Smoke-derived compounds provide a strong chemical signal to seeds in the soil seed bank, allowing them to take advantage of the germination niche created by the occurrence of fire. The germination stimulatory activity of smoke can largely be attributed to karrikinolide (KAR1), while a related compound, trimethylbutenolide (TMB), has been shown to have an inhibitory effect on germination. The aim of this study was to characterize the interaction of these potent fire-generated compounds.
Dose–response analysis, leaching tests and a detailed transcriptome study were performed using highly KAR1-sensitive lettuce (Lactuca sativa cv ‘Grand Rapids’) achenes.
Dose–response analysis demonstrated that the compounds are not competitors and TMB modulates germination in a concentration-dependent manner. The transcriptome analysis revealed a contrasting expression pattern induced by the compounds. KAR1 suppressed, while TMB up-regulated ABA, seed maturation and dormancy-related transcripts. The effect of TMB was reversed by leaching the compound, while the KAR1 effect was only reversible by leaching within the first 2 h of KAR1 treatment.
Our findings suggest that the compounds may act in concert for germination-related signaling. After the occurrence of fire, sufficient rainfall would contribute to post-germination seedling recruitment by reducing the concentration of the inhibitory compound.
Plants interact with their surroundings by ‘sensing’ environmental conditions and signals and responding to these accordingly. Some environmental cues play a permissive role, whereas others may have an inhibitory role. Such cues may also act together to fine-tune the plants’ response to their environment and, as in the case of seed germination, can provide a distinct signal for stimulating germination at the most suitable time. Of particular interest are chemical germination cues that can be found in smoke released by burning vegetation. These compounds function as important environmental signals promoting or inhibiting the germination of many plant species following a fire (Dixon et al., 2009). The phylogenetic spread of species responding to smoke cues is wide and includes species from non-fire-prone habitats, suggesting that this trait was probably an early development in the evolution of angiosperms (Bradshaw et al., 2011). For example, Arabidopsis and major crop and vegetable plants, including maize (Zea mays), wheat (Triticum aestivum), tomato (Lycopersicum esculentum) and lettuce (Lactuca sativa), all show altered germination in the presence of smoke-derived compounds (Light et al., 2009). The germination stimulatory activity can largely be attributed to a highly active butenolide, 3-methyl-2H-furo[2,3-c]pyran-2-one, referred to as karrikinolide (KAR1; Flematti et al., 2004; Van Staden et al., 2004; Dixon et al., 2009), and at least six analogs of karrikinolide are known (KAR1–KAR6; Flematti et al., 2009).
There is currently incomplete information on the molecular action of smoke- and KAR1-stimulated germination and improved seedling vigor, although some studies on the molecular and physiological aspects of KAR1 action have recently been published (for a review, see Nelson et al., 2012). It was reported that treatment of maize kernels with smoke-water yielded seedlings with higher vigor and resulted in the induction of stress-related changes in the transcriptome of young seedlings (Soós et al., 2009b). Thus, the ‘hardening’ effect of smoke appears to be similar to that caused by abscisic acid (ABA). Further transcriptome analyses revealed a predominance of stress- and light-regulated transcripts among karrikin-responsive genes (Nelson et al., 2010; Soós et al., 2010), and it was also shown that, in Arabidopsis, KAR1 signaling involves the F-box protein MAX2 (Nelson et al., 2011) and an α/β fold hydrolase (Waters et al., 2012).
Smoke-water tends to have a ‘dual regulatory’ effect on germination, as high concentrations of smoke-water inhibit germination, whereas lower concentrations have a promotory effect (Light et al., 2002). Another butenolide compound, 3,4,5-trimethylfuran-2(5H)-one (trimethylbutenolide (TMB)), supposedly contributes to the inhibitory effects of smoke-water, and significantly reduced the stimulatory effect of KAR1 when Grand Rapids lettuce achenes were treated simultaneously with both KAR1 and TMB (Light et al., 2010). Thus, the large suite of germination active compounds present in smoke might act in concert; a previous microarray study on smoke- and KAR1-treated germinating maize kernels revealed substantial differences in smoke- and KAR1-induced gene expression (Soós et al., 2010), indicating the interaction of other compounds in smoke which together form the physiological response to smoke treatment. This is to be expected considering the vast number of potentially active compounds found in smoke and smoke-water (Maga, 1988). The common structural feature of KAR1 and TMB (Fig. 1a) might contribute to the inhibitory effect of TMB on Grand Rapids lettuce achene germination, and led to the speculation that TMB may somehow block the action of the promoter KAR1, or may interact with a proposed effector related to the action of KAR1 (Light et al., 2010). The presence of multiple active compounds in smoke indicates that the use of smoke-water to study the effect of smoke on molecular events during germination should be avoided, and a simplified model system should rather be used in which the interaction between a promotory and an inhibitory cue can be evaluated. In the search for a model plant, we concluded that Lactuca sativa cv ‘Grand Rapids’ is suitable for KAR1 research as it exhibits rapid germination, the germinated achenes can be easily distinguished from nongerminated ones, and KAR1 treatment has a characteristic germination response in that it can replace the light requirement for germination in this photoblastic cultivar (Van Staden et al., 2004). The hypothetical antagonistic relationship between KAR1 and TMB suggests the importance of TMB as a regulator of the activity of smoke-derived stimulants. In this present study, the hypothesized mechanism of the KAR1–TMB interaction was investigated with the aim of elucidating the molecular background and revealing the ecological significance of the phenomenon.
