General view of the Arabidopsis transcriptome under SO2 fumigation
A total number of 22 130 genes, including their different splice variants, were identified for WT plants in this experiment: 23 232 for WT[+], 22 424 for SO-KO, and 22 255 for SO-KO[+]. Quantile-normalized, log2-scaled and nonbaseline-transformed RPKM of these transcripts were widely spread (Fig. S1). Each analyzed sample consisted of 10 independently prepared RNAs from a total of 20 treated plants. The biggest spread of RPKM, and therefore the greatest change in transcripts, was detected for WT vs SO-KO[+], followed by SO-KO vs SO-KO[+]. A narrower distribution, indicating a weaker response to SO2 or the genotypic modification, was identified in WT vs WT[+], WT vs SO-KO and SO-KO vs WT[+]. Fig. 1(a,b) present the amounts of differentially expressed genes in relation to the total number of transcripts (different splice variants included) using data within a fivefold-change cutoff, verified with DEGseq (Table S1). With the fivefold-change threshold, between 0.4 and 1.6% of genes were differentially expressed for all condition pairs. Approx. 60% of the differentially expressed genes were up-regulated (Fig. 1a), whereas c. 40% were down-regulated (Fig. 1b).
Figure 1. Differentially expressed transcripts and Venn diagrams presenting intersections after combining the four different Arabidopsis thaliana comparison pairs: wildtype (WT) vs SO2-fumigated WT (WT[+]), sulfite oxidase knockout (SO-KO) vs SO-KO[+], WT vs SO-KO and WT[+] vs SO-KO[+]. The numbers and percentages of differentially expressed transcripts for fivefold up-regulated (a) and down-regulated (b) genes presented the highest abundance of up- and down-regulated transcripts in SO-KO vs SO-KO[+]; the lowest number was observed for WT vs WT[+]. Venn diagrams represent numbers of fivefold up-regulated (c) and down-regulated (d) transcripts when different comparisons overlap. The Venn diagram for up-regulation showed two transcripts which are solely unregulated in SO-KO vs SO-KO[+] and WT vs SO-KO. [+] indicates SO2 fumigation.
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Venn diagrams (Fig. 1c,d) were created to investigate several hypotheses concerning the biological evidence of the genotypic variation in SO-KO and the effects caused by SO2 treatment. The Venn diagrams show the number of fivefold up- (Fig. 1c) or down-regulated (Fig. 1d) transcripts found in different treatment–genotype combinations and which of those genes were differentially expressed in different condition pairs.
First, we asked if knocking out the SO leads to the same change in transcripts and transcript numbers as does fumigation of the WT. If this were the case there would be more transcripts in the overlap of WT vs WT[+] and WT vs SO-KO and fewer in the section of solely regulated transcripts. We identified 11 transcripts for up-regulation and 10 for down-regulation in the overlapping section. For the genotypic comparison, we found 102 transcripts up-regulated and 65 transcripts solely down-regulated, and there were 44 up-regulated transcripts and 29 down-regulated transcripts for WT vs WT [+]. These findings ran counter to our hypothesis that the gene expression changes caused by SO knockout were similar to those caused by SO2 fumigation. This result was, however, in line with the second assumption that we would not find any intersections for WT vs SO-KO and SO-KO vs SO-KO[+], because SO gene knockout and fumigation of SO-KO would not have any regulated transcripts in common, and interpretation of our data validated this expectation. Thirdly, SO is predicted to play a key role in SO2 detoxification, and we therefore hypothesized a higher number of regulated transcripts in SO-KO[+] than in WT[+], since the knockout of SO inhibits SO-mediated SO2 protection. This may further induce other processes. Our findings of 45 up- and 38 down-regulated transcripts in WT vs WT[+] and 287 up- and 161 down- regulated transcripts in SO-KO vs SO-KO[+] confirmed this hypothesis. Only 10 transcripts for up-regulation and one for down-regulation were identified as commonly regulated. Fourthly, we expected that SO-KO plants would have to use different defense mechanisms to detoxify SO2 than those used by WT plants. If this were the