Correlations between milk and plasma levels of amino and carboxylic acids in dairy cows.

The objective of this study was to investigate the relationship between the concentrations of 19 amino acids, glucose, and seven carboxylic acids in the blood and milk of dairy cows and their correlations with established markers of ketosis. To that end, blood plasma and milk specimens were collected throughout lactation in two breeds of dairy cows of different milk yield. Plasma concentrations of glucose, pyruvate, lactate, α-aminobutyrate, β-hydroxybutyrate (BHBA), and most amino acids, except for glutamate and aspartate, were on average 9.9-fold higher than their respective milk levels. In contrast, glutamate, aspartate, and the Krebs cycle intermediates succinate, fumarate, malate, and citrate were on average 9.1-fold higher in milk than in plasma. For most metabolites, with the exception of BHBA and threonine, no significant correlations were observed between their levels in plasma and milk. Additionally, milk levels of acetone showed significant direct relationships with the glycine-to-alanine ratio and the BHBA concentration in plasma. The marked decline in plasma concentrations of glucose, pyruvate, lactate, and alanine in cows with plasma BHBA levels above the diagnostic cutoff point for subclinical ketosis suggests that these animals fail to meet their glucose demand and, as a consequence, rely increasingly on ketone bodies as a source of energy. The concomitant increase in plasma glycine may reflect not only the excessive depletion of protein reserves but also a potential deficiency of vitamin B6

Metabolite extraction from adherently growing mammalian cells for metabolomics studies: optimization of harvesting and extraction protocols

Trypsin/ethylenediaminetetraacetic acid (EDTA) treatment and cell scraping in a buffer solution were compared for harvesting adherently growing mammalian SW480 cells for metabolomics studies. In addition, direct scraping with a solvent was tested. Trypsinated and scraped cell pellets were extracted using seven different extraction protocols including pure methanol, methanol/water, pure acetone, acetone/water, methanol/chloroform/water, methanol/isopropanol/water, and acid-base methanol. The extracts were analyzed by GC-MS after methoximation/silylation and derivatization with propyl chloroformate, respectively. The metabolic fingerprints were compared and 25 selected metabolites including amino acids and intermediates of energy metabolism were quantitatively determined. Moreover, the influence of freeze/thaw cycles, ultrasonication and homogenization using ceramic beads on extraction yield was tested. Pure acetone yielded the lowest extraction efficiency while methanol, methanol/water, methanol/isopropanol/water, and acid-base methanol recovered similar metabolite amounts with good reproducibility. Based on overall performance, methanol/water was chosen as a suitable extraction solvent. Repeated freeze/thaw cycles, ultrasonication and homogenization did not improve overall metabolite yield of the methanol/water extraction. Trypsin/EDTA treatment caused substantial metabolite leakage proving it inadequate for metabolomics studies. Gentle scraping of the cells in a buffer solution and subsequent extraction with methanol/water resulted on average in a sevenfold lower recovery of quantified metabolites compared with direct scraping using methanol/water, making the latter one the method of choice to harvest and extract metabolites from adherently growing mammalian SW480 cells

Improved enantiomer resolution and quantification of free D-amino acids in serum and urine by comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry

The potential of comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC×GC-TOFMS) in the quantitative analysis of amino acid enantiomers (AAEs) as their methyl chloroformate (MCF) derivatives in physiological fluids was investigated. Of the two column sets tested, the combination of an Rt-γDEXsa chiral column with a polar ZB-AAA column provided superior selectivity. Twenty AAEs were baseline resolved including L-Leu and D-Ile, which had failed separation by one-dimensional chiral GC-quadrupole-MS (GC-qMS). Lower limits of quantification (LLOQ) were in the range of 0.03-2 μM. Reproducibility of the analysis of a serum specimen in octaplicate ranged from 1.3 to 16.6%. The GC×GC-TOFMS method was validated by analyzing AAEs in 48 urine and 43 serum specimens, respectively, and by comparing the results with data obtained by a previously validated GC-qMS method. Mean recoveries ranged from 78.4% for D-Leu to 116.4% for D-Pro in urine and 72.2% for L-Thr to 129.4% for L-Ile in serum. The method was applied to the comparison of AAE serum levels in patients suffering from liver cirrhosis to a control group. Significantly increased D-AA concentrations were found for the patient group, whereas L-AA levels were slightly decreased

Performance evaluation of gas chromatography-atmospheric pressure chemical ionization-time-of-flight mass spectrometry for metabolic fingerprinting and profiling

