JXB Advance Access originally published online on October 16, 2006
Journal of Experimental Botany 2006 57(14):3869-3881; doi:10.1093/jxb/erl171
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RESEARCH PAPER |
Expression profiling of Chondrus crispus (Rhodophyta) after exposure to methyl jasmonate
1Centre National de la Recherche Scientifique, Université Pierre et Marie Curie-Paris 6, Laboratoire International Associé-Dispersal and Adaptation in Marine Species, Unité Mixte de Recherche 7139, Station Biologique, BP 74, F-29682 Roscoff Cedex, France
2INSERM U533, Institut du Thorax, BP 53508, F-44035 Nantes Cedex 1, France
* To whom correspondence should be addressed. E-mail: collen{at}sb-roscoff.fr
Received 1 June 2006; Accepted 5 August 2006
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Abstract |
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Methyl jasmonate (MeJA) is a plant hormone important for the mediation of signals for developmental processes and defence reactions in higher plants. The effects of MeJA and the signalling pathways on other photosynthetic organism groups are largely unknown, even though MeJA may have very important roles. Therefore the effects of MeJA in a red alga were studied. A medium-scale expression profiling approach to identify genes regulated by MeJA in the red seaweed Chondrus crispus is described here. The expression profiles were studied 0, 2, 4, 6, 12, and 24 h after the addition of MeJA to the seawater surrounding the algae. The changes in the transcriptome were monitored using cDNA microarrays with 1920 different cDNA representing 1295 unique genes. The responses of selected genes were verified with real-time PCR and the correlation between the two methods was generally satisfying. The study showed that 6% of genes studied showed a response to the addition of MeJA and the most dynamic response was seen after 6 h. Genes that showed up-regulation included several glutathione S-transferases, heat shock protein 20, a xenobiotic reductase, and phycocyanin lyase. Down-regulated transcripts included glucose kinase, phosphoglucose isomerase, and a ribosomal protein. A comparison between different functional groups showed an up-regulation of stress-related genes and a down-regulation of genes involved in energy conversion and general metabolism. It is concluded that MeJA, or a related compound, has a physiological role as a stress hormone in red algae. This study represents to our knowledge the first analysis of gene expression using cDNA microarrays in a red macroalga.
Key words: cDNA microarrays, growth regulator, jasmonate, Rhodophyta, stress, transcriptome
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Introduction |
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TopAbstractIntroductionMaterials and methodsResultsDiscussionSupplementary dataReferences |
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Jasmonates are important signalling molecules in higher plants including primarily methyl jasmonate (MeJA) and jasmonic acid. Jasmonates are cellular regulators involved in, for example, germination, root growth, fertility, fruit ripening, and senescence. Other important roles for jasmonates are in biotic defence mechanisms, i.e. as a response to grazing-induced wounds, and in the response to abiotic stress, such as high light stress, ultraviolet light, and water deficit (Creelman and Mullet, 1997; Weber, 2002; Cheong and Choi, 2003). This group of hormones appears to be ubiquitous in the Viridiplantae (Cheong and Choi, 2003) and effects of MeJA have also been seen on Euglena gracilis Klebs and in red and brown macroalgae (Ueda et al., 1991; Bouarab et al., 2004; Gaquerel, 2005; Arnold et al., 2001), suggesting a widespread use of this signalling molecule in photosynthetic organisms.
Generally, little is known about the effects of higher plant hormones or growth regulators on other photosynthetic groups, such as red or brown macroalgae. However, it is known that MeJA has a potentially important function in the regulation of the biotic defence in the red macroalga Chondrus crispus (Stackh.) since MeJA activated the oxidative metabolism of C20 and C18 polyunsaturated fatty acids and generated hydroperoxides and cyclopentenones, such as prostaglandins and oxygenated fatty acids (Bouarab et al., 2004; Gaquerel, 2005). Addition of MeJA to C. crispus also induced increased activities of enzymes potentially involved in defence reactions, such as shikimate dehydrogenase, phenylalanine ammonium lyase, and an enzyme that hydroxylates polyunsaturated fatty acids (Bouarab et al., 2004; Gaquerel, 2005). The transcription of defence-related genes was also augmented after MeJA addition, i.e. glutathione S-transferase (GST) and NADPH oxidase, a possible key protein in defence mechanisms in red algae (Gaquerel, 2005; Hervé et al., 2006). The up-regulation of defence-related proteins by MeJA is followed by an induced resistance in C. crispus to the pathogenic green algal endophyte Acrochaete operculata Correa et Nielsen (Bouarab et al., 2004). This potentially important function of MeJA in C. crispus led us to explore the effects of MeJA further using cDNA microarrays, with the goal of identifying transcripts that are induced or suppressed by MeJA as well as understanding the dynamics of gene expression after hormone treatment in red algae.
