Journal of Experimental Botany Advance Access published August 27, 2014 Journal of Experimental Botany doi:10.1093/jxb/eru321

Review Paper

Signal interactions in the regulation of root nitrate uptake Sandrine Ruffel, Alain Gojon and Laurence Lejay* Laboratoire de Biochimie et Physiologie Moléculaire des Plantes, Institut de Biologie Intégrative des Plantes ‘Claude Grignon’, UMR CNRS/INRA/SupAgro/UM2, Place Viala, 34060 Montpellier cedex, France *  To whom correspondence should be addressed. E-mail: [email protected] Received 21 February 2014; Revised 10 June 2014; Accepted 3 July 2014

In most aerobic soils, nitrate (NO3–) is the main nitrogen source for plants and is often limiting for plant growth and development. To adapt to a changing environment, plants have developed complex regulatory mechanisms that involve short and long-range signalling pathways in response to both NO3– availability in the soil and other physiological processes like growth or nitrogen (N) and carbon (C) metabolisms. Over the past decade, transcriptomic approaches largely contributed to the identification of molecular elements involved in these regulatory mechanisms, especially at the level of root NO3– uptake. Most strikingly, the data obtained revealed the high level of interaction between N and both hormone and C signalling pathways, suggesting a strong dependence on growth, development, and C metabolism to adapt root NO3– uptake to both external NO3– availability and the N status of the plant. However, the signalling mechanisms involved in the cross-talk between N, C, and hormones for the regulation of root NO3– uptake remain largely obscure. The aim of this review is to discuss the recent advances concerning the regulatory pathways controlling NO3– uptake in response to N signalling, hormones, and C in the model plant Arabidopsis thaliana. Then, to further characterize the level of interaction between these signalling pathways we built on publicly available transcriptome data to determine how hormones and C treatments modify the gene network connecting root NO3– transporters and their regulators. Key words:  Arabidopsis thaliana, carbon, hormone, interaction, nitrate uptake, root.

Introduction Nitrogen (N) is quantitatively the most important inorganic nutrient for plants as it is a basic element for amino acid and protein synthesis. Under temperate climatic conditions, nitrate (NO3–) is most often the main N source and is taken up from the soil solution by root cells. However, several internal and environmental factors can limit NO3– acquisition by the plant. For example, NO3– concentration in the soil solution can vary by several orders of magnitude both seasonally and from place to place within the soil (Miller and Cramer, 2005; Miller et al., 2007). Furthermore, NO3– uptake by the roots also depends on many other physiological processes in the plant (e.g. NO3– assimilation, acquisition of other nutrients, growth) that may prevent the optimal use of the NO3– resource available to the plant. Therefore, plants must constantly modulate the efficiency of root NO3– uptake, not only to

compensate for the fluctuations of external NO3– availability, but also to adjust the rate of NO3– intake to the ‘N demand’ for growth resulting from the overall genotype×environment interaction. To ensure this task, plants rely on both local and long distance signalling mechanisms that inform the roots of the actual external NO3– concentration, and communicate N nutrient status across different tissues and organs (Forde, 2002; Gojon et al., 2009). Significant progress has been made over the past decade to unravel the molecular components of these signalling mechanisms. Major breakthroughs were made on local NO3– sensing and signalling, and components of the long distance signalling of N status have also been found. In addition, many transcriptomic studies have identified thousands of genes targeted by the N transduction pathways, and shown that a wide range of physiological or developmental

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Abstract

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Regulatory components of N-signalling pathways controlling root NO3– transport Root uptake of NO3– is subject to complex regulation by at least two different N-signalling pathways. NO3– itself locally induces the expression of several genes encoding its own transport systems, as well as the main enzymes involved in its assimilation (Crawford and Glass, 1998; Wang et al., 2004; Gojon et  al., 2009). This is a fast response (a few minutes to a few hours) following first NO3– supply (or re-supply after a prolonged N-deprivation period). However, on the

NO3- / N availability CIPK8 CIPK23

N-regulatory components

1

HNI9

4

? 2

Hormones/N

3

Carbon/N

NRT1.1 LBD37 LBD38 LBD39 NLP7 NLP6

Biosynthesis/Signaling Auxin Cytokinin Ethylene

OPPP Glucose*

NRT2 genes expression NO3- transport Fig. 1.  Schematic representation of NO3– transport regulation by N-regulatory components (#1), hormones (#2), and carbon (#3). All of them have been shown to regulate NRT2 gene expression except * which indicates post-transcriptional regulation. In the last part (#4), influence of hormonal and carbon signals on the regulation of NO3– transporter genes by N-regulatory components is questioned.

