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.     

Cosmetobolomics as an incipient ‘-omics’ with high analytical involvement

This article gives an overview of the complex world of cosmetics metabolism. It outlines the necessity of grouping metabolic studies on cosmetics as a sub-discipline of metabolomics and discusses the reasons for having such a sub-discipline. It identifies the role of analytical chemists in the development of methods to identify and to quantify metabolites and in the elucidation of metabolic pathways. It also sets out the future of cosmetobolomics.     

Thiol metabolomics of endothelial cells using capillary liquid chromatography mass spectrometry with isotope coded affinity tags

Thiol and disulfide levels are critical to maintaining the redox potential of a cell. Perturbations of these levels are important in disease pathogenesis. To improve endogenous mammalian metabolome quantitation, thiol specific tagging, extraction and relative quantitation were undertaken. Reduced and oxidized thiol (disulfide) metabolites from endothelial cells were tagged and extracted using cleavable isotope coded affinity tags (cICAT). Extracted cICAT labeled thiols were analyzed using capillary reverse phase liquid chromatography coupled to mass spectrometry (capLC-MS) with positive mode electrospray ionization. Reactions between thiol metabolite standards and the reactive group of cICAT indicate completion by 8h at pH 9 with no apparent disulfide formation. cICAT labeled reduced thiols from endothelial cells showed 1-5% RSD using ratiometric quantitation of isotopes and 6-17% RSD based on signal intensity alone. Sample injection was optimized to 16 pmol. Using high mass accuracy MS, 75 putative thiol metabolites were detected in all experimental samples. Treatment of endothelial cells with 2,3-dimethoxy-5-methyl-1,4-benzoquinone (BQ) shows decreased levels in 28 putative reduced thiols and increased levels of 27 putative disulfides. Treatment of endothelial cells with 30 mM glucose resulted in 22 putative reduced thiols with decreased levels and 7 putative disulfides with increased concentration. Thiols were identified based on accurate mass within 3 ppm and analysis of fragmentation patterns. Using higher collision induced dissociation (HCD), shared product ions between different thiols led to the analysis of thiols from the cysteine-glutathione (Cys-GSH) pathway. Specific reduced thiols and disulfides in this pathway revealed changes different from the overall trends of thiols/disulfides. This suggests varying regulation of the Cys-GSH pathway distinct from other thiol-containing pathways and dependence on the type of environmental stimulus. These results indicate the utility of analyzing reduced thiols and disulfides in eukaryotic samples.     

基于UHPLC-QE-MS的CCI模型大鼠的血清代谢组学研究

采用超高效液相色谱-四级杆静电场轨道阱质谱（UHPLC-QE-MS）非靶向代谢组学方法,观察CCI模型大鼠血清内源性代谢物的变化,筛选出慢性坐骨神经痛大鼠血清差异性代谢物,分析慢性疼痛对差异性代谢物的影响。将12只SPF级SD雄性大鼠随机均分为正常组和坐骨神经慢性压迫损伤（CCI）组,每组6只。CCI组建立大鼠左侧坐骨神经慢性压迫损伤模型,正常组除不结扎坐骨神经,其余步骤一样。14天后腹主动脉采血, 分离血清,对大鼠血清中的代谢物进行代谢组学检测。利用UHPLC-QE-MS技术并结合PCA(主成分分析)筛选差异代谢物,利用MetabolicAnalyst5.0进行差异代谢物的富集分析。富集分析结果表明,与正常对照组相比,CCI模型大鼠血清有机酸、有机杂环化合物、脂肪酰基、碳水化合物、核酸、有机氮化合物、碳氢化合物等9类代谢物具有统计学差异。结果表明：基于UHPLC-QE-MS的血清代谢组学方法能够有效区分正常组和CCI组,筛选出的差异代谢物有助于慢性疼痛的机制及药物靶点研究。