Quantitative Metabolomics Approach Research Articles

PSXII-2 DI/LC-MS/MS-based plasma metabolomics reveals the effects of sequestering agents on the metabolic status of dairy cows challenged with dietary aflatoxin B1

Abstract The study applied a targeted quantitative metabolomics approach using a combination of direct injection and tandem mass spectrometry (DI-MS/MS) with a liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based plasma metabolomics to evaluate the effects of supplementing clay and/or a Saccharomyces cerevisiae fermentation product (SCFP) on the metabolic status of dairy cows challenged with aflatoxin B1. Eight lactating cows were randomly assigned to 1 of 4 treatments in a balanced 4 × 4 Latin square design with 2 squares. Treatments were control, toxin (T; 1725 µg AFB1/head/day), T with clay (CL; 200 g/head/day), and CL with SCFP (CL+SCFP; 35 g of SCFP/head/day). Cows in T, CL, and CL+SCFP were dosed with aflatoxin B1 (AFB1) from d 26 to 30. The sequestering agents were top-dressed from d 1 to 33. On d 30 of each period, 15 mL of blood was taken from the coccygeal vessels and plasma samples were prepared by centrifugation. Plasma samples were analyzed using a kit that combines DI-MS/MS with LC-MS/MS. The data were analyzed using the GLIMMIX procedure of SAS. The model included the effects of treatment, period, and random effects of cow and square. Significance was declared at P ≤ 0.05. A total of 128 metabolites, including amino acids, biogenic amines, acylcarnitines, glycerophospholipids, and organic acids were quantified. Compared to the control, T decreased (P ≤ 0.05) plasma concentrations of 16 metabolites (6 amino acids, 6 acylcarnitines, and 4 glycerophospholipids). In contrast, T increased plasma concentrations of sarcosine, uric acid, and aspartic acid. Treatment with CL increased concentrations of arginine, lysine, and 5 organic acids. Treatment with CL+SCFP increased the concentrations of 7 amino acids and 4 acylcarnitines, but reduced the concentrations of sarcosine and 3 organic acids. Results of this study indicate that supplementing clay and/or SCFP altered plasma metabolomic profile in dairy cows challenged with AFB1.

NMR-based metabolic profiling and comparison of Japanese persimmon cultivars

Persimmons are a traditional, autumnal, and healthy fruit commonly consumed in Japan and East Asia based on the saying, “a persimmon a day keeps the doctor away.” The differences in metabolites among five major Japanese persimmon cultivars were investigated using a nuclear magnetic resonance (NMR)-based metabolomics approach. By using a broadband water suppression enhanced through T1 effects (WET) method for the sensitive detection of minor metabolites, better discrimination among cultivars and more informative details regarding their metabolic differences have been achieved compared to those achieved in conventional 1H NMR sequences. Among the nonastringent cultivars analyzed, the Taishu cultivar has the highest abundance of amino acids. The Matsumotowase-Fuyu cultivar contains ethyl-β-glycosides as characteristic components, which may relate to fruit softening. Citric acid concentration is higher in Maekawa Jiro than in other nonastringent cultivars. Among the two astringent cultivars analyzed, ethanol was significantly higher in Hiratanenashi than in Yotsumizo, which indicates different reactivity during deastringency treatments. The present study proposes an efficient and relatively quantitative metabolomics approach based on broadband WET NMR spectra.

Quantitative metabolomics approach reveals dynamics of primary metabolites in ‘Kinnow’ mandarin (C. nobilis × C. deliciosa) during advanced stages of fruit maturation under contrasting growing climates

ABSTRACTThis study employs a quantitative metabolomics approach to study the dynamics of primary metabolites in ‘Kinnow’ mandarin as influenced by maturation and ripening under contrasting growing climates. Fruit samples were harvested at regular intervals during the advanced stages of maturation and ripening from two contrasting growing locations, one under subtropical–arid (STA) climate and the other under subtropical–humid (STH) climate. Fruit juice samples were analysed using a targeted liquid chromatography-mass spectrometry (LC/MS) technique for identification and quantitation of primary metabolites such as sugars, organic acids and some vitamins. Significant (p < 0.05) differences in the metabolite concentrations were observed to be influenced by maturation stage and growing location. An increase in the concentration of sugars and B-complex vitamins was observed during the final stages of maturation approaching commercial maturity, whereas organic acids and vitamin C concentrations decreased. Fruit grown under STA climate exhibited a higher concentration of vitamin C and a lower concentration of organic acids than those grown under STH climate. The results suggest that fruit metabolism during the final stages of maturation and ripening under arid versus humid climatic conditions is a key determinant of the flavour and nutritional quality of ‘Kinnow’ mandarin.