Materials and Methods
Synthesis of KAR1 and TMB
KAR1 was synthesized as described by Flematti et al. (2005). The synthesis of TMB was accomplished in two steps, following the published procedure of Surmont et al. (2010). Both compounds were characterized by 1H and 13C NMR, and recorded spectra (Bruker Avance I-400, Bruker, Rheinstetten, Germany) are in agreement with published data (Flematti et al., 2005; Surmont et al., 2010). The purity of the KAR1 and TMB batches was checked by GC-MS (Agilent 7890A, Agilent Technologies, Santa Clara, CA, USA) coupled with a 5975C quadrupole mass-selective EI detector (70 eV) (Agilent Technologies, Santa Clara, CA, USA). The purity of KAR1 and TMB was 100% and 99.8%, respectively. The melting point of KAR1 was determined using a Kofler hot-stage apparatus and is uncorrected. The obtained value of 117–119°C is in agreement with published data (117–118°C; Flematti et al., 2005).
Plant material, germination tests and growth conditions
Lactuca sativa L. cv ‘Grand Rapids’ (Stokes, USA) achenes were stored at 4°C until use. Germination tests consisted of three independent experiments with three biological replicates (50 achenes). Achenes were placed in 90-mm Petri dishes on filter paper moistened with 3 ml of water (control), KAR1 (0.1 μM), TMB (10 μM) or the corresponding combination of compounds (0.1 μM KAR1/1 μM TMB and 0.1 μM KAR1/10 μM TMB). Petri dishes were sealed, wrapped in two layers of aluminum foil and incubated at 24°C. At each time-point, germination was evaluated under green safe-light, and data were analyzed with the Germinator package (Joosen et al., 2010).
For Schild regression analysis, achenes were germinated in a solution containing 0, 1, 2, 3, 5, 6, 7 and 10 μM TMB and 10−6, 10−4, 0.001, 0.01, 0.1, 1, 10 and 100 μM KAR1, in a pairwise manner. The Schild regression is useful for studying the effects of agonists and antagonists on the cellular response caused by binding to an effector molecule. It is based on the assumption that, when the same magnitude response is produced by an agonist in the presence and absence of an antagonist, then:
([A′]/[A], the agonist dose ratio for each concentration (the dose of agonist (A′) to produce a specific effect in the presence of the antagonist [B] to the dose required in the absence of the antagonist (A)); KB, the dissociation constant of the antagonist.) If ([A’]/[A]) = 2, then log[B] = logKB. The curves were fitted according to the four-parameter Hill function using the Marquardt–Levenberg algorithm. The Schild plot was constructed by plotting log([A′]/[A]) – 1) against −log[B]. If the regression of log([A′]/[A]) − 1) on −log[B] is linear with a slope of −1 then the compounds are competing for the same recognition sites (Kenakin, 2004). Because TMB has an effect on germination, then [A] is calculated using:
(Rmax, the maximal response (germination percentage in the presence of KAR1); Rbasal, the basal response (germination percentage in the absence of KAR1; Giraldo et al., 2007).) In our batch of achenes the Rmax was 0.93 and the Rbasal was 0.28 (germination of control); therefore, R50 = 0.605. Statistical differences between the calculated slopes were determined using the t-test and considered significant when P < 0.05. For data analysis and curve fitting, the OriginPro statistical software (OriginLab Corporation, Northampton, MA, USA) was used.
For light response assays, Petri dishes were irradiated with constant white fluorescent light (20 μmol m−2 s−1), or red (5 μmol m−2 s−1) or far-red light (2 μmol m−2 s−1; Walz diodes) for 1 or 3 h. For the leaching tests, achenes were treated with 0.1 μM KAR1 or 10 μM TMB, and the achenes were rinsed for 3 × 2 min in 200 ml of distilled water after 10–120 min of KAR1 treatment or 24 h of TMB treatment. The germinated achenes were scored after 24 h (KAR1) or 48 h (TMB). In addition, achenes were treated with 0.1 μM KAR1/10 μM TMB or 1 μM KAR1/10 μM TMB, germinated for 24 h and then rinsed with 27 ml of distilled water for 5 min. The excess solution was drained and the achenes were germinated for a further 24 h. For the pulse treatment tests, achenes were treated with 0.1 μM KAR1, and after 30 min, and every 1 h up to 10 h, the achenes were removed from the filter paper, drained and placed on filter paper moistened with a solution of 0.1 μM KAR1/10 μM TMB. Germinated achenes were scored after 24 h.