Chondrus crispus is an inter- and subtidal red seaweed which commonly occurs on rocky shores in the northern to middle Atlantic and in the northern Pacific Ocean. The cell wall contains the commercially important polysaccharide carrageenan and a limited commercial harvest exists. This red alga has emerged as a model for host–endophyte interactions, defence reactions, and intracellular signalling in red algae through its interaction with the endophytic alga Acrochaete operculata (Bouarab et al., 1999, 2001, 2004; Hervé et al., 2006; Potin et al., 2002; Weinberger et al., 2003). A limited genomic knowledge also exists through an EST project describing 4000 transcripts from thallus and protoplasts (Collén et al., 2006) and the sequence of the mitochondrial genome (Leblanc et al., 1995). The red algae are one of the three groups forming the group Plantae, together with the glaucophytes and the green lineage, which originated from the primary endosymbiosis event and is generally considered to be the sister group to Viridiplantae.
Microarrays have been used in experiments with higher plants since 1995 (Schena et al., 1995) and allows for simultaneous study of the expression of numerous different transcripts, giving a more or less global view of transcription. The majority of microarray experiments on photosynthetic organisms have been performed on Arabidopsis thaliana; however, this technology is increasingly used for studies on other photosynthetic organisms, for example, Pinus contorta Dougl. ex Loud. (Brinker et al., 2004), Chlamydomonas reinhardtii Dang (Zhang et al., 2004), a unicellular red alga, Cyanidioschyzon merolae De Luca, Taddei, Varano (Minoda et al., 2005), and the dinoflagellate Pyrocystis lunula (Schütt) Schütt (Okamoto and Hastings, 2003). cDNA microarrays have to our knowledge not previously been used in experiments with macroalgae.
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Materials and methods |
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Plant material and experimental set-up
Gametophytes of Chondrus crispus (Stackh.) (Gigartinales, Rhodophyta) were collected near Roscoff, Brittany, France in November 2004. The life stage was determined through the presence of blue iridescence (Fournet et al., 1993). Thalli with a minimum of epi- and endophytes, no visible traces of herbivore attack, nor any sexual structures, were used in the experiments. In order to reduce short-term variability between individual thalli, the algae were cultivated in running seawater with irradiance of 100 µmol photons m–2 s–1 in a light regime of equal length of day and night for 2 weeks before experiments.
Entire thalli of C. crispus, 6 g FW in each experiment, three replicates for each treatment, were incubated overnight in 2.0 l of natural seawater at 14 °C. Experiments were started at 10.00 h; 2 h after lights (50 µmol photons m–2 s–1) were turned on. During the experiment, the dark–light cycle from the cultivation was retained. Algae were sampled and immediately afterwards 90 µM MeJA (20 mg l–1) were added to the seawater surrounding the algae. Since little is known about the dynamics of the MeJA response, samples (1 g FW) were taken after 2, 4, 6, 12, and 24 h, immediately frozen in liquid nitrogen, and stored at –80 °C until extraction of RNA. Each biological sample represented one to three individual thalli.
Description of arrays and spotting
The basis for the arrays is two previous EST projects done on C. crispus thalli and protoplasts (Collén et al., 2006). The thallus cDNA had to a large extent ‘house-keeping’ genes, while the protoplast library had an increased repertoire and expression of stress genes, since it was made from severely stressed cells; thus stress genes are proportionally over-represented on the arrays. Clones were selected in order to reduce the redundancy but still keep the diversity; at least one representative of all contigs and most singletons with a putatively known function were used, as well as many singletons with unknown function. Selected clones were picked from frozen stock-cultures and regrown overnight in 2x LB with appropriate antibiotic. 20 µl of the culture was mixed with 80 µl water and denatured at 95 °C for 8 min. The solution was used as template for the PCR reaction. The cDNA used for arrays were produced using PCR and universal probes (T3 and T7). The PCR products were purified using PCR 96 Cleanup kit (Millipore, Bedford, MA, USA). The quality, i.e. the presence of only one distinct band, and quantity were controlled with electrophoresis on agarose gels. Approximately 86% of the PCR products had a single band with an average size of 1.2±0.5 kb; only PCR products with one band were used in the analysis.
