Seedlings of A. thaliana ecotype Col-0 (WT), and transgenic plants 35S::NPR1-GFP, 35S::npr1C82A-GFP, 35S::npr1C216A-GFP (Kinkema et al., 2000; Mou et al., 2003) were grown in 24-well plates in 400 μL of MS liquid medium (Clay et al., 2009) for 10 days in a cycle of 10 h days (120 μE m⁻² s⁻¹, 22°C) and 14 h nights (22°C) at 70% relative humidity. MS liquid medium in the wells was changed on the 7th day.

The plants were treated directly in the wells of plates by changing the growing medium for the chemical-containing medium. 10-day-old seedlings were treated for 6 h with 50 μM and 250 μM salicylic acid sodium salt (Sigma; NaSA), 0.1 and 1% n-butanol (Sigma) or t-butanol (Penta).

The whole seedlings from three wells were immediately frozen in liquid nitrogen. The tissue was homogenized in tubes with 1 g of 1.3 mm silica beads using a FastPrep-24 instrument (MP Biomedicals, CA, USA). RNA isolation and reverse transcription were performed as previously described (Sasek et al., 2012). An equivalent of 6.25 ng of RNA was loaded into a 10 μl reaction with qPCR mastermix EvaLine—E1LC (GeneOn, Ludwigshafen am Rhein, Germany). The reactions were performed in polycarbonate capillaries (Genaxxon, Ulm, Germany) and a LightCycler 1.5 (Roche). The following PCR program was used for PCR assays: 95°C for 10 min; 45 cycles: 95°C for 10 s, 55°C for 10 s, and 72°C for 10 s; finished with a melting curve analysis. Threshold cycles and melting curves were calculated using LightCycler Software 4.1 (Roche). Alternatively, the LightCycler® 480 SYBR Green I master kit was used. The reactions were performed in the LightCycler® 480 Multiwell Plate 96 white. The following PCR program was used for PCR assays: 95°C for 10 min; 45 cycles: 95°C for 20 s, 55°C for 20 s, and 72°C for 10 s; finished with a melting curve analysis. The threshold cycles and melting curves were calculated using LightCycler Software 4.2 (Roche). The relative transcription was calculated with the efficiency correction and normalization (Czechowski et al., 2005). The primers were designed using PerlPrimer v1.1.17 (Marshall, 2004). The list of A. thaliana genes and corresponding accession numbers and primers follows: SAND, AT2G28390, FP: 5′CTG TCT TCT CAT CTC TTG TC 3′, RP: 5′ TCT TGC AAT ATG GTT CCT G 3′, PR-1, AT2G14610, FP: 5′ AGT TGT TTG GAG AAA GTC AG 3′, RP: 5′ GTT CAC ATA ATT CCC ACG A, S3H, AT4G10500, FP: 5′GGA TGA TAA ATG GGT CGC T 3′, RP: 5′TGT TTA CTA CGG CTC TAT GG 3′; WRKY38, AT5G22570, FP: 5′GCC CCT CCA AGA AAA GAA AG 3′, RP: 5′ CCT CCA AAG ATA CCC GTC GT 3′, ICS1 AT1G74710 FP: 5′GCA AGA ATC ATG TTC CTA CC 3′, RP: 5′AAT TAT CCT GCT GTT ACG AG 3′.

The slide with seedlings was positioned onto an inverted platform (with a cover slip at the bottom) of the confocal laser scanning Zeiss LSM 5 DUO microscope. The GFP fluorescence was excited by the 488 nm line of a laser, the DAPI fluorescence was excited by the 405 nm line. The epidermal cells were viewed using an Zeiss Plan-Apochromat 20x/0,8 objective. The emitted light was captured using the HFT405/488 beam splitter and a 505–550 nm or 420–480 nm band-pass filter, respectively. Image analysis was performed using the software APS Asess 2.0.

