interpretations. Further, the new quantitation method demonstrated here for human blood serum can in principle be extended to a variety of biological mixtures.

A distinct serum metabolic signature of distant metastatic papillary thyroid carcinoma

BACKGROUND

Although the incidence rate for thyroid cancer seems to have begun stabilizing in recent years, an increased rate of advanced stage of this disease has been reported. Additionally, distant metastasis is one of the most important prognostic factors of patients with papillary thyroid carcinoma (PTC). Unfortunately, the underlying mechanisms of distant metastasis, as well as cell status like metabolism changes in distant metastatic tumours have not been clearly elucidated.

OBJECTIVE

To identify serum metabolic signature of distant metastatic PTC.

DESIGN, PATIENTS AND MEASUREMENTS

In this study, gas chromatography-time-of-flight mass spectrometry (GC-TOF-MS) was used to analyse the serum from 77 patients diagnosed with PTC (37 in distant metastasis group and 40 in ablation group). Principal component analysis (PCA) and orthogonal partial least-squares-discriminant analysis (OPLS-DA) scores plots were used to analyse the data.

RESULTS

Principal component analysis and OPLS-DA analyses demonstrated an evident trend of separation between 40 serum samples from the ablation group and 37 samples from distant metastasis group. A total of 31 metabolites were identified, which are related to amino acid, lipid, glucose, vitamin metabolism and diet/gut microbiota interaction. Pathway analysis showed "alanine, aspartate and glutamate metabolism" and "inositol phosphate metabolism" were the most relevant pathways.

CONCLUSION

Serum metabolomics profiling could significantly discriminate papillary thyroid cancer patients according to distant metastasis. Potential metabolic aberration in distant metastatic PTC could be involved in different biological behaviours of tumour cells including proliferation, invasion/migration and immune escape. Diet/gut microbiota-produced metabolites could play an important role in these effects. This work may provide new clues to find the underlying mechanisms regarding the distant metastasis of PTC as well as potential adjuvant therapy targets.

Gas Chromatography/Mass Spectrometry Metabolomics of Urine and Serum from Nonhuman Primates Exposed to Ionizing Radiation: Impacts on the Tricarboxylic Acid Cycle and Protein Metabolism

Ionizing radiation (IR) directly damages cells and tissues or indirectly damages them through reactive free radicals that may lead to longer term adverse sequelae such as cancers, persistent inflammation, or possible death. Potential exposures include nuclear reactor accidents, improper disposal of equipment containing radioactive materials or medical errors, and terrorist attacks. Metabolomics (comprehensive analysis of compounds <1 kDa) by mass spectrometry (MS) has been proposed as a tool for high-throughput biodosimetry and rapid assessment of exposed dose and triage needed. While multiple studies have been dedicated to radiation biomarker discovery, many have utilized liquid chromatography (LC) MS platforms that may not detect particular compounds (e.g., small carboxylic acids or isomers) that complementary analytical tools, such as gas chromatography (GC) time-of-flight (TOF) MS, are ideal for. The current study uses global GC-TOF-MS metabolomics to complement previous LC-MS analyses on nonhuman primate biofluids (urine and serum) 7 days after exposure to 2, 4, 6, 7, and 10 Gy IR. Multivariate data analysis was used to visualize differences between control and IR exposed groups. Univariate analysis was used to determine a combined 26 biomarkers in urine and serum that significantly changed after exposure to IR. We found several metabolites involved in tricarboxylic acid cycle function, amino acid metabolism, and host microbiota that were not previously detected by global and targeted LC-MS studies.

Quantification of Metabolites by NMR Spectroscopy in the Presence of Protein

The high reliability of NMR spectroscopy makes it an ideal tool for large-scale metabolomic studies. However, the complexity of biofluids and, in particular, the presence of macromolecules poses a significant challenge. Ultrafiltration and protein precipitation are established means of deproteinization and recovery of free or total metabolite content, but neither is ever complete. In addition, aside from cost and labor, all deproteinization methods constitute an additional source of experimental variation. The Carr-Purcell-Meiboom-Gill (CPMG) echo-train acquisition of NMR spectra obviates the need for prior deproteinization by attenuating signals from macromolecules, but concentration values of metabolites measured in blood plasma will not necessarily reflect total or free metabolite content. Here, in contrast to approaches that propose the determination of individual T₁ and T₂ relaxation times for the computation of correction factors, we demonstrate their determination by spike-in experiments with known amounts of metabolites in pooled samples of the matrix of interest to facilitate the measurement of total metabolite content. Provided that the protein content does not vary too much among individual samples, accurate quantitation of metabolites is feasible. Moreover, samples with significantly deviating protein content may be readily recognized by inclusion of a standard that shows moderate protein binding. It is also shown that urinary proteins when present in high concentrations may effect detection of common urinary metabolites prone to strong protein binding such as tryptophan.