The arrays were spotted with a SDDC2 spotter (Virtek, Ontario, Canada) on amino-silane coated slides (GAPII, Corning, NY, USA). In all, 1920 different cDNA representing putatively 1295 different unique genes and controls were spotted in triplicate. All deposited cDNAs are described in Supplementary Table 1 at JXB online.
Array pretreatment, RNA extraction, and hybridization
The pretreatment of the arrays included hydration of slides over a water bath at 60 °C for 5–10 s until a film of moisture was formed, followed by drying over a hot plate at 70 °C for 2–5 s. This was followed by UV cross-linking (60 mJ) and incubation in a blocking solution (3.3 g succinic anhydride in 180 ml 1-methyl-2-pyrrolidone with 14 ml borate 1 M, pH 8) for 15 min with slow agitation. After this the arrays were dipped five times in near boiling water and incubated for 2 min, followed by dipping the slides five times in 95% ethanol and centrifugation for 3 min at 40 g. The arrays were prehybridized in 3.5x SSC, 0.3% SDS, and 1% BSA for 1 h at 42 °C. Thereafter they were rinsed five times in separate water baths at room temperature and dried by centrifugation at 40 g for 3 min.
RNA was extracted according to Apt et al. (1995); quantity and quality was verified using an Agilent 2100 Bioanalyser (Palo Alto, CA, USA). Total RNA (20 µg) was used for making a probe using the CyScribe Post-labelling kit (Amersham, Munzinger, Germany). Experimental RNA was labelled with Cy5 and control RNA taken at the same time was labelled with Cy3. The labelled and purified probes were mixed and resuspended in a buffer containing 5x Denhardt, 3.5x SSC, 0.3% SDS, 0.5 µg µl–1 yeast tRNA, 0.5 µg µl–1 polyA RNA, and 50% formamide and denatured for 2 min at 99 °C, followed by 30 min at 37 °C. The product was pipetted onto the slide and covered with a cover slip before sealing into a hybridization chamber (ArrayItTM, TeleChem International, Sunnyvale, CA). The sealed chamber was incubated for 16 h at 42 °C. The arrays were washed with, subsequently, 2x SSC with 0.1% SDS, 1x SSC and twice in 0.2x SSC at room temperature for 5 min each. The slides were dried by centrifugation (40 g) for 3 min. The arrays were immediately scanned on a GenePix 4000B (Axon, Union City, USA) scanner at 10 µm resolution using the GenePix Pro 5.1 software (Axon) in which grids were automatically placed and then manually inspected and adjusted to ensure optimal spot recognition and removal of flawed spots. Acuity 3.1 (Molecular Devices Corporation, Sunnyvale, CA, USA) was used for statistical and cluster analyses of the data.
Resequencing of cDNA with unknown function
After the result of the hybridizations were known, the bacterial clones with sequences without similarity to known sequences, hypothetical proteins, and sequences with similarity to known sequences with unknown function, conserved hypothetical proteins, that showed significant change in expression were resequenced in both directions using both T3 and T7 primers. Sequencing was performed on an ABI prism 3100 sequencer (Applied Biosystems, Foster City, CA, USA) as described in Roeder et al. (2005). The new sequences were compared with the previously obtained sequences and when additional sequence data was obtained aligned, if possible, against the old sequence and blasted against GenBank.
