General Regulatory Patterns of Plant Mineral Nutrient Depletion as Revealed by serat Quadruple Mutants Disturbed in Cysteine Synthesis

Molecular Plant Volume 3 Number 2 Pages 438 466 March 2010 RESEARCH ARTICLE General Regulatory Patterns of Plant Mineral Nutrient Depletion as Revealed by serat Quadruple Mutants Disturbed in Cysteine Synthesis Mutsumi Watanabe a,b, Hans-Michael Hubberten b, Kazuki Saito a,c and Rainer Hoefgen b,1 a Graduate School of Pharmaceutical Sciences, Chiba University, 1 33 Yayoi-cho, Inage-ku, Chiba 263-8522, Japan b Max-Planck-Institut fuer Molekulare Pflanzenphysiologie, Wissenschaftspark Golm, Am Muehlenberg 1, 14476 Potsdam-Golm c RIKEN Plant Science Center, Tsurumi-ku, Yokohama 230 0045, Japan ABSTRACT Sulfate is an essential macronutrient for plants. Plants have developed strategies to cope with sulfate deficiency, and other nutrient ion limitations. However, the regulation of these adaptive responses and the coordinating signals that underlie them are still poorly characterized. O-acetylserine (OAS) is a marker metabolite of sulfate starvation and has been speculated to have a signaling function. OAS is synthesized by the enzyme serine acetyltransferase (SERAT), which is encoded by five distinct genes in Arabidopsis. We investigated quadruple knockout mutants of SERAT that retained only one functional isoform. These mutants displayed symptoms of sulfate starvation. Furthermore, some of them displayed phenotypes typical of prolonged sulfate starvation, in particular, developmental programs associated with senescence or stress responses. Thus, we compared metabolite and transcriptome data from these mutants with N-, P-, K-, and S-depleted plants. This revealed many similarities with general nutrient-depletion-induced senescence (NuDIS), indicating the recruitment of existing regulatory programs for nutrient-starvation responses. Several candidate genes that could be involved in these processes were identified, including transcription factors and other regulatory proteins, as well as the functional categories of their target genes. These results outline components of the regulatory network controlling plant development under sulfate stress, forming a basis for further investigations to elucidate the complete network. In turn, this will advance our broader understanding of plant responses to a range of other nutrient stresses. Key words: Abiotic/environmental stress; ion/metabolite sensing; senescence; functional genomics; Arabidopsis; sulfur. INTRODUCTION In addition to uptake of CO 2 and H 2 O for photosynthetic production of carbohydrates, plants are dependent on nutrient ion uptake from the soil. Various macronutrients (N, P, K, and S) and micronutrients (Fe, Cu, Mo, Se, Zn, and others) are necessary in balanced proportions for optimal growth performance and hence optimal crop yield (for review, see Amtmann and Blatt, 2009; Amtmann and Armengaud, 2009; Hänsch and Mendel, 2009). Plants are able to adapt their metabolism to imbalances in nutrient ion supply in a highly dynamic manner. Plant growth, vigor, and yield are compromised to varying degrees, depending on the severity of the malnutrition. Adaptations occur in both directions, allowing plants to cope with undersupply upon nutrient depletion or oversupply leading to adverse effects such as heavy metal toxicity. As multicellular organisms, plants rely on proper allocation of nutrient ions and their assimilated products both between organs and within the cell. Furthermore, developmentally driven reallocation processes that are coupled to developmental senescence occur between source and sink organs, as well as during the processes of floral induction and fruit ripening (Gregersen et al., 2008; Howarth et al., 2008; Masclaux-Daubresse et al., 2008; Schildhauer et al., 2008). Mechanisms to cope with variations in the availability of nutrient ions include varying uptake capacities and assimilation 1 To whom correspondence should be addressed. E-mail hoefgen@mpimp -golm.mpg.de, fax, +49 (0)331 567898205. ª The Author 2009. Published by the Molecular Plant Shanghai Editorial Office in association with Oxford University Press on behalf of CSPP and IPPE, SIBS, CAS. doi: 10.1093/mp/ssq009 Received 25 November 2009; accepted 19 January 2010

Watanabe et al. d General Regulatory Patterns Revealed by serat Quadruple Mutants 439 rates, and remobilization of internal reserves. In addition to these specific responses, which imply sensing mechanisms of the ion status or of downstream metabolites, ionic imbalances usually affect multiple metabolic processes, leading to pleiotropic effects. Thus, changes in ion homoeostasis lead to systemic responses, affect downstream metabolic processes, and eventually alter whole-plant physiology (Wang et al., 2003; Scheible et al., 2004; Morcuende et al., 2007; Hesse and Hoefgen, 2008; Armengaud et al., 2004, 2009; Tschoep et al., 2009). At the macroscopic level, nutrient deficiencies usually result in yield penalties, effects on chlorophyll content, and reduced photosynthetic carbon fixation, due to a decline in photosynthetic capacity, growth retardation, protein degradation, and RNA degradation (Nikiforova et al., 2003; Armengaud et al., 2004; Scheible et al., 2004; Morcuende et al., 2007; Amtmann and Armengaud, 2009). Severe nutrient ion deficiencies result in stress responses such as anthocyanin accumulation, senescence, early flowering, and early seed set (Spiller et al., 1987; Winder and Nishio, 1995; Nikiforova et al., 2003; Scheible et al., 2004; Cao et al., 2006; Mishina et al., 2007; Morcuende et al., 2007; Hoefgen and Nikiforova, 2008). Thus, plants show a broad spectrum of molecular and metabolic responses, depending on ion availability, ranging from reversible adaptive processes under mild deficiency conditions to irreversible emergency programs in response to extreme starvation, when remaining nutrients are reallocated for seed formation, eventually leading to plant death. The term nitrogen depletion induced senescence (NDIS) was coined to describe such nutrient-driven senescence processes observed in maize plants starved of nitrogen (Schulte auf m Erley et al., 2007; Schildhauer et al., 2008). We propose that this term could usefully be broadened to nutrient deficiency induced senescence (NuDIS), as comparable effects can be observed for all types of nutrient depletion, and not just nitrogen. Such NuDIS appears to be clearly differentiated from developmentally induced senescence (DEVS), which occurs as part of the normal plant lifecycle or can be induced by artificial darkening (Lim et al., 2007). Systems biology approaches have been employed to unravel plant responses to nutrient depletion and to discriminate specific from pleiotropic effects at multiple levels (Nikiforova et al., 2003; Hirai et al., 2003, 2005; Maruyama-Nakashita et al., 2003; Wang et al., 2003; Scheible et al., 2004; Morcuende et al., 2007). Data have been accumulated that catalog changes in the transcriptome and the metabolome in response to depletion, starvation, or re-supply of single ions (Maruyama- Nakashita et al., 2006; Doerner, 2008; N/P/Fe reviewed in Yuan et al., 2008; Vidal and Gutiérrez, 2008; Giehl et al., 2009; Gojon et al., 2009). However, due to the complexity of the underlying responses, we are far from a comprehensive understanding of these events. Our goal is to understand the functions and mechanisms underlying the alterations in gene expression and metabolite content. In particular, little is known about the mechanisms that link immediate ion depletion responses to changes in developmental programs that eventually lead to downstream effects such as NuDIS. The transcriptional and metabolic responses of plants to sulfur supply limitation have been investigated by several groups (Nikiforova et al., 2003, 2004, 2005a, 2005b; Maruyama-Nakashita et al., 2003; Hirai et al., 2003, 2005). Apart from sulfurspecific mechanisms, alterations in C/N/S balance, amino acid content, photosynthesis, redox status, plant defense, cell wall structure, translation, and carbohydrate metabolism were observed. A major impact on transcript and metabolite levels of various metabolic pathways was observed when plants were in an advanced state of sulfur starvation. Genes and metabolites related to metabolism of glucosinolates, flavonoids, lipids, jasmonate, auxin, and nucleotides, as well as redox and oxidative stress homeostasis, are affected by long-term sulfur starvation, and several regulatory models for control of specific aspects of sulfur starvation have been proposed. Finally, sulfur starvation forces the plant to switch into a rescue program, investing all its limited resources in reproduction. This process displays a wide overlap with general features of NuDIS, such as growth retardation, altered amino acid content, and chlorosis. Similarly, the question arises how, and through which signals, are imbalances in sulfate metabolism perceived to trigger general developmental response programs, and how do these compare with responses to other nutrient ions? Currently, the best candidate as a signal molecule, if not sulfate itself, is the sulfate-starvation marker, O-acetylserine (OAS), which quickly builds up upon cellular sulfate starvation because sulfide, the co-substrate for consumption of OAS by O-acetylserine thiol lyase (OASTL), is missing. In fact, feeding of OAS to Arabidopsis induced low-s responsive genes such as sulfate transporters (SULTR) and adenosine 5#-phosphosulfate reductase (APR) (Koprivova et al., 2000; Hesse et al., 2003; Hirai et al., 2003). However, the involvement of OAS in the coordination of more general metabolic and developmental adaption has not yet been studied in detail. OAS and sulfide are the substrates for the synthesis of cysteine and thus are fundamental for the homeostasis of reduced sulfur in the plant (Figure 1). OAS is synthesized by serine acetyltransferase (SERAT), which is active when associated with OASTL in the cysteine synthase complex (CSC) (Ruffet et al., 1994; Droux et al., 1998). OASTL in its unbound form catalyzes the synthesis of cysteine from OAS and sulfide, and becomes inactivated when bound to the complex. The CSC thus constitutes a branch point where reduced sulfur gets incorporated into a carbon backbone (Figure 1A). The association state and activities of SERAT and OASTL are strongly regulated by their substrates and products (Berkowitz et al., 2002; Wirtz and Hell, 2006). The importance of the proper assembly of the complex was elucidated by experiments manipulating the individual components of the CSC (Riemenschneider et al., 2005; Wirtz and Hell, 2007; Haas et al., 2008; Heeg et al., 2008; Watanabe et al., 2008a; Krueger et al., 2009). In order to further our understanding of how sulfate metabolism might be linked to NuDIS, we investigated plants with impaired sulfur assimilation due to the controlled knockout of distinct SERAT isoforms. Quadruple serat mutants, which

440 Watanabe et al. d General Regulatory Patterns Revealed by serat Quadruple Mutants have only one remaining functional isoform, displayed slightly lower or unchanged OAS and thiol levels (Watanabe et al., 2008a). However, the mutants with the strongest impact on SERAT activity showed retardations in growth most likely caused by limitations in sulfur assimilation. Presumably, these mutants have switched to a different developmental program upon sensing the disturbance in their sulfur status. We investigatedtheeffectofthequadrupleseratknockouts onplantmetabolism at the metabolic and molecular levels, with the aim of elucidating the role of putative signals, such as OAS, cysteine, and glutathione (GSH), in the activation and coordination of the response of the plant to sulfur limitation. In an attempt to link these results to general features of NuDIS, we also related our findings to results obtained for plants subjected to various nutrient ion starvations, namely N, P, K, and S (Nikiforova et al., 2003, 2004, 2005a, 2005b; Wang et al., 2003; Armengaud et al., 2004, 2009; Scheible et al., 2004; Hammond et al., 2007; Morcuende et al., 2007; Tschoep et al., 2009). RESULTS Quadruple serat Mutants Display Altered Physiological Processes, Including Growth Retardation and Slight Chlorosis Figure 1. Sulfur metabolism in Arabidopsis. (A) Sulfate reduction and assimilation. Sulfate (SO 2 4 ) is taken up by sulfate transporters (SURTL), activated by ATP sulfurylase (ATPS) to adenosine 5#-phosphosulfate (APS), which is further converted to sulfite (SO 2 3 ) by APS reductase (APR) and 3#-phosphoadenosine 5#-phosphosulfate (PAPS) by APS kinase (APK). PAPS serves as a substrate for sulfotransferases producing numerous sulfated metabolites. Sulfite is then reduced to sulfide (S 2 ) by a ferredoxindependent sulfite reductase (SiR). In a side reaction, sulfite is also utilized to synthesize sulfolipids for the photosynthetic chloroplast membranes. Cysteine synthesis takes place via O-acetylserine thiol lyase (OASTL), using O-acetylserine (OAS) and sulfide. Serine acetyltransferase (SERAT) generates OAS using serine and acetyl-coa. Cysteine is the common sulfide precursor of numerous downstream products such as methionine, glutathione (GSH), and S-adenosylmethionine (SAM). All these metabolites are essential for diverse metabolic processes and thus determine plant growth and development, plant performance, and eventually yield. The number of isoforms in each family is shown in brackets. (B) Sub-cellular organization of cysteine synthesis in Arabidopsis. Schematic representation of three OASTL isoforms (BSAS1;1, 2;1, and 2;2) and five SERAT isoforms involved in cysteine metabolism in the cytosol (SERAT1;1, 3;1, and 3;2), plastids (SERAT2;1), and mitochondria (SERAT2;2) of Arabidopsis (Watanabe et al., 2008a, 2008b). Relative significance of each isoform and relative production of each metabolite are indicated by different font sizes. Solid arrows indicate enzymatic reactions. Dashed arrows indicate the proposed schemes for metabolite transfer between the sub-cellular compartments. Five quadruple serat mutants (Q1;1, Q2;1, Q2;2, Q3;1, and Q3;2) were established, for which the number indicates the single SERAT gene that remains functional (Watanabe et al., 2008a). These were employed to investigate the effects on their respective metabolite composition. The manipulation of this key enzyme of cysteine biosynthesis should affect the capacity to synthesize OAS (Figure 1B). The quadruple serat mutants show a spectrum of responses that differ between the individual mutants, and that are not directly correlated to the remaining SERAT activity (Table 1). SERAT activities attributable to the single remaining isoform demonstrate the dominance of the mitochondrial isoform, SERAT2;2, with activity in the Q2;2 mutant being similar to that in control plants, while the other isoforms contribute between 13 and 2% of the overall activity. When plants were grown on agar solidified medium, the quadruple serat mutants exhibited two different phenotypic groups with different patterns of development. Group 1, comprising the mutants Q1;1 and Q2;2, displays a wild-type-like growth pattern. Remarkably, Q1;1 shows no limitations in growth, although SERAT activity is down to 9% of the wild-type level. Group 2 (Q2;1, Q3;1, and Q3;2) exhibits a retardation of plant growth. Q2;1 and Q3;1 show a slight chlorosis and reduction in chlorophyll content, whereas Q3;2, which displays the lowest SERAT activity (2% of wild-type) among all mutants, does not show chlorosis. As the group 2 quadruple mutants are affected in sulfate metabolism, we compared them to plants exposed to nutrient ion depletion and senescence mutants (Table 1). The data for S starvation are taken from our previously published work (Nikiforova et al., 2003, 2004), and those for nitrogen (N) (Wang et al., 2003; Scheible et al., 2004; Tschoep et al., 2009), phosphate (P) (Morcuende et al., 2007) and potassium (K) (Armengaud et al., 2009) starvation, and for the old5 senescence mutant (Se) (Schippers et al., 2008) were taken from the literature. Comparison of the data from these studies indicated that when plants are exposed to nutrient ion-starvation conditions, they display similar phenotypes growth

