- Open Access
Interactions between light and carbon signaling pathways in Arabidopsis
© BioMed Central Ltd 2004
- Published: 27 February 2004
Two major signals perceived by plants are light and the source of carbon. A new report has examined the interactions between the signaling pathways from these two stimuli on a genome-wide scale in the model plant Arabidopsis thaliana.
- InterAct Class
- Asparagine Synthetase
- Model Plant Arabidopsis Thaliana
- Light Signaling Pathway
- Gene ASN1
When a seed germinates under the soil in darkness, the initial growth and development of the seedling is fueled by mobilization of the carbon reserves, which are stored in the cotyledons in dicotyledonous plants (dicots) and the endosperm in monocotyledonous plants (monocots). The dark-grown (etiolated) seedling is then competent to perceive light signals. When the etiolated seedling emerges from the soil, light immediately triggers changes in its growth and development and promotes the dramatic transition from feeding on chemical compounds (heterotrophy) to synthesizing food using light energy (autotrophy). Carbon compounds such as sucrose that are made during photosynthesis in seedlings are transported from the photosynthetic tissues to the rest of the seedling, where they are converted to starch for storage.
As the metabolic requirements and developmental needs of a plant are so different in light and darkness, or in the presence and absence of a supply of carbon, it is not surprising to see complex interactions between the two signals in regulating gene expression. Certain photosynthetic genes (such as the cab genes, which encode the light-harvesting chlorophyll a/b binding proteins) are induced by light but repressed by carbon, whereas other genes are induced by both signals. Until now, however, no-one has attempted a systematic analysis to explore the complexity of these interactions at a genome-wide scale; nor have models been proposed to describe these interactions.
The Coruzzi laboratory has pioneered the systematic analysis of interactions between light and carbon signaling pathways in the model plant Arabidopsis thaliana. Using the genes ASN1 and ASN2 (encoding asparagine synthetases), and GLN2 (encoding a glutamine synthetase), they found that although carbon regulates the expression of ASN1 and GLN2 in etiolated seedlings, this regulation can be overridden by light . Conversely, in light-grown plants, carbon supplants light as the major regulator of GLN2 and ASN2. These regulatory interactions appear to reflect the different roles of glutamine and asparagine in light- and dark-grown plants.
In an article recently published in Genome Biology , Coruzzi and colleagues have extended their investigations into interactions between light and carbon signaling to many more genes. Two-week-old Arabidopsis plants were left untreated or treated with light and carbon (sucrose), giving four conditions denoted '-C-L' (control without carbon or light), '-C+L' (light only), '+C-L' (carbon only), and '+C+L' (both); RNA samples from each condition were analyzed using Affymetrix chips containing 8,000 genes (about 30% of the entire genome). Expression profiles obtained from the experimental samples were compared with that of the -C-L sample in order to measure the effect of the two signal inputs for a total of about 2,000 genes for which complete microarray data were obtained.
Assignment of InterAct classes and models
Examples of other classes in the same model
No change (0x)
None; responds only to light
110, -1-10, 0-1-1
Independent (model 1)
Repressive (such as -1-2-1); antagonistic (such as -10-1)
No change (0x)
No change (0x)
Dependent (model 2)
010 (also synergistic)
Equal effect (whether separately or together)
Independent and Dependent (model 3)
C dominates (such as 221); L dominates (such as 122); suppressed (such as 210); Enhanced (such as -1-20)
Recognizing that this analysis could potentially give important insights, Coruzzi and colleagues  then used the functional classification of the Munich Information Center for Protein Sequences (MIPS) [3, 4] to identify functional categories of genes underpinning metabolic pathways likely to be regulated by carbon and/or light signaling. They found that genes in the categories 'carbon-containing-compound/carbohydrate metabolism', 'cell wall' and 'electron transport' are overrepresented in InterAct class 111 (and thus are likely to be regulated by either carbon or light), whereas the functional categories 'transcription', 'cellular communication/signal transduction' and 'cell cycle and DNA processing' are overrepresented within InterAct class 000 and thus, as a whole, are less likely to be regulated by carbon or light signaling pathways.
Genes with similar regulation patterns (that is, genes that are in the same InterAct class) are likely to share common cis elements that mediate their expression. To investigate whether this is the case, the authors  analyzed a subset of genes involved in similar metabolic processes within a single InterAct class (111) in which both carbon and light have the same effect, whether separately or in combination. They were able to identify DNA sequence elements capable of responding to either one of the signals, putative 'light-or-carbon responsive' elements. At each step of their work, the authors provided strong indications of confidence in their approach. It is clear that well-characterized genes indeed fall into the 'correct' categories according to their known expression profiles. Furthermore, known light-responsive cis-acting motifs are found among the newly described putative light-or-carbon-responsive elements, including GT-1 binding sites, G-boxes, H-boxes and RE1 elements (see Table 7 in Thum et al. ).
The systems-biology approach described by the Coruzzi group  can potentially be applied to investigating interactions of any other pair of signals that mutually modulate a plant developmental process. For example, it is known that responses to pathogen invasion are dependent on light , and ethylene and jasmonic-acid signaling pathways act synergistically as well as antagonistically in regulating gene expression . Detailed descriptions and modeling of these interactions using the methods provided in this study  will eventually lead to a more complete understanding of how plant signaling systems operate.
We thank Peter Hare for discussion. N.H.C. was supported by NIH GM 44640 and J.L.R. was supported by a PEW Latin American Fellowship.
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