Real-time PCR
To validate the results obtained by the microarray analyses, real-time PCR was performed on a selection of representative genes with varying expression profiles with some representing gene families (e.g. HSP-20) and some with putatively no related genes (e.g. cochlin). To eliminate residual genomic DNA, total RNA samples were treated by an RNase-free DNase I (Stratagene). Total RNA (2.1 µg) was reverse transcribed using the Superscript II RT kit (Invitrogen). Primer Express 1.0 (Applied Biosystems) was used to design the primers for the following genes: protein disulphide isomerase, ribosomal protein L11, heat shock protein 20, drug resistance, GST, and cochlin; actin was used as a control: for sequences see Supplementary Table 2 at JXB online. Real-time PCR was performed in a GeneAmp 5700 sequence detector system (Applied Biosystems) using the SYBR Green PCR master kit (Applied Biosystems). PCR cycles were performed according to the following temperature regimen: 95 °C for 15 s, 60 °C for 60 s. To generate a standard curve, genomic DNA of C. crispus (haploid genome size 150 Mbp) was used as a reference matrix. Aliquots of 5-fold serial dilution of this genomic DNA were used as a standard during each real-time PCR set-up. The quantity in unknown samples was calculated by the GeneAmp 5700 system according to the generated standard curve. Primers specificity and annealing efficiency were checked by determining the dissociation curve at the end of the experiment and the rate of amplification at each cycle for each couple. To standardize the data, the ratio of the absolute transcript level of each gene to the absolute transcript level of actin was calculated.
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Data analysis
The experiments with the addition of MeJA to the seawater surrounding Chondrus crispus resulted in 18 exploitable arrays; including three biological replicates from each time point: 0, 2, 4, 6, 12, and 24 h. Changes in transcription were studied in pair-wise hybridizations, with cDNA from controls and methyl jasmonate-treated thalli hybridized on the same array to eliminate changes that were due to changes in the environment, primarily the light–dark cycle, and potential circadian rhythms. Preliminary experiments with dye swaps showed no major bias of the arrays with less than 1% of genes showing significant differences in expression (not shown). Since this is the first study on C. crispus using cDNA microarrays the first priority was to understand the variation in the data caused both by experimental factors and by the heterogenic nature of the experimental material since wild harvested algae were used. The rationale for using wild collected material was to the make the results more relevant to future experiments studying gene expression under natural conditions. In order to decide the threshold for significant changes, the number of genes that changed after different time periods were compared with different criteria. The number of cDNAs that changed using the criteria: (|2lg ratio|–se) > Y (with Y being 0.5, 0.75, and 1; se=standard error) are shown in Fig. 1. A Y of 1, i.e. a 2-fold change after the subtraction of the standard error, resulted in no differentially expressed genes at the start of the experiment and up to 42 (3.2%) after 6 h. The absence of genes with changing gene expression at the start of the experiment indicates that this is a conservative threshold that should minimize false positives. Reducing Y to 0.5 or 0.75 resulted in a drastic increase of genes considered differentially expressed including 48 and 115 at the start of the experiment (Fig. 1). Thus, a 2-fold decrease or increase after the subtraction of the standard error was considered as a significant change in expression in this experiment. Using this criterion the number of genes with changing expression increased during the first 6 h, while a decrease could be seen after 12 h and 24 h. Thus the most dynamic response was seen after 6 h. A global representation of the ratios obtained pooling all data, except at the start of the experiment (0 h), can be seen in Fig. 1. It can be seen that the great majority of genes did not drastically change their expression during the experiment.
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In some cases, different cDNAs from the same gene were spotted on the array and these genes were used as one method to study variability of the arrays and the methods used. In Fig. 2 the response for two actin fragments are shown. The two different cDNAs gave similar results in the analyses. The actin, often used as a control in expression analysis experiments, showed relatively small changes after the addition of methyl jasmonate, with the exception of a non-significant reduction after 12 h. The actin gene expression profile typically reflects the kind of variation generally found for many of the genes studied.
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After the result of the hybridizations were known, the clones with unclear function, that is, hypothetical proteins and conserved hypothetical proteins with significant changes in expression, were resequenced in order to increase the information available for analysis. The new sequences were compared with the previous sequences and when more sequence data was obtained blasted against GenBank. This allowed us to suggest a tentative function to 14 cDNA of 42 with previously unknown function.
