High-throughput metabolomic approach revealed the acupuncture exerting intervention effects by perturbed signatures and pathways

Abstract

Metabolomics can capture global changes and the overall physiological status in biochemical networks and pathways in order to elucidate sites of perturbations. High-throughput metabolomics and acupuncturology have similar characteristics such as entirety, comprehensiveness and dynamic changes, and can identify potential candidates for acupuncture effects and provide valuable information towards understanding therapy mechanisms. Saliva has recently gained popularity as a potential tool for biomarker monitoring, as its composition may potentially reflect plasma metabolite levels and, therefore, may be used as an indicator of the physiological state. However, the underlying mechanism of acupuncture, remains largely unknown, which hinders its widespread use. Acupuncture would produce unique characterization of metabolic perturbations. In this study, UPLC/ESI-HDMS in high-accuracy mode coupled with pattern recognition analysis was carried out to investigate the mechanism and saliva metabolite biomarkers for acupuncture treatment at ‘Zusanli’ acupoint (ST-36) as a case study. Putative metabolite identifications for these ions were obtained through a mass-based database search. As a result, the top canonical pathways including phenylalanine metabolism, alanine, aspartate and glutamate metabolism, D-glutamine and D-glutamate metabolism, and steroid hormone biosynthesis pathways were acutely perturbed. 26 differential metabolites were identified by chemical profiling, and may be useful to clarify the physiological basis and mechanism of ST-36. More importantly, network construction has led to the integration of metabolites associated with the multiple perturbation pathways. These results provide useful insights into biomarker discovery utilizing metabolomics as an efficient and cost effective platform. This study opens new possibilities for the selection of saliva as a source of metabolite biomarkers representative of specific disorders.