Table 1. Metabolite Responses of serat Quadruple Mutants in Comparison to Nutrient Stress Response. Quadruple mutants S N P K Senescence Q2;2 Q1;1 Q2;1 Q3;1 Q3;2 S1 S2 S3 S4 N1 N2 N3 N4 P1 P2 K1 K2 K3 Se1 Se2 Experiment Quadruple mutants of SERAT S deficiency N deficiency P deficiency K deficiency old5 Growth condition (Starvation type) Full nutrient (FN) Const (low S) FN + ind ( S) Const (low N) FN + ind ( N) Const (low P) Const (low P) + ind ( P) Const (low K) FN Sample type Leaf Seedling Seedling Leaf Seedling Seedling Leaf Leaf Plant old 14d 10d 13d 8d+6d 8d+10d 22d 30d 39d 7d+2d 7d 7d+1d 10d 14d 18d 21d 27d SERAT activity 1.1 0.09 0.13 0.05 0.02 Fresh weight 1.0 1.0 0.7 0.5 0.6 0.9 0.8 0.8 0.8 0.8 0.5 0.5 Down a Down a Down a Down a Down a Chlorophyll 1.0 1.0 0.6 0.6 1.0 0.6 0.4 0.9 0.6 0.7 1.1 1.2 1.0 1.0 1.1 1.0 1.0 Soluble protein 1.0 1.2 1.1 1.2 1.3 0.6 1.0 1.2 1.0 1.3 1.3 Total protein 0.4 0.3 0.5 0.4 OAS 0.8 0.5 1.1 1.0 0.5 24.2 14.5 8.5 3.7 0.9 1.2 Cysteine 0.9 0.8 1.2 1.0 0.8, 0.01, 0.01, 0.01, 0.01 1.0 1.3 GSH 0.8 0.7 1.1 1.0 0.4 0.1 0.1 0.1 0.1 2.3 1.8 Alanine 1.0 1.1 2.1 2.6 1.4 1.3 2.1 1.1 2.2 0.7 0.4 0.4 0.1 1.2 1.1 0.7 1.2 1.4 1.2 1.3 Arginine 0.2 0.2 0.6 0.2 1.8 2.4 6.3 4.7 4.1 0.8 2.5 9.1 Asparagine 1.1 1.3 2.3 2.4 2.0 3.0 3.7 2.8 2.3 1.3 0.6 1.2 0.04 1.1 0.9 0.9 2.2 7.1 1.5 2.4 Aspartate 1.0 1.1 1.1 1.3 1.5 0.6 0.9 1.5 0.6 1.0 1.1 0.6 1.3 1.0 0.6 0.7 0.8 1.4 1.9 Glutamate 1.1 1.1 1.7 2.2 1.8 1.3 0.8 1.0 1.1 1.4 1.7 1.8 0.2 1.0 1.0 0.7 0.9 1.1 2.3 2.0 Glutamine 1.3 1.3 4.6 5.7 3.2 5.2 6.8 3.1 4.2 0.8 1.0 2.2 0.02 1.8 1.1 0.8 2.1 4.8 1.4 1.7 Glycine 1.0 1.1 3.0 4.1 2.1 2.6 1.2 8.9 1.2 0.3 1.2 1.8 0.2 4.6 2.4 0.8 1.7 1.5 0.7 0.6 Histidine 1.3 1.2 3.3 3.3 1.9 0.5 1.0 2.0 2 2.9 1.7 1.1 1.3 2.0 Isoleucine 1.2 1.0 1.8 1.5 1.3 1.8 1.3 2.0 2.3 1.1 2.2 1.9 1.8 1.0 1.1 1.5 1.6 0.9 1.5 Leucine 0.5 0.9 2.4 1.6 0.6 0.7 1.6 2.1 1.4 1.2 1.0 1.1 1.3 Lysine 1.2 1.3 2.9 2.4 1.9 1.3 1.1 1.4 1.0 0.8 1.6 3.6 1.5 1.0 1.0 1.3 2.2 0.6 1.5 Methionine 0.9 0.8 1.1 1.1 0.7 0.8 0.8 1.4 0.9 0.6 0.8 0.9 1.6 0.3 0.5 0.8 1.0 0.9 1.3 1.0 Phenylalanine 2.0 1.0 1.9 1.2 0.6 1.0 1.5 2.3 2.2 3.7 0.8 1.3 1.9 1.2 4.0 Proline 0.9 0.7 1.2 0.7 1.7 2.0 Serine 1.3 1.2 3.5 5.0 2.6 2.6 2.0 2.5 2.3 1.3 2.9 2.7 0.2 1.5 1.2 1.1 2.0 2.5 1.7 2.6 Threonine 1.2 1.2 1.5 1.5 1.8 1.9 1.4 2.1 1.5 1.3 0.9 0.9 0.6 2.2 2.1 0.9 1.6 2.7 Tryptophan 1.1 1.0 0.9 1.2 1.4 28.3 7.1 16.6 5.7 0.7 0.5 3.0 0.4 4.2 6.2 0.9 4.5 Tyrosine 1.6 1.2 1.4 1.9 1.3 0.6 1.6 1.9 0.3 2.6 3.4 0.7 1.2 1.3 1.2 1.2 Watanabe et al. d General Regulatory Patterns Revealed by serat Quadruple Mutants 441

Table 1. Continued Quadruple mutants S N P K Senescence Q2;2 Q1;1 Q2;1 Q3;1 Q3;2 S1 S2 S3 S4 N1 N2 N3 N4 P1 P2 K1 K2 K3 Se1 Se2 Experiment Quadruple mutants of SERAT S deficiency N deficiency P deficiency K deficiency old5 Growth condition (Starvation type) Full nutrient (FN) Const (low S) FN + ind ( S) Const (low N) FN + ind ( N) Const (low P) Const (low P) + ind ( P) Const (low K) FN Sample type Leaf Seedling Seedling Leaf Seedling Seedling Leaf Leaf Plant old 14d 10d 13d 8d+6d 8d+10d 22d 30d 39d 7d+2d 7d 7d+1d 10d 14d 18d 21d 27d Valine 1.1 0.9 2.1 1.9 1.3 2.0 1.4 2.0 1.8 1.0 0.9 1.5 0.5 1.6 1.2 0.9 1.6 2.2 1.1 2.1 Sulfate 0.7 0.7 0.5 0.4 0.2 Sulfur 0.3 0.3 0.4 0.3 Nitrate 1.0 1.0 1.0 1.0 1.0 0.3 0.2 0.06, 0.01 0.8 0.8 1.1 Phosphate 1.0 1.0 1.0 0.7 1.0, 0.01, 0.01 a Plants under nutrient-starvation conditions (N4, P1, P2, K2, and K3) exhibited growth retardation, but value data is missing. Const, constitutive nutrient starvation; ind, inducible nutrient starvation; FN, full nutrient condition. Quadruple mutants; data of SERATactivity, fresh weight, OAS, thiols andamino acids is from Watanabe et al. (2008a). Chlorophyll, protein, and ion content were measured in this study. Plants were grown under normal growth conditions for 2 weeks. Fold-changes relative to the wild-type are shown. S1 S4; data are from Nikiforova et al. (2003, 2004). Plants were grown under constitutive (low sulfate) and induced sulfate starvation, and harvested before (S1 and S3) or after (S2 and S4) appearance of the first visible phenotypic changes. N1, N2, and N3; data are from Tschoep et al. (2009). Plants were grown under constitutive (low nitrate) starvation for 22 d (N1), 30 d (N2), and 39 d (N3). Fold changes relative to the nitrate sufficient control are shown. N4; data are from Scheible et al. (2004). Plants were grown under induced nitrate starvation. Fold changes relative to the nitrate-sufficient control are shown. P1 and P2; data are from Morcuende et al. (2007). Plants were grown under constitutive (low phosphate) (P1) and induced (P2) phosphate starvation. Fold changes relative to the phosphate-sufficient control are shown. K1, K2, and K3; data are from Armengaud et al. (2004, 2009). Plants were grown under constitutive low-potassium conditions for 10 d (K1), 14 d (K2), or 18 d (K3). Fold changes relative to the potassium-sufficient control are shown. Se1 and Se2; data are from Schippers et al. (2008). The old5 mutant is an ethyl methanesulfonate-mutagenized mutant of quinolinate synthase, and shows an early senescence phenotype. Plants were grown under normal growth conditions for 21 d (Se1) and 27 d (Se2) before appearance of the first visible phenotypic changes. Fold changes relative to the wild-type are shown. Blank cells indicate not determined..1.5-fold and,0.66-fold changes are colored in pink and blue, respectively. 442 Watanabe et al. d General Regulatory Patterns Revealed by serat Quadruple Mutants

Watanabe et al. d General Regulatory Patterns Revealed by serat Quadruple Mutants 443 retardation, chlorosis, and accumulation of anthocyanins irrespective of which ion is limiting. Metabolite Responses of Quadruple serat Mutants in Comparison with Nutrient Stress Responses As SERAT and OAS are assumed to play a central role in sulfate assimilation, we investigated the abundance of the major nutrient ions nitrate, phosphate, and sulfate in the leaf tissues of the quadruple mutants (Table 1). All mutant lines contain about wild-type levels of nitrate. Phosphate contents are close to wild-type in all mutants, with a slight reduction in Q3;1. Sulfate levels are reduced to different degrees in the quadruple mutants, only slightly in the lines of group 1, Q1;1, and Q2;2 (70% of wild-type), but substantially in the growth-retarded lines (Q2;1, 3;1, and 3;2) with 50, 40, and 20% of control plant contents, respectively. As this indicates an effect on nutrient homeostasis, we compared these data with published nutrient-starvation experiments (Table 1). Not surprisingly, nitrate is drastically reduced in nitrate-depletion experiments, but is also slightly lower in potassium-starved plants. Phosphate is reduced in phosphate-depletion experiments, as expected. Sulfate ion levels have not been determined for the sulfur-starvation experiment; however, the total amount of sulfur, which is a measure of (vacuolar) sulfate plus organic sulfur in the tissue, has been shown to be very low (Nikiforova et al., 2003). Unfortunately, further ionomics data were not available, limiting the comparison of plants under different nutrient-starvation conditions. A decrease in SERAT activity should lead to a fall in the cellular OAS content, and thus to a block in thiol synthesis as one of the substrates for cysteine biosynthesis is depleted. The observed results (Table 1) did not match this expectation, but instead show a scatter of individual responses. Q2;2, Q1;1, and Q3;2 display lower OAS and thiol contents, which did not correlate with the respective remaining enzyme activities. Q2;1 and Q3;1 display unaltered levels of OAS and thiols. If this is compared to sulfate starvation, which depletes sulfide, a decrease in reduced thiol content is observed, accompanied by a characteristic increase in OAS content (Maruyama-Nakashita et al., 2003; Nikiforova et al., 2003). Analysis of the amino acid composition showed that the group 1 quadruple mutants (Q1;1 and Q2;2), which showed no apparent phenotype, have amino acid contents comparable to control plants, whereas the dwarfed mutants (group 2: Q2;1, 3;1, and 3;2) show an overall increase in amino acid concentrations. The common denominator is the correlation of biomass to changes in amino acid contents, which seems not to be correlated with OAS or thiol contents. Nutrient ion stresses lead to perturbations in the composition of the overall amino acid pool, and often increased levels of amino acids can be observed for plants depleted of sulfate (S1 S4), nitrate (N1 N3), phosphate (P1 and P2), or potassium (K1 K3), as well as for the senescence mutant (Se1 and Se2) (Table 1). Full nitrate starvation leads to a general decrease in amino acids (N4) (Table 1). Genome-Wide Transcriptomic Analysis Indicates which Metabolic Pathways Are Most Affected These widespread metabolic shifts are indicative of a wholeorganism,system-levelresponse. Inordertorevealtheseassumed system-level responses, we performed transcriptomic analyses of the serat mutants. A particular aim of this analysis was to investigate whether the group 2 mutants (Q2;1, Q3;1, and Q3;2) display a similar molecular phenotype to each other, which differs from the group 1 mutants (Q1;1 and Q2;2), or whether they scatter randomly. Leaf material was harvested from 2-week-old plants of all five mutants grown on agar solidified medium for transcriptomic analysis using the Affymetrix ATH1 microarray. A hierarchical cluster analysis of the array results (Figure 2A) groups the mutant lines exhibiting a phenotype (Q2;1, Q3;1, and Q3;2) close to one another, while wild-type, Q1;1, and Q2;2 form a distinct clade separate from this group. When subjecting the same dataset to a principal component analysis (PCA) (Figure 2B), the dwarfed mutants again cluster close to one another in the PCA plot, while Q1;1, Q2;2, and wild-type are distant fromoneanotherandfromthegroup2mutants. Fortheloadings of principal components 1 and 2, see Supplemental Table 1. The principal components are not dominated by single, strongly determining transcripts, but by a number of transcripts with minor individual loadings that cumulatively contribute to the separation of the respective components. This indicates common response features within the group 2 dwarfed mutants, when compared to the group 1 mutants and the wild-type, justifying further investigations of the potential links between the phenotype and the genotype of the mutants. The Mapman software (Thimm et al., 2004; Usadel et al., 2005, 2009) was used to quantitatively categorize the transcriptional changes within various functional classes. The percentage of genes in each class that was either up-regulated >1.5- fold or down-regulated >0.66-fold is shown in Table 2. For most A Q2;2 WT Q1;1 Q2;1 Q3;1 Q3;2 B PC1 27.7% Q2;2 WT PC2 19.9% Figure 2. Hierarchical Clustering and Principal Component Analysis of Transcript Data of Quadruple serat Mutants. Hierarchical clustering analysis using Pearson correlation (A) and principal component analysis (B) were conducted with the complete gene datasets on ATH1 Chip by the MultiExperiment Viewer (MeV) (Saeed et al., 2003). The behavior of the transcripts in the mutants correlates to their respective phenotypic appearance and developmental stages. The dwarfed mutants (Q2;1, Q3;1, and Q3;2) are clustered together and are separated from the apparently normally growing plants (Q2;2, Q1;1, and WT). Remarkably, a separation of WT, Q1;1, and Q2;2 can also be observed, indicating the unique function of the SERAT isoforms SERAT1;1 and especially SERAT2;2. Q1;1 Q3;2 Q2;1 Q3;1