Correlation with real-time PCR experiments
The expression of six genes studied on the microarrays was compared with results achieved with real-time PCR (Fig. 3). The cDNA selected represented genes potentially over-expressed, with reduced expression or with a mixed pattern; priority was also given to genes of special interest. The correlation between real-time PCR data and array data was generally good or fair. For the genes coding for drug resistance, GST and cochlin expression patterns are identical and only small differences could be seen between the two methods. Similar effects on GST as seen with the microarray experiment here were also seen by Gaquerel (2005) using northern blots and a similar research set-up, with no effect after 1 h but an increased expression after 2 h that remained high for at least 48 h. Protein disulphide isomerase showed a reasonable correlation between real-time PCR and array data. For ribosomal protein L11 and heat shock protein 20 (HSP-20) the correlations were poor, possibly since both transcripts represent gene families, for example, six different HSP-20s are known from C. crispus after a limited EST project (Collén et al., 2006), and differences in stringency between the two methods may be the cause of the non-correlating data. For genes with good correlation between real-time PCR and the microarray data there was a tendency that the real-time PCR experiment gave more pronounced differences between experiment and control, suggesting that the differences in expression seen in the microarray experiments might be slightly underestimated.
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Differentially expressed genes
The genes that satisfied the criteria for differential expression, i.e. a 2-fold change after the subtraction of the standard error, are presented in Table 1. The analysis showed that 6% of genes studied showed a significant response to the addition of MeJA at some time point. It can also be noted that for most genes (99%) no dramatic increases or decreases were seen with normally up to 4-fold changes; however, 4–11-fold changes in expression were detected for 1% of the genes. Genes with a putative function were divided into three groups: stress, metabolism, and ‘others’. Potential stress genes that were up-regulated included GSTs, HSP-20, protein disulphide isomerase, a peroxidase, phycocyanin lyase, xenobiotic reductase, and a drug resistance protein. Other up-regulated genes in the metabolism and other groups included, aspartate aminotransferase, epimerase, metallo hydrolase, diphthine synthase, oxidoreductase, enolase, cdc protein 48, histone H4, pirin, pyrrolidone peptidase, and ribosomal protein L7. Down-regulated genes included transcripts with similarities to glucose kinase, phosphoglucose isomerase, nodulin, cochlin, a metallo protease, a phosphatidylinositol transfer protein, sugar hydrolysis, and a ribosomal protein. In addition, several genes of unknown function were either up-regulated (17) or down-regulated (13) and one case showed both up- and down-regulation depending on the time point.
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Cluster analysis and functional groups
Since only a limited number of transcripts were significantly over-expressed after MeJA addition and general trends were difficult to ascertain, clustering was performed to emphasize tendencies in the data set. K-means cluster analysis into three groups was performed using Acuity: note that even small and non-significant changes in expression will be considered as changes and all cDNAs are allocated to one group. Group one generally showed reduced expression with time (Fig. 4) and a clear drop of expression level at 6 h. The transcripts of group two showed on average an increase of expression at 2 h after the addition of MeJA followed by a stable expression level. Group three includes transcripts that were up-regulated after 6 h, but otherwise showed small changes.
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Functional annotation of these three groups (Table 2) showed that for genes up-regulated after the addition of MeJA (group 2) there was an over-representation of cell rescue, defence, cell death, and ageing (stress) genes and a comparatively lower percentage of metabolic genes compared with the other groups; this tendency is even stronger if metabolic and energy transcripts are considered together. For genes up-regulated after 6 h (group 3) there were higher percentages of metabolism transcripts and protein destination (a group that includes many proteases) and this was followed by a decrease in stress genes. Group 1, containing genes that are down-regulated after the addition of MeJA, generally showed an intermediate behaviour compared with groups two and three. The entire array data in Table 2 does not represent the sum of the three groups since the percentage in the three groups is based on spots that satisfied the quality criteria, while the entire array data represent the functional annotation of the spotted array, irrespective if any useful data was extracted from the data points.
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To understand the dynamics of functional expression of genes not individually showing a significant change in expression further, the average expression ratio of functional groups were studied (Table 3). This showed that the addition of MeJA caused an up-regulation of stress genes after 2 h that is sustained for at least 24 h. By contrast, decreases in expression were seen after 4 h on the expression of metabolism and energy-related genes, as well as the groups protein destination and hypothetical proteins.