case, we would therefore find only very few transcripts that were commonly up- or down-regulated in WT vs WT[+] and WT[+] vs SO-KO[+]. Transcripts in the overlap represented genes that were already highly regulated in WT[+] and even more highly regulated in SO-KO[+]. This was a small common transcript set resulting from the different transcript usages of WT[+] and SO-KO[+] during fumigation. For up-regulation we identified two transcripts: AT5G44420, which belongs to the plant defensin family (plant defensin 1.2), and AT3G44310, encoding the nitrilase 1. The genotypic comparison (WT vs SO-KO) marked the defensin as an unregulated transcript (1.19-fold), whereas the nitrilase was significantly regulated (3.97-fold) in SO-KO vs SO-KO[+], but this was not visible in the fivefold comparison. For down-regulation there was no transcript detectable in the intersection. Verification of this hypothesis led to the fifth expectation, that we would find more genes regulated in SO-KO vs SO-KO[+] than in WT[+] vs SO-KO[+], but overall a high number of commonly regulated transcripts. Counting the transcripts for SO-KO vs SO-KO[+] revealed 297 up-regulated and 162 down-regulated transcripts. For WT[+] vs SO-KO[+] we found 276 up-regulated and 170 down-regulated transcripts: 249 transcripts were commonly regulated in SO-KO vs SO-KO[+] and WT[+] vs SO-KO[+], and a total of 408 transcripts were solely regulated. These results confirm a high number of commonly regulated transcripts (50%), but calculations did not verify our hypothesis of a much higher percentage of regulated genes in SO-KO vs SO-KO[+] than in WT[+] vs SO-KO[+].
To obtain further insights into the molecular mechanisms affected by knocking out SO, we identified differentially expressed genes by comparing WT and SO-KO with and without SO2 fumigation. Significantly regulated genes with a greater than fivefold transcriptional change were selected and significance was determined with the DEGseq tool. We applied hierarchical clustering (Fig. 2a) to further delineate associated gene groups with similar expression profiles (Fig. 2b). Most of the transcriptional changes were induced after SO2 fumigation in the SO-KO mutant plants, represented by the largest clusters, IV and VII. In total we were able to identify eight individual gene expression clusters numbered from I to VIII. For further analyses we used the top 20 regulated transcripts and GO analyses for each identified cluster.
Figure 2. Hierarchical clustering of fivefold regulated transcripts and profile plots of selected clusters. Colors of the cluster in (a) were assigned based on the normalized, log-scaled RPKM (reads per kilobase of exon model per million mapped reads) values (significance tested using DEGseq). In panel (b), expression profiles of transcripts involved in these eight clusters are depicted. Cluster IV shows transcripts which are solely up-regulated in the SO2-fumigated Arabidopsis thaliana sulfite oxidase knockout (SO-KO[+]); cluster VII includes those which are mutually down-regulated in SO-KO[+]. Both clusters presented the highest number of involved transcripts.
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Application of SO2 to WT plants should lead to several transcriptional changes, but because of the dosage of 600 nl l−1 used and because SO acts as a detoxificating enzyme, we hypothesized a smaller reaction than we would expect for SO-KO treatment. GO analysis of fivefold regulated transcripts in WT vs WT[+] was in line with this expectation by revealing the lowest number of GO terms. Transcripts could be assigned to the categories biological process (16 genes, 36%) and cellular component (29 genes, 64%). We identified up-regulated transcripts for WT vs WT[+] in clusters I, II, and III; down-regulation was detected in clusters V, VI, and VIII. The top 20 transcripts in cluster II included four transcripts associated with ribosomal and translation processeses, which indicated an influence of SO2 fumigation on mRNA synthesis regulation. Cluster II contained transcripts which showed their highest abundances in WT[+] only and which therefore revealed a moderate reaction of WT plants to SO2 with transcriptional adaptation and thus up-regulation of transcripts belonging to ribosomal processes.
