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Because of a limited volume of urine that can be collected from a mouse, it is very difficult to apply the common strategy of using multiple analytical techniques to analyze the metabolites to increase the metabolome coverage for mouse urine metabolomics. We report an enabling method based on differential isotope labeling liquid chromatography mass spectrometry (LC-MS) for relative quantification of over 950 putative metabolites using 20 μL of urine as the starting material. The workflow involves aliquoting 10 μL of an individual urine sample for ¹²C-dansylation labeling that target amines and phenols. Another 10 μL of aliquot was taken from each sample to generate a pooled sample that was subjected to ¹³C-dansylation labeling. The ¹²C-labeled individual sample was mixed with an equal volume of the ¹³C-labeled pooled sample. The mixture was then analyzed by LC-MS to generate information on metabolite concentration differences among different individual samples. The interday repeatability for the LC-MS runs was assessed, and the median relative standard deviation over 4 days was 5.0%. This workflow was then applied to a metabolomic biomarker discovery study using urine samples obtained from the TgCRND8 mouse model of early onset familial Alzheimer's disease (FAD) throughout the course of their pathological deposition of beta amyloid (Aβ). It was showed that there was a distinct metabolomic separation between the AD prone mice and the wild type (control) group. As early as 15-17 weeks of age (presymptomatic), metabolomic differences were observed between the two groups, and after the age of 25 weeks the metabolomic alterations became more pronounced. The metabolomic changes at different ages corroborated well with the phenotype changes in this transgenic mice model. Several useful candidate biomarkers including methionine, desaminotyrosine, taurine, N1-acetylspermidine, and 5-hydroxyindoleacetic acid were identified. Some of them were found in previous metabolomics studies in human cerebrospinal fluid or blood samples. This work illustrates the utility of this isotope labeling LC-MS method for biomarker discovery using mouse urine metabolomics.

We describe a new set of isotope reagents, (12)C4-, (12)C2(13)C2-, and (13)C4-5-diethylamino-naphthalene-1-sulfonyl chloride (DensCl), in combination with liquid chromatography Fourier-transform ion cyclotron resonance mass spectrometry (LC-FTICR-MS), for improved analysis of the amine- and phenol-containing submetabolome. The synthesis of the reagents is reported, and an optimized derivatization protocol for labeling amines and phenols is described. To demonstrate the utility of the triplex reagents for metabolome profiling of biological samples, urine samples collected daily from a healthy volunteer over a period of 14 days were analyzed. The overall workflow is straightforward, including differential isotope labeling of individual samples and a pooled sample that serves a global internal standard, mixing of the isotope differentially labeled samples and LC-MS analysis for relative metabolome quantification. Comparing to the dansyl chloride (DnsCl) duplex isotope reagents, the new triplex DensCl reagents offer the advantages of improved metabolite detectability due to enhanced sensitivity (i.e., about 1000 peak pairs detected by DensCl labeling vs about 600 peak pairs detected by DnsCl labeling) and analysis speed (i.e., simultaneous analysis of two comparative samples by DensCl vs only one comparative sample analyzed by DnsCl).

We report a method of ion-pairing liquid chromatography coupled to mass spectrometry (IP-LC-MS) that we have developed for the sensitive detection and quantification of a variety of biologically relevant polar molecules. We use the ion-pairing agent diamyl ammonium to improve chromatographic resolution of polar compounds, such as nucleotide cofactors, sugar phosphates, and organic acids, that are generally poorly retained by conventional reverse phase chromatographic methods. This method showed good linearity (average R value of 0.996) and reproducibility (generally RSD values <10%). We demonstrate the utility of this method by investigating the metabolomic signature of three distinct biological systems: the metabolic response to lack of superoxide dismutase activity and to paraquat induced oxidative stress, and the metabolic profiles of four different Drosophila species., (Copyright © 2013 Elsevier B.V. All rights reserved.)

