Understanding essential transition metal allocation in plants cells is pivotal to
decode metal homeostasis in
organelles. In that revealing microscopy X-Ray Fluorescence (μXRF) is a powerful technique,
yet indeed
generates a massive amount of data, requiring appropriate bioinformatics in dataset
handling. To understand
intracellular Fe allocation in nitric oxide signaling and autophagy compromised Arabidopsis
thaliana mesophyll
cells, we applied 20 μm thick cryosection samples. Dataset on the K edge signal of
transition metal
distribution were gained at ID21, European Synchrotron Radiation Facility, and analyzed
using two
computational approaches. First, sample was analyzed as composed of foreground and
background layers,
differentiated by intensity thresholds computing, and morphological operations were
applied to improve the
clarity of segmented regions. Focusing on background layer, away from organelles overlapping
or noise,
provided detailed structural interpretation of Fe-rich zones. The second approach
applied k-means
clustering, treating each pixel as a point in multidimensional element space, where
each organelle occupied
a distinct region in this space region based on its characteristic elemental composition
and corresponding to
its specific functions. Both approaches independently indicated that compromised lines
show altered
plastidial Fe allocation at senescence initiation. This agreement increases the confidence
in the biological
findings and in the robustness of each method.
This work was supported by the grant K-146865 of NKFIH, Hungary. Á.S. was supported
by the János
Bolyai Scholarship of the Hungarian Academy of Sciences (BO-00113-23-8). We acknowledge
the European
Synchrotron Radiation Facility (ESRF) for provision of synchrotron radiation facilities
under proposal
number LS-3039.
