posted on 2021-12-03, 18:38authored byLandry Blanc, Gino B. Ferraro, Michael Tuck, Brendan Prideaux, Véronique Dartois, Rakesh K. Jain, Nicolas Desbenoit
Besides
many other applications, isotopic labeling is commonly
used to decipher the metabolism of living biological systems. By giving
a stable isotopically labeled compound as a substrate, the biological
system will use this labeled nutrient as it would with a regular substrate
and incorporate stable heavy atoms into new metabolites. Utilizing
mass spectrometry, by comparing heavy atom enriched isotopic profiles
and naturally occurring ones, it is possible to identify these metabolites
and deduce valuable information about metabolism and biochemical pathways.
The coupling of this approach with mass spectrometry imaging (MSI)
allows one then to obtain 2D maps of metabolisms used by living specimens.
As metabolic networks are convoluted, a global overview of the isotopically
labeled data set to detect unexpected metabolites is crucial. Unfortunately,
due to the complexity of MSI spectra, such untargeted processing approaches
are difficult to decipher. In this technical note, we demonstrate
the potential of a variation around the Kendrick analysis concept
to detect the incorporation of stable heavy atoms into metabolites.
The Kendrick analysis uses as a base unit the difference between the
mass of the most abundant isotope and the mass of the corresponding
stable isotopic tracer (namely, 12C and 13C).
The resulting Kendrick plot offers an alternative method to process
the MSI data set with a new perspective allowing for the rapid detection
of the 13C-enriched metabolites and separating unrelated
compounds. This processing method of MS data could therefore be a
useful tool to decipher isotopic labeling and study metabolic networks,
especially as it does not require advanced computational capabilities.