AccuCor2 Isotope Natural Abundance Correction for Dual-Isotope Tracer Experiments

Stable isotope labeling techniques have been widely applied in the field of metabolomics and proteomics. Before the measured mass spectrum data can be used for quantitative analysis, it must be accurately corrected for isotope natural abundance and tracer isotopic impurity. Despite the increasing popularity of dual-isotope tracing strategy such as ¹³C-¹⁵N or ¹³C-²H, there is no accurate tool for correcting isotope natural abundance for such experiments. Here, we present AccuCor2 as an R-based tool to perform the correction for ¹³C-¹⁵N or ¹³C-²H labeling experiments. Our results show that the dual-isotope experiments often require a mass resolution that is high enough to resolve ¹³C and ¹⁵N or ¹³C and ²H.Otherwise the labeling pattern is not solvable. However, this mass resolution may not be sufficiently high to resolve other non-tracer elements such as oxygen or sulfur from the tracer elements. Therefore, we design AccuCor2 to perform the correction based on the actual mass resolution of the measurements. Using both simulated and experimental data, we show that AccuCor2 performs accurate and resolution dependent correction for dual-isotope tracer data.

AccuCor2 Isotope Natural Abundance Correction for Dual-Isotope Tracer Experiments

Stable isotope labeling techniques have been widely applied in the field of metabolomics and proteomics. Before the measured mass spectrum data can be used for quantitative analysis, it must be accurately corrected for isotope natural abundance and tracer isotopic impurity. Despite the increasing popularity of dual-isotope tracing strategy such as ¹³C-¹⁵N or ¹³C-²H, there is no accurate tool for correcting isotope natural abundance for such experiments. Here, we present AccuCor2 as an R-based tool to perform the correction for ¹³C-¹⁵N or ¹³C-²H labeling experiments. Our results show that the dual-isotope experiments often require a mass resolution that is high enough to resolve ¹³C and ¹⁵N or ¹³C and ²H.Otherwise the labeling pattern is not solvable. However, this mass resolution may not be sufficiently high to resolve other non-tracer elements such as oxygen or sulfur from the tracer elements. Therefore, we design AccuCor2 to perform the correction based on the actual mass resolution of the measurements. Using both simulated and experimental data, we show that AccuCor2 performs accurate and resolution dependent correction for dual-isotope tracer data.

Research on Differential Metabolites in Distinction of Rice (Oryza sativa L.) Origin Based on GC-MS

The analytical method for the metabolomics of the 60 rice seeds from two main rice origins in Heilongjiang Province was developed based on gas chromatography coupled with mass spectrum. The specific differential metabolites between two rice origins were identified, and the distinguish of the two main origins was illustrated by using the R software platform with XCMS software package for gas chromatography coupled with mass spectrum data processing, combined with multivariate statistical analysis software. The result indicated that the 173 peaks were detected, and 54 of which were structurally identified, covering amino acids, aliphatic acid, sugar, polyols, and so on. By comparing the data of Wuchang and Jiansanjiang origins, it was found that there were 9 special metabolites in Wuchang origin and 8 special metabolites in Jiansanjiang origin. The 10 differential metabolites with significant changes (P<0.05, VIP ≥ 1) were filtrated. It is indicated that the differential metabolites of rice carry information of their origin and there are the differences in the metabolites of rice in two main origins. The proposed method is expected to be useful for the metabolomic researches of rice.