Total RNA was isolated and RNA integrity was assayed as described in Soós et al. (2010). For the 2- and 10-h time-points, 50 achenes were germinated. For the 24-h time-point, the number of achenes was increased in order to obtain at least 20 germinated achenes after the TMB treatment. Each harvest was repeated three times for three biological replicates. At 24 h, only achenes with a radicle that had protruded exactly 1 mm were regarded as germinated and achenes with no visible testa rupture were selected as nongerminated.
Custom-made microarray design
Lacking a commercially available microarray for Lactuca sativa, we designed a custom microarray manufactured by Agilent. For probe design, we used the lettuce UniGene Build #14 (7940 sequences), the TIGR Plant Transcript Assembly Database (http://plantta.jcvi.org/) (33 115 assemblies), the DFCI GI database (http://compbio.dfci.harvard.edu/tgi/plant.html) (29 885 sequences) and the NCBI expressed sequence tag (EST) (http://www.ncbi.nlm.nih.gov/dbEST/) section (81 026 sequences). The sequences were analyzed and compared with the blat software (Kent, 2002) to filter identical ones, and thereafter a set of 28 781 sequences were submitted to OligoArray v2.1.3 (Rouillard et al., 2003). The probes were designed to have a length of between 50 and 60 nucleotides and the Tm (melting point) range was between 81 and 99°C. Of these, 241 sequences were rejected, for which the software was unable to make a suitable oligo. The oligos were submitted to the Agilent eArray site (http://earray.chem.agilent.com/earray/; ID: 028289), and after filling up the < 60 nucleotide length oligos with linker sequences, they were synthesized on an Agilent 44 k slide together with positive and negative control probes.
For annotation, we used the available information from UniGene, TIGR and DFCI, complemented with the Arabidopsis information from ENSEMBL. The Lactuca sequences were assigned to known Arabidopsis genes, using the ENSEMBL Plants section (Release 11) protein sequences, employing a BLASTX search. We filtered the possible Arabidopsis orthologs, requiring at least 40% sequence identity and 60% query sequence coverage, and used the descriptions, cross-references, Gene Ontology (GO) and KEGG information (http://www.genome.jp/kegg/) for further analysis.
Microarray, labeling, hybridization and image acquisition
The microarray design consisted of two biological replicates and two dye-swaps. For each biological replicate, RNA samples (1 μg) of three technical replicates were pooled. After 2 and 10 h of treatment, the germinated and nongerminated achenes were indistinguishable and all 50 achenes were used for the RNA isolation. For the 24-h samples, the RNAs of germinated and nongerminated achenes were isolated separately and equal amounts of these RNAs were pooled. All the samples from control experiments (achenes germinated in water and kept in the dark) were compared with samples treated with 0.1 μM KAR1, 0.1 μM KAR1/5 μM TMB or 10 μM TMB. The RNA amplification and labeling procedure was performed with the Agilent QuickAmp Labeling Kit according to the manufacturer's recommendations.
Scanning was performed with an Agilent High-Resolution Microarray Scanner (default settings). The detection of signal intensities and the grid adjustment were accomplished with the Agilent Feature Extraction software.
Microarray data normalization and analysis
Raw intensity data were imported into R v2.13.0 (R Development Core Team, 2011). Data quality was assessed with the arrayQualityMetrics package (Kaufmann et al., 2009) and further analysis was carried out as described in Soós et al. (2010), except that the duplicate correlation method (Smyth et al., 2005) of LIMMA was used to estimate the correlation between technical replicates and to improve the detection of differentially expressed genes. Genes with a fold-change ≥ 2 and a corrected P-value ≤ 0.05 were considered differentially expressed. The microarray data have been deposited in the GEO database (GSE34642) (http://www.ncbi.nlm.nih.gov/geo/).
Visualization of the overlap between data sets was carried out using BioVenn (Hulsen et al., 2008) and hierarchical clustering was accomplished using the TM4 Microarray Software Suite (Saeed et al., 2006) using the Pearson distance metric and average link clustering. The 24-h microarray data were plotted with the ggplot2 package of R.
The RNA samples from three biological replicates (not the same as those used for microarray analysis) were DNase I (Qiagen) treated and reverse-transcribed with SuperScript III (Invitrogen). Real-time PCR was performed with an Applied Biosystems Fast 7500 instrument using SYBR Green detection chemistry (Applied Biosystems, Foster City, CA, USA) and gene-specific primers (Supporting Information Table S4), and reactions were performed in quadruplicate. The relative ratios of threshold cycle (Ct) values between the endogenous control (actin; AY260165) and the specific gene were calculated for each sample. The validation procedure was conducted with the same experimental design (all time-points and treatments) as for microarray analysis using the selected 24 genes.