Hypothetically, treatment of SO-KO plants with SO2 should lead to higher and different transcriptional responses compared with treated WT plants, as this was already verified by Venn diagrams. Additionally, GO analyses of fivefold regulated transcripts showed the highest numbers of significantly enriched transcripts (P < 0.1) in SO-KO vs SO-KO[+] (Fig. S2), which was also clear from the Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses (Fig. S3). GO terms enriched in SO-KO vs SO-KO[+] were principally associated with the terms molecular function and biological process. Up-regulation of transcripts was identified in clusters III, IV, V and VI, while down-regulation was identified in clusters I and VII. Transcript functions for up-regulation in SO-KO vs SO-KO[+] differed from those identified as up-regulated for WT vs WT[+]. The WT[+] top 20 included the greatest number of transcripts associated with transcriptional regulation (cluster I, II), whereas the SO-KO[+] top 20 included transcripts involved in defense processes (cluster IV) and peptidase activity (cluster VI). The top 20 of cluster IV contained nine transcripts associated with defense, including defensins (AT5G44420, AT5G44430, AT2G26020 and AT2G26010), GSTs (AT1G02930, AT1G02920, AT4G02520) and peroxidase CB (AT3G49120).
Transcriptional regulation of enzymes related to sulfur metabolism: effects resulting from SO2 and/or genotypic variation of SO knockout
We recently reported enzyme activities and S-metabolites of A. thaliana WT and transgenic lines subjected to SO2 fumigation (Randewig et al., 2012). Aliquots of the same plant material were used in this study for the RNAseq experiment. This combination of transcriptome data with enzyme activities and metabolite concentrations provided new insights into the regulation of sulfate assimilation and related metabolic pathways. We hypothesized that excess SO2, especially in the absence of SO, would lead to transcriptional down-regulation of the enzymes producing sulfite and transcriptional increases in at least some enzymes mediating reactions downstream of sulfite to sequester the excess organic sulfur produced. The following description and discussion of the results are summarized in Fig. 3, which presents the regulation of genes for SO-KO vs SO-KO[+]. Raw data and fold changes are presented in Table S2.
Figure 3. Alterations in the sulfur metabolism for the Arabidopsis thaliana sulfite oxidase knockout (SO-KO) vs SO2-fumigated SO-KO (SO-KO[+]) comparison. Regulation of sulfur metabolism-associated genes for SO-KO[+] is presented using different colors, as described in the color range. Gene name abbreviations are described in Table S2. To generate this scheme no fold change was applied to the expression values; mostly the glutathione S-transferases (GSTs) and the sulfotransferase (SOT) show a strong reaction in the SO-KO[+], in particular in the up-regulated transcripts.
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Sulfate is taken up by the root and transported via the xylem stream into the leaves for further assimilation. Required sulfate transporters (SULTR) are divided into subfamilies on the basis of their protein sequence similarities (Hawkesford, 2003; for review, see Davidian & Kopriva, 2010). With the exception of SULTR3;1, none of the sulfate transporters was significantly regulated in leaves as analyzed by the DEGseq tool. However, from the group two of the SULTR, responsible for long-distance transport and localized in xylem parenchyma cells, SULTR2;1 transcript abundances were similar in the nonfumigated plant material, but increased in WT[+] by 30% or decreased in SO-KO[+] by 50%. Moreover, the expression of SULTR2;2 was down-regulated threefold in SO-KO plants in the fumigation experiment, which possibly reflects a reduction in sulfate uptake and transport. From the SULTR of group four – suggested to function in vacuolar sulfate remobilization to the cytoplasm in roots and leaves (Kataoka et al., 2004) – SULTR4;2 mRNA amounts were two- and 10-fold decreased during fumigation in WT and SO-KO rosettes, respectively. This led us to the hypothesis that, particularly in SO-KO, sulfite cannot be oxidized to sulfate and hence there is no requirement for sulfate to be introduced into the assimilatory stream via SULTR2 and SULTR4.
For assimilation, sulfate has to be activated by the ATP sulfurylase (APS), which catalyzes the first step in this pathway. Determination of APS transcript abundances revealed that APS1 was the most abundant (between 244 and 349 quantile-normalized RPKM; Table S2) and the only isoform that was significantly down-regulated (1.3-fold) in SO-KO[+] and when comparing WT[+] and SO-KO[+]. This supported the hypothesis that sulfate reduction is down-regulated transcriptionally if excess SO2 is present. The activated sulfate is partly converted into PAPS (3′-phosphoadenosine 5′-phosphosulfate) by one of the four isoforms of APS kinase (APK). Compared with all other samples, a significant decrease (two- to threefold) of APK1-3 mRNA was detected only in SO-KO[+] plants. Plants possess large numbers of sulfotransferases (SOTs) that are responsible for sulfonation of small molecules by using PAPS, cysteine, or other reduced S-compounds, as an important component of plant stress responses (Klein & Papenbrock, 2004). SOTs thus can sequester organic sulfur. Fumigation of SO-KO led to an almost 13-fold increase of SOT12 transcript amounts. SOT12 is known to be stress-inducible and has been described to confer pathogen resistance in A. thaliana by sulfonation of salicylic acid (Baek et al., 2010).