Table 2. Gene Expression Changes in Metabolism Categories. % of gene number (. 1.5 up) Q2;2 Q1;1 Q2;1 Q3;1 Q3;2 S1 S2 S3 S4 N4 P2 K K2 Total up genes 18 [22810] 14 [22810] 18 [22810] 19 [22810] 19 [22810] 31 [4090] 22 [4077] 24 [4090] 28 [4077] 26 [22800] 10 [22746] 16 [21769] 0.6 [22342] Central amino acid 17 [18] 17 [18] 33 [18] 44 [18] 28 [18] 50 [6] 33 [6] 33 [6] 33 [6] 39 [18] 22 [18] 20 [15] 0 [18] Amino acid synthesis 2 [132] 6 [132] 16 [132] 17 [132] 10 [132] 31 [49] 19 [48] 31 [49] 35 [48] 13 [132] 17 [132] 11 [120] 2 [124] Amino acids degradation 6 [69] 9 [69] 26 [69] 25 [69] 19 [69] 19 [27] 11 [27] 11 [27] 26 [27] 30 [69] 10 [69] 21 [67] 6 [69] Nitrogen metabolism 11 [19] 5 [19] 16 [19] 26 [19] 11 [19] 55 [11] 45 [11] 27 [11] 45 [11] 32 [19] 16 [19] 16 [19] 0 [19] Sulfur metabolism 7 [115] 11 [115] 25 [115] 30 [115] 25 [115] 45 [44] 40 [43] 34 [44] 37 [43] 24 [115] 22 [110] 16 [110] 1 [110] Redox, Ascorbate, GSH 7 [58] 7 [58] 29 [58] 29 [58] 26 [58] 33 [24] 29 [24] 29 [24] 25 [24] 14 [58] 24 [58] 23 [57] 4 [54] TCA 4 [72] 8 [72] 24 [72] 29 [72] 22 [72] 30 [27] 22 [27] 26 [27] 44 [27] 18 [72] 6 [72] 6 [68] 0 [68] Gluconeogenese 30 [10] 10 [10] 20 [10] 20 [10] 20 [10] 20 [5] 0 [5] 0 [5] 40 [5] 30 [10] 0 [10] 20 [10] 0 [10] Glycolysis 8 [60] 8 [60] 20 [60] 33 [60] 15 [60] 37 [19] 26 [19] 37 [19] 16 [19] 23 [60] 27 [60] 7 [57] 0 [58] OPP 16 [31] 19 [31] 35 [31] 52 [31] 39 [31] 30 [10] 30 [10] 10 [10] 20 [10] 13 [31] 16 [31] 16 [31] 3 [31] Fermentation 8 [13] 15 [13] 38 [13] 31 [13] 23 [13] 50 [6] 17 [6] 17 [6] 83 [6] 38 [13] 31 [13] 17 [12] 0 [13] Calvin cycle 0 [23] 0 [23] 4 [23] 4 [23] 4 [23] 0 [9] 0 [9] 0 [9] 0 [9] 0 [23] 0 [23] 0 [22] 0 [20] PS_lightreaction 2 [134] 5 [134] 4 [134] 4 [134] 3 [134] 5 [37] 3 [37] 5 [37] 11 [37] 1 [134] 0 [134] 1 [129] 0 [84] Photorespiration 0 [9] 0 [9] 0 [9] 22 [9] 22 [9] 0 [5] 0 [5] 20 [5] 20 [5] 11 [9] 11 [9] 17 [6] 0 [8] Tetrapyrrole 5 [43] 7 [43] 7 [43] 14 [43] 9 [43] 0 [12] 8 [12] 17 [12] 42 [12] 7 [43] 2 [43] 5 [43] 0 [42] Mitochondrial 8 [98] 7 [98] 16 [98] 18 [98] 13 [98] 39 [31] 26 [31] 23 [31] 32 [31] 19 [98] 11 [98] 34 [98] 0 [89] electron transport C1 metabolism 7 [30] 10 [30] 17 [30] 13 [30] 13 [30] 13 [8] 25 [8] 25 [8] 25 [8] 7 [30] 0 [30] 8 [25] 0 [29] Nucleotide synthesis 9 [122] 9 [122] 18 [122] 18 [122] 14 [122] 17 [24] 8 [24] 17 [24] 21 [24] 22 [122] 11 [122] 11 [115] 0 [120] Nucleotide degradation 14 [36] 8 [36] 22 [36] 17 [36] 22 [36] 0 [4] 0 [4] 25 [4] 0 [4] 44 [36] 14 [36] 19 [32] 0 [34] Major CHO synthesis 17 [30] 10 [30] 20 [30] 17 [30] 23 [30] 50 [4] 0 [4] 0 [4] 25 [4] 30 [30] 30 [30] 13 [30] 0 [30] Major CHO degradation 15 [62] 18 [62] 31 [62] 32 [62] 34 [62] 23 [13] 15 [13] 23 [13] 15 [13] 24 [62] 23 [62] 16 [61] 2 [58] Minor CHO synthesis 8 [114] 8 [114] 20 [114] 15 [114] 20 [114] 22 [23] 9 [23] 9 [23] 30 [23] 20 [114] 14 [114] 14 [113] 2 [109] Lipid synthesis 15 [158] 11 [158] 16 [158] 15 [158] 15 [158] 30 [40] 18 [40] 20 [40] 43 [40] 32 [158] 13 [158] 7 [149] 0 [151] Lipid metabolism 13 [70] 13 [70] 21 [70] 19 [70] 16 [70] 38 [24] 13 [24] 25 [24] 42 [24] 27 [70] 9 [70] 13 [64] 0 [67] Lipid degradation 19 [94] 12 [94] 21 [94] 24 [94] 19 [94] 41 [22] 14 [22] 27 [22] 45 [22] 30 [94] 24 [94] 13 [91] 0 [82] Cell wall protein 16 [76] 14 [76] 17 [76] 25 [76] 18 [76] 27 [22] 14 [22] 41 [22] 27 [22] 22 [76] 8 [76] 17 [75] 1 [68] Cell wall synthesis 14 [101] 10 [101] 19 [101] 21 [101] 16 [101] 30 [30] 20 [30] 37 [30] 33 [30] 33 [101] 14 [101] 11 [97] 1 [99] Cell wall degradation 33 [116] 20 [116] 23 [116] 20 [116] 23 [116] 22 [18] 17 [18] 17 [18] 28 [18] 26 [116] 12 [116] 18 [106] 1 [104] Cell wall modification 18 [143] 13 [143] 21 [143] 20 [143] 20 [143] 33 [21] 29 [21] 10 [21] 29 [21] 24 [143] 14 [143] 20 [138] 2 [132] Wax 13 [23] 13 [23] 13 [23] 13 [23] 17 [23] 33 [3] 33 [3] 33 [3] 33 [3] 26 [23] 13 [23] 9 [22] 0 [20] Phenylpropanoids 22 [79] 14 [79] 28 [79] 27 [79] 22 [79] 46 [24] 29 [24] 38 [24] 29 [24] 49 [79] 34 [79] 24 [75] 3 [77] Flavonoid metabolism 19 [83] 27 [83] 37 [83] 40 [83] 47 [83] 41 [17] 41 [17] 12 [17] 35 [17] 48 [83] 37 [83] 35 [74] 1 [80] Terpen 17 [109] 16 [109] 23 [109] 17 [109] 17 [109] 19 [21] 10 [21] 33 [21] 14 [21] 32 [109] 20 [109] 12 [103] 0 [102] Phenolics 28 [18] 33 [18] 28 [18] 33 [18] 39 [18] 0 [2] 0 [2] 0 [2] 0 [2] 78 [18] 28 [18] 12 [17] 6 [17] Misc 8 [40] 13 [40] 30 [40] 28 [40] 28 [40] 14 [7] 17 [6] 43 [7] 33 [6] 28 [40] 20 [40] 29 [38] 3 [40] SAGs 17 [827] 17 [827] 44 [827] 37 [827] 32 [827] 38 [216] 32 [216] 28 [216] 34 [216] 71 [827] 50 [827] 60 [787] 3 [784] 444 Watanabe et al. d General Regulatory Patterns Revealed by serat Quadruple Mutants