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longer term (several hours to several days), NO3– was also reported to have the opposite action in locally repressing some of these genes (Muños et al., 2004; Krouk et al., 2006). Conversely, the root NO3– uptake system is under systemic feedback repression by whole-plant signals associated with high N status of the whole organism (Crawford and Glass, 1998; Gansel et al., 2001; Forde, 2002). The identity of these signals remains unclear. It has been suggested that downstream N metabolites such as amino acids translocated from the shoot to the roots via the phloem may be the signalling molecules mediating the down-regulation of root N uptake (Cooper and Clarkson, 1989; Müller and Touraine, 1992). However, evidence for a systemic signalling by NO3– itself has also been reported (Forde, 2002; Ruffel et al., 2011). In the past few years the vast majority of the research concerning the regulation of root NO3– uptake by N focused on the local regulation by NO3– itself, and on the expression of the transporter gene NRT2.1, which encodes a main component of the high-affinity NO3– transport system (Fig.  1). Surprisingly, the first regulatory gene identified was NRT1.1/ NPF6.3 (Muños et al., 2004), which codes for a dual affinity NO3– transporter (Tsay et al., 1993; Liu et al., 1999). NRT1.1 was shown to act as a NO3– transceptor (transporter/sensor) (Gojon et  al., 2011), triggering one or several NO3– signalling pathways controlling the expression of the high-affinity NO3– transporter gene NRT2.1, and the development of lateral roots (Krouk et  al., 2006; Remans et  al., 2006a; Ho et  al., 2009; Wang et  al., 2009). This led to original discoveries showing that (i) NRT1.1 is required for both the local induction (short term) and repression (long term) of NRT2.1 expression by NO3– (Muños et al., 2004; Krouk et al. 2006; Ho et al., 2009; Wang et al., 2009) and (ii) low NO3– concentration triggers phosphorylation of NRT1.1 at the T101 residue by a CBL-interacting protein kinase CIPK23 (Ho et al. 2009). This phosphorylation has profound consequences on both the structure and the function of the protein (Parker and Newstead, 2014; Sun et al., 2014), and in particular switches NRT1.1 to the high-affinity function leading to a weak induction of NRT2.1 gene expression. Conversely, in experiments with high NO3– concentration, T101 is not phosphorylated,

processes are under the control of endogenous or exogenous N signals (Wang et al., 2003; Scheible et al., 2004; Wang et al., 2004; Peng et al., 2007a; Gutierrez et al., 2008; Krouk et al., 2010; Ruffel et al., 2011). These data have also revealed the high level of integration of the N signalling mechanisms with other regulatory pathways. Indeed, one striking conclusion arising from transcriptome profiling in response to N treatments is that only a minor proportion of the differentially expressed genes is specifically regulated by N signals. In particular, combinatorial studies have demonstrated that most N-responsive genes are also under the control of hormone and carbon (C) signalling pathways (Gutierrez et  al., 2007; Krouk et al., 2009; Nero et al., 2009). This observation suggests that the way plants are reacting to changes in external N availability or in endogenous N status is strongly dependent on both development and C acquisition. However, the signalling mechanisms involved in the cross-talk between N, C, and hormones remain largely obscure. In this review, we focus on N signalling mechanisms that regulate root NO3– transporters and on their interaction with hormones and signals related to the C status of the plant (Fig. 1). We discuss recent advances on the molecular mechanisms identified in the model plant Arabidopsis thaliana, and analyse publicly available transcriptome data to further understand how the transcriptional correlations found between high-affinity NO3– transporter genes and N signalling genes are altered by auxin, cytokinin, light, and sucrose (Fig. 1).