Comparison of triterpene compounds of four botanical parts from Poria cocos (Schw.) wolf using simultaneous qualitative and quantitative method and metabolomics approach

Poria cocos (Schw.) Wolf (PCW) is a widely used traditional Chinese medicine and dietary supplement. Its four parts including Poriae Cutis (PC), Rubra Poria (RP), White Poria (WP) and Poria cum Radix Pini (PRP) have different pharmacological effects and clinical applications. It is necessary to establish analytical platforms for differentiating the chemical composition of four botanical parts for the rational utilization. We established a simultaneous qualitative and quantitative method based on UHPLC-MS combined metabolomics approach to give an explanation of the distribution of triterpene compounds in four parts. Eight triterpene compounds were determined absolutely and a total of 51 triterpene compounds were tentatively identified in PCW. PC and PRP showed a quite clear discrimination by the principal component analysis (PCA) and orthogonal projections to latent structures-discriminant analysis (OPLS-DA) and twelve differential compounds were found. Four compounds including poricoic acid D, 16α-hydroxydehydrotrametenolic acid, 3-epidehydrotumulosic acid, 25-hydroxypolyporenic acid C were speculated to be related to diuretic effects.

An integrated quantitative proteomic and metabolomics approach to reveal the negative regulation mechanism of LamB in antibiotics resistance

Previously, a maltose-specific channel porin, LamB was found to be associate with multi-drug resistance in a lamB deleted strain, but the exact mechanisms require further elucidation. Herein, differential protein expression between the Escherichia coli mutant strain ΔlamB and the wild type strain BW25113, with and without ciprofloxacin (CFLX), was identified using iTRAQ based liquid chromatography-tandem mass spectrometry (LC-MS/MS); while differential metabolite expression was examined using gas chromatography–mass spectrometry (GC–MS). Further Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses showed that lamB deletion leads to a decrease in several key metabolic pathways such as tricarboxylic acid (TCA) cycle, pentose phosphate pathway and glycolysis/gluconeogenesis. When examining the ΔlamB strain without CFLX, many aminoacyl-tRNA biosynthesis and pyrimidine metabolism-related proteins were unaltered, but the addition of CFLX resulted in reduced levels. These findings indicate that a lamB deletion may confer antibiotic resistance by relieving the pressure of protein translation and DNA replication. To further examine antibiotic resistance, exogenous metabolites, including maltose, and several amino acids metabolites were evaluated to determine whether the resistance level could be reduced in the presence of CFLX. The obtained results indicate that lamB knockout may increase bacterial antibiotics resistance by decreasing metabolic pathway activity levels. Biological significanceAn integrated metabonomic-proteomic method was performed to systematically compare the profiles of metabolites and proteins between ΔlamB and its wild type strain, with and without ciprofloxacin (CFLX) treatment. Following bioinformatics analysis showed that lamB deletion in CFLX stress leads to the decreasing of several key metabolic pathways. Many amino acid-tRNA biosynthesis and pyrimidine metabolism related proteins didn't change in ΔlamB strain but largely decreased after treated with CFLX. Further exogenous metabolites addition assay reveals that maltose and several amino acids metabolites contribute to the CFLX resistance mediated by LamB. Our results indicate that the down-regulation of LamB may increase bacterial antibiotics resistance by decreasing the intracellular metabolism pathways.