The majority of activated sulfate is metabolized further on by APS reductase (APR). Three isoforms described in the literature are localized in the chloroplast. APR is known to be the key enzyme of the sulfate assimilation pathway (Kopriva & Rennenberg, 2004) and is regulated transcriptionally and post-translationally, respectively (Kopriva & Koprivova, 2004). Our data confirm these findings: in WT plants, 600 nl l−1 SO2 did not change the transcript abundances of any APR isoform or splice variant. The enzyme activity decreased significantly (Randewig et al., 2012), presumably as a result of feedback inhibition (Vauclare et al., 2002). In SO-KO control plants, APR1, APR2 and APR3 transcripts were increased significantly compared with WT control samples (Table S2). Fumigation of these SO-KO plants led to a dramatic decrease in both transcript abundance (Table S2) and enzyme activity levels (Randewig et al., 2012). The strong down-regulation of APR reflects a tight control of sulfite synthesis at the transcriptional level as well as at the post-translational level. Such a negative feedback inhibition of APR mediated by increasing amounts of thiols (Vauclare et al., 2002) has been discussed previously (for a review, see Kopriva & Koprivova, 2004; Davidian & Kopriva, 2010). Moreover, GSH itself is involved in cell proliferation of cell cultures and lateral roots of Arabidopsis (Vivancos et al., 2010) as well as in meristem development and embryo maturation of Brassica (Stasolla et al., 2008) by changing the transcript abundance of definite genes. This has also been proposed by Szalai et al. (2009) for abiotic stress conditions either via H2O2 or GSH/ oxidized glutathione (GSSG) in general.
Sulfite reductase (SiR) converts sulfite into sulfide and is a single copy gene. O-acetylserine(thiol)lyase (OASTL, OASx, CYSC1) and serine acetyltransferase (SAT, Seratx;x) together form the cysteine synthase complex (Wirtz et al., 2010), which produces organic sulfocompounds from sulfide (Fig. 3). For SIR transcripts, no significant regulation was observed for WT and SO-KO plants after fumigation. OASTL and SAT enzymes occur as different isoforms, which are located in several cellular compartments. OASB and Serat2;1 are localized in chloroplasts, Serat2;2, OASC and CYSC1 were described to act within the mitochondria, and OASA1, OASA2, Serat1;1, Serat3;1 and Serat3;2 are cytosolic enzymes (Jost et al., 2000; Yamaguchi et al., 2000; Kawashima et al., 2005). We found that, after fumigation of SO-KO, only transcripts encoding the chloroplastidic SERAT2;1 and mitochondrial CYSC1 were significantly increased. This provokes the hypothesis that S-assimilation, and therefore cysteine synthesis, is possibly induced after fumigation. In summary, OASTL and SAT transcript abundances showed that additional sulfur was channeled into the direction of cysteine production after SO2 fumigation, which held true for both fumigated WT and SO-KO plants.
Organic sulfur may flow towards methionine via cystathione or towards GSH. Cysteine gamma-synthase (CGS/MTO1) is involved in the conversion of cysteine into cystathionine. CGS sequencing data did not show any alterations after fumigation regarding WT and SO-KO samples. Cystathionine beta-lyases (CBL and CORI3) are involved in the conversion of cystathionine into homocysteine. For SO-KO and SO-KO[+], significantly lower transcript abundances (roughly fivefold) were found for all of the three CORI3 splice variants. Moreover, after fumigation of WT plants, CORI3 transcripts were up-regulated. CGS was expressed at a higher level than CBL (Table S2). RNAseq data showed only minor alterations in methionine synthase (MS) and S-adenosylmethionine synthetase (SAM-synthetase) transcripts. MS converts homocysteine into methionine, which could be used by SAM-synthetase to generate S-adenosylmethionine as a methyl group donor in numerous transmethylation reactions (Peleman et al., 1989). Only MS2 displayed a twofold decrease in SO-KO[+] compared with SO-KO, and a threefold decrease in SO-KO[+] compared with WT [+]. Based on the transcriptional profile, the excess SO2 did not flow towards methionine.
