Open Access Open Badges Research

Integration of metabolite with transcript and enzyme activity profiling during diurnal cycles in Arabidopsis rosettes

Yves Gibon1*, Bjoern Usadel1, Oliver E Blaesing12, Beate Kamlage2, Melanie Hoehne1, Richard Trethewey2 and Mark Stitt1

Author affiliations

1 Max Planck Institute of Molecular Plant Physiology, Science Park Golm, Am Muehlenberg, D-14476 Potsdam-Golm, Germany

2 metanomics GmbH, Tegeler Weg, 10589, Berlin, Germany

For all author emails, please log on.

Citation and License

Genome Biology 2006, 7:R76  doi:10.1186/gb-2006-7-8-r76

Published: 17 August 2006



Genome-wide transcript profiling and analyses of enzyme activities from central carbon and nitrogen metabolism show that transcript levels undergo marked and rapid changes during diurnal cycles and after transfer to darkness, whereas changes in activities are smaller and delayed. In the starchless pgm mutant, where sugars are depleted every night, there are accentuated diurnal changes in transcript levels. Enzyme activities in this mutant do not show larger diurnal changes; instead, they shift towards the levels found in the wild type after several days of darkness. This indicates that enzyme activities change slowly, integrating the changes in transcript levels over several diurnal cycles.


To generalize this conclusion, 137 metabolites were profiled using gas and liquid chromatography coupled to mass spectroscopy. The amplitudes of the diurnal changes in metabolite levels in pgm were (with the exception of sugars) similar or smaller than in the wild type. The average levels shifted towards those found after several days of darkness in the wild type. Examples include increased levels of amino acids due to protein degradation, decreased levels of fatty acids, increased tocopherol and decreased myo-inositol. Many metabolite-transcript correlations were found and the proportion of transcripts correlated with sugars increased dramatically in the starchless mutant.


Rapid diurnal changes in transcript levels are integrated over time to generate quasi-stable changes across large sectors of metabolism. This implies that correlations between metabolites and transcripts are due to regulation of gene expression by metabolites, rather than metabolites being changed as a consequence of a change in gene expression.