The extraction procedure was modified according to Vaclavik et al. (2013). Whole seedlings from three independent wells were immediately frozen using liquid nitrogen. Six independent samples for one type of treatment were prepared for one biological replicate. 150–250 mg of plant tissue was homogenized in tubes with 1 g of 1.3 mm silica beads using a FastPrep-24 instrument (MP Biomedicals, CA, USA). After the addition of 700 μL of methanol (p.a.; PENTA), the plant tissue was homogenized again. The silica beads were washed once with 700 μL methanol and both extracts were combined. The samples were kept on ice during the extraction. Prior to instrumental analysis, the samples were stored in a dark and dry environment at −70°C. The UHPLC–Q-TOF-MS analyses were performed using an Acquity Ultra-Performance LC system coupled to a Synapt G2 high definition mass spectrometer (Waters, USA). The LC separation was performed by an Acquity UPLC® HSS T3 column (100 × 1.8 mm, 1.7 μm particle size; Waters, USA). The gradient elution was used with the mobile phases consisting of (A) 0.1% formic acid in Milli-Q water and (B) 0.1% formic acid in methanol.

The Synapt G2 HD instrument was operated in the negative electrospray ionization (ESI) mode. The parameter settings used during the measurements were as follows: capillary voltage (−700 V), cone voltage (−25 V), source temperature (120°C), and desolvation temperature (350°C). Nitrogen was used as both desolvation and cone gas at a flow rate of 800 and 10 L/h, respectively. Both full MS and MS/MS fragmentation mass spectra were acquired at a rate of two spectra per second in the range m/z 50–1000. In order to diminish any possible time dependent changes in the UHPLC-MS chromatographic fingerprints, the sequence of the samples was randomized and one sample was chosen as a quality control sample, which was injected after every set of 20 samples. The MassLynx 4.1 software (Waters, USA) was used for data acquisition and the MarkerLynx software (Waters, USA) was used for data mining and processing. The software SIMCA (v. 13.0, Umetrics, Sweden) was then used for data processing based on Principal Components Analysis (PCA).

Values are expressed as means ± standard error (SE). For statistical analysis, Student's t-test or One-Way ANOVA followed by Fisher's Least-Significant-Difference (LSD) were used as appropriate, with a value P < 0.05 considered significant for mean differences using STATGRAPHICS® Centurion XVII software.

The increased levels of SA or exogenous treatment with this phytohormone activates the signaling pathway resulting in the transcription of defense related genes (e.g., pathogenesis related). The generally accepted marker of SA signaling is the PR-1 gene. In order to examine possible role of PLD/PA in this process, we co-treated 10-day-old seedlings of A. thaliana with both SA and increasing concentrations of n-butanol. The SA induced PR-1 transcription was decreased in the presence of n-butanol in a strongly dose-dependent manner (Figure 1A). Contrarily, the t-butanol showed no effect on the PR-1 transcription (Figure 1B).

We also examined the effect of both alcohols on the transcription of other SA related genes, WRKY38 and S3H, both encoding proteins with different functions. While the PR-1 protein is responsible for a direct antimicrobial effect as the end product of SA pathway, WRKY38 is a transcription factor which negatively regulates PR-1 transcription, but it is NPR1 dependent (Kim et al., 2008). S3H is an enzyme responsible for the conversion of SA to a less biologically active compound, gentisic acid (Zhang et al., 2013). WRKY38 and S3H transcriptions were not as significantly blocked as PR-1 transcription. The relative transcription of WRKY38 decreased only two times and even less in the case of S3H (Figures 1B–D). Also, the dose dependence of the n-butanol effect on the transcription of these two genes was far less apparent (Supplemental Figure S1).

