The diel course allocation toward primary and secondary
metabolisms is distinct between ferns and angiosperms
Ferns and angiosperms have different evolutionary histories (Sussmilchet al. 2019), which may reflect in their metabolome. Furthermore,
our previous results suggest that ferns and angiosperms have distinct
allocation of the daily CO2 assimilated toward the
synthesis of primary/secondary metabolites (Lima et al. 2019),
which may have consequences for both A -g sand growth-stress tolerance trade-offs. We then next carried out a
LC-MS-based metabolic fingerprinting analysis in leaf samples harvested
throughout the diel course to better understand the metabolic
differences between these plant groups. Metabolic fingerprinting is an
untargeted metabolomics approach suitable to discriminate biological
samples without metabolite identification, i.e. based in the intensity
of the features (peaks found in the chromatograms) detected in the
samples (Scholz et al. 2004; Kruger et al. 2008; Kosmideset al. 2013; Silveira-Sotelo et al. 2015; Perez de Souzaet al. 2019). Given that the LC-MS platform used here mostly
detects secondary metabolites (Tohge & Fernie 2010; Perez de Souzaet al. 2021), metabolic fingerprinting analysis was next used to
investigate how ferns and angiosperms differ with regard to their
contents of secondary metabolites. Analysis of the chromatograms
revealed an incredible metabolic diversity in ferns, as evidenced by the
higher number of peaks solely detected in ferns. However a high
intensity of peaks for a given compounds was found in both plant groups
(Figures 4a-d). Similarly, several mass-to-charge ratio (m/z )
features obtained by MS analysis were solely found in ferns, especially
at 5:00 h and 14:00 h (Figures 5a-d). A total of 19340, 7741, 9668 and
19598 features were statistically different (P < 0.05)
between ferns and angiosperms at 5:00 h, 8:00 h, 14:00 h and 17:00 h,
respectively. Several of these features had higher intensity in ferns,
compared to angiosperms (Figures 6a-d). Hierarchical clustering analysis
(HCA) (Figures 6a-d), orthogonal partial least squares discriminant
analysis (orthoPLS-DA) (Figures 7a-d) or principal component analysis
(PCA) (Figures S6a-d) of these features indicate that ferns and
angiosperms differ substantially at the secondary metabolic level.
Similarly, PCA using previously published GC-MS metabolite profiling
data (Lima et al. 2019), which mostly refers to primary
metabolites, also discriminate ferns and angiosperms (Figures S7a-d).
The results obtained here coupled to previous studies provide compelling
evidence highlighting that fern stomata can respond to the circadian
rhythm and close in response to sucrose, mannitol, dark, high VPD and
high CO2 concentration (Franks & Britton-Harper 2016;
Hõrak et al. 2017; Lima et al. 2019; Cardoso et al.2019; Gong et al. 2021; Plackett et al. 2021). However, no
ABA response was observed in the ferns used here (Figure 8a). These
results indicate that the slower ferns stomatal closure is associated to
their limited capacity to respond to ABA and to mesophyll-derived
metabolites, especially sucrose, when compared to angiosperms. This idea
is supported by the fact that the faster high
CO2-induced stomatal closure of angiosperms was
associated to their higher capacity to produce sucrose (Figure 8b) (Limaet al. 2019), when compared to ferns. Furthermore, our
metabolomics analyses suggest that ferns and angiosperms exhibit
distinct patterns of allocation toward primary and secondary metabolisms
throughout the diel course, which may affect the level of ROS in the
guard cells of these species (Figure 8c) and ultimately have
implications for the regulation of bothA -g s and growth-stress tolerance
trade-offs (Figure 9).