Evaluation of GC/MS-Based 13C-Positional Approaches for TMS Derivatives of Organic and Amino Acids and Application to Plant 13C-Labeled Experiments

Analysis of plant metabolite C-13-enrichments with gas-chromatography mass spectrometry (GC/MS) has gained interest recently. By combining multiple fragments of a trimethylsilyl (TMS) derivative, C-13-positional enrichments can be calculated. However, this new approach may suffer from analytical biases depending on the fragments selected for calculation leading to significant errors in the final results. The goal of this study was to provide a framework for the validation of C-13-positional approaches and their application to plants based on some key metabolites (glycine, serine, glutamate, proline, alpha-alanine and malate). For this purpose, we used tailor-made C-13-PT standards, harboring known carbon isotopologue distributions and C-13-positional enrichments, to evaluate the reliability of GC-MS measurements and positional calculations. Overall, we showed that some mass fragments of proline_2TMS, glutamate_3TMS, malate_3TMS and alpha-alanine_2TMS had important biases for C-13 measurements resulting in significant errors in the computational estimation of C-13-positional enrichments. Nevertheless, we validated a GC/MS-based C-13-positional approach for the following atomic positions: (i) C1 and C2 of glycine_3TMS, (ii) C1, C2 and C3 of serine_3TMS, and (iii) C1 of malate_3TMS and glutamate_3TMS. We successfully applied this approach to plant C-13-labeled experiments for investigating key metabolic fluxes of plant primary metabolism (photorespiration, tricarboxylic acid cycle and phosphoenolpyruvate carboxylase activity).

Automated summary

The reliability of GC/MS measurements and computational estimation of C-13-positional enrichments were evaluated in this study using tailor-made C-13-PT compounds. It was found that certain mass fragments had significant biases, leading to errors in the calculation of C-13-positional enrichments. However, a GC/MS-based C-13-positional approach was successfully validated and applied to investigate key metabolic fluxes in plant primary metabolism.