On the processing of metabolic information through metabolite-gene communication networks: an approach for modelling causality.
Gene-metabolite correlation networks of three independent biological systems were interrogated using an approach to define, and subsequently model, causality. The major goal of this work was to analyse how information from those metabolites, that displayed a rapid response to perturbation of the biological system, is processed through the response network to provide signal-specific adaptation of metabolism. For this purpose, comparison of network topologies was carried out on three different groups of system elements: transcription factors, other genes and metabolites, with special emphasis placed on those features which are possible sites of metabolic regulation or response propagation. The degree of connectivity in all three analysed gene-metabolite networks followed power-law and exponential functions, whilst a comparison of connectivities of the various cellular entities suggested, that metabolites are less involved in the regulation of the sulfur stress response than in the ripening of tomatoes (in which metabolites seem to have an even greater regulatory role than transcription factors). These findings reflect different degree of metabolic regulation for distinct biological processes. Implementing causality into the network allowed classification of metabolite-gene associations into those with causal directionality from gene to metabolite and from metabolite to gene. Several metabolites were positioned relatively early in the causal hierarchy and possessed many connections to the downstream elements. Such metabolites were considered to have higher regulatory potential. For the biological example of hypo-sulfur stress response in Arabidopsis, the highest regulatory potential scores were established for fructose and sucrose, isoleucine, methionine and sinapic acid. Further developments in profiling techniques will allow greater cross-systems comparisons, necessary for reliability and universality checks of inferred regulatory capacities of the particular metabolites.
Szymanski
Jedrzej
J
Max-Planck-Institut für Molekulare Pflanzenphysiologie, Am Mühlenberg 1, 14476 Potsdam-Golm, Germany.
Bielecka
Monika
M
Carrari
Fernando
F
Fernie
Alisdair R
AR
Hoefgen
Rainer
R
Nikiforova
Victoria J
VJ
D000220:Adaptation, Biological; D017360:Arabidopsis / Q000235:genetics / Q000378:metabolism*; D018506:Gene Expression Regulation, Plant; D018551:Solanum lycopersicum / Q000235:genetics / Q000378:metabolism*; D008954:Models, Biological; D010940:Plant Proteins / Q000235:genetics* / Q000378:metabolism; D015398:Signal Transduction; D013455:Sulfur / Q000378:metabolism; D014157:Transcription Factors / Q000235:genetics / Q000378:metabolism
D010940:Plant Proteins; D014157:Transcription Factors; D013455:Sulfur