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Responses of selected genes
The expression patterns of a few genes that did not meet the criteria for differential expression, although they were expected to be potentially induced by MeJA, were examined more in detail. In the signal transduction pathways for jasmonate response in higher plants several genes are suggested to play important roles (Turner et al., 2002), for two of these, cullin and ubiquitin ligase, potential C. crispus counterparts were present on the array. However, the genes did not show a clear pattern indicating their function as important in the signalling (data not shown). However, this does not exclude their importance in C. crispus; since the expression could be rapid, i.e. before the 2 h time point and thus not identified in this study, or small differences in gene expression represents physiologically relevant changes.
Some genes showed a clear pattern of increased or decreased expression after the addition of MeJA, even though the threshold of a 2-fold change was not attained at any specific time point. Four examples of stress genes with this pattern are shown in Fig. 5; NADPH oxidase, a peroxiredoxin-like transcript and a potential disease resistance protein. The NADPH oxidase from C. crispus is described in detail in Hervé et al. (2006); the gene is potentially important in defence reactions producing an oxidative burst and was, similarly to this report, found to increase after the addition of MeJA. The function of peroxiredoxin is to reduce the concentration of active oxygen and potentially to regulate hydrogen peroxide-mediated signalling important for the regulation of stress responses (Wood et al., 2003). Haloalkane dehalogenase has a potential role in halogen metabolism, since halogens are thought to be important in red algal defence mechanisms (Potin et al., 2002), and the disease resistance gene, with similarities to a TIR (Toll/Interleukin-1 receptor) disease resistance gene in Medicago truncatula, has a possible involvement in biotic defence. Since the gene for peroxiredoxin showed signs of over-expression three other antioxidative genes, catalase, ascorbate peroxidase Mn-SOD, and methionine sulphoxide reductase, were analysed in a more pointed manner (Fig. 6) and they indicated an up-regulation, at least initially, of reactive oxygen scavenging enzymes.
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Microarray analysis has to our knowledge not previously been used in macroalgae. This is thus the first report using this technology for physiological studies in a red seaweed. It also exemplifies the potential of cDNA microarray experiments on organisms with limited genomic background knowledge.
The Chondrus arrays are valid
The results presented here validate the Chondrus crispus cDNA microarrays. In most cases there was a good correlation between the microarray results and real-time PCR data. In this study, using non-optimized cDNA from an organism without a sequenced genome, one-third of the results differed between real-time PCR and microarray data (Fig. 3). This can be compared with optimized commercial human oligonucleotide microarrays where a poor correlation was seen between the two methods for 13–16% of transcripts (Dallas et al., 2005). Thus, the discrepancy between the two methods found here is not surprisingly large and differences are probably due to the different specificity of real-time PCR and microarrays and miss-spotting of the arrays. Another validation of the arrays was that, when several cDNA from the same gene were spotted, similar results were normally found (Figs 2, 6). The results obtained here were also generally possible to explain in a physiological relevant context, for example, the findings that 6% of genes were regulated by MeJA and that, after the addition of a known stress hormone, stress genes were up-regulated. The microarray results are therefore considered to be valid and that the discrepancies found are within the precision of the method. However, for some data points relatively large differences were seen between the biological triplicates, this is probably caused by the use of wild harvested material and the use of a limited number of individuals (1–3) in each RNA extraction. Thus, the variations found between the biological triplicates are likely to represent biological differences between individuals and therefore represents additional information.
The approach of resequencing of cDNA with unknown or unclear function resulted in the clarification of the identity of one-third of these sequences with a considerable added value to the study. This shows that cDNA microarrays can be a part of a strategy to identify genes for further sequencing studies in an organism with limited genetic knowledge (see also below).
The response to MeJA is dynamic
It is considered important to address the dynamics of the response to MeJA in a previously not-well-studied organism, therefore the experimental set-up involved six different time points in order to identify genes with transient expression as well as genes with a stable differential change in gene expression. This approach was vindicated through the diversity of genes seen with a significant change in expression at different time points. This also indicates that the response to MeJA is dynamic with different pathways influenced after different times. For example, these data clearly show that, 6 h after the addition of MeJA, the number of genes that are significantly up- or down-regulated are at a maximum, suggesting that the MeJA-triggered signal has a major effect on gene expression at that time. Further studies on the effects of MeJA on red algae should consider this as an important time point.