Gamma glutamylcysteine synthase (γ-ECS) catalyzes the first step in GSH biosynthesis. We identified a small increase in γ-ECS transcript amounts for SO-KO[+]. Glutathione synthetase (GSHS) produces GSH from γ-glutamylcysteine and glycine. GSHS transcripts showed an average abundance of 30 RPKM for WT, WT[+] and SO-KO. Transcript abundances for SO-KO[+] were significantly higher (2.6-fold) compared with other samples, indicating that the higher amounts of produced γ-glutamylcysteine are converted into GSH. Glutathione reductase (GR) reduces GSSG to GSH. GR1 had enhanced transcript abundance, especially in SO-KO[+]. Transcript abundances of SO-KO and SO-KO[+] were higher than those measured for WT and WT[+]. Higher amounts of GR1 transcripts in SO-KO[+] samples may indicate that higher amounts of GSSG have to be reduced back to GSH during the SO2 fumigation process. Based on the transcriptional profile, the excess SO2 flowed towards GSH. These transcriptional up-regulations of several enzymes in GSH biosynthesis fitted well with the increased amount of γ-glutamylcysteine and GSH measured in these samples previously (Randewig et al., 2012) and confirmed the hypothesis of an enhanced S-flux into the S-assimilation stream. However, accumulation of GSH above a specific threshold could be dangerous to plant cells, causing increased oxidative stress in tobacco (Creissen et al., 1999) and affecting photosynthesis, growth and sulfur metabolism in poplar (Herschbach et al., 2010). Moreover, GSH is demonstrated to be the sulfur donor in the biosynthesis of glucosinolates in Arabidopsis (Schlaeppi et al., 2008; Geu-Flores et al., 2011). However, in our investigation, transcript data of the key enzymes processing GSH conjugates into glucosinolate and camalexin pathways (γ-glutamyl peptidases GGP1 (AT4G30530) and GGP3 (AT4G30550)) were not altered or even slightly decreased (Table S1), suggesting that formation of glucosinolates was only a minor sink for excess sulfur, as was also shown in previous studies with Arabidopsis (Van der Kooij et al., 1997). Therefore a supplemental mass storage for the reduced sulfur should be postulated.
Glutathione S-transferase (GST) proteins are arranged in different subfamilies, GSTF, GSTL, GSTT, GSTU and GSTZ (Frova, 2003). In all GST subfamilies, isoform transcripts seemed to be regulated after fumigation with SO2, which was especially obvious for SO-KO[+], with an up-regulation of 10-fold and higher. GST6 (AT1G02930) was 10.5-fold up-regulated in response to the fumigation stress.
In WT plants, excess sulfite can be detoxified by oxidation to sulfate (Fig. 3). Sulfite oxidase (SO) counteracting the APR is supposed to be the most effective tool within the plant cell for removing excess amounts of sulfite (Brychkova et al., 2007; Lang et al., 2007; Randewig et al., 2012). As shown very recently using microarrays, fumigation of grape berries with 1–3 μl l−1 SO2 surprisingly resulted in a decrease of SO transcripts (Giraud et al., 2012). In our RNAseq experiment, transcript numbers of all three different SO splice variants were determined. SO splice variant 1 (SO-1) showed the highest transcript abundance for WT and WT[+] (60 and 57 normalized RPKM) in comparison to the two additional splice variants (0.07 and 0.16 normalized RPKM for SO-2, and 0.2 and 0.45 normalized RPKM for SO-3). SO-KO plants lacked detectable amounts of SO protein, as determined by immunoblot analysis, because of the T-DNA insertion within this gene (Lang et al., 2007); consequently, no SO activity was detectable (Randewig et al., 2012). Activity measurements applied in Randewig et al. (2012)showed no alterations in SO activity for WT[+]. RNAseq confirmed this result (Table S2). Surprisingly, RNAseq data showed that in SO-KO the SO transcripts were detectable. However, a closer look into the sequencing data (i.e. mapping of sequence reads to Arabidopsis mRNA sequences) showed that SO-KO did not produce a functional transcript. Although the reading frame for the transcript is disrupted as a result of the T-DNA insertion and the resulting mRNA is thus noncoding, the transcriptional response apparently attempts to enhance SO production (Figs S4, S5). For SO-1 we detected 2.5-fold (and for SO-2 c. 16-fold) increased transcript abundance after fumigation with 600 nl l−1 SO2 for 60 h. At present, the physiological relevance of the different splice variants is unclear. The current interpretation of SO-1 and SO-2 abundances could only be alternative splicing as known from other eukaryotic systems (Graveley, 2005; Smith, 2005).