Signal interactions in the regulation of root nitrate uptake  |  Page 3 of 9

Hormone/nitrogen control of nitrogen acquisition The obvious interconnection between growth and nutrition led to questions over the influence of N availability on

hormonal status, and conversely the role of hormone biosynthesis and signalling on the control of N sensing and acquisition. A review of these interconnections based on up-to-date studies suggested that growth and nutrition are probably linked by a feed-forward cycle that controls their respective balance from physiological to molecular levels (Krouk et al., 2011). In this section, we will focus on one part of this cycle, which corresponds to the hormonal control of nitrogen acquisition in response to N variability (Fig. 1). So far, the role of each phytohormone and their combination on root NO3– transport activity is not known as it is for root development (Wilson et al., 2013). Indeed, to establish the consequence of hormonal modulation on root NO3– uptake (i.e. physiological level of the connection), specific experiments measuring high and low NO3– affinity transport using a stable isotope (15N) in combination with various N supplies and exogenous hormone supply, or mutation of signalling pathways are still needed. The first example that could directly connect hormone regulation to NO3– transport activity still relies on the characterization of the transceptor NRT1.1. Indeed, NRT1.1 not only transports NO3–, but also facilitates uptake of the phytohormone auxin at low NO3– availability (Krouk et  al., 2010). This mechanism has been proposed to explain the repression of lateral root growth by NRT1.1, because the auxin transport activity of NRT1.1 is expected to promote basipetal auxin transport out of these roots. The impact of auxin on the NO3– transport activity of NRT1.1 has been tested in Xenopus oocytes and was found to be weak, whereas NO3– strongly inhibits auxin influx in oocytes (Krouk et al., 2010). Interaction between NO3– and hormones at the transporter level may be an integrative mechanism between nutrition and development more largely used by plants. Indeed, recently, the low affinity NO3– transporter NPF4.6/NRT1.2/AIT1, another member of the NPF family (Leran et  al., 2014), has been identified as an ABA transporter in a heterologous cellular system (Kanno et al., 2012). NO3– does not seem to inhibit ABA transport in a yeast system (Kanno et al., 2013), but the impact of ABA on NO3– transport by NPF4.6 has still to be determined. Compared with the physiological and functional levels, a relatively larger amount of data is available about the molecular relationship between hormones and NO3– transport. Indeed, as a well-accepted proxy for the regulation of NO3– uptake is the regulation of mRNA accumulation for genes encoding for NO3– transporters, several studies report the impact of hormone and/or hormonal signalling on the regulation of gene expression in combination or not with N treatment. The first justification for assessing the relation between hormones and NO3– transporter genes was the accumulation of their mRNA in specific tissues within the plant. The localization of NRT1.1 mRNA preferentially in nascent organs drove the hypothesis for a regulation by a growth signal (Guo et  al., 2001). Then, more than 10  years ago, the authors of this study demonstrated a regulation of this gene by auxin in the presence of NO3– (Guo et  al., 2002). Secondly, connecting hormonal and NO3– transport regulation at the transcriptional level relies on the statement that a large part of

