Application to plant samples
Here, we took advantage of Arabidopsis samples to show how exact mass GC-MS analysis can be performed routinely on plant samples, with a rather good outcome, i.e. identification and quantification of more than 200 analytes. Another attempt to carry out high-resolution GC-MS for primary metabolites and pesticides analysis in Arabidopsis can be found in, e.g., (Peterson et al., 2010). In terms of methodology and instrumentation, high resolution exact mass GC-MS is similar to nominal mass GC-MS analysis in that it requires standardised derivatisation (optimally with a robotic facility) ensuring that all samples are treated evenly (including the same time lag between the end of derivatisation and injection), and quality controls to assess reproducibility and quantitativity (for a specific discussion about automation of derivatisation for GC-MS, see (Zarate et al., 2016)). Of course, a specific feature of exact mass analysis is that it requires checking mass accuracy (W. Lu et al., 2017), and here this was performed on a day-to-day basis with calibration gas FC43 containing perfluorotributylamine PFTBA (from ThermoFisher Scientific). Also, it is extremely useful to have specific samples to appreciate mass accuracy, for example with a compound that does not require derivatisation like IMT (Fig. 2a-b). This allows one to check not only mass accuracy but also precision of mass excess values associated with all relevant isotopes (C, N, S isotopes; Fig. 2c).
It should be noted that exact mass GC-MS, however, does not solve the issue of multiple derivatives for some specific metabolites. In particular, amino acids can form by-products upon silylation. So is the case of glutamic acid and glutamine, that can both yield pyroglutamate (for a recent discussion on this issue, see (Miyagawa & Bamba, 2019)). It is also the case of arginine, which is known to yield several products (Molnár-Perl & Katona, 2000), and here it formed four products (Fig. 4). High resolution analysis nevertheless provides a method to have a better picture of derivatives and here, we identified 4 main products of arginine derivatisation: ornithine lactam 2TMS, ornithine 3TMS, arginine 3TMS and citrulline 3TMS. Since these different compounds do not have the same response coefficient in the mass spectrometer (i.e. distinct observed signal response curve to concentration), arginine cannot be quantified very precisely by this method.
Basically, GC-MS analysis provides semi-quantitative information on plant samples. A good method to have information on effective quantity (i.e., absolute quantity) of analytes is GC-C-IRMS (GC coupled to combustion and isotope ratio mass spectrometry). In effect, the same sample (same derivatisation) can be injected and the GC-C-IRMS converts quantitatively each peak to CO2 and N2and thus can provide direct information on the amount of carbon (via mass 44 monitoring) or nitrogen (via mass 28 monitoring) in each peak of interest. This method has been used recently (using alfalfa seed protein extracts) and shown to provide satisfactory estimates of absolute amino acid contents (Domergue, Lalande, Abadie, & Tcherkez, 2022). More classical method can also be used, such as external calibration curves, or deuterated standards (internal references). The use of deuterated standards has three drawbacks: First, it complicates mass spectra, with some probability to coincide with m/z features of interest. An example with plant samples is cysteine 3TMS where the target peak (C8H22NSSi2) at 220.1009 Da might coincide with a deuterated fragment ([2H]-C7H21NOSi3, 220.0995 Da). Second, having all deuterated standards is tedious and expensive. Third, deuteration can cause an isotope effect in either chromatography or ionisation efficiency so that the GC-MS signal differs between deuterated and the protiated forms (Alzweiri, Khanfar, & Al-Hiari, 2015; Caban & Stepnowski, 2020; Matucha, Jockisch, Verner, & Anders, 1991; Ripszam, Grabic, & Haglund, 2013).