We further intended to take a closer look at the site of n-butanol action in the SA signaling pathway. To decipher, we used 35S::NPR1-GFP A. thaliana transgenic plants. It was confirmed earlier that the treatment of these mutants with 2,6-dichloroisonicotinic acid (INA), a functional analog of SA, causes monomerization of NPR1, which is afterwards accumulated in the plant cell nucleus (Mou et al., 2003). We treated 10-day-old 35S::NPR1-GFP A. thaliana seedlings with 250 μM NaSA and observed a significant increase of fluorescence in the nuclei (Figures 2A,B), the same effect was described for INA treatment. The accumulation of 35S::NPR1-GFP in the nuclei in the presence of NaSA decreased after addition of 1% n-butanol (Figures 2A,B). When t-butanol was applied as a negative control, no effect on the 35S::NPR1-GFP accumulation in the nuclei was observed (Figures 2A,B). n-butanol alone decreased the basal accumulation of NPR1 in the nuclei in the control plants, while no effect was observed for t-butanol. The localization of NPR1-GFP in the nuclei was verified by DAPI staining (Supplemental Figure S2). All these results correlate with the aforementioned PR-1 transcription analysis (Figure 1B). Consequently, we wanted to examine whether the decreased amount of NPR1 in the nucleus caused by n-butanol is due to the higher actvity of proteasomes in NPR1 degradation (Spoel et al., 2009). For this experiment, we used 35S::npr1C82A-GFP and 35S::npr1C216A-GFP seedlings expressing constitutively monomerized NPR1, which is overaccumulated in the nucleus (Mou et al., 2003). The treatment of these mutants with 0.1% and 1% n-butanol did not decrease the accumulation of NPR1 in the nuclei (Figure 3). This experiment also provides evidence that n-butanol does not influence fluorescence intensity.

Zhang et al. (2010) showed that nuclear localization of NPR1 is required for SA accumulation, ICS1 transcription and SA tolerance. When NPR1 was retained in the cytoplasm, plants accumulated higher levels of ICS1 transcripts compared to the wild type. Based on this, we measured the transcription of ICS1 upon the addition of the n-butanol treatment and as expected, n-butanol induced ICS1 transcription in a dose-dependent manner (Figure 4A), while t-butanol had no effect (Figure 4B). These results support our suggestion that n-butanol inhibits the translocation of NPR1 to the nucleus. Accordingly, we also found that the ICS1 transcription in 35S::npr1C82A-GFP and 35S::npr1C216-GFP mutants were significantly decreased but n-butanol treatment partially reverted this effect (Figure 4C).

As the accumulation of SA leads to the massive reprogramming of the plant transcriptome, it was obviously accompanied by significant changes in the whole metabolome. We investigated these changes in plants treated with SA and n-butanol to test if we could reveal compounds involved in the SA/phospholipid signaling pathway.

The principle component analysis (PCA) represents a highly useful and widely employed tool for the interpretation of complex data sets generated by several modern instruments including mass spectrometry. In our study, PCA was employed to explore alterations in the metabolomes of differently treated A. thaliana samples measured by LC-MS. As shown in Figure 5, there was a significant difference in the metabolomic fingerprints of samples treated with n-butanol (right side of the PCA plot) and untreated ones (left side of the PCA plot). The samples treated with SA were clearly differentiated (bottom part of the PCA plot) from the untreated samples (top part of the PCA plot). The list of the most distinct markers (ions recovered from the LC-MS records) is summarized in Table 1. Obviously, SA and its metabolite SA hexoside are typical markers for the samples treated with SA. Unfortunately, the identification of markers present in n-butanol treated plants was mostly unsuccessful, mainly due to their high m/z values resulting in many possible elemental formulas and also due to the limited information about the changes induced by n-butanol in the metabolism. Important observations were that the t-butanol treated samples did not differentiate from the untreated samples and also that t-butanol had no effect on the SA treated samples (Figure 5).

We identified 114 metabolites, from which 61 were statistically (P = 0.05; two tailed Student's t-test) changed at least in one of the used treatments (Figure 6). Based on the response to treatment, we were able to divide the metabolites into six groups (Figure 6) according to whether they were induced or suppressed by SA, n-butanol or both chemicals together.