Table 2. Continued % of gene number (, 0.66 down) Q2;2 Q1;1 Q2;1 Q3;1 Q3;2 S1 S2 S3 S4 N4 P2 K K2 Total down genes 15 [22810] 16 [22810] 21 [22810] 22 [22810] 19 [22810] 9 [4090] 15 [4077] 10 [4090] 9 [4077] 14 [22800] 9 [22746] 21 [21769] 0.1 [22342] Central amino acid 0 [18] 11 [18] 6 [18] 22 [18] 17 [18] 0 [6] 0 [6] 0 [6] 0 [6] 17 [18] 11 [18] 13 [15] 0 [18] Amino acid synthesis 7 [132] 4 [132] 5 [132] 13 [132] 8 [132] 6 [49] 17 [48] 8 [49] 4 [48] 23 [132] 14 [132] 30 [120] 0 [124] Amino acids degradation 10 [69] 7 [69] 12 [69] 12 [69] 10 [69] 19 [27] 26 [27] 4 [27] 4 [27] 16 [69] 9 [69] 18 [67] 0 [69] Nitrogen metabolism 0 [19] 0 [19] 5 [19] 11 [19] 11 [19] 0 [11] 27 [11] 27 [11] 18 [11] 21 [19] 11 [19] 32 [19] 0 [19] Sulfur metabolism 18 [115] 14 [115] 12[115] 17 [115] 16 [115] 14 [44] 21 [43] 11 [44] 5 [43] 23 [115] 20 [115] 25 [115] 0 [110] Redox, Ascorbate, GSH 7 [58] 7 [58] 7 [58] 10 [58] 7 [58] 4 [24] 8 [24] 0 [24] 4 [24] 22 [58] 14 [58] 16 [57] 0 [54] TCA 6 [72] 4 [72] 4 [72] 10 [72] 8 [72] 7 [27] 22 [27] 0 [27] 7 [27] 13 [72] 3 [72] 21 [68] 0 [68] Gluconeogenese 0 [10] 10 [10] 10 [10] 30 [10] 10 [10] 20 [5] 40 [5] 20 [5] 0 [5] 10 [10] 10 [10] 10 [10] 0 [10] Glycolysis 13 [60] 12 [60] 15 [60] 15 [60] 18 [60] 11 [19] 26 [19] 16 [19] 21 [19] 17 [60] 8 [60] 21 [57] 0 [58] OPP 10 [31] 6 [31] 10 [31] 10 [31] 13 [31] 10 [10] 30 [10] 10 [10] 10 [10] 32 [31] 16 [31] 23 [31] 0 [31] Fermentation 8 [13] 8 [13] 0 [13] 0 [13] 8 [13] 17 [6] 33 [6] 17 [6] 17 [6] 15 [13] 0 [13] 8 [12] 0 [13] Calvin cycle 0 [23] 0 [23] 13 [23] 35 [23] 26 [23] 89 [9] 89 [9] 33 [9] 33 [9] 91 [23] 74 [23] 55 [22] 0 [20] PS_lightreaction 1 [134] 0 [134] 18 [134] 46 [134] 28 [134] 35 [37] 59 [37] 30 [37] 32 [37] 88 [134] 60 [134] 37 [129] 0 [84] Photorespiration 11 [9] 0 [9] 0 [9] 33 [9] 11 [9] 0 [5] 0 [5] 20 [5] 20 [5] 56 [9] 56 [9] 17 [6] 0 [8] Tetrapyrrole 9 [43] 2 [43] 12 [43] 14 [43] 14 [43] 8 [12] 50 [12] 17 [12] 0 [12] 70 [43] 56 [43] 56 [43] 0 [42] Mitochondrial 5 [98] 4 [98] 5 [98] 7 [98] 7 [98] 0 [31] 3 [31] 3 [31] 10 [31] 4 [98] 1 [98] 5 [98] 0 [89] electron transport C1 metabolism 7 [30] 3 [30] 7 [30] 13 [30] 3 [30] 13 [8] 25 [8] 25 [8] 13 [8] 23 [30] 13 [30] 20 [25] 0 [29] Nucleotide synthesis 12 [122] 8 [122] 11 [122] 11 [122] 11 [122] 17 [24] 17 [24] 8 [24] 8 [24] 15 [122] 9 [122] 14 [115] 1 [120] Nucleotide degradation 17 [36] 22 [36] 22 [36] 17 [36] 17 [36] 0 [4] 0 [4] 25 [4] 0 [4] 8 [36] 0 [36] 9 [32] 3 [34] Major CHO synthesis 3 [30] 0 [30] 3 [30] 7 [30] 0 [30] 25 [4] 25 [4] 0 [4] 0 [4] 27 [30] 20 [30] 50 [30] 0 [30] Major CHO degradation 10 [62] 11 [62] 10 [62] 18 [62] 26 [62] 8 [13] 23 [13] 23 [13] 8 [13] 18 [62] 10 [62] 34 [61] 0 [58] Minor CHO synthesis 13 [114] 13 [114] 14 [114] 18 [114] 18 [114] 4 [23] 17 [23] 17 [23] 9 [23] 20 [114] 13 [114] 27 [113] 0 [109] Lipid synthesis 8 [158] 10 [158] 13 [158] 11 [158] 11 [158] 8 [40] 18 [40] 13 [40] 10 [40] 13 [158] 13 [158] 36 [149] 1 [151] Lipid metabolism 14 [70] 7 [70] 10 [70] 13 [70] 9 [70] 8 [24] 8 [24] 13 [24] 8 [24] 11 [70] 7 [70] 27 [64] 0 [67] Lipid degradation 16 [94] 18 [94] 17 [94] 20 [94] 20 [94] 5 [22] 14 [22] 5 [22] 14 [22] 11 [94] 6 [94] 24 [91] 0 [82] Cell wall protein 12 [76] 16 [76] 28 [76] 26 [76] 22 [76] 23 [22] 18 [22] 5 [22] 5 [22] 25 [76] 21 [76] 32 [75] 0 [68] Cell wall synthesis 15 [101] 12 [101] 16 [101] 13 [101] 12 [101] 13 [30] 13 [30] 3 [30] 3 [30] 12 [101] 9 [101] 29 [97] 0 [99] Cell wall degradation 21 [116] 28 [116] 30 [116] 33 [116] 25 [116] 17 [18] 39 [18] 11 [18] 6 [18] 26 [116] 15 [116] 29 [106] 0 [104] Cell wall modification 23 [143] 27 [143] 34 [143] 36 [143] 31 [143] 10 [21] 10 [21] 10 [21] 0 [21] 24 [143] 20 [143] 21 [138] 0 [132] Wax 22 [23] 17 [23] 39 [23] 48 [23] 35 [23] 0 [3] 0 [3] 0 [3] 0 [3] 26 [23] 4 [23] 32 [22] 0 [20] Phenylpropanoids 19 [79] 20 [79] 19 [79] 19 [79] 14 [79] 13 [24] 17 [24] 8 [24] 8 [24] 13 [79] 4 [79] 13 [75] 0 [77] Flavonoid metabolism 18 [83] 16 [83] 18 [83] 20 [83] 18 [83] 6 [17] 6 [17] 6 [17] 12 [17] 10 [83] 5 [83] 14 [74] 0 [80] Terpen 13 [109] 19 [109] 17 [109] 25 [109] 22 [109] 0 [21] 14 [21] 5 [21] 5 [21] 15 [109] 13 [109] 31 [103] 0 [102] Phenolics 28 [18] 28 [18] 28 [18] 44 [18] 22 [18] 0 [2] 0 [2] 0 [2] 0 [2] 0 [18] 0 [18] 29 [17] 0 [17] Misc 18 [40] 10 [40] 18 [40] 23 [40] 15 [40] 14 [7] 33 [6] 14 [7] 0 [6] 25 [40] 10 [40] 24 [38] 0 [40] SAGs 15 [827] 13 [827] 8 [827] 13 [827] 13 [827] 7 [216] 10 [216] 8 [216] 6 [216] 4 [827] 4 [827] 5 [787] 0 [784] The percentage of gene numbers with.1.5-fold and,0.66-fold changes is calculated in each metabolism category according to the Mapman ontology (Thimm et al., 2004). Categories of sulfur metabolism and SAGs are based on Table 3 and the SAGs list published in Buchanan-Wollaston et al. (2003), respectively. The percentage of gene numbers with.20% are colored in pink and blue for tables of.1.5-fold and,0.66-fold changes, respectively. The total number of genes in each category is shown in brackets. Data for S1 S4, N4, P2, and K2 are from the same referenceastable1.fold changes relative totheeachcontrol areshown.k;dataarefromhammond etal. (2007).Plants weregrownunderinduced phosphate starvation. Fold changes relative to the potassium-sufficient control are shown. Watanabe et al. d General Regulatory Patterns Revealed by serat Quadruple Mutants 445

446 Watanabe et al. d General Regulatory Patterns Revealed by serat Quadruple Mutants of the functional classes, the quadruple mutants that show a growth-retardation phenotype (group 2: Q2;1, Q3;1, and Q3;2) display more transcriptional changes than the less affected mutants (Q2;2 and Q1;1). For example, most of the genes associated with the light reactions or Calvin cycle were downregulated in the dwarf mutants, whereas genes linked to the TCA cycle, oxidative pentose phosphate pathway (OPPP), fermentation pathways, and secondary metabolite pathways (e.g. flavonoids and phenylpropanoids) were up-regulated. Furthermore, in addition to sulfur metabolism, genes linked to other aspects of redox metabolism were also mostly upregulated in the dwarfed mutants. Many genes involved in cell wall degradation and modification were also affected in a mixed pattern, with some being up-regulated and others down-regulated, but these responses were observed in all of the quadruple mutants. This suggests that further analysis of the serat mutants could reveal some interesting differences in cell wall composition and cell wall metabolism. As Mapman plots indicated broad similarities between the transcriptional phenotypes of the quadruple mutants and plants exposed to nutrient starvation (data not shown), we compared the transcriptomic data of the quadruple mutants with the available data from ion depletion experiments in more detail (Table 2). The overall changes in gene expression in the group 2 quadruple mutants were comparable with those observed in plants under N, P, S, starvation, but to a lesser extent with K-depleted plants. Similar functional classes display prominent changes, which are even more pronounced than in the quadruple mutants (Amtmann and Armengaud, 2009) (Table 2). In all cases in which the disturbance of mineral nutrient metabolism leads to alterations of amino acid pools (Table 1), carbohydrate assimilation genes, genes of redox scavenging systems, namely ascorbate and GSH, as well as flavonoids are increased, while light reaction and Calvin cycle genes are down-regulated (Table 2). As no transcript data were available for the mild nitrogen starvation, we used data from strongly nitrogen-starved plants (N4). The potassium-starved plants (constitutive K2, and induced K; Hammond et al., 2007) displayed relatively fewer alterations in gene expression. It must be mentioned that the K2 dataset is derived from a microarray spotted with the Arabidopsis Genome Oligo Set version 1.0. (Qiagen), and not from the Affymetrix ATH1 array. For sulfate starvation only, macroarray data (S1 S4) are currently available, providing a fragmentary view on the low-s response in comparison to the other treatments and the mutants. Due to the lower number of genes represented on the macroarray, and the different type of probe (11 000 cdna probes derived from ESTs; Nikiforova et al., 2003), caution is required when comparing the low-s transcript data with datasets derived from hybridizations with the more comprehensive ATH1 gene microarrays. Nevertheless, for the most part, the transcript responses of the group 2 serat plants resemble those of the nutrient-depleted plants. These matches provided a basis to embark on a more detailed analysis. Next to these quantitative changes, it is important to assess whether the changes also match qualitatively, namely whether, indeed, the same genes are expressed under the various conditions. For the following functional categories: light reactions, Calvin cycle, sulfur metabolism, and senescenceassociated genes (SAGs) (see Table 2), we pairwise compared the qualitative overlap of the gene sets by counting the number of genes displaying similar expression patterns (Table 3). However, although the numbers are given in Table 3, we did not consider this set for a pairwise comparison. It is evident that group 2 quadruple mutants and plants under N, P, and S starvation show a high degree of identical gene expression responses, while the group 1 quadruple mutants and the K- starved plants display much less overlap. In fact, K2 displays very few changes in expression at all; out of a total of 22 342 genes, only 139 genes were up-regulated more than 1.5-fold and even fewer, 14 genes, were repressed more than 0.66-fold compared to control, and so closely resemble the nutrient-sufficient and wild-type controls. The total number of genes affected in a given mutant varies between the mutant lines or treatments, and for the low-s experiments, only a limited dataset was available (these data are in the table for reference purposes, but limit discussion of their significance for the reasons outlined above). As an example of differences between the mutants, consider the category light reaction, which includes 134 genes. For Q3;1, the plant exhibiting the strongest change, 61 genes in this category are down-regulated (46%, see Table 2). Of these genes, 18 and 21 genes show a similar response in Q2;1 (30%) and Q3;2 (34%), respectively, but none of these genes responded in the group 1 quadruples. In the N-, P-, and K-starved plants, 96, 60, and 21% of these genes, respectively, are down-regulated, while no similarity was found to constitutive potassium starvation (K2). For the category sulfate metabolism (115 genes), 35 genes (30%) are up-regulated in the Q3;1 mutant. Of these genes, 23 29% respond in a similar manner in the group 1 quadruples, but 77 and 70% show responses in the dwarfed mutants Q2;1 and Q3;2, respectively. The overlap of these sulfur metabolism genes to N, P, and K is still 49, 40, and 31%, respectively, while K2 displays only 3% identical gene expression. For further evaluation, the category of SAGs (827 genes) is of particular interest, with 37% of these genes being up-regulated in Q3;1 mutant. In the group 1 quadruple mutants, 34% (Q2;2) and 39% (Q1;1) are identical to this set, while the other group 2 quadruple mutants match to 82% (Q2;1) and 70% (Q3;2). For N, P, and K, the match is 70, 63, and 68%, respectively. K2 only displays 4% identical genes. Expression Changes of Genes of Sulfur Metabolism SERAT is a central enzyme of the sulfate assimilation pathway, and all of the serat mutants, especially the group 2 serat plants, showed reduced sulfate contents (Table 1). Therefore, we analyzed in detail the transcript response of all five quadruple mutants for the genes involved in sulfur metabolism, including additional genes not included in this Mapman category

Watanabe et al. d General Regulatory Patterns Revealed by serat Quadruple Mutants 447 Table 3. Pairwise Comparison of the Qualitative Overlap between Up- or Down-Regulated Gene Sets of Quadruple serat Mutants and Nutrient-Starved Plants. (A) Sulfur metabolism (up-regulated genes) Q2;2 Q1;1 Q2;1 Q3;1 Q3;2 S1 S2 S3 S4 N4 P2 K K2 Q2;2 8 3 7 8 7 2 2 3 4 4 4 3 0 Q1;1 13 7 10 8 3 3 4 4 7 6 4 0 Q2;1 29 27 22 6 7 8 8 13 12 10 1 Q3;1 35 26 6 7 8 7 17 14 11 1 Q3;2 29 8 9 8 8 14 13 11 1 S1 20 14 9 12 5 5 3 0 S2 17 9 10 4 5 3 0 S3 15 9 3 5 3 0 S4 16 6 6 4 0 N4 28 15 9 1 P2 25 12 1 K 18 1 K2 1 Total 115 115 115 115 115 44 43 44 43 115 115 110 110 (B) SAGs (up-regulated genes) Q2;2 Q1;1 Q2;1 Q3;1 Q3;2 S1 S2 S3 S4 N4 P2 K K2 Q2;2 143 75 121 104 106 9 6 10 10 101 80 97 7 Q1;1 143 126 119 111 13 13 13 12 97 88 97 3 Q2;1 363 249 217 35 34 31 31 252 222 249 20 Q3;1 302 213 32 27 30 31 211 191 206 13 Q3;2 264 27 22 23 23 182 160 183 14 S1 82 49 31 24 57 41 45 2 S2 70 30 20 50 34 38 2 S3 60 29 43 32 35 3 S4 73 48 33 33 1 N4 588 339 345 14 P2 415 298 25 K 471 24 K2 27 Total 827 827 827 827 827 216 216 216 216 827 827 787 784 (Table 4). We applied a 1.5-fold threshold to mark genes as upor down-regulated. The transcript response is as complex as the metabolic and phenotypic response pattern. Despite their apparently wild-type-like appearance, Q2;2 (7% genes up, 18% genes down) and Q1;1 (11% up, 14% down) reveal substantial responses at the transcript level compared to controls, but these responses were still less pronounced than those observed in the growth-retarded phenotypes Q2;1, Q3;1, and Q3;2 (up 25, 30, and 25%, down, 12, 17, and 16%, respectively) (Table 2). Notably, when applying a threshold of 1.5-fold change, all mutants show increased APR expression, except Q2;2, although this also increases, but to a lesser extent. APR is believed to be a central regulator of sulfur metabolism in plants and to integrate other Table 3. Continued (C) Light reaction (down-regulated genes) Q2;2 Q1;1 Q2;1 Q3;1 Q3;2 S1 S2 S3 S4 N4 P2 K K2 Q2;2 1 0 0 0 0 0 0 0 0 0 0 0 0 Q1;1 0 0 0 0 0 0 0 0 0 0 0 0 Q2;1 24 18 7 6 7 4 5 22 12 4 0 Q3;1 61 21 9 14 8 10 59 37 19 0 Q3;2 38 4 5 3 4 35 26 19 0 S1 13 12 4 7 13 5 2 0 S2 22 9 8 22 12 3 0 S3 11 3 11 7 1 0 S4 12 11 8 2 0 N4 118 79 45 0 P2 80 37 0 K 48 0 K2 0 Total 134 134 134 134 134 37 37 37 37 134 134 129 84 (D) Calvin cycle (down-regulated genes) Q2;2 Q1;1 Q2;1 Q3;1 Q3;2 S1 S2 S3 S4 N4 P2 K K2 Q2;2 0 0 0 0 0 0 0 0 0 0 0 0 0 Q1;1 0 0 0 0 0 0 0 0 0 0 0 0 Q2;1 3 3 1 1 1 0 1 3 3 1 0 Q3;1 8 4 3 3 0 1 8 7 3 0 Q3;2 6 3 3 0 1 6 5 2 0 S1 8 8 3 3 7 7 4 0 S2 8 3 3 7 7 4 0 S3 3 2 2 2 2 0 S4 3 2 2 1 0 N4 21 17 11 0 P2 17 10 0 K 12 0 K2 0 Total 23 23 23 23 23 9 9 9 9 23 23 22 21 The values in the table show the number of overlapping genes between each experiment in each Mapman category (Table 2). The colored values are total number of the up (pink) or down (blue) regulated genes in each category. The values under the table are total number of genes in each category. The up-regulated gene sets for (A) sulfur metabolism and (B) SAGs and the down-regulated gene sets for (C) light reactions and (D) Calvin cycle were used for this comparison. Data are from the same reference as Table 2. metabolic responses (as discussed in a review of this issue). Further, Q2;1, Q3;1, and Q3;2 share a greater number of responses in common (see also Tables 2 and 3); for example, genes of GSH synthesis are induced, and several genes of serine biosynthesis are induced, coinciding with increased serine levels (Table 1) and S-adenosylmethioninesynthase3 (SAMS3; At3g17390) a gene linked to SAM biosynthesis. Taking into consideration that leaf tissue of 2-week-old plants was harvested and subjected to transcriptome analysis, the results of the SULTR family are