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NRT1.1 switches to the low-affinity function and NRT2.1 gene expression is strongly induced. Recently, two additional components of NO3– signalling pathways targeting NRT2.1 expression have been identified: another CBL-interacting protein kinase, CIPK8 (Hu et al., 2009), and a putative transcription factor called NIN-Like Protein7 (NLP7) (Castaings et al., 2009; Marchive et al., 2013), which are both involved in the induction of NRT2.1 expression by NO3–. The discovery of NLP7 is very exciting as it is not only involved in the regulation of NRT2.1 but it directly regulates many steps of the primary N assimilation and NO3– signalling pathways. Indeed chip–chip experiments performed by Marchive et al. 2013 revealed that NLP7 binds hundreds of genes including all of those described in this part and characterized as being involved in N signalling. This regulation is associated with a NO3–-dependent nuclear retention of NLP7. However, the role of the NLP gene family in the transcriptional reprogramming of genes involved in NO3– metabolism is not restricted to NLP7, as at least six other members are DNA-binding proteins that recognize NO3–-responsive cis-element present in NO3–-responsive genes like the Nitrite reductase gene. For instance, NLP6 has also a function in regulating the expression of NO3– transporter genes (Konishi and Yanagisawa, 2013). All these results highlight a central role for NLPs in the plant primary NO3– response. Concerning the long distance N signalling pathway responsible for the down-regulation of NRT2.1 by high N status of the plant, expression of the transcription factors LBD37/38/39 seem to mimic the effect of organic N compounds (Rubin et al., 2009). Furthermore, a forward genetic screen enabled the isolation of the Arabidopsis high nitrogen-insensitive 9-1 (hni9-1) mutant, impaired in the systemic feedback repression of the root nitrate transporter NRT2.1 by high N supply (Girin et al., 2010). HNI9 encodes Arabidopsis INTERACT WITH SPT6 (AtIWS1), an evolutionary conserved component of the RNA polymerase II complex. HNI9–AtIWS1 acts in roots to repress NRT2.1 transcription in response to high N supply and is associated with an HNI9–AtIWS1dependent increase in histone H3 lysine 27 trimethylation at the NRT2.1 locus (Widiez et al., 2011; Fig. 1). Few other elements like the transcription factors ANR1 (Zhang and Forde, 1998; Gan et  al., 2005), SPL9 (Krouk et al. 2010), the RING-type ubiquitin ligase NLA (Peng et al., 2007b), or the master clock control gene CCA1 (Gutierrez et al. 2008) have been shown to respond to NO3– or N metabolites. However, despite the fact that ANR1 is involved in the regulation of root architecture in response to N and that CCA1 is part of a sub-network regulated by organic N with target genes involved in N-assimilation, their putative role in the regulation of root NO3– uptake has not been described for now.

Page 4 of 9 | Ruffel et al. regulation allowing extensive communication between shoots and roots. Indeed, simultaneous plant de-topping and auxin supply decrease the inhibition level, suggesting that the auxin-dependent NRT2.1 regulation is mediated by a shootdependent signalling pathway (Gan et  al., 2005). Similarly, the cytokinin-NO3– systemic-driven NRT2.1/NAR2.1 regulation is lost in de-topped plants (Ruffel et al., 2011). Finally, to what extent hormones affect the action of the known N regulatory components of NO3– transport is completely unknown. First, it is tempting to speculate that modification of auxin flux by NRT1.1 could play a role in NRT2.1 regulation. For example, in roots exposed to a NO3–-free medium (less lateral root and no NRT2.1 induction), all the auxin that is not accumulated in root primordia, to prevent root development, could lead to a repression of NRT2.1 in the older part of the primary root. HNI9–IWS1, the regulatory component involved in the NRT2.1 repression in high N status condition, could be a second example of such a connecting hub between hormone- and N-signalling. Indeed, it has been shown that IWS1 also interacts with the transcription factor BES1 and participates in brassinosteroid-regulated gene expression (Li et al., 2010). However, the role of brassinosteroid in interaction with IWS1 for NO3– transport regulation remains to be studied. Thus, because our knowledge about the interaction between hormones and regulatory components of N-signalling is still limited, in the last part of this review, we propose to try to connect them by looking at a correlation network that we generated from available data.

Carbon/nitrogen control of nitrogen acquisition As C skeletons are essential for the incorporation of inorganic N into important molecules such as amino acids, proteins, and nucleic acids, NO3– uptake is a highly integrated process that is not only determined by NO3– availability and the N demand of the whole plant (Imsande and Touraine, 1994; Forde, 2002; Alvarez et  al., 2012), but also by the C metabolites produced by photosynthesis (Delhon et  al., 1996). Therefore, plants have evolved complex regulatory networks to maintain a viable C:N ratio under a large range of environmental conditions. The regulation of root NO3– uptake by photosynthesis has been well described at the physiological level. It is characterized by a diurnal rhythm of NO3– uptake, with a peak during the light period and a minimum in the dark. It has been attributed to a stimulatory effect of sugars produced by photosynthesis and transported down to the roots (Delhon et al., 1996; Lejay et al., 1999). At the molecular level, several NO3– transporter genes were reported to be responsive in the roots to changes in photosynthesis in the shoots, and, interestingly, these genes are in general also those that are responsive to N, making it difficult to clearly separate N and C effects. For instance, the regulation of root NO3– uptake has been correlated with changes in the expression of both NRT2.1 and NRT1.1 in response to both N and C treatments (Filleur and Daniel-Vedele, 1999;

