LAUSR

This study investigated the optimal inter-batch normalization method for gas chromatography/tandem mass spectrometry (GC/MS/MS)-based targeted metabolome analysis of rodent blood samples. The effect of centrifugal concentration on inter-batch variation was also investigated. Six serum samples prepared from a mouse and 2 quality control (QC) samples from pooled mouse serum were assigned to each batch, and the 3 batches were analyzed by GC/MS/MS at different days. The following inter-batch normalization methods were applied to metabolome data: QC-based methods with quadratic (QUAD)- or cubic spline (CS)-fitting, total signal intensity (TI)-based method, median signal intensity (MI)-based method, and isotope labeled internal standard (IS)-based method. We revealed that centrifugal concentration was a critical factor to cause inter-batch variation. Unexpectedly, neither the QC-based normalization methods nor the IS-based method was able to normalize inter-batch variation, though MI- or TI-based normalization methods were effective in normalizing inter-batch variation. For further validation, 6 disease model rat and 6 control rat plasma were evenly divided into 3 batches, and analyzed as different batches. Same as the results above, MI- or TI-based methods were able to normalize inter-batch variation. In particular, the data normalized by TI-based method showed similar metabolic profiles obtained from their intra-batch analysis. In conclusion, the TI-based normalization method is the most effective to normalize inter-batch variation for GC/MS/MS-based metabolome analysis. Graphical abstract Graphical abstract