Gene Ontology (GO) and KEGG analysis
Based on the available annotation from the Arabidopsis orthologs, the up- or down-regulated genes at a given time-point in a given experiment were assigned to the available GO categories. The ‘biological process’ category seemed to be the most informative and important in this study, and was given the most attention. The significant overrepresentation of certain categories in the up- and down-regulated gene sets was detected with the goal v1.0 software (Tchagang et al., 2010).
Germination characteristics of lettuce achenes after KAR1 and TMB treatments
To evaluate the potential differences between the KAR1- and TMB-treated achenes germinated in the dark, the relevant parameters were extracted from the germination time-curve (Fig. 1b,c). Application of 0.1 μM KAR1 or the combination of 0.1 μM KAR1/1 μM TMB resulted in a significant increase in germination (Joosen et al., 2010). The maximum percentage of germination (gMAX), the time to reach 50% germination (t50), the mean germination time (MGT) and the area under the curve (AUC; a parameter that combines information on the above-mentioned values and germination uniformity values) all showed that KAR1 alone, and a combination with a low concentration of TMB, not only increased the germination rate, but also increased germination uniformity. By contrast, the application of 10 μM TMB or 0.1 μM KAR1/10 μM TMB resulted in a significant decrease in the parameters evaluated, demonstrating that TMB is a strong germination inhibitor (see Table S1 for statistical analyses).
To characterize the proposed antagonistic relationship between the two compounds, Schild regression analysis was applied, by which the effects of agonists and antagonists on the response caused by binding to an effector molecule can be studied (Tallarida, 2000). Each of the seven fixed doses of TMB produced a decrease in the response magnitude and a rightward and parallel shift of the KAR1 dose–response curves (Fig. 2a). At high concentrations of TMB (10 and 7 μM), KAR1 was unable to fully overcome the negative effect of TMB, while at a lower TMB concentration (1 μM), the KAR1 effect could exceed that of TMB. At intermediate concentrations, however, the germination response depended on the TMB concentration, demonstrating that, irrespective of the KAR1 concentration used, germination can be significantly reduced by increasing the dose of TMB. The Schild plot for TMB against KAR1 was nonlinear and the apparent slopes from the three experiments were significantly different from unity (t-test P < 0.05), indicating that KAR1 and TMB are not competitors (Fig. 2b).
Germination response of KAR1- and TMB-treated achenes to white, red (R) and far-red (FR) irradiation
The microarray data presented in this study suggest that KAR1 and TMB interact with light-dependent processes in Grand Rapids lettuce achenes. In order to distinguish between light and KAR1/TMB responses, germinating achenes treated with the compounds were irradiated with continuous white, FR and R light and the germinated achenes were counted after 24 h (Fig. 3). Continuous white light or 1 h of R fluence resulted in 96% and 100% germination, respectively. In contrast, 1 h of FR fluence blocked germination and resulted in c. 7% germination, and 3 h of FR irradiation resulted in 0% germination (data not shown). The negative effect of FR could be overcome by 0.1 μM KAR1 in the presence of 1 μM TMB, while 10 μM TMB completely blocked germination, even when 0.1 μM KAR1 was added. Treatment with white light could not overcome the effect of 10 μM TMB, whereas R irradiation could only partially do so.
Leaching of KAR1 and TMB from germinating lettuce achenes
It was hypothesized that the proposed antagonistic relationship between the two compounds is modulated by the different binding affinities of KAR1 and TMB to their prospective effectors. The ecological importance of this theory is that excess water might wash out TMB from binding sites and that KAR1 might then exert its positive effect on germination. To test this hypothesis, rinsing tests were carried out with both compounds and the germination response of the achenes in the dark was then recorded. KAR1 could only be leached within the first 30 min of incubation and, thereafter, the germination rate increased sharply with incubation time, reaching a plateau at around 80 min, after which the effect of KAR1 was not reversible by rinsing the achenes (Fig. 4a). The TMB, however, could be leached at any time within the first 24 h, where the germination rate was similar to that for achenes kept in the dark (Fig. 4c). The simultaneous application of 0.1 or 1 μM KAR1 along with 10 μM TMB revealed that after 24 h only the TMB effect was diminished by rinsing, and KAR1 exerted its positive effect within the following 24 h (Fig. 4c). We also studied whether KAR1 action could be reversed by TMB with the onset of germination. We found that a pulse treatment with 10 μM TMB resulted in the full reversal of the effect of 0.1 μM KAR1 only within the first few hours, whereas no effect was observed after 8 h (Fig. 4b).