Integrated analyses utilizing metabolomics and transcriptomics reveal perturbation of the polyamine pathway in oral cavity squamous cell carcinoma

Oral cavity squamous cell carcinoma (OSCC), the most common malignancy of the oral cavity, is associated with poor prognosis and high mortality worldwide. Moreover, knowledge of the metabolic alterations that occur in OSCC is still limited. In the present study, we used a quantitative metabolomic approach with chemical isotope labeling (CIL) to analyze alterations in the metabolite levels in paired cancerous (T) and adjacent noncancerous (AN) tissues from 31 OSCC patients. Using volcano plot and orthogonal projections to latent structure-discriminant analysis (OPLS-DA), we uncovered 99 dysregulated metabolites in OSCC and verified the identities of seven metabolites via comparison with authenticated standards. From these seven metabolites, we constructed a 3-marker panel, consisting of putrescine, glycyl-leucine, and phenylalanine, using a support vector machine (SVM) model that can discriminate T from AN with high sensitivity and specificity based on receiver operator characteristic (ROC) analysis. Furthermore, by integrating the metabolomics profiles with transcriptomics data obtained from the same sample set, we revealed the dysregulation of the polyamine pathway in OSCC. Our findings provide insights into the metabolic perturbations present in OSCC and have uncovered potential metabolic biomarkers and therapeutic targets for use in the treatment of OSCC.

Interactions of Mycorrhiza and Protists in the Rhizosphere Systemically Alter Microbial Community Composition, Plant Shoot-to-Root Ratio and Within-Root System Nitrogen Allocation

Arbuscular mycorrhizal fungi (AMF) are important symbionts for plant nutrient uptake, but their exact role in plant nitrogen (N) nutrition is unclear. Protists on the other hand play an acknowledged role in plant N acquisition, and there is increasing evidence for a close interaction with AMF. In a split root set up, we investigated the distinct roles of mycorrhiza (Rhizophagus irregularis), protists (Acanthamoeba castellanii), and their interaction on plant N uptake, within-root system allocation patterns, and shoot-to-root ratio of winter wheat. In addition, we applied a quantitative metabolomics approach to characterize associated changes in soil microbial communities by microbial phospholipid fatty acid (PLFA) analysis from rhizosphere soil. AMF markedly altered plant shoot-to-root allometry by reducing root biomass of wheat, and mycorrhiza partly took over root system functioning. Protists promoted shoot and root growth, and improved plant N uptake by the release of N from consumed bacterial biomass, a mechanism known as microbial loop. The shoot system however responded little to these alterations of the root system and of the rhizosphere community composition, indicating that the plants optimized shoot growth despite varying investment into roots. Mycorrhiza reduced root biomass and plant N, especially in the combined treatments with protists by changing within root system allocation of N and root biomass. These systemic effects on root allocation pattern suggest that mycorrhiza also gained control over N provided by protist grazers. Protists and mycorrhiza altered rhizosphere bacterial communities in contrasting but consistent ways as shown by quantitative shifts in microbial PLFA profiles. Remarkably, the changes in bacterial community composition were systemically conveyed within the root system to the split-root chamber where the symbionts were lacking. Accordingly the synergistic effects of protists and mycorrhiza indicated systemic effects on nutrient- and on root-allocation within root systems as an emergent property that could not be predicted from single treatments with mycorrhiza or protists alone. The tight plant and microbial feed backs uncovered in this study have far reaching implications for understanding the assembly of plant microbiomes, and testify central roles of both protists and mycorrhizas in the assembly process.

A quantitative metabolomics study of bacterial metabolites in different domains

Absolute metabolite concentrations are essential information for quantitative metabolomics studies, as concentrations are closely related to metabolic reactions, enzyme kinetics and other important biological activities. A well-performed metabolites extraction procedure, a reliable detection method, and a robust quantitative approach are all critical factors for obtaining absolute metabolite concentrations. Here, we used a HPLC-MS/MS based platform to successfully develop a 13C-labeled quantitative metabolomics approach, and applied this novel method to quantify bacterial metabolite concentrations in three different domains (i.e., intracellularly, extracellularly and to the whole culture), with high accuracy for a model Escherichia coli bacteria. The bacterial culture was grown in universal 13C-labeled medium and the metabolites were extracted by 40/40/20/methanol/ACN/H2O with 0.1% formic acid. One hundred and twenty-five metabolites were initially screened and one hundred and six 13C metabolites were confidently detected from the model bacteria grown in 13C-labeled medium. A subset of twenty-one metabolites was subsequently quantified using 12C-metabolite chemical standards to assist the calculation of 13C metabolite concentration. This rigorous 13C-labled quantitative method was then applied to characterize the metabolic profile changes in three domains of E. coli going through antibiotic treatment. Our results demonstrated that metabolites from all three domains can be used to significantly differentiate the ampicillin treatment group and control group (without ampicillin). In conclusion, our work demonstrated that the quantitative metabolomics approach can be used as a valuable tool to study bacterial metabolism in different domains and to understand their response to environmental perturbations.