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hormonal signalling involves transcriptional reprogramming of complex gene networks (for reviews on cytokinin and auxin transcriptional network see for example Chapman and Estelle, 2009; Hwang et al., 2012). The transcriptional regulation of NRT2 genes by hormones has been shown by exogenous supply of these growth regulators. Indeed, within 2 h, NRT2.1 mRNA accumulation is strongly inhibited by root supply of 100 µM NAA (naphthaleneacetic acid) (Gan et al., 2005). However, how the auxin signalling pathway regulates NRT2.1 gene expression is still largely unknown. So far, we only know that some mutants affected in the auxin signalling pathway (independently of N and auxin treatments) are affected in NRT2 expression. Indeed, the gain-of-function axr3-1/iaa17-1 mutant (i.e. auxin-insensitive and constitutive transcriptional repressor of auxin-mediated gene expression) as well as the double mutant arf7/arf19 displays NRT2.1 overexpression (Okushima et al., 2005; Overvoorde et  al., 2005). Interestingly, ARF7 and ARF19 directly regulate genes belonging to the LBD transcription factors family to control lateral root development (i.e. LBD16 and 29) (Okushima et  al., 2007). It would be tempting to speculate that there is a connection between the auxin signalling pathway, LBD37/38/39, and NRT2.1 regulation, but testing their connection in different N treatments has still to be done. Similarly, exogenous supply of cytokinin (combined or not to the use of transgenic plants affected in the cytokinin signalling pathway) down-regulates the expression of NRT2 genes, such as NRT2.1, NRT2.3, and NRT2.6 (Brenner et al., 2005; Kiba et al., 2005; Sakakibara et al., 2006). Once again, the regulatory elements of the cytokinin signalling pathway affecting the regulation of NO3– transporter genes are still unknown. However, we have a better understanding of cytokinin-driven NRT2 regulation by N availability than for others hormones, as it has been demonstrated that NRT2.1 and NAR2.1 regulation by NO3–-related systemic signalling depends on cytokinin biosynthesis controlled by IPT3 and/ or IPT5 and/or IPT7 genes (Ruffel et al., 2011). In addition to auxin and cytokinin, abscisic acid and ethylene are also known to influence NO3– transporter gene expression (Tian et  al., 2009; Kiba et  al., 2011; Zheng et  al., 2013), showing that a large range of the hormonal network as part of the regulatory network adapting NO3– acquisition to the developmental programme still needs to be discovered. In these studies, NRT2.1 was often used as a marker gene, as it encodes for the major high-affinity NO3– transport system (Cerezo et al., 2001). So, in this hormonal context, it is noteworthy that NRT2.1 is likely to also have a role of NO3– sensor, controlling lateral root development independently of its NO3– transport activity (Little et al., 2005; Remans et al., 2006b). Then, at a physiological level, the role of hormonal signalling in NRT2-dependent root development and/or NO3– transport has also to be explored. Actually, the determination of the spatial territories where the molecular interaction between hormone signalling and NO3– transporter gene regulation is occurring could help to decipher the role of hormones in the regulation of NRT2.1 dual function. For now, we only know that auxin and cytokinin involves systemic

