Abstract
Calibration-Curve-Locking Databases (CCLDs) have been constructed for automatic compound search and semi-quantitative screening by gas chromatography/mass spectrometry (GC/MS) in several fields. CCLD felicitates the semi-quantification of target compounds without calibration curve preparation because it contains the retention time (RT), calibration curves, and electron ionization (EI) mass spectra, which are obtained under stable apparatus conditions. Despite its usefulness, there is no CCLD for metabolomics. Herein, we developed a novel CCLD and semi-quantification framework for GC/MS-based metabolomics. All analytes were subjected to GC/MS after derivatization under stable apparatus conditions using (1) target tuning, (2) RT locking technique, and (3) automatic derivatization and injection by a robotic platform. The RTs and EI mass spectra were obtained from an existing authorized database. A quantifier ion and one or two qualifier ions were selected for each target metabolite. The calibration curves were obtained as plots of the peak area ratio of the target compounds to an internal standard versus the target compound concentration. These data were registered in a database as a novel CCLD. We examined the applicability of CCLD for analyzing human plasma, resulting in time-saving and labor-saving semi-qualitative screening without the need for standard substances.
Highlights
The demand for quantitative metabolomics to derive metabolite concentrations has increased with the expansion of research fields that require a data comparison across measurement batches, methods, and facilities [1,2,3]
In the case of DFTPP tuning, the fluctuation of the relative abundance ratio between each m/z was 3.8% and 9.7% (Figure 2C). These results showed that the relative peak area (RPA) for the calibration curve of each target metabolite remained constant among different analytical batches by DFTPP tuning
We constructed a novel Calibration-Curve-Locking Databases (CCLDs) for quantitative metabolomics, including electron ionization (EI) mass spectrum, retention time (RT), quantifier ion, and calibration curves, for 52 metabolites in central carbon metabolism
Summary
The demand for quantitative metabolomics to derive metabolite concentrations has increased with the expansion of research fields that require a data comparison across measurement batches, methods, and facilities (e.g., cohort studies, international collaborative research, pharmacokinetic analysis, and trans-omics research) [1,2,3]. It is not easy to guarantee quantitative performance with mass spectrometry-based metabolomics because procedures for experiments and data processing are highly complex and error-prone [5]. It is necessary to obtain calibration curves for numerous target metabolites for each experiment because the detection sensitivity for each quantifier ion in mass spectrometry generally fluctuates day by day. Obtaining metabolite concentrations from mass spectrometry-based metabolomics is labor-intensive. GC/MS is utilized as a primary method for metabolomics because of its high sensitivity, peak capacity, and repeatability, especially for low–molecular-weight metabolites [6]. The repeatability of the GC separation can be improved Taking advantage of these features of GC/MS, public databases have been constructed for GC/MS-based metabolomics with accurate metabolite identification [7,8,9]. Several research groups have constructed and updated GC/MS libraries for target/non-target metabolome analyses [8,9,10]
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