Urea nitrogen induces changes in rumen microbial and host metabolic profiles in dairy cows

Urea has been used in diets of cattle as a non-protein nitrogen source. It is hydrolyzed to ammonia, which can be used for microbial protein synthesis. Use of metabolomics methodologies to study the rumen microbial and host blood metabolic profiles induced by urea nitrogen has not been previously characterized. The objective of this study was to identify changes in rumen microbial and plasma metabolite profiles in dairy cows after urea supplementation using a nuclear magnetic resonance (NMR)-based untargeted quantitative metabolomic approach. Six dairy cows with rumen fistulas were randomly assigned to two groups used in a two period cross-over trial and each experimental period lasted 21 days. All the cows were fed the same total mixed rations, but were intraruminally supplemented with 180 g urea per cow daily or not during the experimental period. Rumen fluid and blood samples were collected and analyzed using nuclear magnetic resonance spectroscopy and multivariate analysis of variance. Differences in rumen and plasma metabolite concentrations in cows from the two groups were assessed using orthogonal partial least-squares discriminant analysis and identified by searching against related databases. Concentrations of valine, aspartate, glutamate, and uracil in the rumen, and urea and pyroglutamate in the plasma, were higher (P < 0.05) in the urea-supplemented group than in the control group. Metabolic pathway analysis of the affected metabolites revealed that pantothenate and CoA biosynthesis, beta-alanine metabolism, valine, leucine, and isoleucine metabolism in the rumen, and urea and glutathione metabolism in the plasma were significantly increased by urea nitrogen. The levels of aspartate and glutamate in the rumen correlated strongly (P < 0.01) with the level of urea in plasma. These findings provided novel information to aid understanding of the metabolic pathways affected by urea nitrogen in dairy cows, and could potentially help to guide efforts directed at improving the efficiency of urea utilization in the rumen.

NMR approach for the authentication of 10 cinnamon spice accessions analyzed via chemometric tools

Quantitative NMR metabolomics approach was developed to distinguish two cinnamon species (Ceylon Cinnamon, Cinnamomum verum and Chinese Cinnamon, Cinnamomum cassia) that are interchangeably used in food products. The results of the analyses of 10 bark accessions revealed for 9 key sensory metabolites, with (E)-cinnamaldehyde as the major form. Multivariate data analyses revealed for eugenol leading presence in C. verum versus fatty acid enrichment in C. cassia. This research provides the first NMR metabolites fingerprinting of the two major cinnamon resources. Compounds related to C. verum aroma and taste were identified and quantified that can be utilized as markers for the authentication of this valuable drug. Novel insight on metabolites mediating for C. verum antidiabetic effect is also presented.

Targeted metabolomics: new insights into pathobiology of retained placenta in dairy cows and potential risk biomarkers

A targeted quantitative metabolomics approach was used to study temporal changes of serum metabolites in cows that normally released their fetal membranes and those that retained the placenta. We identified and measured serum concentrations of 128 metabolites including amino acids, acylcarnitines, biogenic amines, glycerophospholipids, sphingolipids and hexose at −8 and −4 weeks before parturition, during the week of retained placenta (RP) diagnosis, and at +4 and +8 weeks after parturition. In addition, we aimed at identifying metabolite signatures of pre-RP in the serum that might be used as predictive biomarkers for risk of developing RP in dairy cows. Results revealed major alterations in the metabolite fingerprints of pre-RP cows starting as early as −8 weeks before parturition and continuing as far as +8 weeks after calving. Biomarker candidates found in this study are mainly biomarkers of inflammation which might not be specific to RP. Therefore, the relevance of serum Lys, Orn, acetylornithine, lysophophatidylcholine LysoPC a C28:0, Asp, Leu and Ile as potential serum biomarkers for prediction of risk of RP in dairy cows will have to be tested in the future. In addition, lower concentrations of LysoPCs, Trp, and higher kynurenine in the serum during prepartum and the week of occurrence of RP suggest involvement of inflammation in the pathobiology of RP.