Transcriptome analysis of KAR1- and TMB-treated germinating lettuce achenes
In order to obtain a more accurate and detailed picture of the proposed divergence of KAR1- and TMB-related pathways, a time-course microarray analysis of KAR1- and TMB-treated achenes was performed using custom-made microarrays. Early time-points for sampling the transcriptome were chosen, taking into account that treatment with KAR1 is irreversible (by leaching with water) after 2 h, and that the KAR1-treated achenes enter a TMB-insensitive stage after 8 h. Therefore, samples were harvested after 2 and 10 h of initial exposure to 0.1 μM KAR1 or 10 μM TMB, and after 24 h, when germinated and nongerminating achenes could be distinguished visually. To assess the divergence between the expression patterns induced by the two compounds, a sample of achenes treated with 0.1 μM KAR1/10 μM TMB was harvested after 2 h. At 24 h, samples were collected from germinating and nongerminating achenes separately, and equal amounts of mRNA were pooled. Although there is a small chance of losing data with this design, our primary aim at 24 h was to screen for differences between the KAR1- and TMB-induced transcriptomes. Achenes germinated in distilled water served as controls and were compared to the samples treated as described above. The microarray data presented here have been deposited in the GEO database (series GSE34642). The full list of the genes with fold-change ≥ 2, their annotations and corrected P-values in the different treatments and time-points are available as Supporting Information (Table S2). The microarray analysis shows that, throughout the course of the experiments, only a narrow subset of genes were affected at all time-points by the treatments.
At 2 h, there was no overlap between the KAR1- and TMB-responsive genes (Fig. 5a). In contrast, simultaneous application of the two compounds resulted in changes in the expression of all individual KAR1- and TMB-responsive genes and a few other genes (Table S2), such as the BTF3-like transcription factor (DY981384). The data indicate that there are extensive differences in the scope and degree of the gene expression changes provoked by the two compounds applied alone, and there is an intermediate response when both compounds are present. KAR1 treatment manifested at the gene level by the repression of two gene families, the 11S globulin (e.g. DY981362) and the 2S albumin (e.g. BQ856290) genes. TMB treatment resulted in the down-regulation of several genes, including alcohol dehydrogenases (D44449), a wound-induced protein (DY982994), kaurene synthase (DY968894), UDP-glucose glucosyltransferases (BQ856171), a phosphate translocator (TA9661_4236), and a putative WD-repeat protein (BQ873149). Only one gene, a phosphatase (DY984045), showed induction above the 2-fold cut-off.
At 10 h, there was an overlap between the genes up-regulated by both compounds (Fig. 5a). Surprisingly, all three TMB-induced genes, LEA (DW126825), a photosystem Q(B) protein precursor (TC15985) and a hypothetical protein (TA9719_4236), could be found on the list of KAR1-induced genes. TMB treatment repressed a hypothetical protein gene (DW130002), FAR1 (TA11042_4236) and oxidoreductases, and also down-regulated the alcohol dehydrogenases (D44449) and a putative wound-induced protein gene (DY982994), which were also affected at 2 h. KAR1 treatment resulted in the marked up-regulation of an α/β fold hydrolase (DY983731), an AP2/ERF transcription factor (DW143685) and histone H2B (TA6237_4236), and the distinct down-regulation of cysteine protease-3 (DY983401). The hierarchical clustering analysis of 119 genes (selected on the basis that their log2 fold-change was > 1 or < −1, with corrected P-values ≤ 0.05 at the 2- or 10-h time-point) revealed a pattern associated with time-points (Fig. 5b).
Inspection of the KAR1- and TMB-responsive gene lists at 24 h revealed a reciprocal effect of TMB (Fig. 6), and a specific set of genes showed a contrasting expression pattern after treatments with the two compounds. The FUS3 (BQ849928), HVA22 (EU028335), LEA (TA7012_4236) and NCED genes (e.g. LsNCED2; AB120108) and globulins were repressed after KAR1 exposure, and induced in TMB-treated samples. In contrast, the abundance of an aquaporin (DW130983) and hypothetical protein (DW123747) transcripts increased with KAR1 treatment, and decreased with TMB treatment. Several light-related genes, such as the early light-induced protein (ELIP; BQ865306), HY5 (TA10549_4236) and chlorophyll a/b binding proteins, were induced by KAR1 treatment, whereas others, including hypothetical proteins and ATFP6 (BQ865118), were repressed.
Validation of the microarray study and the real-time PCR analysis of the expression of selected genes
To validate the microarray results, the differential expression of selected genes from all time-points was corroborated using qRT-PCR. The 24 genes with distinct and characteristic expression changes were chosen, and several genes showing no expression change were also selected randomly for the validation process. The expression pattern observed in the microarray experiments was consistent with the genes analyzed by real-time PCR (Fig. 7a). The linear regression analysis showed a significant correlation between the two data sets, with R2 = 0.7498.
The expression analysis of KAR1- and TMB-responsive genes at the earliest time-point showed that the transcript abundances of these genes were moderately altered, except for the 2S albumin and the 11S globulin isoform genes, which were excessively down-regulated in KAR1- and KAR1/TMB-treated samples (Fig. 7b). The expression of all the other genes displayed a moderate, uniform, 2- to 10-fold decrease, with a clear tendency for down-regulation in the TMB-treated samples. At 10 h, the expression level of the chosen genes showed a very similar pattern to the microarray study. The application of 0.1 μM KAR1/5 μM TMB at both time-points produced an intermediate change in gene expression (Fig. 7b).