We report a novel two-dimensional (2D) separation strategy aimed at improving the detectability of liquid chromatography mass spectrometry (LC-MS) for metabolome analysis. It is based on the use of ion-pairing (IP) reversed-phase (RP) LC as the first dimension separation to fractionate the metabolites, followed by isotope labeling of individual fractions using dansylation chemistry to alter the physiochemical properties of the metabolites. The labeled metabolites having different hydrophobicity from their unlabeled counterparts are then separated and analyzed by on-line RPLC Fourier-transform ion-cyclotron resonance mass spectrometry (FTICR-MS). This off-line 2D-LC-MS strategy offers significant improvement over the one-dimensional (1D) RPLC MS technique in terms of the number of detectable metabolites. As an example, in the analysis of a human urine sample, 3564 ¹³C-/¹²C-dansylated ion pairs or metabolites were detected from seven IP RPLC fractions, compared to 1218 metabolites found in 1D-RPLC-MS. Using a library of 220 amine- and phenol-containing metabolite standards, 167 metabolites were positively identified based on retention time and accurate mass matches, which was about 2.5 times the number metabolites identified by 1D-RPLC-MS analysis of the same urine sample., (Copyright © 2011 Elsevier B.V. All rights reserved.)

Metabolome analysis of human cerebrospinal fluid (CSF) is challenging because of low abundance of metabolites present in a small volume of sample. We describe and apply a sensitive isotope labeling LC-MS technique for qualitative analysis of the CSF metabolome. After a CSF sample is divided into two aliquots, they are labeled by (13)C-dansyl and (12)C-dansyl chloride, respectively. The differentially labeled aliquots are then mixed and subjected to LC-MS using Fourier-transform ion cyclotron resonance mass spectrometry (FTICR MS). Dansylation offers significant improvement in the performance of chromatography separation and detection sensitivity. Moreover, peaks detected in the mass spectra can be readily analyzed for ion pair recognition and database search based on accurate mass and/or retention time information. It is shown that about 14,000 features can be detected in a 25-min LC-FTICR MS run of a dansyl-labeled CSF sample, from which about 500 metabolites can be profiled. Results from four CSF samples are compared to gauge the detectability of metabolites by this method. About 261 metabolites are commonly detected in replicate runs of four samples. In total, 1132 unique metabolite ion pairs are detected and 347 pairs (31%) matched with at least one metabolite in the Human Metabolome Database. We also report a dansylation library of 220 standard compounds and, using this library, about 85 metabolites can be positively identified. Among them, 21 metabolites have never been reported to be associated with CSF. These results illustrate that the dansylation LC-FTICR MS method can be used to analyze the CSF metabolome in a more comprehensive manner., (© American Society for Mass Spectrometry, 2011)

Abstract: Acylglycines play a crucial regulatory and detoxification role in the accumulation of the corresponding acyl CoA esters and are an important class of metabolites in the diagnoses of inborn errors of metabolism. Sensitive quantification of a large number of acylglycines not only improves diagnosis but also enables the discovery of potential new biomarkers of diseases. We report an ultra-high performance liquid chromatography tandem mass spectrometry (UPLC–MS) method for quantifying acylglycines in human urine with high sensitivity. This method is based on the use of a newly developed isotope labeling reagent, p-dimethylaminophenacyl (DmPA) bromide, to label acylglycines to improve detection sensitivity. Eighteen acylglycines, namely acetylglycine, propionylglycine, isobutyrylglycine, butyrylglycine, 4-hydroxyphenylacetylglycine, 2-furoylglycine, tiglylglycine, 2-methybutyrylglycine, 3-methylcrotonylglycine, isovalerylglycine, valerylglycine, hexanoylglycine, phenylacetylglycine, phenylpropionylglycine, glutarylglycine, heptanoylglycine, octanoylglycine and suberylglycine, were measured. This method uses calibration standards prepared in surrogate matrix (un-derivatized urine) and stable-isotope labeled analytes as the internal standards. The analysis was carried out in the positive ion detection mode using multiple reaction monitoring (MRM) survey scans. The calibration curves were validated over the range of 1.0–500nM. The method achieved a lower limit of quantitation (LLOQ) of 1–5nM for all analytes, as measured by the standard derivations associated with calibration curves and confirmed in surrogate matrix; the signal-to-noise ratio at LLOQ ranged from 12.50 to 156.70. Both accuracy (% RE or relative error) and precision (% CV) were <15%. Matrix effects were minimized using the surrogate matrix. All eighteen analytes were stable in urine for at least 5h at room temperature, autosampler (4°C) for 24h, 7 weeks at −20°C and after three freeze/thaw cycles. This surrogate matrix approach was validated using a standard addition experiment. As an example of applications, the endogenous concentrations of all eighteen analytes in urine samples of 20 healthy individuals collected in three consecutive days (i.e., 60 samples) were determined; there was no significant correlation found between the acylglycine profile and gender or body mass indices. [Copyright &y& Elsevier]