In our study, we have shown that n-butanol is a molecule with a high impact on the SA signaling pathway in A. thaliana seedlings. n-butanol has been for a long time accepted by the “PLD community” as a modulator of PLD activity due to its preference for primary alcohols as substrates (Yang et al., 1967; Munnik et al., 1995). Potocky et al. (2014) recently provided excellent evidence that n-butanol alters the concentration of PA on the pollen tube's plasma membrane in vivo. n-butanol was used to establish the PLD/PA signaling connection with G proteins, ABA triggered germination, primary root elongation, hypocotyl length, cotyledon expansion, inhibition of pollen tube germination and growth, proline accumulation, actin cytoskeleton rearangement and microtubule reorganization (Munnik et al., 1995; Ritchie and Gilroy, 1998; Dhonukshe et al., 2003; Gardiner et al., 2003; Potocky et al., 2003; Thiery et al., 2004; Motes et al., 2005; Pleskot et al., 2010, 2014). We would like to mention that it is necessary to keep in mind the possibility that the effect of n-butanol is not so specific as was mentioned by Hirase et al. (2006), who observed that n-butanol induced the depolymerization of microtubules. Although the use of t-butanol, as a control, can serve as convincing proof.

In our study, the treatment of A. thaliana seedlings with n-butanol rapidly decreased PR-1 transcription in the presence of SA and this effect is clearly dose dependent (Figures 1A,B). The effect on the transcription of WRKY38 and S3H was much less pronounced (Figures 1C,D) but in the case of WRKY38 the decrease was significant (more than two times) and so the transcription pattern seems similar to PR-1. It is not surprising, as the transcription of WRKY38 is also NPR1 dependent. Our results are in agreement with the results obtained by Krinke et al. (2009) in A. thaliana suspension cells. n-butanol did not have a significant effect on S3H transcription. S3H is responsible for a conversion of SA, therefore its transcription should be induced immediately by higher levels of SA and the signaling events downstream to SA can have only a minor effect on S3H transcription (Figure 1D). In fact, the connection between the S3H effect and NPR1 has not yet been described in detail.

A deeper insight into the mode of action of n-butanol in SA signaling provided the experiment with 35S::NPR1-GFP A. thaliana mutants. We observed that effect of n-butanol is closely connected with the NPR1 localization in plant cells. In the 35S::NPR1-GFP plants, n-butanol blocks NPR1 accumulation in the nucleus in the presence of SA (Figure 2). This finding well corresponds with the suppressive effect of n-butanol on the transcription of PR-1. Zhang et al. (2010) showed that nuclear localization of NPR1 negatively regulates the transcription of the ICS1 gene. We observed that n-butanol induces the transcription of ICS1 (Figure 4), which supports the idea that n-butanol blocks translocation of monomeric NPR1 to the nucleus. It was reported that the proteasome degrades NPR1 monomers in the nucleus (Spoel et al., 2009). Based on that fact we used 35S::npr1C82A-GFP and 35S::npr1C216A-GFP mutants which constitutively express a higher amount of NPR1 monomers and also exhibit a higher accumulation of NPR1 in the nucleus (Mou et al., 2003). In these mutants, we investigated the effect of n-butanol. As n-butanol treatment revealed no effect on the nuclear localization of NPR1 in the 35S::npr1C82A-GFP and 35S::npr1C216A-GFP mutants (Figure 3), we can assume that n-butanol acts in the cytosol in the SA pathway before or during NPR1 translocation to the nucleus. n-butanol could either affect the transmission of the monomer from the cytosol to the nucleus e.g., by direct effect of n-butanol on the nucleopores or by active transport which can be mediated by PA. This mechanism was recently shown in the nuclear localization of the MYB transcription factor (Yao et al., 2013). Nevertheless, we cannot exclude the possibility that n-butanol acts upstream to NPR1 monomerization (Figure 8).