In the present study, SO2 at a concentration of 600 nl l−1 was applied to Arabidopsis WT and SO-KO for 60 h, which represents neither fully acclimated plants nor immediate stress responses. Before the current investigations of mRNA alterations, S-metabolism-related enzyme activities and S-metabolite concentrations were determined using aliquots of the same plant material (Randewig et al., 2012). Changes in S-metabolite concentrations of WT and SO-KO plants in response to SO2 were related to enzyme activities and absolute transcript abundances of mRNA. Removal of excess sulfate by conversion into sulfur-containing compounds via the sulfur assimilatory stream in response to SO2 exposure – as concluded from S-associated enzyme activities (Randewig et al., 2012) – was supported by transcript data of the present investigations. These results make the hypothesis of a tight coregulation between SO and APR plausible, meaning there is a role in keeping the intracellular sulfite pool constant at a low concentration.
To prevent damage from atmospheric SO2, additional mechanisms play a role in planta as well. In this RNAseq experiment, two other factors that are possibly involved in sulfite detoxification, and which therefore assist in coregulation of APR and SO, were identified: PDFs, a group of small cysteine-rich peptides, and a peroxidase which is localized in the apoplastic space (Shah et al., 2004). Up-regulation of PDFs after fumigation seems to be a strikingly new response to excess SO2 concentrations. Owing to the strong reaction of WT and SO-KO plants to SO2, defensins may function in both processes: excess sulfur storage and sulfite detoxification. Another outstanding finding of this RNAseq analysis is the up-regulation of transcripts encoding a peroxidase (peroxidase CB, AT3G49120). As a result of the apoplastic localization, this enzyme may function as a first line of defense in the detoxification of SO2. This hypothesis was advanced previously (Pfanz et al., 1990; Pfanz & Oppmann, 1991), but was never tested at the molecular level. The up-regulation of peroxidase CB in SO-KO[+] may indicate it has some role in removing sulfite before it enters the cytoplasm. Both topics will be of great interest in our upcoming investigations.
Our transcript analyses exhibited a set of regulated genes amounting to c. 5% (cluster analyses). Giraud et al. (2012) reported a strong influence of 1–3 μl l−1 SO2 on grape berries using microarray analyses. Although 600 nl l−1 SO2 is a nontoxic dosage for Arabidopsis (Hänsch & Mendel, 2005), the first responses at the mRNA level were detected in WT[+], though to a lesser extent than detected in SO-KO [+]. WT plants showed a strong and fast reaction to SO2 (Fig. 1), whereas SO-KO[+] presented the highest RPKM values of several transcripts and a reaction involving a much broader range of transcripts. In contrast to microarray approaches, RNAseq enabled us to obtain details on splice variant gene expression and therefore even allowed SO transcript observations for SO-KO[+]. Although the resulting protein products are not functional, as determined in SO enzyme activities for SO-KO and SO-KO[+] (Randewig et al., 2012), plants seem to have a driving force that categorically tries to produce SO when SO2 is present.
In conclusion, RNAseq of WT[+] and SO-KO[+] and their controls not only gave quantitative insights into the transcriptional response of Arabidopsis plants to SO2 fumigation, but also permitted some first insights into novel putative mechanisms for SO2 detoxification beyond SO activity and transportation of excess sulfite into the S-assimilation stream. Mainly based on SO-KO, we present in Fig. 4 our new working model for plant reactions to excess SO2, including the hypothesized SO2 detoxification mechanisms.