We report a new quantitative metabolome profiling technique based on differential 12C-13C-isotope dansylation labeling of metabolites, fast liquid chromatography (LC) separation and electrospray ionization Fourier-transform ion cyclotron resonance mass spectrometry (ESI-FTICR MS) detection. An isotope reagent, 13C-dansyl chloride, can be readily synthesized. This reagent, along with 12C-dansyl chloride, provides a simple and robust means of labeling metabolites containing primary amine, secondary amine, or phenolic hydroxyl group(s). It is shown that dansylation labeling offers 1-3 orders of magnitude ESI signal enhancement over the underivatized counterparts. Dansylation alters the chromatographic behaviors of polar and ionic metabolites normally not retainable on a reversed phase (RP) column to an extent that they can be retained and separated by RPLC with high efficiency. There is no isotopic effect on RPLC separation of the differential isotope labeled metabolites, and 12C-13C-labeled isoforms of metabolites are coeluted and detected by MS for precise and accurate quantification and confident metabolite identification. It is demonstrated that, in the analysis of 20 amino acids, a linear response of over 2 orders of magnitude is achieved for relative metabolite quantification with an average relative standard deviation (RSD) of about 5.3% from replicate experiments. A dansylation standard compound library consisting of 121 known amines and phenols has been constructed and is proven to be useful for absolute metabolite quantification and MS-based metabolite identification in biological samples. As an example, the absolute concentrations of 93 metabolites, ranging from 30 nM to 2510 μM, can be determined from a pooled sample of human urines collected in 5 consecutive days labeled with 12C-dansylation and spiked with the 121 13C-dansylated standards. Relative concentration variations of these metabolites in individual urine samples can also be monitored by mixing the 13C-dansylated pooled urine sample with the 12C-dansylated individual sample. With a 12 min fast LC separation combined with FTICR MS, 672 metabolites were detected in a human urine sample with each metabolite peak having a signal-to-noise ratio of greater than 20; the identities of most of the metabolites remain to be determined. This work illustrates that dansylation labeling and fast LC/FTICR MS can be a powerful technique for quantitative profiling of at least 672 metabolites in urine samples in 12 min. [ABSTRACT FROM AUTHOR]

• A high throughput method to simultaneously quantitate sulfadoxine and pyrimethamine. • The method requires only 5 µL plasma sample and 1.6 min of run time per sample. • A low abundant product ion enables simple linear regression for sulfadoxine. • The method is suitable for capillary microsampling and pediatric studies. To support the pharmacokinetic study of sulfadoxine (SD) and pyrimethamine (PM) in pregnant women and children, sensitive methods with small sample volume are desirable. Here we report a method to determine SD and PM with microvolume plasma samples: 5 µL plasma samples were cleaned up by protein precipitation with acetonitrile. The deuterated analytes were used as the internal standards. The samples after cleanup were injected onto an ACE Excel SuperC 18 column (50 × 2.1 mm, 1.7 μm, Hichrom Limited) connected to a Waters I class UPLC coupled with a Sciex Triple Quad 6500+ Mass Spectrometer and eluted with water and acetonitrile both containing 0.1% formic acid in a gradient mode at 0.8mL/min. Detection utilized ESI+ as the ion source and MRM as the quantification mode. The precursor-to-product ion transitions m / z 311→245 for SD and 249→233 for PM were selected for quantification. The ion transitions for the corresponding internal standards were 315→249 for SD-d 4 and 254→235 for PM-d 3. The simplest linear regression weighted by 1/x was used for the calibration curves. The calibration ranges were 1–200 µg/mL SD and 2 – 1000ng/mL PM. The mean (± standard deviation) recoveries were 94.3±3.2% (SD) and 97.0±1.5% (PM). The validated method was applied to analysis of 1719 clinical samples, demonstrating the method is suitable for the pharmacokinetic study with samples collected up to day 28 post-dose. [ABSTRACT FROM AUTHOR]