Table 4. Gene Expression Changes in Sulfur Metabolism and S Response Genes. Gene family Name AGI Q2;2 Q1;1 Q2;1 Q3;1 Q3;2 S1 S2 S3 S4 N4 P21 K11 K2 Sulfate transporter SULTR1;1 At4g08620 0.2 0.5 0.1 1.0 0.5 0.9 0.8 2.3 1.0 SULTR1;2 At1g78000 1.0 1.0 2.5 4.8 2.8 0.4 1.2 2.5 1.1 SULTR1;3 At1g22150 0.3 0.5 0.7 2.0 4.5 3.5 3.1 1.2 0.9 SULTR2;1 At5g10180 1.2 1.6 0.9 1.0 0.8 2.1 4.1 3.1 3.5 0.8 1.3 0.7 1.0 SULTR2;2 At1g77990 0.6 1.4 1.1 1.6 2.8 0.3 0.3 0.9 1.1 SULTR3;1 At3g51900 SULTR3;2 At4g02700 1.3 0.6 0.6 0.6 1.0 2.9 1.8 1.1 1.1 0.7 0.6 0.9 1.0 SULTR3;3 At1g23090 0.6 0.7 1.2 1.2 1.2 0.7 0.6 0.7 1.0 SULTR3;4 At3g15990 1.2 1.6 1.6 1.6 2.2 2.5 3.8 2.7 1.0 SULTR3;5 At5g19600 1.1 0.7 0.6 0.7 0.7 0.6 0.8 1.0 1.0 SULTR4;1 At5g13550 1.0 1.5 1.4 1.5 1.8 2.4 2.6 1.3 3.1 3.0 3.1 1.1 1.0 SULTR4;2 At3g12520 0.8 1.5 1.9 2.2 2.7 1.0 1.0 0.9 1.2 SULTR? At1g80310 1.0 1.2 1.0 1.0 1.0 1.2 1.5 1.0 1.1 1.6 1.5 1.0 0.9 SULTR? At2g25680 0.7 0.6 0.8 0.8 0.6 0.3 0.5 1.2 1.0 ATP sulfurylase ATPS1 At3g22890 1.2 1.3 1.4 1.2 1.2 0.9 1.6 1.0 1.0 ATPS2 At1g19920 1.1 1.3 1.3 1.2 0.8 0.6 0.5 1.3 0.8 0.6 0.7 0.4 1.0 ATPS3 At4g14680 1.1 1.4 1.3 1.4 1.6 1.0 1.4 0.7 1.1 ATPS4 At5g43780 1.4 1.0 1.6 1.0 0.6 0.7 0.7 1.0 1.2 1.8 1.3 0.8 1.0 APS kinase APK1 At2g14750 0.9 1.3 0.9 0.7 1.1 1.3 1.8 1.7 0.9 APK2 At4g39940 0.9 1.1 0.9 0.8 1.0 0.5 0.6 0.7 1.1 1.1 2.3 1.7 0.9 APK3 At3g03900 1.2 0.9 0.8 0.8 0.7 1.4 1.2 1.0 1.1 APK4 At5g67520 0.5 2.8 0.6 2.1 0.4 2.5 0.4 0.9 1.0 APS reductase APR1 At4g04610 1.0 1.5 1.3 1.5 1.5 1.7 2.6 1.0 1.3 APR2 At1g62180 1.1 1.5 2.0 1.7 1.6 0.6 1.1 0.6 1.0 APR3 At4g21990 1.4 2.2 3.0 4.2 4.1 1.9 2.8 0.7 1.0 Sulfite reductase SIR At5g04590 1.3 1.3 1.4 1.4 1.3 1.1 1.5 1.7 1.1 1.0 1.5 0.9 0.9 OASTL&CAS BSAS1;1 At4g14880 1.1 1.3 1.2 1.0 1.1 1.3 1.3 1.6 1.3 0.7 1.0 1.0 1.1 BSAS1;2 At3g22460 0.7 0.8 1.1 0.6 1.0 1.1 0.6 1.1 1.2 BSAS2;1 At2g43750 1.1 1.1 1.2 1.1 1.3 0.6 0.7 0.6 1.0 BSAS2;2 At3g59760 0.8 1.2 1.7 1.4 1.3 1.1 0.9 1.2 2.0 1.2 1.4 0.9 1.1 BSAS3;1 At3g61440 1.0 1.0 1.2 1.2 1.1 1.1 0.8 0.6 0.8 0.7 1.1 0.6 1.2 BSAS4;1 At5g28020 1.2 1.1 1.0 1.1 1.1 1.7 1.4 0.9 0.9 0.4 0.4 0.5 1.0 BSAS4;2 At3g04940 0.6 0.9 1.0 1.0 0.8 1.7 1.4 1.3 1.1 0.9 0.7 0.8 1.0 BSAS4;3 At5g28030 0.2 1.0 1.1 0.5 0.8 0.7 0.7 0.5 BSAS5;1 At3g03630 0.6 1.1 1.1 0.9 0.6 0.4 0.6 0.7 0.3 0.3 0.3 0.6 1.1 Serine SERAT1;1 At5g56760 0.3 1.1 0.2 0.3 0.2 1.1 1.6 1.2 1.0 acetyltransferase SERAT2;1 At1g55920 0.3 0.3 1.2 0.2 0.2 1.7 2.2 1.4 1.0 448 Watanabe et al. d General Regulatory Patterns Revealed by serat Quadruple Mutants

Table 4. Continued Gene family Name AGI Q2;2 Q1;1 Q2;1 Q3;1 Q3;2 S1 S2 S3 S4 N4 P21 K11 K2 Gamma-glutamyl cysteine SERAT2;2 At3g13110 1.1 0.2 0.3 0.2 0.3 2.0 1.0 0.9 1.5 1.3 4.5 1.3 1.2 SERAT3;1 At2g17640 0.3 0.2 0.2 0.8 0.2 0.7 0.6 0.6 1.1 SERAT3;2 At4g35640 GSH1 At4g23100 1.3 1.4 1.8 1.6 1.4 1.1 0.6 0.7 0.7 1.6 1.3 0.7 1.0 GSH GSH2 At5g27380 1.2 1.5 2.3 1.9 1.5 2.6 1.6 1.3 0.7 1.1 1.3 0.6 1.2 Phytochelatin AtPCS1 At5g44070 0.9 1.1 1.3 1.2 1.4 1.5 1.2 1.2 1.2 1.4 1.2 0.8 0.9 synthase AtPCS2 At1g03980 0.1 0.7 0.4 0.4 1.0 1.1 1.2 0.9 0.9 predicted GPIanchored At5g60920 1.2 1.0 1.1 1.0 0.9 0.6 0.4 0.8 1.4 0.9 0.6 0.4 0.9 protein Cystathionine At3g01120 1.1 1.0 1.1 1.0 0.9 1.3 0.9 0.9 1.4 0.8 0.9 0.9 1.0 gamma-synthase At1g33320 0.8 0.3 0.02 0.8 0.1 1.0 1.0 1.3 0.9 Cyatathionine At3g57050 1.1 1.3 1.3 1.7 1.3 0.8 0.9 1.3 1.4 0.9 0.9 1.0 1.0 beta-lyase Methionine synthase At5g17920 0.9 At3g03780 1.1 1.1 1.3 1.0 0.9 1.3 0.6 1.1 2.5 1.2 1.1 0.5 0.9 S-Adenosylmethionine SAMS1 At1g02500 0.9 0.9 1.2 1.1 1.0 1.1 1.2 0.9 1.0 synthetase SAMS2 At4g01850 0.9 1.0 1.1 1.0 0.9 1.4 1.5 1.3 1.5 0.9 1.1 1.1 0.9 SAMS3 At3g17390 1.2 1.1 1.6 1.6 1.6 3.2 2.3 1.6 2.7 0.9 0.9 1.0 1.0 SAM At2g36880 1.0 1.0 1.3 0.9 1.0 1.5 1.5 0.9 1.1 3-Phosphoglycerate PGDH At1g17745 1.1 1.4 3.2 4.1 3.2 2.9 4.0 1.8 1.5 dehydrogenase putative PGDH At4g34200 0.9 1.2 1.6 1.8 1.5 1.2 0.9 1.9 0.7 1.0 4.5 1.4 1.0 putative PGDH At3g19480 0.8 1.0 0.9 0.7 0.7 0.2 0.4 0.3 1.0 3-Phosphoserine PSAT At4g35630 0.9 1.2 2.3 2.5 2.5 1.6 2.6 1.6 1.1 aminotransferase putative PSAT At2g17630 1.1 1.3 1.7 2.0 1.5 1.0 0.8 0.6 1.0 3-Phosphoserine PSP At1g18640 1.0 1.0 1.2 1.6 1.3 1.1 0.9 0.9 1.0 phosphatase Sulfite oxidase SOX At3g01910 1.0 1.0 1.2 1.1 0.9 1.1 1.0 0.9 1.0 Thiohydroximate At1g24100 0.8 1.2 1.3 1.0 1.1 0.8 1.4 0.7 1.1 glucosyltransferase Sulfite:UDP-glucose At4g33030 1.1 1.1 1.9 1.9 1.4 0.7 6.9 0.8 1.0 sulfotransferase Methionine sulfoxide At4g21840/30 3.2 0.3 5.1 1.2 1.3 1.8 4.9 1.4 reductase domaincontaining protein S-Adenosyl-L-methionine: carboxyl methyltransferase family protein At1g66690 15.5 0.4 3.8 5.9 11.5 7.0 12.0 1.1 Watanabe et al. d General Regulatory Patterns Revealed by serat Quadruple Mutants 449

Table 4. Continued Gene family Name AGI Q2;2 Q1;1 Q2;1 Q3;1 Q3;2 S1 S2 S3 S4 N4 P21 K11 K2 MutT/nudix family protein similar to Thiamine pyrophosphokinase At5g19470 0.9 2.2 3.5 9.4 13.4 1.9 2.2 1.8 2.6 1.0 1.1 Sulfotransferase At3g45070 3.0 0.2 1.8 4.2 0.9 1.2 0.9 1.3 1.7 1.9 0.6 1.0 At3g45080 1.0 At1g28170 0.1 0.1 0.1 0.1 0.9 4.8 1.1 0.4 1.1 brassinosteroid ST At2g14920 14.5 0.9 9.2 12.9 2.1 0.8 1.1 1.0 At2g03770 1.8 0.8 0.8 2.8 9.0 3.6 1.0 0.9 1.0 brassinosteroid At1g13420 0.1 1.0 1.3 1.2 1.9 1.6 2.2 2.2 1.6 1.3 1.2 1.3 1.0 putative ST brassinosteroid At1g13430 1.0 putative ST brassinosteroid ST At2g03760 1.0 1.0 2.5 4.3 2.0 4.9 1.9 2.3 1.2 At5g43690 0.6 1.7 0.8 6.2 6.3 3.2 2.2 1.5 0.9 At2g03750 0.9 1.0 0.7 0.6 0.7 0.3 0.5 0.4 1.0 steroid sulfotr At4g26280 5.0 2.0 1.7 5.5 1.9 1.0 1.1 1.0 0.9 ansferase ST hydroxy jasm At5g07010 1.9 3.7 7.2 5.7 3.2 1.0 0.8 1.6 1.5 1.0 5.5 2.4 1.0 onates ST At5g07000 1.2 1.1 1.1 1.1 0.6 0.7 1.5 0.5 1.0 AtST5a dsgss, Phe/ At1g74100 0.9 1.1 1.2 1.0 1.0 0.8 1.5 1.6 1.0 Trp-derived At2g27570 0.5 4.7 1.3 0.2 1.1 1.5 1.0 1.2 AtST5b dsgss, At1g74090 1.0 1.2 1.0 1.3 1.2 0.9 0.9 0.8 1.0 Met-derived AtST5c dsgss, At1g18590 1.0 1.3 1.0 1.1 1.3 0.7 0.8 2.2 1.1 Met-derived Oligopeptide AtOPT1 At5g55930 1.1 1.2 2.6 2.6 1.7 0.8 1.5 1.5 1.0 1.5 0.8 1.5 0.8 transporter AtOPT2 At1g09930 AtOPT3 At4g16370 AtOPT4 At5g64410 0.5 1.0 0.7 0.6 0.6 2.0 1.5 1.7 2.4 3.5 0.7 1.4 1.1 AtOPT5 At4g26590 0.8 0.9 0.8 0.5 0.7 1.3 1.0 1.3 1.0 AtOPT6 At4g27730 1.2 1.4 8.7 9.9 1.9 0.4 0.5 0.6 0.9 AtOPT7 At4g10770 1.4 1.3 0.9 0.8 1.1 1.4 0.8 0.7 0.9 AtOPT8 At5g53520 0.9 5.9 0.5 2.7 0.9 3.6 0.9 1.4 0.9 AtOPT9 At5g53510 0.2 0.2 0.1 0.3 0.5 0.9 1.1 1.4 1.1 Sulfurtransferasese/ Rhodanese Gene Family AtStrI AtStr1 At1g79230 0.9 1.0 1.3 1.5 1.0 1.0 0.9 1.0 1.0 450 Watanabe et al. d General Regulatory Patterns Revealed by serat Quadruple Mutants