Gas chromatography-atmospheric-pressure chemical ionization-time-of-flight mass spectrometry (GC-APCI-TOFMS) was compared to GC × GC-electron ionization (EI)-TOFMS, GC-EI-TOFMS, GC-chemical ionization (CI)-quadrupole mass spectrometry (qMS), and GC-EI-qMS in terms of reproducibility, dynamic range, limit of detection, and quantification using a mix of 43 metabolites and 12 stable isotope-labeled standards. Lower limits of quantification for GC-APCI-TOFMS ranged between 0.06 and 7.81 μM, and relative standard deviations for calibration replicates were between 0.4% and 8.7%. For all compounds and techniques, except in four cases, R(2) values were above 0.99. Regarding limits of quantification, GC-APCI-TOFMS was inferior to only GC × GC-EI-TOFMS, but outperformed all other techniques tested. GC-APCI-TOFMS was further applied to the metabolic fingerprinting of two Escherichia coli strains. Of 45 features that differed significantly (false discovery rate < 0.05) between the strains, 25 metabolites were identified through highly accurate and reproducible (Δm ± SD below 5 mDa over m/z 190-722) mass measurements. Starting from the quasimolecular ion, six additional metabolites were identified that had not been found in a previous study using GC × GC-EI-TOFMS and an EI mass spectral library for identification purposes. Silylation adducts formed in the APCI source assisted the identification of unknown compounds, as their formation is structure-dependent and is not observed for compounds lacking a carboxylic group

Comparison of serum versus plasma collection in gas chromatography--mass spectrometry-based metabolomics

Bovine serum, EDTA-plasma and EDTA-plasma fortified with acetylsalicylic acid (ASA) as antioxidant were compared with regard to their suitability for metabolomic studies. Metabolic fingerprints were generated from GC-TOF-MS data using the Leco ChromaTOF software in combination with the in-house retention time correction and data alignment tool INCA. A total of 6, 9 and 21 significant features with a false discovery rate of <0.05 were identified by INCA upon comparing EDTA- versus EDTA-ASA-plasma, EDTA-plasma versus serum and EDTA-ASA-plasma versus serum, respectively. To confirm that the observed signal intensities in the GC-TOF-MS fingerprints reflected true metabolite abundances, 19 amino acids, glucose and 6 organic acids were quantified by means of GC-MS using stable-isotope-labeled internal standards. As observed with the fingerprints, only the concentrations of lactate and citrate were found to be significantly lower in EDTA-plasma and serum, respectively, whereas the concentrations of the other metabolites were similar among the three sample types investigated

Distinct metabolic differences between various human cancer and primary cells

Recent years have seen resurging interest in cancer cell metabolism and the role of secreted cancer metabolites in modulating the tumor stroma. Using a combination of nontargeted and targeted LC and GC-MS methods, the exometabolomes of three leukemia, two melanoma, three renal cell carcinoma, two colorectal adenocarcinoma, four hepatocellular carcinoma, three breast cancer, two bladder carcinoma, and one glioblastoma cell line, as well as five primary cultures of human melanocytes, hepatocytes, monocytes, CD4 and CD8 lymphocytes, that had been all cultivated under identical conditions, were investigated. Unsupervised affinity propagation clustering of the metabolic footprints yielded five distinct clusters that grouped the investigated cell cultures mainly according to the tissue of origin. A common expected feature of all neoplastic cells was high lactate production. Extracellular arginine and nicotinamide were major discriminants between normal and neoplastic hepatocytes. Further, significant differences in the assimilation of di- and tripeptides were observed. This finding appears to underscore the importance of peptides for meeting the increased bioenergetic and biosynthetic demands of many cancers

Nuclear magnetic resonance and mass spectrometry-based milk metabolomics in dairy cows during early and late lactation

Milk production in dairy cows has dramatically increased over the past few decades. The selection for higher milk yield affects the partitioning of available nutrients, with more energy being allocated to milk synthesis and less to physiological processes essential to fertility and fitness. In this study, the abundance of numerous milk metabolites in early and late lactation was systematically investigated, with an emphasis on metabolites related to energy metabolism. The aim of the study was the identification and correlation of milk constituents to the metabolic status of the cows. To investigate the influence of lactation stage on physiological and metabolic variables, 2 breeds of different productivity were selected for investigation by high-resolution nuclear magnetic resonance spectroscopy and gas chromatography-mass spectrometry. We could reliably quantify 44 different milk metabolites. The results show that biomarkers such as acetone and beta-hydroxybutyrate are clearly correlated to the metabolic status of the individual cows during early lactation. Based on these data, the selection of cows that cope well with the metabolic stress of early lactation should become an option

Evaluation of dilution and normalization strategies to correct for urinary output in HPLC-HRTOFMS metabolomics

Reliable identification of features distinguishing biological groups of interest in urinary metabolite fingerprints requires the control of total metabolite abundance, which may vary significantly as the kidneys adjust the excretion of water and solutes to meet the homeostatic needs of the body. Failure to account for such variation may lead to misclassification and accumulation of missing data in case of less concentrated urine specimens. Here, different pre- and post-acquisition methods of normalization were compared systematically for their ability to recover features from liquid chromatography-mass spectrometry metabolite fingerprints of urine that allow distinction between patients with chronic kidney disease and healthy controls. Methods of normalization that were employed prior to analysis included dilution of urine specimens to either a fixed creatinine concentration or osmolality value. Post-acquisition normalization methods applied to chromatograms of 1:4 diluted urine specimens comprised normalization to creatinine, osmolality, and sum of all integrals. Dilution of urine specimens to a fixed creatinine concentration resulted not only in the least number of missing values, but it was also the only method allowing the unambiguous classification of urine specimens from healthy and diseased individuals. The robustness of classification could be confirmed for two independent patient cohorts of chronic kidney disease patients and yielded a shared set of 49 discriminant metabolite features