To assess the detailed expression profiles of the selected genes, samples from 24-h germinated and nongerminated KAR1- or TMB-treated achenes were analyzed separately. The real-time PCR study revealed that, in several cases, the transcript abundance changed in contrasting patterns in KAR1- and TMB-treated samples (Fig. 8a). For example, in the nongerminating achenes, the FUSCA3-like gene was up-regulated in the TMB-treated and down-regulated in the KAR1-treated samples. A more contrasting expression pattern was observed in the case of HVA22, the putative TIP gene and a hypothetical protein gene, which showed the greatest changes in their transcript abundances after the treatments. HVA22 was down-regulated in KAR1-treated germinated and nongerminated samples, and up-regulated in TMB-treated achenes. In contrast, the putative TIP gene and the hypothetical protein gene were up-regulated in KAR1-treated samples and down-regulated in all TMB-treated achenes. HY5 showed a distinct up-regulation in KAR1-treated samples, while ELIP was up-regulated only in KAR1-treated germinating achenes. LEA, alpha/beta fold hydrolase, the storage protein gene and the coatomer beta subunit gene exhibited KAR1-specific expression patterns. To demonstrate that FUS3 and ELIP showed compound-specific expression patterns over a relatively short time (4 h), RNA samples of 10 achenes (both germinating and quiescent) were isolated separately after 20 and 24 h and the expression of the genes was assayed. The box plot analysis (Fig. 8b) shows that there was very little variability among the transcript abundances of the genes and the individual achenes, suggesting, albeit not postulating, that the changes in the expression of these genes are related to the compounds.
Gene Ontology (GO) and KEGG analysis
Genes up- or down-regulated ≥ 2-fold and with a corrected P-value < 0.05, as a result of KAR1 or TMB treatment, were associated with different GO terms. The significantly overrepresented GO terms after 24 h are shown in Fig. 9. For GO lists and P-values for the 2-, 10- and 24-h data, see Table S3. The most represented GO terms, following KAR1 or TMB exposure, were different and reflect fundamental differences induced by the two compounds. The presence of genes related to various biosynthetic and metabolic processes was robust in the ‘TMB-down’ list. A number of GO terms related to ABA were overrepresented in ‘KAR1-down’ and ‘TMB-up’ lists in a reciprocal manner. A similar contrasting pattern was observed in seed-related terms, where seed maturation-, seed development- and seed dormancy-related terms were abundant in the ‘KAR1-down’ and ‘TMB-up’ lists. Photosynthesis and light response-related terms were distinctly overrepresented in the ‘KAR1-up’ list. Stress-related terms were also present in all lists.
The dose–response curves showed that the KAR1 effect can be reversed by TMB in a concentration-dependent manner, although Schild regression demonstrated that TMB is not competing for the same binding site as KAR1. The deviation from unit slope and the linearity of the plot suggest that a more complex interaction takes place when both cues are present (Tallarida, 2000). The large difference between the dynamic ranges of the two compounds and the evidence that TMB can reverse the positive effect of KAR1 and that TMB can be more easily washed out of the achenes support the finding of the Schild analysis. Leaching tests showed that there was a 4–5-h TMB-reversible phase of the KAR1 effect, during which both cues could reach their effective concentrations, even in the case of reduced uptake/penetration. Irrespective of the KAR1 concentration used, TMB exerted its negative effect on germination when its concentration was > 10 μM. Therefore, if a finite amount of a common effector was present, and the compounds competed for the same binding site, the effector would bind TMB preferentially, which is antithetic to the observation that TMB could be more easily washed out. Furthermore, KAR1 could not be washed out after 2 h and the KAR1-induced germination had a TMB-sensitive stage during which TMB treatment could nullify the KAR1 effect. Providing that KAR1-induced signaling requires the persistent binding of the cue and the compounds are binding to a common site, TMB could diminish the KAR1 effect only by displacing it from the binding site. However, the Schild analysis, the dynamic range and the low affinity of TMB for its proposed effector preclude that the inhibitory cue could displace KAR1. Assuming that a switch mechanism is a prerequisite for the KAR1 effect (e.g. the signaling does not require persistent binding), then TMB could only impede KAR1 action through allosteric inhibition or by binding to a different effector. Taking these findings together, we can conclude that TMB is not bound by the same binding site. It should be noted, however, that the binding characteristics of the two cues in vitro have not been assayed because the molecular properties, localization and inducibility of the effector are unknown and proved to be very difficult to determine.
The total transcriptome analysis provided evidence that both compounds elicit their respective gene expression patterns. The abundances of KAR1- and TMB-related transcripts of achenes treated with 0.1 μM KAR1 and 5 μM TMB (IC50 value) exhibited overlapping expression patterns compared with the samples treated with either compound alone. The expression patterns of KAR1- and TMB-related genes obtained by real-time PCR clearly demonstrated that the dose-dependent response is manifested even at the level of gene expression. These findings indicate that TMB can reverse KAR1-responsive expression and the compounds interact in signaling which directly relates to the germination.
