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Differential Gene Expression in Response to Mechanical Wounding and Insect Feeding in ArabidopsisPhilippe Reymonda, Hans Webera, Martine Damonda, and Edward E. Farmeraa Laboratoire de Biologie et de Physiologie Végétales, Institut d'Écologie, Université de Lausanne, Bâtiment de Biologie, 1015 Lausanne, Switzerland Correspondence to: Edward E. Farmer, edwardelliston.farmer{at}ie-bpv.unil.ch (E-mail), 41-21-6924195 (fax)
Wounding in multicellular eukaryotes results in marked changes in gene expression that contribute to tissue defense and repair. Using a cDNA microarray technique, we analyzed the timing, dynamics, and regulation of the expression of 150 genes in mechanically wounded leaves of Arabidopsis. Temporal accumulation of a group of transcripts was correlated with the appearance of oxylipin signals of the jasmonate family. Analysis of the coronatine-insensitive coi1-1 Arabidopsis mutant that is also insensitive to jasmonate allowed us to identify a large number of COI1-dependent and COI1-independent wound-inducible genes. Water stress was found to contribute to the regulation of an unexpectedly large fraction of these genes. Comparing the results of mechanical wounding with damage by feeding larvae of the cabbage butterfly (Pieris rapae) resulted in very different transcript profiles. One gene was specifically induced by insect feeding but not by wounding; moreover, there was a relative lack of water stressinduced gene expression during insect feeding. These results help reveal a feeding strategy of P. rapae that may minimize the activation of a subset of water stressinducible, defense-related genes.
Wounding is a continual threat to the survival of all organisms. Responses to wounding have been extensively studied in plants, which in the wild seldom escape some degree of damage from environmental stresses such as wind, sand, hail, and rain. An open wound caused by mechanical wounding is a potential infection site for pathogens; thus, expression of defense genes at the wound site is a barrier against opportunistic microorganisms. Plants respond to mechanical wounding with the induction of numerous genes. The first identified wound-inducible defense proteins in plants include proteinase inhibitors I and II from potato and tomato (
In Arabidopsis, many genes have been shown to be induced by mechanical wounding (reviewed in
A large proportion of multicellular eukaryotes eat plants, and a particularly common source of injury to plants is insect herbivory. Inevitably, insect feeding causes wounding of the plant, but little is known about how plants distinguish and respond to the very different threats posed by mechanical wounding and herbivory. Although reports show that some genes or proteins can be activated by both mechanical wounding and insect challenge ( In this study, our goal was to better understand how plant responses to mechanical wounding differ from those to insect feeding. An answer to this question is important because insects have probably evolved strategies to avoid activating the expression of at least some plant defense processes. We first studied gene expression dynamics in mechanically wounded Arabidopsis leaves by using a cDNA microarray that included 150 defense-related genes. We then dissected the signal requirements for the expression of wound-inducible genes, using Arabidopsis mutants impaired in the jasmonate and ethylene perception pathways. From these results, we determined which signal pathways are selectively activated by a feeding insect and which categories of genes escape activation during feeding. Our results illustrate fundamental differences in responses to damage caused by mechanical wounding and to damage from insect feeding; they also help to link feeding strategy to molecular responses in the plant.
Construction of a cDNA Microarray Containing Arabidopsis Defense-Related Genes We included 16 genes for which the expression was unlikely to vary greatly during experiments (e.g., tubulin, actin, and translation elongation factors); these allowed us to calibrate the signal output and correct for sample-to-sample variability. In some cases, a so-called control gene showed a more than twofold variation in expression after wounding and thus could not be used for calibration. This speaks for the use of as many control genes as possible for data normalization.
Finally, three animal genes having no substantial homology to any sequence in the Arabidopsis database were printed on the microarray to assess for nonspecific hybridization. One of them, the peroxisome proliferator-activated receptor (PPAR
Dynamics of Wound-Inducible Gene Expression
Fig 2 illustrates that use of this clustering program allowed grouping of genes with similar expression profiles during the time course. Various patterns of gene expression were observed, including early, mid-, and late gene induction as well as early repression of gene expression. By 15 min after wounding, the expression of 20 genes was already induced, including, for example, PR-1, PR-2, PR-5, touch genes (TCH2, TCH3, and TCH4), and genes encoding mitogen-activated kinases (MPK3 and MEKK1). In several cases (e.g., PR-1 and MPK3), the increase in transcript abundance was short-lived and fell rapidly to the base value. The number of upregulated genes increased to 39 at 90 min but was only 13 at 9 hr after wounding and seven by 24 hr after wounding.
