Identifying metabolomic correlations can be achieved using
gas chromatography-mass spectrometry (GC-MS) as part of a graph-clustering approach, according to scientists writing in BMC Systems Biology.
The periodical specialises in theoretical and experimental findings relating to cellular, molecular and organismal functioning of biological systems.
A team comprising scientists from the universities of Tokyo, Yokohama City, Keio and Chiba in Japan, working with the RIKEN Plant Science Center, describe their use of GC-MS to study metabolite profiles.
"We demonstrate that the graph-clustering approach identifies tissue- and genotype-dependent metabolomic clusters related to the biochemical pathway," they write.
Using metabolomic correlations in conjunction with data about metabolite level changes may lead to elucidation of how metabolically functional molecules are organised, they add.
In particular, GC-MS was used on root tissues to compare metabolomic correlations in aerial and root parts of Arabidopsis, making use of published information on aerial tissue parts to allow for the comparison to take place.