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).