Signal interactions in the regulation of root nitrate uptake  |  Page 5 of 9 the OPPP (Marchive et  al., 2013). And finally, microarray experiments showed that genes involved in the OPPP are misregulated by NO3– in two nrt1.1 mutants (Wang et al., 2009). Thus, the understanding of the signalling mechanism linked to the OPPP could be key to find out how the known C and N signalling pathways are integrated to regulate root NO3– uptake. However, recent data indicate that it will certainly be necessary in the future to take into account the regulation of NRT2.1 at the protein level to fully understand the regulatory mechanism of root NO3– uptake in response to C and N interactions. Indeed, transgenic plants expressing NRT2.1 constitutively showed that regulation by C and N acts also at the post-translational level (Laugier et  al., 2012). Furthermore, using gin2-1 plants, de Jong et al. (2014) showed that glucose stimulates NRT2.1 protein levels and transport activity independently of the stimulation of NRT2.1 expression through OPPP, demonstrating another possible post-transcriptional mechanism influencing NO3– uptake in response to C. A very intriguing aspect of the N/C interaction governing root N uptake is that if it is firmly established that photosynthesis promotes root N uptake in the short term (thus explaining the diurnal rhythms of N acquisition), but evidence is accumulating that a long-term stimulation of photosynthesis results in the opposite effect. Indeed, it has been highlighted by many studies indicating that prolonged exposure of plants to high CO2 concentrations in the atmosphere (e.g. 500–800 ppm) is associated with a decrease in the total N concentration in the shoots, suggesting a lowered N status of the whole plant (Stitt and Krapp, 1999; Ellsworth et al., 2004; Taub and Wang, 2008; Leakey et al., 2009). A classical explanation of these observations is that rising CO2 concentration leads in many C3 species to a stimulation of photosynthesis (the socalled ‘CO2 fertilization’ effect) that is counterbalanced in the long term by a feedback repression reducing steady-state Rubisco levels. This response, referred to as ‘acclimation’ of photosynthesis, significantly lowers the growth stimulation theoretically expected from ‘CO2 fertilization’ (Long and Ort, 2010), and accounts for reduced total N accumulation in shoots, simply because Rubisco is by far the main protein present in these organs. However, several lines of evidence rather suggest that, unlike what is seen on the short term (i.e., hours or days, see above), the long-term stimulation of photosynthesis by rising CO2 concentration impairs root uptake of NO3– in C3 species such as Arabidopsis or wheat (Bloom et al., 2002; Bloom et al., 2010; Bloom et al., 2014). The reasons for that are largely unclear (Taub and Wang, 2008), which suggests that a key aspect of the interaction between C and N acquisition by plants is still not understood.

Hormonal and carbon regulation of the N-signalling components controlling NO3– transport Our dive into the genomic era, and in particular the easy access to whole-genome transcriptomic data, has largely led to the identification of new N-regulatory components of NO3– transporters. For instance, NRT1.1, CIPK8, CIPK23,

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Lejay et al., 1999; Zhuo et al., 1999; Lejay et al., 2003). More recently, NRT2.4, another high affinity NO3– transporter expressed in the roots, has been found to be also induced, similarly to NRT2.1, by both N starvation and C (Kiba et al., 2012). Among these three nitrate transporters, NRT2.1 has been by far the most well studied concerning its regulation by N and C.  All levels of NRT2.1 expression (promoter activity, transcript level, transport activity) have been shown to be repressed by downstream N metabolites, and induced by NO3– and C.  Furthermore, transgenic plants expressing the GUS reporter gene under the control of upstream sequences of NRT2.1 led to the identification of a 150 bp sequence located upstream of the TATA box that is able to confer these three regulations to a minimal promoter (Girin et al., 2007). It suggests the existence of interactions between N and C signalling within this short region. However, despite intensive studies, the molecular mechanisms involved in N and C signalling pathways are mostly unknown, especially regarding the molecular elements generating cross-talk between C and N signalling. In Arabidopsis, the signalling pathways involving TOR and SnRK1 kinases have been recently described as central components of nutrient and C sensing (for review see Robaglia et al., 2012; Dobrenel et al., 2013). Like in animals and yeast, TOR kinase in plants seems to be activated in favourable nutritional and energy conditions, whereas the SnRK1 kinase is stimulated upon nutrient and energy starvation (Deprost et al., 2007; Halford and Hey, 2009). It is thus proposed that these kinases function in an antagonistic way in the global regulation of many growth-related and metabolicrelated processes, including N assimilation and the synthesis of C metabolites, such as starch or raffinose. However, to date there is no evidence concerning a role for these kinases in the regulation of root NO3– uptake by C and N. Furthermore, the regulation by C of both NRT2.1 and NRT1.1 is not affected in SnRK1 mutants (unpublished data L. Lejay). The only information concerning the signalling mechanism involved in the induction of NRT2.1 and NRT1.1 expression by C is the link with the oxidative pentose phosphate pathway (OPPP) (Lejay et al., 2008; de Jong et al., 2014; Fig. 1). However, to date no molecular element involved in this signalling pathway has been identified. It is interesting to note that the regulation by a signal coming from OPPP activity does not only concern NO3– transporter but also NO3– assimilation and the regulation of NO3– assimilatory genes in response to sucrose in the roots (Bussell et al., 2013; de Jong et al., 2014). As OPPP in roots provides the reducing power for nitrite reductase and GOGAT, two enzymes involved in N assimilation, this could be one of the components of a cross-talk between C and N signalling (Oji et al., 1985; Bowsher et al., 1989; Bowsher et  al., 1992). This hypothesis is supported by the fact that NO3– and nearly all the molecular elements involved in the NO3– and reduced N signalling pathways regulate also the expression of some genes in the OPPP (Wang et  al., 2003, 2004). The transcription factors LBD37/38/39 repress the expression of the plastidic glucose-6-phosphate dehydrogenase G6PD2, the first step of the OPPP (Rubin et al. 2009). NLP7 is involved in the regulation of the gene coding for the 6-phosphogluconate dehydrogenase, the third step of