Research on the hepatotoxicity mechanism of citrate-modified silver nanoparticles based on metabolomics and proteomics

Citrate-modified silver nanoparticles (AgNP-cit) have received extensive attention due to their excellent antimicrobial properties. However, these particles tend to migrate in vivo, thereby entering the blood circulatory system in granular form and accumulating in the liver, causing toxic reactions. However, the mechanism underlying AgNP-cit toxicity is not yet clear. Thus, we adopted a tandem mass tag (TMT)-labeled quantitative proteomics and metabolomics approach to identify proteins and small molecule metabolites associated with AgNP-cit-induced liver damage and constructed interaction networks between the differentially expressed proteins and metabolites to explain the AgNP-cit toxicity mechanism. AgNP-cit resulted in abnormal purine metabolism mainly by affecting xanthine and other key metabolites along with pyruvate kinase and other bodily proteins, leading to oxidative stress. AgNP-cit regulated the metabolism of amino acids and glycerol phospholipids through glycerol phospholipids, CYP450 enzymes and other key proteins, causing liver inflammation. Via alanine, isoleucine, L-serine dehydratase/L-threonine deaminase and other proteins, AgNP-cit altered the metabolism of glycine, serine and threonine, cysteine and methionine, affecting oxidation and deamination, and ultimately leading to liver damage. This work clearly explains toxic reactions induced by AgNP-cit from three perspectives, oxidative stress, inflammatory response, and oxidation and deamination, thus providing an experimental basis for the safe application of nanomaterials.

Development of a Data-Independent Targeted Metabolomics Method for Relative Quantification Using Liquid Chromatography Coupled with Tandem Mass Spectrometry.

Quantitative metabolomics approaches can significantly improve the repeatability and reliability of metabolomics investigations but face critical technical challenges, owing to the vast number of unknown endogenous metabolites and the lack of authentic standards. The present study contributes to the development of a novel method known as "data-independent targeted quantitative metabolomics" (DITQM), which was used to investigate the label-free quantitative metabolomics of multiple known and unknown metabolites in biofluid samples. This approach initially involved the acquisition of MS/MS data for all metabolites in biosamples using a sequentially stepped targeted MS/MS (sst-MS/MS) method, in which multiple product ion scans were performed by selecting all ions in the targeted mass ranges as the precursor ions. Subsequently, scheduled multiple reaction monitoring (MRM) by LC-MS/MS of the metabolome was established for 1658 characteristic ion pairs of 1324 metabolites. For sensitive and accurate quantification of these metabolites, mixed calibration curves were generated using sequentially diluted standard reference plasma samples using established MRM methods. Relative concentrations of all metabolites in each sample were calculated without using individual authentic standards. To evaluate the reliability and applicability of this new method, the performance of DITQM was validated by comparison to absolute quantification of 12 acylcarnitines using authentic standards and traditional metabolomics analysis for lung cancer. The results proved that the DITQM protocol is more reliable and can significantly improve clustering effects and repeatability in biomarker discovery. In this study, we established a novel methodology to standardize and quantify large-scale metabolome, providing a new choice for metabolomics research and its clinical applications.

Metabolomic biomarkers of concussion

ObjectiveTo determine if1H NMR spectroscopy of urine and a quantitative metabolomics approach can aid diagnostic and prognostic outcomes in patients who have suffered acute sport concussion.DesignPre-concussion urine samples were collected from WinSport athletes at the beginning of the sport season. Any athlete who experienced a head injury reported to a brain injury clinic to be tested within 72 hours of head injury. This testing included collection of a post-concussion urine sample for metabolomic analysis.SettingBrain injury clinic and metabolomics laboratory.Participants167 athletes entered the study with a total of 39 concussions occurring. Inclusion criteria: at least 18 years old, diagnosis of concussion, and concussion sustained within 72 hours. Exclusion criteria: multiple injuries coinciding with concussion and a past history of neurological pathology.Outcome measuresMetabolite concentrations were calculated in pre- and post-concussion urine samples and compared using a paired t-test and partial least squares discriminant analysis (PLS-DA) to determine which metabolites led to significant variation between samples.Main resultsThe PLS-DA model showed significant variation between baseline and post-injury sample groups and passed all permutation and cross-validation testing. A paired t-test, with cross-validation, isolated five significant metabolites of interest in the concussion group (p&lt;0.05).ConclusionsUsing NMR spectroscopy we quantified urinary metabolites in patients before and after concussion. This revealed several metabolites that were shown to be significantly altered following injury, opening up future inquiry into both the pathways and processes involved in concussion and new avenues for personalized diagnosis and treatment.Competing interestsNone.

