Metabolite profiling of human urine by CE-ESI-MS using separation electrolytes at low pH

We investigated the potential of CE coupled to electrospray MS (CE-ESI-MS) in metabolite profiling of human urine without any sample prefractionation step. A heterogeneous mixture of biologically relevant compounds covering a broad range of physicochemical properties was used to optimize separation conditions in fused-silica capillaries. A running electrolyte containing 50 mM of acetic acid and 50 mM of formic acid at pH 2.5 was used for the CE separations. A sheath-flow electrospray interface was employed for CE-ESI-MS analysis. Sheath liquids containing 80:20 v/v methanol/water with 0.1% v/v of acetic acid or 60:40 v/v isopropanol/water with 0.5% v/v of ammonia were selected for optimum detection in positive and negative ESI modes, respectively. Reproducibility and sensitivity were studied, and strategies for identification of the separated urinary compounds are suggested. We report major advantages and disadvantages of CE-ESI-MS for metabolite profiling of human body fluids. This work may be regarded as a first step in the use of CE-ESI-MS for reliable differential analysis of body fluids from healthy and diseased individuals.     

Metabolomic profiling of serum in the progression of Alzheimer's disease by capillary electrophoresis–mass spectrometry

There is high interest in the discovery of early diagnostic biomarkers of Alzheimer's disease, for which metabolomics exhibits a great potential. In this work, a metabolomic approach based on ultrafiltration and analysis by CE‐MS has been used to obtain representative fingerprints of polar metabolites from serum samples in order to distinguish between patients with Alzheimer's disease, mild cognitive impairment, and healthy controls. By the use of partial least squares discriminant analysis it was possible to classify patients according to the disease stage and then identify potential markers. Significant increase was observed with progression of disease in levels of choline, creatinine, asymmetric dimethyl‐arginine, homocysteine‐cysteine disulfide, phenylalanyl‐phenylalanine, and different medium chain acylcarnitines. On the other hand, asparagine, methionine, histidine, carnitine, acetyl‐spermidine, and C5‐carnitine were reduced in these serum samples. In this way, multiple essential pathways were found implicated in the underlying pathology, such as oxidative stress or defects in energy metabolism. However, the most interesting results are related to the association of several vascular risk factors with Alzheimer's disease.     

Metabolic profiling of yeast culture using gas chromatography coupled with orthogonal acceleration accurate mass time-of-flight mass spectrometry: Application to biomarker discovery

Yeast and yeast cultures are frequently used as additives in diets of dairy cows. Beneficial effects from the inclusion of yeast culture in diets for dairy mammals have been reported, and the aim of this study was to develop a comprehensive analytical method for the accurate mass identification of the ‘global’ metabolites in order to differentiate a variety of yeasts at varying growth stages (Diamond V XP, Yea-Sacc and Levucell). Microwave-assisted derivatization for metabolic profiling is demonstrated through the analysis of differing yeast samples developed for cattle feed, which include a wide range of metabolites of interest covering a large range of compound classes. Accurate identification of the components was undertaken using GC-oa-ToFMS (gas chromatography-orthogonal acceleration-time-of-flight mass spectrometry), followed by principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) for data reduction and biomarker discovery. Semi-quantification (fold changes in relative peak areas) was reported for metabolites identified as possible discriminative biomarkers (p-value <0.05, fold change >2), including d-ribose (four fold decrease), myo-inositol (five fold increase), l-phenylalanine (three fold increase), glucopyranoside (two fold increase), fructose (three fold increase) and threitol (three fold increase) respectively.     

Pairwise alignment of chromatograms using an extended Fisher–Rao metric

A conceptually new approach for aligning chromatograms is introduced and applied to examples of metabolite identification in human blood plasma by liquid chromatography–mass spectrometry (LC–MS). A square-root representation of the chromatogram's derivative coupled with an extended Fisher–Rao metric enables the computation of relative differences between chromatograms. Minimization of these differences using a common dynamic programming algorithm brings the chromatograms into alignment. Application to a complex sample, National Institute of Standards and Technology (NIST) Standard Reference Material 1950, Metabolites in Human Plasma, analyzed by two different LC–MS methods having significantly different ranges of elution time is described.     