Based on the above mentioned observations, we would like to highlight the possible connection between the phospholipid signaling system and the SA pathway. SA treatment increased the PA level or the PLD activity in A. thaliana, B. napus. and soybean (Profotova et al., 2006; Kalachova et al., 2012, 2013; Rainteau et al., 2012). Krinke et al. (2009) showed in A. thaliana suspension cells that SA treatment led to a rapid increase of the PA level in vivo. We observed that the exogenous PA is capable of preventing the disruption of the actin cytoskeleton caused by SA (Matouskova et al., 2014). PLD and PA are not the only members of large phospholipid family involved in SA signaling. Interestingly, it was shown that SA treatment activates type-III phosphatidylinositol-4-kinase (PI4K), which is responsible for the formation of phosphatidylinositol-4-phosphate (PI4P) and phosphatidylinositol-4,5-bisphosphate (PIP₂) in A. thaliana suspension cells (Krinke et al., 2007). Recently, we showed that double knock-out mutation of two isoforms PI4Kβ1β2 triggers SA signaling, suggesting them to be negative regulators of SA signaling (Sasek et al., 2014). For more information about the connection between hormones and phospholipid signaling see the review (Janda et al., 2013).

The interest of importance is to find out the particular isoform(s) of PLD responsible for the effect of n-butanol. Based on this, we performed the in silico experiment to find the possible PLD isoforms involved in SA signaling (Figure 7). We investigated the transcription of all PLD isoforms in the publicly available database, Genevestigator (Hruz et al., 2008), in response to SA, BTH (benzothiadiazole; a functional analog of SA), EF-Tu, flg22, pep2 (well described PAMPs) triggering SA signaling. All studies, which we included to this analysis, were performed on the A. thaliana ecotype Col-0. The screening showed that the promising candidates could be PIP₂-dependent isoforms from the PLDβ, PLDγ and PLDζ families (Figure 7). We can speculate that they could be connected with the above mentioned PI4K activity, producing precursor for PIP₂ biosynthesis. The evidence that PLD isoforms exhibit redundant effect upon Pseudomonas syrigae infection was provided recently by Johansson et al. (2014).

The aim of this part of our study was to find the metabolic compounds, which are affected by n-butanol and involved in the SA pathway. For this purpose, we used the mass spectrometry-based metabolomic fingerprinting described by Vaclavik et al. (2013). A very important output from the screening is the evidence that t-butanol treatment, used in our study (but also by other researchers studying PLD function) as a negative control to n-butanol, is really biologically “inactive.” This is based on the fact that the PCA analysis of the samples determined no differences between control samples vs. t-butanol and the SA treated samples vs. t-butanol (i.e., their metabolomes were similar). On the other hand, the samples treated with n-butanol clustered very well (Figure 5). We were able to identify several characteristic metabolites for the samples treated with n-butanol. We were also able to predict the molecular formulas and we proposed their tentative identification (Table 1). It is not surprising that a higher amount of SA and SA-hexoside was found in the samples treated by SA. In fact, we were able to identify only a few metabolites affected by SA, probably due to the relatively short time of treatment. It was shown that BTH causes significant alterations in metabolome 24 h after treatment, while after 4 h the changes were much less significant (Hien Dao et al., 2009). We chose the 6 h time-point to get the information in the same time frame as we used for the transcriptional study (Figure 1). Interestingly, n-butanol had a higher impact on the A. thaliana metabolome compared to the SA treatment. Seventeen metabolites were affected by SA and 34 by n-butanol (Figure 6).

We were able to predict structure for several metabolites that changed upon treatment. The heat map representing the changes of 61 metabolites supplemented with RT-m/z and the putative names of several predicted compounds is shown in Figure 6. Interestingly, the behavior of phenylalanine, a precursor of SA biosynthesis, exhibits a similar pattern as PR-1 transcription upon treatment. Another two compounds exhibit patterns similar to PR-1 (RT_m/z 7.89_804.5 and 0.69_536.1; Figure 6). These compounds could be interesting targets of further research.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.