Phenolic compounds profile and antioxidant properties of six sweet cherry (Prunus avium) cultivars

Sweet cherry (Prunus avium) fruits are a nutritionally important food rich in dietary phenolic compounds. The aim of this study was to investigate the phenolic profile and chemometric discrimination of fruits from six cherry cultivars using a quantitative metabolomics approach, which combine non-targeted mass spectrometry and chemometric analysis. The assessment of the phenolic fingerprint of cherries allowed the tentative identification of 86 compounds. A total of 40 chlorogenic acids were identified in cherry fruit, which pointed out hydroxycinnamic acid derivatives as the main class of phenolics by number of compounds. Among the compounds detected, 40 have been reported for the first time in sweet cherry fruit. Hydroxycinnamic acids are also the quantitatively most represented class of phenolic compounds in the cherry cultivars with the exception of Lapins and Durone della Marca where the most representative class of phenolic compounds were anthocyanins and flavan-3-ols, respectively. This non-targeted approach allowed the tentative identification of the cultivar-compound relationships of these six cherry cultivars. Both anthocyanins and colorless phenolic compounds profile appeared to be cultivar-dependent. In detail, anthocyanins and flavonols patterns have the potential to be used for the determination of a varietal assignment of cherries.

Mortality prediction in patients with severe septic shock: a pilot study using a target metabolomics approach.

Septic shock remains a major problem in Intensive Care Unit, with high lethality and high-risk second lines treatments. In this preliminary retrospective investigation we examined plasma metabolome and clinical features in a subset of 20 patients with severe septic shock (SOFA score >8), enrolled in the multicenter Albumin Italian Outcome Sepsis study (ALBIOS, NCT00707122). Our purpose was to evaluate the changes of circulating metabolites in relation to mortality as a pilot study to be extended in a larger cohort. Patients were analyzed according to their 28-days and 90-days mortality. Metabolites were measured using a targeted mass spectrometry-based quantitative metabolomic approach that included acylcarnitines, aminoacids, biogenic amines, glycerophospholipids, sphingolipids, and sugars. Data-mining techniques were applied to evaluate the association of metabolites with mortality. Low unsaturated long-chain phosphatidylcholines and lysophosphatidylcholines species were associated with long-term survival (90-days) together with circulating kynurenine. Moreover, a decrease of these glycerophospholipids was associated to the event at 28-days and 90-days in combination with clinical variables such as cardiovascular SOFA score (28-day mortality model) or renal replacement therapy (90-day mortality model). Early changes in the plasma levels of both lipid species and kynurenine associated with mortality have potential implications for early intervention and discovering new target therapy.

Novel Quantitative Metabolomic Approach for the Study of Stress Responses of Plant Root Metabolism

Quantitative metabolomics (qMetabolomics) is a powerful tool for understanding the intricate metabolic processes involved in plant abiotic stress responses. qMetabolomics is hindered by the limited coverage and high cost of isotopically labeled standards. In this study, we first selected 271 metabolites which might play important roles in abiotic stress responses as the targets and established a comprehensive LC-MS/MS based qMetabolomic method. We then developed a novel metabolic labeling method using E. coli-Saccharomyces cerevisiae two-step cultivation for the production of uniformly (13)C-labeled metabolites as internal standards. Finally, we applied the developed qMetabolomic method to investigate the influence of Pb stress on maize root metabolism. The absolute concentration of 226 metabolites in maize roots was accurately quantified in a single run within 30 min. Our study also revealed that glycolysis, purine, pyrimidine, and phospholipids were the main metabolic pathways in maize roots involved in Pb stress response. To our knowledge, this is the most comprehensive qMetabolomic method for plant metabolomics thus far. We developed a simple and inexpensive metabolic labeling method which dramatically expanded the availability of uniformly (13)C labeled metabolites. Our findings also provided new insights of maize metabolic responses to Pb stress.