MeJA is a stress hormone
The experiments presented here clearly show changes in gene expression in C. crispus after exposure to MeJA. The predominant pattern is an increased expression of stress genes with a simultaneous down-regulation of genes involved in energy conversion and general metabolism (Table 3). For example, all stress genes that showed differential expression, GST, HSP-20, haloalkane dehalogenase, and phycocyanin lyase, showed an increase in expression, except the DNA mismatch repair protein. Our interpretation of the results is that MeJA, or a related compound, has a role as a stress hormone in this red alga. This hypothesis is supported by the findings of Gaquerel (2005) and Bouarab et al. (2004) which showed that MeJA triggers the oxidation of polyunsaturated fatty acids, induced the activities of the two defence-related enzymes, shikimate dehydrogenase and phenylalanine ammonia-lyase, and that addition of MeJA confers resistance of C. crispus to a green algal endophyte, Acrochaete operculata. Interestingly, it was found here that the gene for DAHP synthase, which is the first enzyme in the shikimate pathways, was over-expressed after 6 h (no more transcripts involved in the shikimate pathway have been identified).
To our knowledge no conclusive evidence exists that MeJA is an endogenous compound in C. crispus, however, MeJA has been detected in cell-free extracts alga after the addition of linolenic acid (Bouarab et al., 2004) and MeJA is taken up by C. crispus and causes a dose-dependent production of oxylipins (Gaquerel, 2005). The presence of MeJA has, however, been detected in another florideophyte red alga, Gelidium latifolium (Greville) Bornet et Thuret. (Krupina and Dathe, 1991). In addition, the enzymes involved in the biosynthesis of jasmonate from linolenic acid have been identified in two other florideophyte red algae, Lithothamnion coralloides Foslie and Gracilariopsis sp. (Hamberg and Gardner, 1992; Hamberg and Gerwick, 1993). Altogether, this indicates that MeJA, or a related compound, has a physiological role in C. crispus and other advanced red algae and one of the functions is as a stress hormone.
In higher plants jasmonates have additional roles in development, such as involvement in germination, root growth, and fruit ripening (Creelman and Mullet, 1997). The result from this study does not allow for the confirmation of similar roles of MeJA in red algae.
The responses are not due to toxicity
It is not clear what the physiological concentrations of MeJA in C. crispus are (Gaquerel, 2005), but there are indications that they are rather low, thus much lower than the present experiment. It is also known that high concentrations of MeJA (>100 mg l–1) are toxic to C. crispus (Bouarab et al., 2004). It is possible that some of the potentially induced proteins also serve to detoxify MeJA. Examples of genes that may have a role in detoxification and are potentially up-regulated include GST, xenobiotic reductase and ‘drug resistance’. However, the addition of MeJA in this work was five times lower than toxic concentrations and three cDNA with similarities to the detoxifying enzymes cytochrome P-450 are present on the array and none of these showed a significant response (not shown). The up-regulation of GST is interesting since GSTs do not just have a detoxifying role; some mammalian GST show prostaglandin synthase activity (Jowsey et al., 2001) and thus GST could be involved in the prostaglandin synthesis in red algae (Gaquerel, 2005). Up-regulation of detoxifying genes have also been found after the addition of jasmonates in A. thaliana (von Rad et al., 2005). We therefore believe that the majority of effects found in this experiment reflect effects of a growth regulator rather than toxic effects.
Active oxygen is putatively involved in MeJA signalling
The expression data from the antioxidative genes, that is, the potential increase in peroxiredoxin, catalase, ascorbate peroxidase, Mn-SOD, and methionine sulphoxide reductase, at least at some time points, suggests an involvement of active oxygen in the responses to MeJA. In addition, an increase in NADPH oxidase transcripts was found and this enzyme could be related to the production of superoxide and hydrogen peroxide. This suggests a general induction of reactive oxygen metabolism. Similarly, in higher plants, MeJA will induce the accumulation of H2O2 in leaves which in turn act as a second messenger for defence responses (Orozco-Cardenas and Ryan, 1999; Orozco-Cardenas et al., 2001). Hydrogen peroxide and reactive oxygen metabolism have also been shown to be involved in both abiotic and biotic stress reactions in C. crispus (Collén and Davison, 1999; Bouarab et al., 2004) so these findings support the role of MeJA as a stress hormone. It is also known that MeJA induces the generation of oxidized polyunsaturated fatty acids in C. crispus, even though an oxidative burst is not seen (Bouarab et al., 2004). The results presented here thus support the idea that active oxygen are part of the signalling of the MeJA response in C. crispus and suggests that signalling might be modulated by increased expression of antioxidative genes.
