Target-based metabolomics for the quantitative measurement of 37 pathway metabolites in rat brain and serum using hydrophilic interaction ultra-high-performance liquid chromatography–tandem mass spectrometry

Abstract

Amino acids, neurotransmitters, purines, and pyrimidines are bioactive molecules that play fundamental roles in maintaining various physiological functions. Their metabolism is closely related to the health, growth, development, reproduction, and homeostasis of organisms. Most recently, comprehensive measurements of these metabolites have shown their potential as innovative approaches in disease surveillance or drug intervention. However, simultaneous measurement of these metabolites presents great difficulties. Here, we report a novel quantitative method that uses hydrophilic interaction ultra-high-performance liquid chromatography-tandem mass spectrometry (HILIC-UPLC-MS/MS), which is highly selective, high throughput, and exhibits better chromatographic behavior than existing methods. The developed method enabled the rapid quantification of 37 metabolites, spanning amino acids, neurotransmitters, purines, and pyrimidines pathways, within 6.5 min. The compounds were separated on an ACQUITY UPLC® BEH Amide column. Serum and brain homogenate were extracted by protein precipitation. The intra- and interday precision of all of the analytes was less than 11.34 %, and the accuracy was between -11.74 and 11.51 % for all quality control (QC) levels. The extraction recoveries of serum ranged from 84.58 % to 116.43 % and those of brain samples from 80.80 % to 119.39 %, while the RSD was 14.61 % or less for all recoveries. This method was used to successfully characterize alterations in the rat brain and, in particular, their dynamics in serum. The following study was performed to simultaneously test global changes of these metabolites in a serotonin antagonist p-chlorophenylalanine (PCPA)-induced anxiety and insomnia rat model to understand the effect and mechanism of PCPA. Taken together, these results show that the method is able to simultaneously monitor a large panel of metabolites and that this protocol may represent a metabolomic method to diagnose toxicological and pathophysiological states.

Metabolic and transcriptional changes in seminal plasma of asthenozoospermia patients

“…It was noteworthy that Try and Spe levels were observably reduced in the AS group, indicating that turbulences occurred during Try utilization and Spe biosynthesis. Compared with the control group, the levels of Hyp, Tyr, Ino, Phe, Met, and Val were significantly reduced in the seminal plasma of patients in the AS group, and they were related to tyrosine degradation, purine metabolism, branched chain amino acid (BCAA) metabolism, and methionine cycle (Cavuoto & Fenech, ; Chen et al, ; Markowitz et al, ). To intuitively observe the changes in energy‐related metabolites, a graphical heatmap was generated after Z‐score normalization of these data (Figure ).…”

How close are we to complete annotation of metabolomes?

“…What has occurred recently is a considerable growth of targeted methods for studying swathes of metabolism, likely driven by the very frustration of limited peak annotation in non-targeted metabolomics, as discussed above. For example, a number of targeted LC-MS/MS assays have been developed to profile from a few tens to a couple of hundred metabolites in rice [22–24] and mammalian samples [25, 26]. While benefitting from yielding metabolic data that is identified and often quantitative, all of these studies only scrape the surface of the thousands of metabolites estimated to comprise a metabolome.…”

Emerging Applications of Metabolomics in Clinical Pharmacology

“…Untargeted metabolomics mainly provides global profiles of a large number of metabolites in biological samples and contains much information on known and unknown metabolites . Targeted metabolomics usually focuses on the analysis of a specific subset of known metabolites, such as tricarboxylic acid cycle intermediates or amino acids . The metabolomic workflow for both targeted and untargeted metabolomics analysis usually comprises the sequential steps of experimental design, sample collection and preparation, data acquisition, data analysis, metabolite identification (for untargeted metabolomics), and biological interpretation ( Figure ) .…”