One measure of the reproducibility of the changes we observed in gene expression is exemplified in Fig 2, in which, for most genes, we could see a gradual change over a few time points. This effectively provided independent measurements for all of the observations. To better assess the reproducibility of the microarray technique under our laboratory conditions, we performed nine independent replications of the same experiment. Arabidopsis leaves were wounded, RNA was isolated after 90 min, and labeled mRNA samples from control and treated plants were hybridized with a microarray. The average expression ratios calculated for the nine independent experiments are shown in Fig 3 for a set of representative genes and illustrate the small variability in the measurements. In some cases in which duplicate genes were included, highly similar values were obtained (Fig 3). In addition, hybridization of different microarrays with the same mRNA samples indicated good correlation (data not shown).
The time-course analysis of gene expression revealed groups of genes with similar behavior (Fig 2). One implication of a common temporal pattern of expression is that genes might share similar or related roles in cellular processes, or they might be regulated by the same signal molecules. Fig 4A shows the mean expression ratios of a group of 17 transcripts that had similar temporal expression profiles. Among these are two genes (LOX2 and AOS; Table 1) implicated in the synthesis of JA as well as a gene known to be induced by jasmonate, JR3. Moreover, JA and its precursor OPDA as well as its C16 carbon homolog dinor OPDA are known to accumulate in wounded plant tissues (
Several Signal Pathways Regulate Wound-Inducible Gene Expression
To find a potential signal involved in the induction of the COI1-independent group of genes, we investigated the role of ethylene in wounding. Ethylene is essential for the wound induction of proteinase inhibitors in tomato (
Searching for another potential stimulus responsible for the induction of COI1-independent genes, we noticed the strong wound activation of genes (XERO2 and ER5; Table 1) that are also induced by water stress (
Transcript Signatures in Wounding, Dehydration, and Insect Feeding
A comparison of data sets from mechanical wounding, dehydration, and insect feeding allowed us to recognize different patterns of gene expression, as illustrated in Fig 7 with a set of representative genes. We observed that some genes were induced in all treatments, some induced transcripts were common to mechanical wounding and dehydration, and others were unique to each treatment. Some of these marker genes (Fig 7A and Fig 7C) will provide a good tool for the further analysis of signaling pathways specifically involved in the responses to mechanical wounding or insect damage. We found no examples of genes that were induced by both dehydration and insect feeding but not by mechanical wounding. The transcript signature of mechanical wounding was more similar to that of dehydration than to that of insect feeding (Fig 7).
In this study, we used cDNA microarrays to identify a number of Arabidopis genes for which we were unable to find reports of wound induction in the literature. The data also confirmed previous studies of other genes for which activation by wounding was described ( Another example is provided by genes involved in the synthesis or metabolism of members of the jasmonate family (FAD7, LOX2, and AOS), which are coordinately induced during wounding (Fig 4A). Concomitantly with changes in gene expression, the amounts of three members of the jasmonate familyOPDA, dinor OPDA, and JAtransiently increased (Fig 4B). The results revealed that temporal changes in JA content correlate tightly with the induction of a group of genes, including genes involved in JA biosynthesis. Moreover, the relative proportion of JA to the cyclopentenones OPDA and dinor OPDA constantly changed during wounding. Shortly after the wound stimulus, molar amounts of JA exceeded the combined quantities of OPDA and dinor OPDA. However, 2 to 3 hr after wounding, the combined amounts of the cyclopentenone oxylipins exceeded those of JA. This crossover point might be relevant to regulation of gene expression by different jasmonates. Future work should address the specific role of each of these molecules in gene expression as determined with cDNA microarrays. The experiment shown here highlights the potential of combining "oxylipin signatures" with "transcript signatures"; it will be interesting to make comparisons in larger databases containing more values for gene expression and more complex pools of oxylipins.
