Global transcription profiling reveals multiple sugar signal transduction mechanisms in Arabidopsis

Abstract

Complex and interconnected signaling networks allow organisms to control cell division, growth, differentiation, or programmed cell death in response to metabolic and environmental cues. In plants, it is known that sugar and nitrogen are critical nutrient signals; however, our understanding of the molecular mechanisms underlying nutrient signal transduction is very limited. To begin unraveling complex sugar signaling networks in plants, DNA microarray analysis was used to determine the effects of glucose and inorganic nitrogen source on gene expression on a global scale in Arabidopsis thaliana. In whole seedling tissue, glucose is a more potent signal in regulating transcription than inorganic nitrogen. In fact, other than genes associated with nitrate assimilation, glucose had a greater effect in regulating nitrogen metabolic genes than nitrogen itself. Glucose also regulated a broader range of genes, including genes associated with carbohydrate metabolism, signal transduction, and metabolite transport. In addition, a large number of stress responsive genes were also induced by glucose, indicating a role of sugar in environmental responses. Cluster analysis revealed significant interaction between glucose and nitrogen in regulating gene expression because glucose can modulate the effects of nitrogen and vise versa. Intriguingly, cycloheximide treatment appeared to disrupt glucose induction more than glucose repression, suggesting that de novo protein synthesis is an intermediary event required before most glucose induction can occur. Cross talk between sugar and ethylene signaling may take place on the transcriptional level because several ethylene biosynthetic and signal transduction genes are repressed by glucose, and the repression is largely unaffected by cycloheximide. Collectively, our global expression data strongly support the idea that glucose and inorganic nitrogen act as both metabolites and signaling molecules.

Figure 1.

Glucose Has Profound Effects on Gene Expression Compared with Inorganic Nitrogen in 6-d-Old Arabidopsis Seedlings Predominantly Consisting of Shoot Tissue. To remove inconsistent replicates, log₁₀ normalized signal scores were subjected to RCBD analysis (P ≤ 0.001) before twofold filtering.

Figure 2.

Regulation of Gene Expression Orchestrated by Glucose and Nitrogen. Cluster analysis was conducted using GeneCluster2 (Golub et al., 1999) using the genes identified in Figure 1, except those showing significant regulation by 3-OMG were removed from consideration. A self-organizing map (SOM) was generated for genes showing greater than a twofold change with expression above background/noise levels. Blue lines represent the mean expression, and the area between red lines represents the range of values within the cluster. This SOM explained 95.1% of the variance occurring in the data set. Value associated with each cluster represents the number of genes with similar behavior.

Figure 3.

Microarray Data Validation by RNA Gel Blot and RT-PCR Analyses. Genes chosen for analysis include glucose downregulated genes (A), glucose upregulated genes (B), a gene upregulated specifically by glucose and nitrogen (C), nitrate upregulated genes (D), and two unregulated genes (E).

Figure 4.

Glucose Regulates Genes with Diverse Functions. Shown are genes responding to glucose with at least threefold change after normalizing data and conducting RCBD analysis at P ≤ 0.001. Putative functions were determined using spot annotations (The Arabidopsis Information Resource; http://arabidopsis.org), gene ontology searches (http://www.geneontology.org), pathway analyses, and literature review.

Figure 5.

Glucose Induction Often Requires de Novo Protein Synthesis. Frequency of glucose induction versus glucose repression in the presence of CHX. Expression patterns with and without CHX were determined for the genes identified in Figure 2 using SOM software.

Figure 6.

Expression Patterns of Carbohydrate-Related Genes Identified in Figure 4 with or without CHX. Hierarchical average linkage clustering with correlation measure–based distance (uncentered) was used for the analysis. Red or green represents upregulation or downregulation, respectively, and gray represents either genes at background/noise levels or changes below the fold-change cutoff.

Figure 7.

Transcription Factors Are Differentially Regulated by Glucose. (A) Number of all genes versus transcription factors upregulated or downregulated by glucose with a twofold or threefold cutoff. (B) Distribution comparison of glucose-regulated transcription factors with all transcription factors in the Arabidopsis genome (Jiao et al., 2003). Percentage of glucose responsive TFs is derived from the number of each category versus total number of glucose responsive TFs.

Figure 8.

Glucose Affects Expression of Ethylene and Stress Associated Genes. Shown are hierarchical average linkage clustering analyses. Red or green represents upregulation or downregulation, respectively, and gray represents either genes at background/noise levels or no changes with specified cutoff. (A) Nutrient response of genes implicated in sugar signaling based on genetic studies (León and Sheen, 2003; Gibson, 2004). ABI4 is not included because expression levels were near background/noise levels. None of these genes showed a more than twofold change in the presence of CHX; however, CTR1, EIN3, and EIL1 were repressed by glucose more than 1.5-fold in the presence of CHX (Table 2). (B) Nutrient response of hormone biosynthetic genes. Filtering criteria were relaxed to twofold for CHX-treated plants. (C) Numerous heat shock proteins are affected by glucose. (D) Other stress-associated genes are highly glucose-responsive.

Figure 8.

Glucose Affects Expression of Ethylene and Stress Associated Genes. Shown are hierarchical average linkage clustering analyses. Red or green represents upregulation or downregulation, respectively, and gray represents either genes at background/noise levels or no changes with specified cutoff. (A) Nutrient response of genes implicated in sugar signaling based on genetic studies (León and Sheen, 2003; Gibson, 2004). ABI4 is not included because expression levels were near background/noise levels. None of these genes showed a more than twofold change in the presence of CHX; however, CTR1, EIN3, and EIL1 were repressed by glucose more than 1.5-fold in the presence of CHX (Table 2). (B) Nutrient response of hormone biosynthetic genes. Filtering criteria were relaxed to twofold for CHX-treated plants. (C) Numerous heat shock proteins are affected by glucose. (D) Other stress-associated genes are highly glucose-responsive.

Figure 9.

Nutrient Response of Various Transporters. Shown are hierarchical average linkage clustering analyses. Red or green represents upregulation or downregulation, respectively, and gray represents either genes at background/noise levels or no changes with specified cutoff.

Figure 10.

Multiple Sugar Signaling Pathways Revealed by the Regulation of Sugar Transporters. Glucose has profound effects on the expression of monosaccharide transporters. By contrast, only one disaccharide transporter is affected by glucose, consistent with the idea that disaccharide transporters are uniquely regulated by disaccharides (Choiu and Bush, 1998).

Figure 11.

Genes Associated with Nitrogen Metabolism Are Predominantly Regulated by Glucose. The selected genes were normalized and subjected to RCBD analysis (P ≤ 0.001) and showed a more than twofold transcriptional change.

Figure 12.

A Proposed Model Summarizes the Metabolic and Signaling Roles of Glucose. Arrows pointing upward are induction and those pointing downward are repression.