多重安定同位体標識Chemical-taggingを用いた標的／非標的融合型メタボロミクスの開発とヒト運動負荷血液測定への応用

抄録

In the past decade, numerous methodologies in metabolomics have emerged alongside advancements in mass spectrometry (MS) technologies. These metabolomics studies can be categorized into targeted and nontargeted methods, and having trade-offs like as lack information and quantitative reliability issues. The fundamental cause of this trade-off lies in the difficulty of collecting isotopic surrogates due to cost constraints and synthetic technological challenges. One potential solution to this issue is the utilization of stable isotope chemical-tagging (SIC). The method is based on paired SIC, i.e., one to the sample and another to a reference as surrogates. Although the matrix effect can be corrected comprehensively without isotopic surrogates, the impact of tagging efficiencies remains as a problematic issue. This study introduces a novel hole correction method, termed multiSIC (MUSIC), which addresses the recovery of tagging efficiencies to matric effects. A series of diluted MUSIC experiments can establish an internal calibration curve (ICC) with only a standard mixture (targeted function) preparation. Notably, by employing a high-resolution MS system, the ICC slope ratio can be utilized to identify similar metabolites (nontarget function). Following the validation, we applied this approach to blood samples to elucidate the relationship between metabolome fluctuations and exercise loading. Eighty-two metabolites were successfully quantitated in the serum of healthy adults who were habitually exercising. Among these, 13 metabolites were significantly fluctuated after 8-week exercise loading, and glutathione pathway was enriched from the pathway analysis.