The fact that genes showed similar expression profiles when wounded does not imply that they are regulated by the same signal. Indeed, we found several genes (e.g., GST1, TCH1, and ER5) for which the temporal expression profile was similar to that of JA-related genes (Fig 4A) but that were still induced by wounding in JA-insensitive coi1-1 plants (Table 1). Surprisingly, one of these was OPR1, which possibly participates in the synthesis of JA ( The use of the coi1-1 mutant yielded two broad categories of wound-inducible genes: COI1-dependent and COI1-independent genes (Table 1). It is important to note that a gene defined as COI1-dependent or -independent in this study might be controlled differently under other conditions, and we used these two categories only for the present study. We assume that most, if not all, COI1-dependent genes are jasmonate dependent and that their expression is altered by a direct or indirect effect of the loss of a functional COI1 gene. Additionally, the category of COI1-independent genes contains genes that were differentially expressed in wounded wild-type and coi1-1 plants. Some genes were more highly induced in wild-type plants (e.g., ACX1 and GST5), whereas others (e.g., ER5 and PGIP) were more highly induced in coi1-1 plants. These results merit further attention because they indicate that COI1 might play subtle roles as a positive or negative regulator of other signal pathways controlling wound-inducible gene expression.
Interestingly, the transcript levels of two genes (NPR1 and MPK3; Fig 5A) were induced in wounded coi1-1 plants after 90 min but not in wounded wild-type plants. MPK3 shows an early induction after wounding of wild-type plants, but its transcript level returns to the control value 60 min after wounding (Fig 2). These two genes have been implicated in the signaling pathway that leads to resistance to bacterial and fungal pathogens (
Our finding that many genes (21) are regulated in a COI1-independent manner (genes that are wound-regulated in both the wild-type and the coi1-1 plants) is in strong agreement with the literature, and several wound-inducible but jasmonate-independent genes are known (
Water Stress Is an Important Component in the Response to Mechanical Wounding
Exactly how water stress leads to changes in gene expression is not clear. In tomato, at least two wound-inducible genes are upregulated by water deficit, abscisic acid, and salinity (
Finally, for four genes (PME1, PR3AIV, OPR1, and PRODH), the signal or stimulus that controls their induction during wounding is not known. Possible candidates would be oxylipins (different from jasmonates), cell wallderived oligosaccharides ( In summary, our results lead to a more comprehensive view of gene expression in response to mechanical wounding. Several factors, including tissue damage and water loss, lead to a complex, dynamic pattern of transcript levels in which waves of gene expression involving groups of similarly behaving transcripts were observed. Underlying these patterns is the complex interplay of stimuli that control gene expression, in which one input (e.g., wounding) can override another (e.g., water stress), as demonstrated by the interesting behavior of PRODH, which was strongly upregulated by mechanical wounding and downregulated by water stress (Table 1).
Reduced Water StressInducible Gene Expression during P. rapae Feeding
As our results definitively show, many genes that were strongly induced by mechanical damage were less or not at all induced when a plant was attacked by P. rapae. The fact that the insect did not induce the expression of many wound-inducible genes is likely to be to the insect's advantage. Several genes that were not induced by insect feeding include PR genes (e.g., PR-2 and PAL) or genes involved in the synthesis of aromatic metabolites (e.g., CCR and COMT), which might reduce insect fitness. On the other hand, the defense gene HEL was reproducibly induced by P. rapae larvae but not by mechanical wounding. HEL is known to be induced by microbial pathogens by way of a JA-dependent pathway ( Use of cDNA microarrays containing many more genes might reveal a new class of insect-specific genes that might be useful in developing biotechnological tools for insect control. Although our array contained only 150 genes, it was already large enough to permit the detection of a gene (HEL) induced by feeding P. rapae larvae but not by mechanical wounding. Our results illustrate the advantages of using small boutique arrays. First, the quality of each clone on the array can be controlled and printing errors can be rapidly rectified. Second, assembly of boutique arrays is possible in small laboratories that currently lack the resources to print genome-scale arrays.