Table 4. Continued Gene family Name AGI Q2;2 Q1;1 Q2;1 Q3;1 Q3;2 S1 S2 S3 S4 N4 P21 K11 K2 AtStr2 At1g16460 1.0 1.0 1.2 1.0 1.0 0.8 0.7 0.6 1.0 AtStrII AtStr3 At5g23060 1.1 1.0 0.9 0.7 0.9 1.3 0.8 1.0 1.0 0.1 0.3 0.5 0.8 AtStr4 At4g01050 1.1 0.8 0.7 0.6 0.8 1.0 0.5 0.6 0.9 0.2 0.5 0.5 0.9 AtStrIII AtStr5 At5g03455 0.8 0.9 1.2 1.1 1.0 1.1 1.2 2.7 1.0 AtStr6 At1g09280 1.1 0.9 1.1 0.8 1.1 0.7 0.9 0.9 1.0 AtStr7 At2g40760 1.1 1.3 1.3 1.2 1.2 0.6 0.8 0.8 AtStr8 At1g17850 0.8 1.1 0.9 1.2 0.9 2.4 1.6 1.0 1.1 0.5 0.7 0.8 AtStrIV AtStr9 At2g42220 1.0 1.0 0.7 0.7 0.8 0.1 0.4 0.5 0.9 AtStr10 At3g08920 1.3 1.0 0.8 0.9 1.1 0.6 0.8 1.3 1.0 0.1 0.5 0.6 1.0 AtStr11 At4g24750 0.9 1.0 1.1 0.9 0.8 0.2 0.5 0.4 1.1 AtStrV AtStr12 At5g19370 0.8 1.0 1.0 0.9 1.0 0.5 0.8 1.0 1.0 AtStr13 At5g55130 1.0 0.9 1.0 1.2 1.1 2.6 1.6 0.6 0.7 1.1 1.0 0.9 1.1 AtStrVI AtStr14 At4g27700 0.9 1.0 0.7 0.7 0.8 0.2 0.5 0.6 1.0 AtStr15 At4g35770 0.6 0.7 1.0 0.6 0.4 0.2 0.1 0.3 0.5 0.1 0.2 0.7 1.2 AtStr16 At5g66040 0.9 1.1 1.5 1.5 1.1 1.4 0.6 1.5 1.1 0.4 1.0 1.0 1.0 AtStr17 At2g17850 1.4 1.3 0.9 1.0 1.3 0.6 1.0 1.2 1.0 AtStr18 At5g66170 1.1 0.5 1.0 0.8 1.2 1.5 2.0 0.9 1.7 2.8 3.0 4.1 1.0 Alliinase family At1g23320 0.4 0.3 0.8 0.7 1.5 1.8 1.0 0.6 1.1 Cysteine desulfurase family At1g34040 0.7 0.6 0.5 0.5 0.4 6.3 0.6 0.9 At1g34060 0.6 At1g70560 0.9 0.9 1.3 1.2 0.9 1.5 1.6 1.3 1.0 0.8 0.9 At4g24670 0.7 1.0 0.7 0.5 0.6 0.5 0.7 0.3 0.9 At1g08490 1.1 0.7 1.1 1.1 0.8 1.3 1.0 1.0 1.0 At3g62130 1.2 1.0 1.1 1.0 1.2 0.8 1.1 1.1 1.2 At5g26600 At5g65720 1.1 1.1 1.4 1.3 1.1 2.2 1.8 1.2 2.1 1.2 0.9 0.7 1.0 S response genes Vikin/UP9/LSU At3g49580 2.4 2.0 6.4 26.6 36.6 27.3 30.9 28.5 4.1 10.1 6.5 4.1 1.1 Chac-c protein At5g26220 1.6 1.4 4.2 10.5 18.3 6.8 10.6 3.8 13.7 1.2 1.9 3.8 1.0 SHM7 At1g36370 0.9 1.1 1.6 1.9 2.0 6.0 7.9 5.0 9.0 2.7 1.2 1.0 1.1 MS 5 protein At5g48850 0.1 0.9 3.1 12.6 13.9 4.0 1.7 2.0 1.2 putative At2g44460 1.0 0.5 2.7 8.3 7.3 2.6 1.3 2.1 1.0 myrosinases F-box protein At1g23390 0.9 1.2 0.8 0.4 0.3 0.2 0.4 0.6 1.0 Fold changes relative to the each control are shown. Blank cells indicate not determined. Changes.1.5-fold and,0.66-fold are colored in pink and blue, respectively. Data are from the same reference as Table 2 Watanabe et al. d General Regulatory Patterns Revealed by serat Quadruple Mutants 451

452 Watanabe et al. d General Regulatory Patterns Revealed by serat Quadruple Mutants noteworthy. No uniform response was identified that can easily be related to either OAS or thiol contents, or to a particular phenotype. The root high-affinity SULTR were detected in these samples and SULTR1;1 (At4g08620) is down-regulated in four of the mutants but not in Q3;1, and SULTR1;2 (At1g78000) is consistently up-regulated in the group 2 mutants; however, SULTR1;3 (At1g22150) shows an inconsistent pattern. The vacuolar export transporters, especially SULTR4;2 (At3g12520), are up-regulated in the group 2 quadruple mutants, correlating with the sulfate-starvation phenotype. The reason for the induction of these sulfur genes remains elusive, as the tissue is still not entirely deprived of sulfate, with the lowest sulfate amounts being found in the Q2;1, Q3;1, and Q3;2 mutants, with 50, 40, and 20% of wild-type, respectively (Table 1). However, induction does appear to be related to growth repression. Thus, we also scored for classical S- starvation response markers besides those genes directly associated with sulfate metabolism (Figure 1 and Table 4). The amounts of the likely signal molecule OAS in the mutants are either close to the level in wild-type plants (Q2;2, Q2;1, and Q3;1) or even decreased (Q1;1 and Q3;2) (Table 1). Correlating with the sulfate content and the phenotype, but not with the OAS content, the low-s marker genes (Nikiforova et al., 2003; Maruyama-Nakashita et al., 2006; Howarth et al., 2008; Dan et al., 2007), LSU (response to low sulfur) (At3g49580), a Chac (cation transport)-like gene (At5g26220), an MS5 (male-sterile 5) family gene (At5g48850), a putative myrosinase (At2g44460), and SHM7 (serine hydroxymethyltransferase 7; At1g36370) are most strongly induced in the lines Q3;1 and Q3;2, but also clearly increased in line Q2;1; however, little or no change in the expression of these genes is seen in the group 1 mutants, again corroborating the clustering results (Figure 2) and the functional categorizations (Tables 2 and 3). As an induction of the low-s marker genes is also displayed by N-, P-, and K- deprived plants, a NuDIS-related activation of these genes can be assumed, indicating the involvement of metabolic and physiological processes in common. Quadruple serat Mutants Display Senescence-Like Processes Maintenance of only one SERAT isoform resulted in transcriptional and metabolic consequences that are eventually reflected in phenotypic effects. The physiological and metabolic features of the group 2 quadruple mutants Q2;1, Q3;1, and Q3;2 resemble features of NuDIS, namely retarded growth, chlorosis, and perturbed amino acid content (Table 1). In order to investigate whether the phenotype of the group 2 quadruple mutants can be related to senescence processes, transcript data from the quadruple mutants were scored for effects on 827 known SAGs (Buchanan-Wollaston et al., 2003; Gepstein et al., 2003), which are up-regulated during DEVS. The quadruple mutants showed a clearly over-represented alteration of SAG gene expression (Table 2). Furthermore, the group 2 mutants display an very similar transcript response, both quantitatively and qualitatively, to one another and a good match to N, P, and induced K starvation, whereas the similarities to the group 1 quadruple mutants and to constitutive K starvation are much fewer (Tables 2 and 3). These results indicate that the dwarf quadruple mutants in particular and the nutrientstarved plants display substantial overlaps with senescence processes (see also Table 3). For selection of SAGs that were altered in the quadruple mutants, a cut-off of four-fold in at least one of the mutants for regulatory genes and of 10-fold for all other SAGs was applied. In total, 189 of the known 827 SAGs (23%) show large alterations in their transcript levels compared to wild-type plants, using these stringent cut-off values. The resulting gene list of SAGs includes genes coding for, among others, transcription factors, proteins with roles in signal transduction, macromolecule degradation and mobilization, stress, transport, hormone-related proteins, and secondary metabolite synthesis (Table 5). In comparison to the response of the SULTR (Table 4), it is especially intriguing to see that a nitrate transporter (At1g12940) and a phosphate transporter (At2g38940) are up-regulated, and a zinc efflux transporter (At1g05300) is induced, while potassium transporters (At2g35060 and At1g70300) remained unaltered or slightly decreased (Table 5). For comparative reasons, genes with lower expression values were also included when matching to the data of a senescence mutant old1/cpr5 (Jing et al., 2008), which shows early senescence through deregulation of the cellular redox balance, with increased expression of reactive oxygen species network genes. The selected SAGs list includes various classical senescence genes and categories, such as WRKY53 (At4g23810) (Miao et al., 2004), SAG12 (At5g45890) (Gombert et al., 2006), PAP1 (At1g56650), and PAP2 (At1g66390) (Borevitz et al., 2000) or RNAse1 (At2g02990) involved in RNA degradation, genes of degradatory pathways (Bariola et al., 1994) and transcription factors (e.g. the NAC family known to be involved in senescence) (Guo and Gan, 2006; Balazadeh et al., 2008). All these genes show substantial overlap to altered expression patterns under nutrient-deprived growth conditions (Table 5). DISCUSSION Plant homoeostasis is a result of complex regulatory processes that keep plant metabolic contents and physiological responses in balance, despite regular, temporary, or localized changes in inputs such as light, nutrients, and water, or other environmental conditions as well as biotic stresses. The system is generally thought to be able to buffer imbalances to a certain extent, but may then have to shift to new homoeostatic states when severe deficiencies in nutrient supply or limitations in growth conditions occur. Such adaptations might be reversible in the short term, but prolonged imbalances seem to lead to progression into salvage and rescue programs. These usually give rise to accelerated-developmental programs leading to early flowering and seed formation in annual plants, and generally accompanied by senescence processes such as reserve metabolite mobilization and nutrient re-allocation to

Table 5. Gene Expression Changes in Senescence-Associated Genes (SAGs). Name AGI Q2;2 Q1;1 Q2;1 Q3;1 Q3;2 12S1 S212 S312 S412 N4 P2 K K2 Putative transcription factors and nucleic acid binding proteins Putative protein:protein interaction Putative ubiquitination control ANAC42 At2g43000 3.6 16.1 9.5 13.2 19.1 3.4 3.6 2.0 1.0 WRKY26 At5g07100 3.3 2.1 33.7 36.9 13.7 1.3 0.8 2.2 1.1 0.5 0.7 0.9 1.1 AT hook At4g12080 1.8 2.0 9.3 8.2 10.1 1.4 1.7 1.8 1.0 ANAC3 At1g02220 2.6 4.0 13.3 7.7 2.1 2.1 2.0 1.7 1.0 eif-2 At1g76720 3.5 3.3 6.4 1.1 3.9 1.2 0.8 1.0 WRKY75 At5g13080 0.9 2.3 10.3 2.7 4.1 2.8 12.6 12.7 1.1 ANAC47 At3g04070 1.2 0.9 3.3 4.7 1.9 1.0 1.6 5.9 1.5 AP2/ERF At5g13330 0.7 1.4 4.4 4.3 0.8 1.5 1.6 0.8 1.6 0.7 2.3 4.1 1.3 ANAC102* At5g63790 1.1 1.0 1.6 1.6 1.7 0.7 0.7 1.2 1.9 2.6 2.8 1.8 1.3 NAC19* At1g52890 0.7 1.1 2.5 1.1 1.8 1.8 0.8 2.1 0.8 2.4 22.5 6.1 1.1 ANAC92 At5g39610 0.9 1.2 1.3 1.2 1.0 2.2 1.4 1.1 0.6 0.9 1.4 1.0 0.9 ANAC32 At1g77450 0.2 0.8 1.5 1.9 1.5 1.3 1.6 2.9 2.4 6.8 2.8 5.3 1.0 ANAC87 At5g18270 0.2 0.7 1.5 1.7 0.8 1.7 1.4 2.9 1.1 Telomeric DNA-binding At5g13820 0.1 0.8 1.2 1.5 1.2 2.0 3.0 1.9 1.0 protein 1 (TBP1) Yippee family At3g55890 1.3 1.7 2.1 0.3 0.1 3.8 1.9 3.9 1.1 protein (mdgl-1) CCAAT-binding (NF-YA10) At5g06510 0.1 0.4 1.1 1.5 1.6 10.0 1.9 2.3 1.3 MYB2 At2g47190 0.4 1.6 1.3 0.2 0.4 5.3 3.7 5.1 1.0 ANAC56 At3g15510 0.1 0.6 0.8 0.6 0.7 1.7 0.8 1.3 1.0 ANAC29/NAP At1g69490 0.8 0.7 0.4 0.3 0.4 1.8 0.7 1.8 0.8 1.2 0.9 1.2 0.9 ANAC16 At1g34180 1.3 0.2 0.6 1.3 0.1 2.0 0.9 6.5 1.0 Jumonji (jmjc) (PLU-1) At1g63490 0.1 0.7 0.6 0.6 1.3 1.9 1.2 0.7 1.0 Zinc finger_an1-like At3g28210 0.1 1.2 0.3 1.6 0.2 0.9 1.1 1.5 1.2 2.2 2.8 3.3 1.1 ANAC100 At5g61430 0.6 0.6 0.5 0.6 0.03 2.6 1.7 1.7 1.2 LIM domaincontaining At5g66630 0.9 0.2 0.6 0.2 0.1 2.4 1.3 0.7 1.0 protein ANAC46 At3g04060 0.2 0.2 0.6 0.5 0.1 0.9 1.1 1.0 1.4 2.0 1.4 3.5 1.0 WD-40 At5g42010 4.4 0.5 3.2 4.4 3.4 2.5 2.3 1.5 1.1 Ankyrin repeat family At4g26120 0.2 0.7 1.2 0.6 1.0 5.6 1.9 1.4 1.0 protein (BTB/POZ) VQ motif-containing At1g68450 0.6 0.6 0.2 1.2 1.0 1.5 1.8 1.8 1.4 1.6 4.5 3.9 1.0 protein Zinc finger (C3HC4- At2g42360 4.3 1.3 6.5 4.3 6.7 0.4 1.4 23.4 1.2 type RING) Zinc finger (C3HC4- type RING) At4g23450 9.4 0.7 4.3 1.5 2.7 1.1 1.0 1.9 2.9 1.8 1.1 2.2 1.0 Watanabe et al. d General Regulatory Patterns Revealed by serat Quadruple Mutants 453