Pyroglutamate (5-oxoproline) measured with hydrophilic interaction chromatography (HILIC) tandem mass spectrometry in acutely ill patients

BACKGROUND

Pyroglutamic acid (PGA) is challenging to quantify in plasma and is a rare cause of metabolic acidosis that is associated with inherited disorders or acquired after exposure to drugs.

METHOD

We developed a hydrophilic interaction liquid chromatography tandem mass spectrometry method with a short analysis time. We established a reference interval and then measured PGA in acutely ill patients to investigate associations with clinical, pharmaceutical and laboratory parameters.

RESULTS

The assay limit of the blank was 0.14μmol/L and was linear to 5000μmol/L with good precision. In-source formation of PGA from glutamate and glutamine was avoided by chromatographic separation. The PGA in controls had a reference interval of 22.6 to 47.8μmol/L. The median PGA concentration in acutely ill patients was similar (P=0.21), but 18 individuals were above the reference interval with concentrations up to 250μmol/L. We detected an association between PGA concentration and antibiotic and acetaminophen administration as well as renal impairment and severity of illness. Elevations of PGA in this unselected cohort were small compared to those reported in patients with pyroglutamic acidosis.

CONCLUSION

The method is suitable for routine clinical use. We confirmed several expected associations with PGA in an acutely ill population.

The dental calculus metabolome in modern and historic samples

INTRODUCTION

Dental calculus is a mineralized microbial dental plaque biofilm that forms throughout life by precipitation of salivary calcium salts. Successive cycles of dental plaque growth and calcification make it an unusually well-preserved, long-term record of host-microbial interaction in the archaeological record. Recent studies have confirmed the survival of authentic ancient DNA and proteins within historic and prehistoric dental calculus, making it a promising substrate for investigating oral microbiome evolution via direct measurement and comparison of modern and ancient specimens.

OBJECTIVE

We present the first comprehensive characterization of the human dental calculus metabolome using a multi-platform approach.

METHODS

Ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) quantified 285 metabolites in modern and historic (200 years old) dental calculus, including metabolites of drug and dietary origin. A subset of historic samples was additionally analyzed by high-resolution gas chromatography-MS (GC-MS) and UPLC-MS/MS for further characterization of metabolites and lipids. Metabolite profiles of modern and historic calculus were compared to identify patterns of persistence and loss.

RESULTS

Dipeptides, free amino acids, free nucleotides, and carbohydrates substantially decrease in abundance and ubiquity in archaeological samples, with some exceptions. Lipids generally persist, and saturated and mono-unsaturated medium and long chain fatty acids appear to be well-preserved, while metabolic derivatives related to oxidation and chemical degradation are found at higher levels in archaeological dental calculus than fresh samples.

CONCLUSIONS

The results of this study indicate that certain metabolite classes have higher potential for recovery over long time scales and may serve as appropriate targets for oral microbiome evolutionary studies.

The future of NMR-based metabolomics

The two leading analytical approaches to metabolomics are mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy. Although currently overshadowed by MS in terms of numbers of compounds resolved, NMR spectroscopy offers advantages both on its own and coupled with MS. NMR data are highly reproducible and quantitative over a wide dynamic range and are unmatched for determining structures of unknowns. NMR is adept at tracing metabolic pathways and fluxes using isotope labels. Moreover, NMR is non-destructive and can be utilized in vivo. NMR results have a proven track record of translating in vitro findings to in vivo clinical applications.

Effects of sex and site on amino acid metabolism enzyme gene expression and activity in rat white adipose tissue

Background and Objectives. White adipose tissue (WAT) shows marked sex- and diet-dependent differences. However, our metabolic knowledge of WAT, especially on amino acid metabolism, is considerably limited. In the present study, we compared the influence of sex on the amino acid metabolism profile of the four main WAT sites, focused on the paths related to ammonium handling and the urea cycle, as a way to estimate the extent of WAT implication on body amino-nitrogen metabolism. Experimental Design. Adult female and male rats were maintained, undisturbed, under standard conditions for one month. After killing them under isoflurane anesthesia. WAT sites were dissected and weighed. Subcutaneous, perigonadal, retroperitoneal and mesenteric WAT were analyzed for amino acid metabolism gene expression and enzyme activities. Results. There was a considerable stability of the urea cycle activities and expressions, irrespective of sex, and with only limited influence of site. Urea cycle was more resilient to change than other site-specialized metabolic pathways. The control of WAT urea cycle was probably related to the provision of arginine/citrulline, as deduced from the enzyme activity profiles. These data support a generalized role of WAT in overall amino-N handling. In contrast, sex markedly affected WAT ammonium-centered amino acid metabolism in a site-related way, with relatively higher emphasis in males' subcutaneous WAT. Conclusions. We found that WAT has an active amino acid metabolism. Its gene expressions were lower than those of glucose-lipid interactions, but the differences were quantitatively less important than usually reported. The effects of sex on urea cycle enzymes expression and activity were limited, in contrast with the wider variations observed in other metabolic pathways. The results agree with a centralized control of urea cycle operation affecting the adipose organ as a whole.