The leaching experiments demonstrated that KAR1 elicits a very early response, so the earliest changes in transcriptome were assessed at around 2 h. We speculate that the KAR1-down-regulated genes representing two gene families (basic 2S albumins and 11S globulins) and the GST (glutathione S-transferase) gene might be the primary response genes which are repressed by KAR1 in the absence of any intervening protein synthesis. Their expression exhibits a temporal pattern coinciding with seed maturation (Guerche et al., 1990), and shows that KAR1 primarily affects seed maturation-related genes either by shutting down their expression rapidly or by influencing RNA turnover. The 2-h transcriptome data also revealed that TMB represses the kaurene synthase gene, which encodes the key enzyme of gibberellin synthesis (Olszewski et al., 2002).
At 10 h, when KAR1 signaling has entered a TMB-insensitive phase leading to germination, a novel α/β fold hydrolase gene was distinctly up-regulated. α/β fold hydrolase proteins may have very diversified roles and might function as enzymes, or may act as signaling molecules in light and gibberellin signaling without a need for their catalytic functions (Sun & Ni, 2011). Conversely, KAR1 impaired the expression of a cysteine protease gene which is suggested to have a regulatory role during germination (Sheokand et al., 2005). TMB treatment resulted in a strong down-regulation of the FAR1 gene, a transcription factor essential for light-induced phytochrome A nuclear accumulation and subsequent light responses (Hudson et al., 1999). This is in agreement with the observation that R irradiation can only partially compensate for the inhibitory effect of TMB, suggesting interference of the signaling events. This interplay between light and KAR1-related events is manifested more obviously after 24 h, as a high proportion of KAR1-responsive transcripts are related to light signaling. ELIP and the HY5 transcription factor were up-regulated in the absence of light, demonstrating the interaction of KAR1 with light signaling. This was further confirmed by the fact that KAR1 could fully compensate for the effect of FR irradiation. This finding is in agreement with previous reports suggesting that KAR1 induces light-related genes in maize (Soós et al., 2010) and Arabidopsis (Nelson et al., 2010).
At 24 h, the list of genes up-regulated by TMB was enriched with ABA, seed maturation and desiccation-related accessions. Among others, storage protein genes, LEA, HVA22 and FUS3 were all markedly induced by TMB, and down-regulated by KAR1 treatment. These accessions are all linked to seed maturation and ABA action. LEA proteins accumulate in the late phase of embryogenesis, concomitant with the onset of seed desiccation tolerance (Shen et al., 1996). HVA22 affects the secretion of hydrolytic enzymes from the aleurone layer and its expression is ABA-induced and confined to early seed development (Shen et al., 2001; Becerra et al., 2006). FUSCA3 (FUS3) is a plant-specific transcription factor (Stone et al., 2001) which regulates key pathways during seed maturation (Santos-Mendoza et al., 2008). NCED genes encode the key regulated enzymes in the biosynthesis of ABA, an inhibitor of germination. These findings correspond with the observation that the endogenous ABA level decreases in smoke-treated seeds of Nicotiana attenuata (Schwachtje & Baldwin, 2004). We previously identified HVA22 and an LEA gene by differential display RT-PCR as smoke-responsive genes in Grand Rapids lettuce achenes (Soós et al., 2009a), which corresponds well with our present results. KAR1 up-regulated, while TMB markedly down-regulated several aquaporin genes. Aquaporins facilitate water supply to the expanding tissues in germinating seeds (Vander Willigen et al., 2006). We previously showed that the TIP3.1 aquaporin was markedly up-regulated in KAR1-treated germinating maize kernels (Soós et al., 2010), confirming that aquaporins indeed play an important role in KAR1 action. Interestingly, the genes mentioned above exhibited contrasting expression patterns after KAR1 and TMB treatments. We interpret this symmetrical shift in the abundance of these maturation-related genes as a consequence of the blockade of the primary germination signaling by TMB, and the acceleration of these signaling events by KAR1. The GO analysis provides further evidence of the reciprocal effects of the compounds. KAR1 distinctly induced photosynthesis- and light response-related genes, which supports the finding that KAR1 can replace the light requirement for germination in this cultivar. TMB, conversely, strongly down-regulated genes related to various metabolic pathways, suggesting that this compound might fundamentally block basic metabolic processes required for storage mobilization. KAR1 blocked and TMB induced several ABA-related genes, and seed development-, maturation- and dormancy-related genes were overrepresented, indicating that TMB prevents the onset of germination and maintains the nongerminating state of the achenes.