Page 6 of 9 | Ruffel et al. of the different signalling pathways. Similarly, NRT2.1 and NAR2.1 display a strong correlation, but only in hormonerelated datasets. At a first glance, this could suggest that NAR2.1 is less essential for NRT2-dependent NO3– transport stimulation by C provision. Measuring whether the stimulation of NO3– influx by C provision is modified in nar2.1 mutant could validate this hypothesis. But, overall, except NRT1.1, none of the N-regulatory components are found co-regulated with NRT2 gene expression in the carbon dataset. Thus, we don’t rule out that post-transcriptional regulation of the gene network is also required to adapt NO3– transport activity to the physiological status of the plant. Interestingly, the different networks also display specificity. For instance, the auxin-related network displays specificity with the presence of the three LBD genes only within this network. This observation suggests a control of the expression of these genes by auxin rather than cytokinin, which is consistent with the previously known control of other LBD members by auxin signalling (Okushima et  al., 2007; Goh et al., 2012). Thus, NO3– transport regulation by auxin through the LBD genes illustrates the type of hypothesis that could be derived from simple network analysis. Similarly, the regulatory component HNI9 is only found in the cytokininrelated network. For sure, these connections and hypothesis derived from this analysis require in-silico reinforcement and then experimental validation. However, these networks at least show the existence of a dynamic and specific co-regulation of NO3– transporter genes and their regulatory components in response to auxin, cytokinin, and carbon, suggesting an interconnection and maybe an integration of these different signalling pathways at the level of the transcriptional control of known regulatory components.

Table 1.  NO3– transporter genes involved in NO3– transport, and their N-regulatory components High affinity NO3– transporter system

AGI

ATH1 Probe

NRT2.1 NRT2.2 NRT2.3 NRT2.4 NRT2.5 NRT2.6 NRT2.7 NAR2.1/NRT3.1 NRT1.1

at1g08090 at1g08100 at5g60780 at5g60770 at1g12940 at3g45060 at5g14570 at5g50200 at1g12110

260623_at 260624_at 247592_at 247591_at 261198_at 252604_at 250151_at 248551_at 264348_at

N-regulatory Components

AGI

ATH1 Probe

References

NRT1.1 NLP7

at1g12110 at4g24020

264348_at 254195_at

CIPK8 CIPK23 LBD37 LBD38 LBD39 HNI9 NLP6

at4g24400 at1g30270 at5g67420 at3g49940 at4g37540 at1g32130 at1g64530

254167_at 245775_at 246996_at 252220_at 253043_at 245787_at 261945_at

Muños et al. (2004) Castaings et al. (2009); Marchive et al. (2013) Hu et al. (2009) Ho et al. (2009) Rubin et al. (2009)

Widiez et al. (2011) Konishi and Yanagisawa (2013)