Glucose and glutamine metabolism in oral squamous cell carcinoma: insight from a quantitative metabolomic approach.

To characterize the metabolic system of oral squamous cell carcinoma (OSCC) by metabolome analysis. The metabolome profiles, including the Embden-Meyerhof-Parnas pathway (EMPP), the pentose phosphate pathway, the tricarboxylic acid cycle (TCAC), and amino acids, were obtained from OSCC and its surrounding normal tissues (32 patients) using capillary electrophoresis and a time-of-flight mass spectrometer. Enhancement of glucose consumption and lactate production (Warburg effect) was observed in OSCC tissues. The decrease of glucose along with the decrease of the downstream intermediates in the EMPP suggests that incorporated glucose is mainly consumed for biosynthesis. Glutamine consumption with the increase of the intermediates in the last half of the TCAC suggests the involvement of glutaminolysis, in which glutamine is converted to lactate via the last half of the TCAC. It is suggested that OSCC tissues show the Warburg effect, which stems from the combined enhancement of glucose consumption and glutaminolysis.

Identification of predictive biomarkers of disease state in transition dairy cows

In dairy cows, periparturient disease states, such as metritis, mastitis, and laminitis, are leading to increasingly significant economic losses for the dairy industry. Treatments for these pathologies are often expensive, ineffective, or not cost-efficient, leading to production losses, high veterinary bills, or early culling of the cows. Early diagnosis or detection of these conditions before they manifest themselves could lower their incidence, level of morbidity, and the associated economic losses. In an effort to identify predictive biomarkers for postpartum or periparturient disease states in dairy cows, we undertook a cross-sectional and longitudinal metabolomics study to look at plasma metabolite levels of dairy cows during the transition period, before and after becoming ill with postpartum diseases. Specifically we employed a targeted quantitative metabolomics approach that uses direct flow injection mass spectrometry to track the metabolite changes in 120 different plasma metabolites. Blood plasma samples were collected from 12 dairy cows at 4 time points during the transition period (−4 and −1wk before and 1 and 4wk after parturition). Out of the 12 cows studied, 6 developed multiple periparturient disorders in the postcalving period, whereas the other 6 remained healthy during the entire experimental period. Multivariate data analysis (principal component analysis and partial least squares discriminant analysis) revealed a clear separation between healthy controls and diseased cows at all 4 time points. This analysis allowed us to identify several metabolites most responsible for separating the 2 groups, especially before parturition and the start of any postpartum disease. Three metabolites, carnitine, propionyl carnitine, and lysophosphatidylcholine acyl C14:0, were significantly elevated in diseased cows as compared with healthy controls as early as 4wk before parturition, whereas 2 metabolites, phosphatidylcholine acyl-alkyl C42:4 and phosphatidylcholine diacyl C42:6, could be used to discriminate healthy controls from diseased cows 1wk before parturition. A 3-metabolite plasma biomarker profile was developed that could predict which cows would develop periparturient diseases, up to 4wk before clinical symptoms appearing, with a sensitivity of 87% and a specificity of 85%. This is the first report showing that periparturient diseases can be predicted in dairy cattle before their development using a multimetabolite biomarker model. Further research is warranted to validate these potential predictive biomarkers.

Integrated Proteomics and Metabolomics of Arabidopsis Acclimation to Gene-Dosage Dependent Perturbation of Isopropylmalate Dehydrogenases

Maintaining metabolic homeostasis is critical for plant growth and development. Here we report proteome and metabolome changes when the metabolic homeostasis is perturbed due to gene-dosage dependent mutation of Arabidopsis isopropylmalate dehydrogenases (IPMDHs). By integrating complementary quantitative proteomics and metabolomics approaches, we discovered that gradual ablation of the oxidative decarboxylation step in leucine biosynthesis caused imbalance of amino acid homeostasis, redox changes and oxidative stress, increased protein synthesis, as well as a decline in photosynthesis, which led to rearrangement of central metabolism and growth retardation. Disruption of IPMDHs involved in aliphatic glucosinolate biosynthesis led to synchronized increase of both upstream and downstream biosynthetic enzymes, and concomitant repression of the degradation pathway, indicating metabolic regulatory mechanisms in controlling glucosinolate biosynthesis.