Our aim was to screen for genes showing altered expression after exposure to the two compounds. The microarray design used leaves open the possibility that expression patterns interpreted as constitutively altered by either KAR1 or TMB were instead, to an unknown extent, germination-related responses resulting from different developmental stages at the time of sampling. We attempted to circumvent these ambiguities by choosing early time-points, by harvesting achenes rigorously at visually the same stage, by pooling equal amounts of RNA from germinating and nongerminating achenes (at 24 h; pooling implies the small chance of losing data) and by the separate real-time PCR analysis of these two stages (at 24 h). We acknowledge that it is not easy to distinguish between KAR1/TMB ‘specific’ and germination-related transcripts, and that the differences may be attributable to different developmental stages. However, the contrasting expression pattern at 24 h was also observed in the real-time PCR study with the addition that, for the majority of the genes, expression showed compound specificity and changed in the same direction, although the response was more marked in nongerminating achenes. The box plot analysis of FUS3 and ELIP expression in 10 separate achenes after 20 and 24 h of exposure to the cues showed a minimal variance of transcript abundance in the germinating achenes, suggesting that at least these genes demonstrate compound-specific expression. However, as the GO analysis clearly demonstrated, TMB maintained a latent dormant state, implying that the difference observed in the expression patterns can rather be attributed to the different developmental stages. From this point of view, there is no TMB-induced expression because the transcriptome differences reflect only the progression of germination in the control and KAR1-treated samples. Thus, the contrasting gene expression after 24 h can be interpreted as the reciprocal effect of the compounds at the same signaling event.
We propose a constitutive signaling model in which KAR1 and TMB bind to their own effector molecule populations and, while KAR1 elicits the signal transduction, TMB shuts it down (Fig. 10). As a function of TMB concentration, the cues provoke a signaling cascade resulting in a germination response differing from the FR light-reversible reference signaling (the basal, ‘trudging’ activity in water-imbibed achenes in the dark). In terms of germination, the positive effect of KAR1 is manifested in return for the water imbibed, dark-kept control, in which the signaling leads to germination operating at a basal level. In contrast, TMB shuts down these pathways and, as a consequence, germination will be blocked and the achenes enter a latent dormancy state. As the leaching experiments showed, the inhibitory effect is maintained until the TMB concentration is diluted by excess water. These observations outline the potential ecological importance of TMB as an inhibitory germination cue. Because fire events usually take place during the dry season, it is intriguing to consider that germination is consistent with a trade-off between the increased risk of failure of a cohort of seedlings to survive, and benefits of early establishment of a cohort with higher vigor that might survive in an environment with a seasonal rainfall. Not only is the smoke-derived signal (which ‘informs’ seeds about the germination niche) needed for successful seed germination, but water is also required in sufficient amounts for successful seedling establishment. We previously determined the concentrations of both compounds in crude smoke-water batches (Soós et al., 2010), and found that TMB was present at a relatively high concentration, well over the inhibitory 10 μM limit. This finding suggests that TMB is generated in much higher quantities during a fire compared with KAR1, although soil components and degradation might alter their concentrations and subsequent activities. It is also important to consider, however, that other compounds with biological activity (promontory or inhibitory) may also be formed in smoke. Nevertheless, TMB may provide an important signal by which it blocks germination until rain washes it out or dilutes it to below a threshold where the promotory cues can exert their positive effect on germination. Post-fire seasonal seedling emergence is a common phenomenon in many Mediterranean-type fire-prone habitats, where germination is considered to coincide with distinct winter rainfall periods (Bradstock & Bedward, 1992; Bell, 1999). In a recent study, germination and seedling recruitment from the seed banks of tropical savanna increased strongly with precipitation and fire frequency (Anderson et al., 2012). In addition, in the eastern fynbos biome fires, which immediately precede or coincide with peak rainfall months, the highest seedling recruitments are observed (Heelemann et al., 2008). This suggests that enhanced recruitment is associated with rainfall immediately after the fire, although post-fire emergence patterns vary with habitat, species and other germination cues (e.g. heat; Ooi et al., 2006). Taken together, our findings suggest that by ‘sensing’ the ratio of smoke-derived environmental cues, plants can not only respond to the disturbance (fire) but also fine-tune seedling stand establishment.
An intriguing issue for future studies is to understand the molecular basis underlying the primary responses to smoke-derived cues. It will also be interesting to investigate whether the outlined KAR1–TMB interaction works in ecological systems, and what other factors might influence the interplay presented here. Our results also demonstrated that TMB is a useful tool with which to study seed dormancy, germination and ABA-related events in seeds. In summary, this study might serve as a good starting point from which to systematically study the germination-active butenolides in terms of their molecular and ecological functions.
Thanks are due to Katalin Éder (Semmelweis University) for scanning the microarray slides. This work was supported by the ICGEB, the Generation Challenge Programme, the Hungarian-South African S&T Cooperation Programme, the Hungarian Scientific Research Fund (OTKA 100763), the National Research Foundation, South Africa, the University of KwaZulu-Natal and the IOCB project Z40550506, Czech Republic. V.S. was granted a Bolyai Scholarship.