Improved analysis of multivariate data by variable stability scaling: application to NMR-based metabolic profiling

Variable scaling alters the covariance structure of data, affecting the outcome of multivariate analysis and calibration. Here we present a new method, variable stability (VAST) scaling, which weights each variable according to a metric of its stability. The beneficial effect of VAST scaling is demonstrated for a data set of ¹H NMR spectra of urine acquired as part of a metabonomic study into the effects of unilateral nephrectomy in an animal model. The application of VAST scaling improved the class distinction and predictive power of partial least squares discriminant analysis (PLS-DA) models. The effects of other data scaling and pre-processing methods, such as orthogonal signal correction (OSC), were also tested. VAST scaling produced the most robust models in terms of class prediction, outperforming OSC in this aspect. As a result the subtle, but consistent, metabolic perturbation caused by unilateral nephrectomy could be accurately characterised despite the presence of much greater biological differences caused by normal physiological variation. VAST scaling presents itself as an interpretable, robust and easily implemented data treatment for the enhancement of multivariate data analysis.     

Is sarcosine a biomarker for prostate cancer?

Sarcosine was suggested in a letter to Nature in 2009 as a biomarker for prostate cancer. This communication reviews what has been accomplished to date to determine whether sarcosine is or is not a biomarker for prostate cancer that can replace prostate-specific antigen tests.     

Effects of freeze-drying of samples on metabolite levels in metabolome analyses

Freeze-drying (FD) is a useful technique for removing water from biological tissues, such as food samples. Cellular components freeze at once, and the ice sublimates under conditions of high vacuum and low temperatures. Because biological activity is restricted during FD, the degradation of cellular metabolites is often believed to be limited. However, the cellular structure is damaged by several factors, such as the increase in cell volume during freezing, and this has serious effects on the levels of some cellular metabolites. We studied these effects of FD on metabolite levels when using it as a sample preparation step in metabolome analysis. We observed significant decreases in the levels of some metabolites, such as succinate and choline, in Arabidopsis and pear, respectively. We also found that the effects of FD on certain metabolite levels differed between Arabidopsis plants and pear fruits. These results suggest that it is necessary to confirm the metabolite recovery in each sample species when FD is used for sample preparation.     

Strategy of using microsome-based metabolite production to facilitate the identification of endogenous metabolites by liquid chromatography mass spectrometry

One of the challenges in metabolomic profiling of complex biological samples is to identify new and unknown compounds. Typically, standards are used to help identify metabolites, yet standards cannot be purchased or readily synthesized for many unknowns. In this work we present a strategy of using human liver microsomes (HLM) to metabolize known endogenous human metabolites (substrates), producing potentially new metabolites that have yet to be documented. The metabolites produced by HLM can be tentatively identified based on the associated substrate structure, known metabolic processes, tandem mass spectrometry (MS/MS) fragmentation patterns and, if necessary, accurate mass measurements. Once identified, these metabolites can be used as references for identification of the same compounds in complex biological samples. As a proof of principle, a total of 9 metabolites have been identified from individual HLM incubations using 5 different substrates. Each metabolite was used as a standard. In the analysis of human urine sample by liquid chromatography MS/MS, four spectral matches were found from the 9 microsome-produced metabolite standards. Two of them have previously been documented as endogenous human metabolites, the third is an isomer of a microsome-metabolite and the fourth compound has not been previously reported and is also an isomer of a microsome-metabolite. This work illustrates the feasibility of using microsome-based metabolism to produce metabolites of endogenous human metabolites that can be used to facilitate the identification of unknowns in biological samples. Future work on improving the performance of this strategy is also discussed.