Comparison with higher plants
Genes up-regulated by MeJA in higher plants include those involved in jasmonate biosynthesis, secondary metabolism, formation of cell wall and stress and defence proteins (Cheong and Choi, 2003). In this project an up-regulation of potential stress genes were found, for example, GST, HSP, and oxidoreductase, genes that were also over-expressed in A. thaliana after the addition of MeJA (Taki et al., 2005). Jasmonic acid has also been shown to increase the transcripts of, for example, catalase, Mn-SOD, epimerase, and GST in A. thaliana similar to the findings here (von Rad et al., 2005). Unfortunately, no cDNA were spotted on the array that unequivocally is involved in the formation of cell wall or jasmonate biosynthesis and secondary metabolism genes are poorly represented, however DAHP synthase, the first step in the shikimate acid pathway, is present and was up-regulated after 6 h. Genes coding for cell wall, jasmonate biosynthesis, and secondary metabolism are likely to be present on the arrays, but because of the limited knowledge of red algal genes they have not been identified. Our objective is to use this experiment, together with other microarray experiments in progress on abiotic stress responses, to elucidate potential functions of some of the unknown genes, especially genes involved in cell wall synthesis and stress. Results from the literature on down-regulated genes include photosynthesis-related genes, unfortunately such genes are not well represented on the arrays used here because of the low representation in the cDNA libraries that were the base (Collén et al., 2006); however, the gene for phycocyanin lyase was up-regulated (phycocyanin is a part of the photosynthetic antenna of red algae). In addition, the down-regulation of genes coding for energy metabolism indicates a similar behaviour in red algae as in higher plants: the organism centres its metabolism toward defence rather than growth. Thus, in general, responses for this growth regulator of higher plants seem to be similar to higher plants, even though the metabolism of oxylipins, including jasmonates, in C. crispus has unusual features, representing an intermediate between metazoan and higher plant metabolism (Bouarab et al., 2004).
Putative identification of unknown transcripts
Among the genes with unknown function there are several that showed very dynamic expression after MeJA addition and would thus be interesting subjects for further, more in-depth, studies in order to find key unknown genes in MeJA responses.
To use the results of this study putatively to identify differentially expressed cDNAs with unknown function, the results were clustered (Pearson's centred) and the cDNAs with known function that clustered with significantly expressed unknowns were compared with the BLAST results. The expression profiles of the cDNAs were also compared with the average expression profiles from Table 3. In some cases this allowed a function to be suggested for the genes, and an example can be seen in Fig. 7. CO651728 [GenBank] clustered with a zinc finger protein (CO650184 [GenBank] ) and had a best BLASTX hit against a zinc finger protein (e=8.2), as well as having a profile similar to the average transcription expression; it could therefore be suggested that this gene is involved in transcription and is a possible zinc finger protein, alternatively it is regulated by the zinc finger protein. Another example is CO650706 [GenBank] where the analysis suggests an involvement in stress responses and, possibly, in detoxification. This type of analysis can thus be used to guide further studies of transcripts of unknown function and increased amounts of microarray data for C. crispus will augment the accuracy of the predictions.
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Supplementary data |
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TopAbstractIntroductionMaterials and methodsResultsDiscussionSupplementary dataReferences |
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Supplementary data can be found at JXB online.
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Acknowledgements |
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We are grateful to Erwan Corre for help with the bioinformatic treatment. The research was supported by Ouest Génopole®, the Genomer priority program ‘4ème contrat de plan Etat/Région Bretagne’, and the European Union FP6 network of excellence project Marine Genomics Europe (GOCE-CT-2004-505403).
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Abbreviations |
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MeJA, methyl jasmonate; GST, glutathione S-transferase; HSP-20, heat shock protein 20.
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