Table 5. Continued Protein kinase and phosphatases Name AGI Q2;2 Q1;1 Q2;1 Q3;1 Q3;2 12S1 S212 S312 S412 N4 P2 K K2 Kelch repeatcontaining At1g15670 1.6 1.5 5.0 3.3 2.3 2.1 2.4 1.0 1.7 0.8 0.9 2.8 1.1 F-box F-box (SKIP2) At2g27310 1.2 3.8 1.6 5.9 0.7 1.3 2.0 2.1 1.3 Seven in absentia (SINA) At3g13672 1.0 1.0 4.3 1.9 1.7 1.2 0.5 2.6 1.0 Disease resistance (LRR) At3g24954 5.5 11.1 79.8 1.8 3.7 8.6 4.8 4.6 CBL-interacting protein At5g25110 0.9 5.6 13.7 4.0 11.7 1.4 0.7 1.2 1.6 1.3 1.2 1.1 kinase 25 (CIPK25) Leucine-rich repeat At3g25010 1.2 1.0 1.6 0.1 0.7 11.2 1.5 2.4 1.0 Leucine-rich repeat At4g39270 0.04 1.3 1.0 0.9 1.0 2.2 1.5 1.0 1.0 Protein kinase At5g55560 0.1 0.5 0.7 0.5 0.6 1.3 2.4 2.2 1.7 Disease resistance At1g57630 0.2 0.7 0.3 0.1 1.0 12.3 7.9 13.9 1.0 (TIR class) Signaling Meprin and TRAF At4g01390 8.0 17.4 6.1 21.4 29.5 0.9 2.7 1.1 Hormone pathways Auxin-responsive protein At2g45210 7.9 0.4 22.7 13.3 5.1 0.7 0.6 0.8 1.1 1.7 1.6 113.6 1.0 Phosphotransfer At3g16360 0.3 1.5 5.2 12.3 5.9 1.3 2.6 2.6 1.0 WRKY53-related WRKY53 At4g23810 3.7 6.5 10.6 9.2 6.7 0.4 2.0 2.7 genes SAG12 (cysteine At5g45890 1.6 5.9 2.3 12.3 7.0 120.3 1.0 1.9 0.8 proteinase) SAG24 (60S ribosomal At1g66580 1.0 1.0 1.0 1.1 1.0 1.9 1.1 0.8 1.8 1.0 1.3 1.5 1.1 protein) SAG101 (putative At5g14930 1.2 0.8 1.2 1.4 1.7 1.2 1.4 1.9 1.2 1.5 0.9 1.9 1.0 acyl hydrolase) SIRK (light At2g19190 0.4 0.9 1.8 2.9 1.1 0.4 1.4 1.8 0.9 repressible receptor protein kinase) SUVH2 (SET domaincontaining At2g33290 0.6 4.5 5.5 5.5 3.5 1.5 1.3 0.8 1.1 protein) PAP1-related MYB (PAP1, AtMYB75) At1g56650 1.2 1.3 4.2 5.4 6.7 2.1 1.7 1.4 1.2 16.9 8.3 2.1 1.0 genes MYB (PAP2, AtMYB90) At1g66390 0.8 0.4 0.6 10.4 5.6 1.7 2.3 1.2 1.1 179.4 26.6 0.7 1.2 EGL3 Enhancer of Glabra3 At1g63650 3.4 4.0 8.2 7.3 3.5 1.1 bhlh (TT8) At4g09820 2.7 1.6 4.7 2.0 3.2 15.3 1.1 0.7 1.0 WRKY (TTG2) At2g37260 1.3 2.8 2.1 3.4 2.8 2.5 1.1 1.2 1.0 CHS (TT4) At5g13930 0.8 0.9 1.4 2.1 1.8 0.4 0.6 0.9 1.0 1.9 2.1 1.9 1.1 CHI (TT5) At3g55120 0.9 1.1 1.4 1.7 1.7 2.1 1.2 1.1 0.5 1.2 1.2 1.3 0.9 CHI (CHI) At5g05270 0.9 0.8 1.0 1.3 1.4 0.9 0.9 1.4 1.7 2.2 1.5 1.3 1.0 F3H (TT6) At3g51240 1.0 0.8 1.3 2.0 1.9 1.3 1.2 1.3 0.8 3.2 2.2 1.7 0.9 F3#H (TT7) At5g07990 2.0 1.6 2.1 3.4 2.9 3.3 2.6 1.0 1.0 454 Watanabe et al. d General Regulatory Patterns Revealed by serat Quadruple Mutants

Table 5. Continued Name AGI Q2;2 Q1;1 Q2;1 Q3;1 Q3;2 12S1 S212 S312 S412 N4 P2 K K2 ANAC12-related genes OLD1/CPR5 OLD5 Fd3GT (UGT78D2) At5g17050 1.0 1.3 1.6 1.6 1.7 2.0 2.2 1.2 0.8 DFR (TT3) At5g42800 0.7 1.4 2.3 5.3 5.4 20.2 18.7 2.0 1.0 ANS (TT18, LDOX) At4g22880 0.7 1.1 1.7 4.9 4.5 25.0 6.9 1.1 A5GT (UGT75C1) At4g14090 0.4 1.5 3.7 7.0 9.0 17.1 5.1 2.3 1.0 A3G2 XTvUGT79B1 At5g54060 1.4 1.9 6.0 14.6 12.1 8.2 6.9 1.8 1.0 A5GMaT (A5G6# MaT) At3g29590 0.1 0.2 1.4 2.7 2.8 3.7 2.6 1.1 1.1 A3GCoT (A3G6 p-cout) At1g03940 0.8 2.3 3.1 7.2 6.5 50.6 11.4 0.9 A3GCoT (A3G6 p-cout) At1g03495 0.8 2.3 3.1 7.2 6.5 50.6 11.4 GST (TT19, AtGSTF12) At5g17220 0.7 1.5 2.9 4.6 5.8 0.7 1.3 1.7 1.0 23.2 19.0 2.9 1.0 ANAC12 At1g32770 0.2 0.1 0.3 0.1 0.2 0.9 0.9 1.0 1.1 Remorin family protein At4g00670 30.2 19.8 10.0 96.1 59.7 2.6 1.8 1.9 Regulator of pathogenesisrelated At5g64930 0.8 1.0 1.0 0.8 0.7 1.4 0.9 0.9 1.0 (PR) genes Fe-S binding protein At5g50210 1.3 1.3 0.8 0.8 0.9 1.3 1.5 0.9 0.9 with quinolinate synthase activity Macromolecule degradation and mobilization AGI Q2;2 Q1;1 Q2;1 Q3;1 Q3;2 S1 S2 S3 S4 N4 P2 K K2 Protein degradation Amino acid degradation and N mobilization Matrix At4g16640 23.6 1.2 12.5 5.4 14.4 2.0 1.2 0.6 0.9 metalloproteinase Subtilase At1g32940 0.9 4.2 13.9 4.8 6.4 2.9 3.0 2.1 1.1 Glutamate decarboxylase At5g17330 2.3 1.9 7.8 16.1 13.0 1.6 2.3 1.7 1.5 1.7 1.4 24.1 1.5 1 (GAD 1) Glutamate decarboxylase At2g02010 0.9 1.9 12.0 22.0 13.4 2.2 3.8 1.0 Lactoylglutathione At1g15380 0.4 0.1 0.7 0.9 0.2 0.2 1.0 3.4 1.0 lyase/ glyoxalase I Nucleic acid degradation Ribonuclease 1 (RNSse1) At2g02990 2.4 26.2 31.9 28.1 10.5 7.2 25.1 6.6 1.0 Lipid degradation Lipid transfer protein 3 (LTP3) At5g59320 1.4 1.2 24.2 13.6 4.4 0.5 0.6 1.1 1.3 0.5 0.3 3.1 1.8 and mobilization Phospholipase D At3g05630 1.3 2.0 9.2 10.2 6.1 1.3 0.4 0.8 1.6 4.2 21.8 2.3 1.1 Carbohydrate Arabinogalactanprotein At2g22470 6.1 13.5 19.4 16.7 8.4 1.6 1.4 11.3 1.2 metabolism (AGP2) Glycosyl hydrolase At3g04010 17.7 3.5 11.3 14.9 15.7 1.3 1.3 5.7 1.3 Wall-associated kinase At1g21240 5.1 0.6 49.9 20.4 20.8 75.6 1.8 1.6 1.0 1 (WAK1) UDP-glucoronosyl/UDPglucosyl transferase At4g34135 5.3 3.5 12.3 24.8 9.0 6.5 4.0 1.1 Watanabe et al. d General Regulatory Patterns Revealed by serat Quadruple Mutants 455

Table 5. Continued Macromolecule degradation and mobilization AGI Q2;2 Q1;1 Q2;1 Q3;1 Q3;2 S1 S2 S3 S4 N4 P2 K K2 Glycosyl hydrolase At4g16260 0.9 3.2 23.7 20.1 15.4 1.0 0.8 0.5 0.6 0.2 3.8 3.0 1.0 Glycosyl hydrolase At5g24540 12.8 3.3 3.4 2.8 10.9 1.7 1.3 9.7 1.1 UDP-glucoronosyl/UDPglucosyl At2g15480 2.1 1.1 13.6 7.6 3.8 3.9 2.5 3.3 1.0 transferase Pectinesterase At2g47040 3.6 1.2 10.5 1.1 1.9 0.6 1.1 1.0 Pectinesterase At2g45220 1.0 1.5 13.2 1.4 1.0 1.1 3.3 2.8 1.5 Invertase/pectin At5g46960 0.1 1.0 1.0 0.6 0.5 1.2 1.0 1.0 methylesterase inhibitor Endo-polygalacturonase At2g41850 0.6 0.7 0.1 0.6 0.2 2.4 1.3 2.4 1.0 Endo-polygalacturonase At3g57510 0.2 0.6 0.05 0.1 1.5 1.2 1.1 2.1 1.4 (ADPG1) Pyruvate kinase At3g49160 0.1 0.8 1.1 0.1 0.04 7.8 6.8 0.7 1.0 Transport High-affinity nitrate At1g12940 7.3 5.0 4.1 2.1 1.0 8.8 0.8 1.4 0.6 transporter Zinc transporter protein At1g05300 1.1 3.5 1.3 8.8 2.8 0.5 0.4 1.8 1.0 Phosphate transporter At2g38940 3.6 5.3 29.6 30.7 14.3 0.9 35.5 1.0 (AtPT2) Tic20 (chloroplast protein import component) At1g04940 4.3 8.5 8.5 15.7 5.9 1.7 1.2 1.1 Sugar transporter At3g05400 2.9 3.4 6.3 14.3 29.6 12.0 30.8 5.5 11.9 2.8 1.9 5.4 1.1 Tic20 (chloroplast protein At4g03320 3.5 0.9 16.7 22.7 11.2 2.2 1.3 16.3 1.0 import component) Cation/hydrogen exchanger At1g64170 0.5 0.8 15.1 20.1 6.9 0.9 0.5 4.1 0.9 Glucose-6-phosphate/ At1g61800 0.2 1.4 9.2 16.0 15.6 15.5 36.7 13.1 2.8 phosphate translocator Proton-dependent oligopeptide At5g46050 0.9 1.0 11.8 11.8 0.7 0.7 0.9 2.4 1.1 transport (POT) Mitochondrial benzodiazepine At2g47770 0.7 1.1 10.3 2.1 1.6 1.2 1.2 10.8 1.0 receptor Potassium transporter At2g35060 0.8 1.0 1.2 0.7 0.6 1.8 1.9 0.6 0.8 Potassium transporter At1g70300 0.7 0.6 1.3 1.1 0.7 1.7 2.5 1.2 1.1 ATPases AAA-type ATPase At3g28510 12.8 0.4 3.7 3.5 5.0 466.7 1.2 4.4 1.0 AAA-type ATPase At3g28580 25.1 1.3 7.2 0.7 1.8 5.6 1.5 3.2 1.0 Antioxidants Glutaredoxin At1g03850 4.3 2.8 13.2 10.5 6.6 0.4 0.9 3.9 1.4 (thioltransferase) Stress and Glutathione S-transferase At5g62480 1.4 1.9 4.1 7.4 10.5 3.0 1.5 4.9 1.1 detoxification (ATGSTU9) Glutathione S-transferase (AtGSTU10) At1g74590 2.5 5.8 13.2 0.5 2.0 2.4 5.8 5.7 1.1 456 Watanabe et al. d General Regulatory Patterns Revealed by serat Quadruple Mutants

