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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 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.)

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)

We report a new quantitative metabolome profiling technique based on differential (12)C-/(13)C-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, (13)C-dansyl chloride, can be readily synthesized. This reagent, along with (12)C-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 (12)C-/(13)C-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 microM, can be determined from a pooled sample of human urines collected in 5 consecutive days labeled with (12)C-dansylation and spiked with the 121 (13)C-dansylated standards. Relative concentration variations of these metabolites in individual urine samples can also be monitored by mixing the (13)C-dansylated pooled urine sample with the (12)C-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.

One of the challenges associated with metabolome profiling in complex biological samples is to generate quantitative information on the metabolites of interest. In this work, a targeted metabolome analysis strategy is presented for the quantification of amine-containing metabolites. A dimethylation reaction is used to introduce a stable isotopic tag onto amine-containing metabolites followed by LC-ESI MS analysis. This labeling reaction employs a common reagent, formaldehyde, to label globally the amine groups through reductive amination. The performance of this strategy was investigated in the analysis of 20 amino acids and 15 amines by LC-ESI MS. It is shown that the labeling chemistry is simple, fast (<10-min reaction time), specific, and provides high yields under mild reaction conditions. The issue of isotopic effects of the labeled amines on reversed-phase (RP) and hydrophilic interaction (HILIC) LC separations was examined. It was found that deuterium labeling causes an isotope effect on the elution of labeled amines on RPLC but has no effect on HILIC LC. However, 13C-dimethylation does not show any isotope effect on either RPLC or HILIC LC, indicating that 13C-labeling is a preferred approach for relative quantification of amine-containing metabolites in different samples. The isotopically labeled 35 amine-containing analogues were found to be stable and proved to be effective in overcoming matrix effects in both relative and absolute quantification of these analytes present in a complicated sample, human urine. Finally, the characteristic mass difference provides additional structural information that reveals the existence of primary or secondary amine functional groups in amine-containing metabolites. As an example, for a human urine sample, a total of 438 pairs of different amine-containing metabolites were detected, at signal-to-noise ratios of greater than 10, by using the labeling strategy in conjunction with RP LC-ESI Fourier-transform ion cyclotron resonance MS.