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

Abstract

Background: 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.

Results: 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.

Conclusion: 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.

Figure 1

Heat map representing the changes in transcript levels and in the corresponding 23 enzyme activities in rosettes of Arabidopsis. Samples were taken from Col0 WT plants and Col0 pgm growing in a 12 h night and 12 h day cycle, throughout one day and night cycle, and in WT plants transferred to an extended night (XN). Log₂ ratios were calculated for each value, by dividing it by the average of diurnal WT values and applying the logarithm (base 2). Log₂ ratios give the intensity of the blue or red colors, according to the scale from the legend. Relative proportions among isoforms were calculated using the entire dataset and give the intensity of the gray color. These data are taken from [4] and [37]. CHO, carbohydrate.

Figure 2

Heat map representing the changes in metabolite levels in rosettes of Arabidopsis. Metabolites of Col0 WT plants growing in 12 h light and 12 h night throughout one day and night cycle are shown. Log₂ ratios were calculated for each value by dividing it by the average. Log₂ ratios give the intensity of the blue or red colors according to the scale bar. CHO, carbohydrate.

Figure 3

Timing of maxima and minima for metabolites across a 12 h light and 12 h night cycle, in rosettes of Arabidopsis Col0 WT plants. Data were smoothed prior to calculations. The shaded region indicates the dark period.

Figure 4

Heat map representing the changes in metabolites throughout one day and night cycle in rosettes of Arabidopsis Col0 WT plants, in Col0 pgm growing in a 12 h night and day cycle, and in WT plants transferred to an extended night (XN). Log₂ ratios were calculated for each value by dividing it by the average of diurnal WT values and applying the logarithm (base 2). Log₂ ratios give the intensity of the blue or red colors, according to the scale bar. CHO, carbohydrate.

Figure 5

Comparative analysis of metabolite profiles obtained from Arabidopsis Col0 pgm and WT plants transferred to an extended night (XN). Heat map representing the differences in amplitudes of diurnal changes in individual metabolites calculated as maximum value - minimum value from smoothed data in WT and pgm (left); Log₂ values of average (pgm) to average (WT) levels (middle), and Log₂ values of average(WT) to 144 h XN (right). Scales are given in the legend.

Figure 6

Correlation plots comparing changes in 137 metabolites in pgm to changes due to the extension of the night in WT. Colored plots correspond to the metabolites listed in the legend.

Figure 7

Distribution of amplitudes of diurnal changes in transcripts, metabolites and enzyme activities. Distribution of amplitudes of diurnal changes in (a) 2,433 transcripts assigned to metabolism, (b) the subset of 82 transcripts encoding the enzymes measured, (c) 23 enzyme activities, and (d) 137 metabolites. Distributions are expressed as probability densities and were calculated with R using the function 'density', which computes kernel density estimations. The same bandwidth of 0.06 was used for all datasets.

Figure 8

Distribution of global changes in transcript and metabolite levels and enzyme activities during the diurnal cycle and an extended night (XN). Distribution of changes in (a) 2,433 transcripts assigned to metabolism, (b) 23 enzyme activities and (c) 140 metabolites after 2, 4, 8, 24, 48, 72 and 144 h of extension of the night. Transcript levels were not determined at 72 and 144 h. Distributions are expressed as probability densities and were calculated with R using the function 'density', which computes kernel density estimations. The same bandwidth of 0.2 was used for all datasets.

Figure 9

Details of specific changes in transcript levels, metabolites and enzyme activities during the diurnal cycle and an extended night. Changes in specific transcripts, enzyme activities and metabolites in rosettes of Arabidopsis Col0 WT plants (WT diurnal) and pgm (pgm diurnal) throughout a day and night cycle, and in WT transferred to an extended night. (a) Glycerolipid metabolism: levels of transcripts encoding glycerol-3P dehydrogenase (At5g40610) and fatty acid desaturase 6 (At4g30950), activity of glycerol-3P dehydrogenase, and levels of glycerol-3P and palmitolenate. (b) Inositol metabolism: levels of transcripts encoding inositol oxidase (At5g56640, At4g26260 and At2g19800), and inositol levels. FW, fresh weight.

Figure 10

Metabolite correlation networks resulting from diurnal changes. Correlation networks of 137 metabolites determined across a day and night cycle in Arabidopsis Col0 WT plants and pgm growing in 12 h day/12 h night cycles. Metabolites with significant correlations are linked together; green discs represent the number of transcripts correlated to a given metabolite. Solid lines indicate positive correlations, dotted lines indicate negative correlations.

Figure 11

Identification of robust sugar-responsive genes whose transcripts correlate with changes in glucose, sucrose or glucose-6-phosphate during diurnal cycles in WT plants and pgm, and in an extended night treatment. (a) Correlation coefficients and corresponding p values (x axis, logarithmic scale) were calculated between the transcript levels for each of these genes and the levels of glucose, sucrose, or glucose-6P using a combined dataset, including data obtained from WT and pgm across a night and day cycle, and WT plants transferred to an extended night. The top graphs show the number of genes whose transcripts correlate with glucose (left hand), sucrose (middle) or glucose-6P (right hand) at a significance level. The bottom graphs show the proportion of the genes that correlate with a given metabolite, which are found in a set of 'sugar-responsive' genes (thick line). A set of 1,312 'sugar-responsive' genes was defined by inspection of public domain data for experiments in which sugars were added to carbon-starved seedlings for 3 h, or leaves were illuminated for 4 h in the presence and absence of CO₂(see main text for details). The plot also shows a similar comparison against a set of genes that are induced or repressed within 30 minutes by addition of sucrose to starved seedlings (dotted line). Blue lines correspond to positive correlations, red lines to negative correlations. (b) Venn Diagram of sugar-regulated genes correlated to sucrose, glucose and glucose-6-phosphate with a significance level of 0.001 or better. In total, 1,141 of the 1,312 genes correlated with at least one metabolite with a p value < 10^-3.