Table 5. Continued Macromolecule degradation and mobilization AGI Q2;2 Q1;1 Q2;1 Q3;1 Q3;2 S1 S2 S3 S4 N4 P2 K K2 Defense-related Chitinase At2g43570 l4.1 4.7 44.9 6.3 2.6 0.6 3.5 9.6 1.0 Avirulence induced At1g33960 3.5 2.9 17.7 8.0 0.2 1.9 1.1 5.3 1.0 gene (AIG1) Alkaloid biosynthesis FAD binding protein At1g30700 1.9 3.7 11.9 21.6 21.4 1.1 2.5 2.4 1.2 FAD binding protein At1g26390 7.6 7.5 23.6 0.8 11.8 0.8 18.3 2.4 2.8 FAD binding protein At1g26420 2.6 2.0 3.7 8.0 11.7 0.2 2.9 3.0 1.8 Strictosidine synthase At3g51440 1.2 0.9 11.5 5.5 1.1 1.4 1.8 4.6 1.3 Flavonoid/anthocyanin Acyltransferase At5g39090 6.1 5.3 16.4 13.8 7.2 2.9 1.1 2.1 1.0 pathway Leucoanthocyanidin At3g55970 1.4 1.7 25.0 0.8 2.6 0.8 26.5 5.0 1.1 dioxygenase Unclassified enzymes, Fe-S metabolism (SufE2) At1g67810 6.3 1.9 6.2 5.5 10.2 10.0 18.0 1.9 0.9 of unknown role in senescence Cytochrome P450 At5g67310 22.7 3.2 9.3 2.4 1.9 3.7 2.5 3.5 1.1 Similar protein to SAG102 At1g19200 5.3 2.7 11.9 6.8 2.4 2.9 10.2 1.7 0.8 putative cytochrome At2g30750 15.4 1.4 1.9 4.6 1.2 1.3 12.2 7.9 2.4 P450 71A12 Phospholipid-transporting At3g25610 1.4 0.8 12.0 5.6 2.4 2.1 2.6 2.7 0.9 ATPase Flavin-containing At1g19250 1.9 0.6 24.4 2.2 2.8 4.0 7.0 12.3 1.0 monooxygenase (FMO) Cytochrome P450 76C2 (YLS6) At2g45570 1.2 1.8 14.2 3.1 0.6 13.5 3.0 3.5 1.2 Unknown genes Expressed protein At2g04460 21.1 12.4 32.2 25.7 12.1 0.8 27.9 0.8 0.9 Expressed protein (Copper At2g18680 0.9 16.0 11.0 5.1 14.8 3.2 2.2 3.8 1.2 amine oxidase) Expressed protein At3g57950 5.8 4.1 12.6 6.0 3.5 6.3 1.0 12.3 1.1 Expressed protein At3g18250 4.1 1.1 13.2 7.7 3.3 0.5 2.3 6.1 Expressed protein At2g44240 1.1 1.2 1.2 1.4 10.0 6.5 1.1 12.6 1.0 Expressed protein At1g30250 0.9 0.7 0.4 0.1 0.1 1.4 1.0 1.8 Gene expression changes on 827 SAGs (Buchanan-Wollaston et al., 2003) are scored. Cut-offs of four-fold in at least one of the quadruple mutants for regulatory genes, and of 10-fold for all other SAGs, were applied to select the genes displayed. A few genes that were up-regulated in old1/cpr5 mutant (Jing et al., 2008) but with values below the cut-offs are also included and are indicated by an asterisk. In addition, expression changes for WRKY53, PAP1, and ANAC12-related genes are shown. Blank cells indicate not determined. Changes.2-fold and,0.5-fold are colored in pink and blue, respectively. Data are from the same references as Table 2. Watanabe et al. d General Regulatory Patterns Revealed by serat Quadruple Mutants 457

458 Watanabe et al. d General Regulatory Patterns Revealed by serat Quadruple Mutants generative organs (Figure 3). We thus linked observations on plants perturbed in sulfur metabolism by serial knockouts of each of four of five SERAT isoforms (Watanabe et al., 2008a) to results obtained for plants exposed to nutrient stress, specifically S, N, P, and K deprivation and a senescence mutant. Metabolite Profiling of the Quadruple Mutants Serial serat quadruple mutants, each of which has only one of the isoforms remaining, were used to address the question what is the effect of a continuous perturbation of the OAS and thiol synthesizing system (Table 1)? First, all mutants, even those that showed no morphological phenotype, displayed metabolic and transcriptional responses, although these differed somewhat between the genotypes. With the exception of Q2;2, in which the mitochondrial isoform remained intact and SERAT activity was similar to wild-type, all other mutants displayed very low enzyme activities of about 10% of wild-type or less. However, all five mutants showed levels of OAS, thiols, and chlorophyll that did not correlate with the residual enzyme activity. Moreover, the sub-cellular location of the remaining isoform did not correlate with the observed phenotypes and metabolic profiles. Q1;1 and Q2;2 (group 1) both grow normally and show slightly decreased OAS and thiol levels. In contrast, Q2;1, Q3;1, and Q3;2 (group 2) display growth retardation and perturbed amino acid contents. It can be assumed that in these mutants, plant growth rates are adjusted to the limited availability of thiols. As a consequence, upon reaching a new equilibrium, OAS and thiol contents of the mutants are comparable to the wild-type in Q2;1 and Q3;1. Thus, plant growth appears to be correlated with a reduced metabolite supply, most likely by sensing alterations in metabolic fluxes rather than changes in pool size. In Q3;2, the mutant with the lowest remaining SERAT activity (2%), cysteine synthesis is too low to supply enough reduced sulfur, even with lower growth rates. Thus, in Q3;2, OAS and thiol levels are decreased. We asked whether a disturbed nutrient ion pathway, here sulfate, affects the homeostasis of the target and of other ions, since the metabolic pathways form part of a larger interlinked network. All mutant lines contained approximately wild-type levels of nitrate and phosphate, except for slightly lower phosphate in Q3;1 (Table 1). Sulfate levels, however, were unexpectedly decreased in the quadruple mutants, only slightly in lines Q1;1 and Q2;2, but substantially in the growthretarded lines, Q2;1, 3;1, and 3;2. The strong decrease in sulfate levels in Q3;2 fits with the lower content of cysteine and methionine in this mutant line. An explanation for this lower sulfate content in the shoot, even though the demand for sulfur is high and sulfate is available, might be found by investigating nutrient uptake in the root. In contrast to the shoot, OAS in the root is decreased in four of the mutants, in comparison to the wild-type, but not in Q2;2 (Watanabe et al., 2008a). Thus, it can be assumed that sulfate uptake from the soil is not stimulated, as the lower OAS levels are unlikely to activate high-affinity sulfate uptake from the soil (Neuenschwander et al., 1991; Koprivova et al., 2000; Kopriva et al., 2002; Hesse et al., 2003). Nevertheless, further signals might be necessary to lead to the observed decrease in sulfate uptake in the root, which would then lead to lower levels of sulfate in the shoot. However, sulfate measurements of the root uptake capacity are not available, and the almost wild-type-like level of OAS in the roots of the Q2;2 mutant (Watanabe et al., 2008a) cannot explain the decrease to 70% of sulfate in the shoot, again implying the involvement of additional signals. Future analyses of the mutants, including the sub-cellular analysis of metabolites involved in S metabolism, might help to reveal the regulatory mechanisms responsible for this observation. A further metabolic effect of the block in SERAT activity was perturbation of the content of most amino acids, which mainly increase (Table 1). This response is closely coupled to growth retardation and decreased sulfate content, but not to alterations in OAS or thiol (cysteine and GSH) levels, which are likely to be most immediately affected by blocking SERAT activity. This amino acid perturbation resembles the downstream effects observed after nutrient starvation for S, P, and K and mild N-starvation (Table 1; S1 S4, P1 P2, K1 K3, N1 N3). A full nitrate starvation, though, resulted in massive amino acid decreases (Table 1; N4). Interestingly, in S, P, and K starvation and mild N starvation, the increase in amino acids is also closely related to growth retardation (Table 1). The fact that those quadruple mutants with either wild-type or even decreased levels of OAS and thiols display similarities to nutrientstarvation phenotypes, including sulfate deprivation, would tend to exclude OAS as a signal of this senescence-related downstream response. It can be assumed that limitations in the flux through the pathway, resulting in a decrease in reduced sulfur due to the limited synthesis of OAS, are responsible for the altered growth program and the perturbations in amino acids. This prompted us to suggest that an OAS- and probably thiol-independent induction pathway is mainly responsible for the downstream response (Figure 3). A similar observation has been made when blocking biosynthesis of leucine, valine, and isoleucine through antisense inhibition of the acetolactate synthase gene in potato (Hoefgen et al., 1995), which resulted in growth rate reduction and, unexpectedly, control plant levels of the amino acids whose synthesis is restricted, while all the other amino acids accumulated to higher concentrations. One explanation might be that protein biosynthesis is dependent on the appropriate supply of amino acids. In this scenario, the system senses any imbalance in the amino acid pool and boosts the amino acid biosynthesis in order to obtain sufficient amounts of all necessary components, including the limiting amino acids. Amino acid backbones derived from carbohydrates are mainly supplied through the anaplerotic reactions of the TCA cycle, which is substantially induced in the quadruple mutants and upon sulfate starvation, although to a much lesser extent upon N, P, or K starvation (Table 2). It has been shown that if more precursors are provided, then more amino acids are synthesized, demonstrating the flexibility and capacity of the system (Carrari et al.,

Watanabe et al. d General Regulatory Patterns Revealed by serat Quadruple Mutants 459 Figure 3. Generalized Model of the Responses to Sulfate and Other Nutrient Ion Starvation in Plants. (A) When the plant faces limitations of a nutrient (N, nitrogen; P, phosphor; S, sulfur; K, potassium; X, any other nutrient macro- or micronutrient), it compensates by activation of specific mechanisms that allow it to optimize the availability of the limiting factor. Such mechanisms include the activation of uptake and assimilation, as well as release from internal reservoirs. The nutrient-specific responses are maintained by nutrient-specific signals such as OAS (sulfur). (B) An extended limitation of a mineral nutrient results in a retardation of growth (C) and eventually leads to nutrient depletion-induced senescence (NuDIS) (D). Nutrient depletion response strategies share developmental rescue mechanisms as indicated by overlapping phenotypic, metabolic, and transcriptomic behavior. NuDIS displays a wide overlap with developmental senescence (DEVS) and also affects nutrient-specific mechanisms (A). Depending on the strength and duration of the nutrient limitation, senescence-related processes eventually become dominant. 2003; Roessner-Tunali et al., 2003, 2004; Sienkiewicz-Porzucek et al., 2008). In a similar way, amino acid increases in the dwarfed mutants can be assumed to be a reaction to amino acid imbalances, and as the flux cannot be increased, a cessation of growth allows a new equilibrium to be found. Thus, the amount of cysteine, and hence GSH content, in the Q2;1 and Q3;1 mutants might be kept at normal levels by retarding growth. This essentially agrees with Liebig s Law of the Minimum that a limiting factor actually determines growth rates (Van der Ploeg et al., 1999). For Q3;2 mutant (dwarfed and reduced in OAS and thiols), which retains only the cytosolic isoform of SERAT, it seems likely that the very strong decrease in SERAT activity impairs thiol synthesis to such an extent that even growth retardation is insufficient to compensate for the loss of SERAT activity and allow maintenance of normal metabolite levels. Changes in protein synthesis and degradation, both common features of NuDIS, might also contribute to determine the size and composition of the amino acid pool. However, the protein content in the mutants remains unchanged (Table 1). Therefore, it can be speculated that there might be a direct causality between the limitation of a nutrient, with restriction of the synthesis of one or more amino acids resulting in a decrease in protein synthesis, thus leading to an increase in the free amino acid pool and a retardation of plant growth. At least, the changes in amino acids observed under mild nitrogen starvation and potassium starvation also were accompanied by constant or even increased protein levels and reduced growth (Table 1; N1 N3, K1 K3). It must be mentioned that the influence of potassium on metabolism is generally different from that of the other nutrients, as potassium is not incorporated into organic compounds. However, eventually, potassium affects metabolism through its function as a cofactor in enzymatic reactions and as a counter ion (Armengaud et al., 2009). In summary, it has been observed that limitations of quite different nutrients lead to an altered growth program accompanied by an increase in free amino acids. Independently of whether the altered amino acid pattern provokes the changes in growth, or whether it is a consequence of a switch in the developmental program, it defines a developmental state of a plant. Thus, the analysis of plants with similar alterations in amino acid contents might indeed allow identification of regulatory elements that induce developmental changes in response to metabolic limitations. Evidence to support this proposal is provided by the expression pattern of the F-box protein gene (At1g23390) whose expression could be showntobecloselyrelatedtobiomass(usadeletal., 2008; Sulpice et al., 2009). The F-box gene is an S-responsive gene (Table 4), being down-regulated under S starvation (data not shown). The F-box gene expression is reduced in the quadruple mutants in direct correlation with the sulfate content (Tables 1 and 4), and