Concerning the signal pathways activated by feeding P. rapae, several COI1-dependent genes (e.g., LOX2, MT1, TSA, and JIP) as well as several COI1-independent genes (e.g., GST1, ERF4, RNS1, and PRODH) were induced. Thus, the insect did not appear to preferentially activate either jasmonate-dependent or -independent genes. It is remarkable that the feeding of P. rapae had little effect on genes such as XERO2, RNS1, ER5, TSA, and COMT (Table 1), all of which are water stress inducible. Perhaps P. rapae minimizes the effects of water stress on gene expression when feeding by reducing the crushing of tissue and by keeping to a minimum the cut edge of the lamina while removing the maximum tissue mass. In other words, it might not be a coincidence that cabbage butterfly larvae often leave circular or semicircular holes in host plant leaves in contrast to following a feeding strategy that might expose a greater length of ragged or crushed leaf edge to the air. Indeed, some specialist insects use elaborate vein-cutting strategies to cut the flow of defense chemicals to the feeding site (
Plant Materials and Growth Conditions
Plant Treatments
Quantitative Analysis of Jasmonate Family Members
cDNA Clones and Microarray Preparation
Microarray fabrication was performed according to published methods (
mRNA Isolation and Preparation of Fluorescent Probes Each mRNA sample (one control and one treated sample) was reverse-transcribed in the presence of Cy3-dCTP or Cy5-dCTP (Amersham Pharmacia Biotech, Dübendorf, Switzerland). Each reaction was performed in a 30-µL volume containing 2 µg of mRNA, 2 µg of oligo(dT) 21-mer, 500 µM each for dATP, dGTP, and dTTP, 200 µM dCTP, 100 µM Cy3-dCTP or Cy5-dCTP, 30 units of RNase inhibitor (Life Technologies, Basel, Switzerland), 10 µM DTT, and 400 units of SuperScriptII reverse transcriptase (Life Technologies) in SuperScript buffer (Life Technologies). After incubation at 42°C for 1 hr, the sample tubes containing Cy3 and Cy5 labeling were pooled and treated with 2.65 µL of 25 mM EDTA and 3.3 µL of 1 M NaOH for 10 min at 65°C to degrade the RNA. After the addition of 3.3 µL of 1 M HCl and 5 µL of 1 M Tris-HCL, pH 6.8, labeled single-stranded DNA was precipitated with 0.1 volume of 3 M sodium acetate and 2 volumes of ethanol, and the pellet was washed with 80% ethanol, dried under vacuum, and resuspended in 10 µL of hybridization solution containing 3 x SSC, 0.2% SDS, and 0.02% yeast tRNA (Life Technologies). Probes were purified by Millipore (Volketswil, Switzerland) Ultrafree-MC filters.
Hybridization Reaction and Microarray Analysis
Microarrays were scanned with a scanning laser microscope (ScanArray3000; GSI Lumonics, Watertown, MA). Separate images were acquired for each fluor at a resolution of 10 µm per pixel. To normalize the two channels with respect to signal intensity, we adjusted photomultiplier and laser power settings such that the signal ratio of the majority of control genes was as close to 1.0 as possible. The average fluorescence intensity for each fluor and for each gene was determined by using the ScanAlyze program (written by M. Eisen, Stanford University; available at http://rana.stanford.edu/software). Background fluorescence was calculated as the median fluorescence signal of nontarget pixels around each gene spot. Genes showing a signal value <1000 (which was typically twice the mean background value) in both Cy3 and Cy5 channels were not considered for the analyses. For all of the experiments, we defined induction or repression of a gene as a minimum twofold change in its transcript level. Gene-clustering analysis was performed as described previously (
RNA Gel Blot Analysis
We thank Stéphanie Stolz and Aurore Chételat for excellent technical assistance, Boris Künstner for maintaining plants and insects, and Pauline Bariola for comments on the manuscript. We are grateful to Shauna Somerville for introducing P.R. to the cDNA microarray technology and to Clarence A. Ryan and Robin Liechti for valuable discussion of preliminary results. We thank John G. Turner for coi1-1 seeds. This work was supported by the Leenaards Foundation, the Société Académique Vaudoise, the Fondation du 450ième Anniversaire, the Fonds Université de LausanneÉcole Polytechnique Fédérale de Lausanne, the Sandoz Foundation, the Fondation Herbette, and the Swiss National Science Foundation. Received December 23, 1999; accepted February 29, 2000.
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