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and LBDs factors have been identified from simple analysis of transcriptomic data obtained from mutant analysis and/ or differential N provision and by validation through candidate gene approach (Muños et  al., 2004; Scheible et  al., 2004; Ho et al., 2009; Hu et al., 2009; Rubin et al., 2009). In this last section, we propose a way to further mine transcriptomic data to unravel possible interaction between different signals regulating NO3– transporters. Indeed, our understanding of the influence of hormones and C on the known N-regulatory components of NO3– transport is still limited (Fig.  1). Thus, we propose to try to connect them together by briefly analysing gene expression correlation between high-affinity NO3– transporter genes (e.g. genes of the NRT2 family) and their N-regulatory components (Table 1), in transcriptome data sets originating from auxin, cytokinin, and carbon treatments (Figure 2, see legend for details about the analysis). A general observation is that few NRT2 transporter genes appear within these networks. De facto, NRT2.1 is present as the choice of datasets has been driven by the misregulation of this particular gene. NRT2.6 is the only other NRT2 gene appearing and only in the cytokinin related network. The link between NRT2.1 and NRT2.6 is probably not fortuitous as they share the singularity to both be involved in the response to biotic stress (Dechorgnat et  al., 2012; Kechid et  al., 2013). It is the specific link between biotic stress, these two genes, and cytokinin that remains to be determined. Interestingly, in the three networks, we always observe a strong correlation between NRT2.1 and NRT1.1, suggesting that if NRT1.1 is part of the N-regulatory components of NRT2.1 regulation (Muños et al., 2004; Ho et al., 2009), it is probably a regulatory component that integrates many different signals and that could act extremely downstream

Signal interactions in the regulation of root nitrate uptake  |  Page 7 of 9 A. Auxin-related data set

LBD38

LBD39 LBD37

NLP7

B. Cytokinin-related data set

CIPK23

C. Carbon-related data set

HNI9

CIPK23

NRT1.1 NRT1.1

NRT1.1

NAR2.1 NRT2.1

NAR2.1

NRT2.1

NRT2.6

NRT2.1

Acknowledgements The work in our laboratory was supported by a grant from the ANR in France and Conicyt in Chile (ModelN ANR-09-BLAN-0395), and by a grant from the Agropolis Foundation (RHIZOPOLIS).

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Fig. 2.  Correlation network of NO3– transporter genes (grey circles) and their N-regulatory components (white diamond and rectangles) (Table 1) in hormone and carbon responsive transcriptomes. (A) Correlation network obtained from three microarray datasets relying on auxin treatments and/or use of mutants impaired for auxin signalling. Dataset 1: wild-type, single mutant arf7, single mutant arf19, and double mutant arf7arf19 seedlings are treated with 5 µM IAA or EtOH (control) for 2 h (GSE627; 24 microarrays; Okushima et al., 2005). Dataset 2: wild-type, single loss of function mutant iaa17-6 and single gain of function mutant axr3-1 were treated with 5 µM IAA or EtOH (control) for 2 h (GSE629; 18 microarrays; Overvoorde et al., 2005). Dataset 3: whole root treated with 5 µM IAA or EtOH (control) for 2–3 h, digested or not for protoplasting. Protoplasts are sorted by flow cytometry and fluorescentactivated cell sorting using the cell-specific lines marking epidermis, pericycle, stele, and columella (GSE35580; 30 microarrays; Bargmann et al., 2013). (B) Correlation network obtained from two microarray datasets relying on cytokinin treatments and/or use of mutants or transgenic plants modified for cytokinin signalling. Dataset 1: wild-type and double mutant arr10arr12 seedlings were treated with 20 µM t-zeatin or DMSO (control) for 1 h (GSE20232; 12 microarrays; Yokoyama et al., 2007). Dataset 2: wild-type and ARR22 overexpressor transgenic lines were treated with 20 µM t-zeatin or DMSO (control) for 3 h (GSE5698; 12 microarrays; Goda et al. 2008). (C) Correlation network obtained from two microarray datasets relying on carbon/light treatments. Dataset 1: wild-type roots are N-deprived but supplied with sucrose from 0–90 mM for 8 h (E-MEXP-828; 10 microarrays; Gutiérrez et al., 2007). Dataset 2: wild-type seedlings grown in dark with or without 1% sucrose are transferred or not for 3 h in light (E-MEXP-1112; 8 microarrays; Thum et al., 2008). For each dataset, raw data (i.e. .CEL files) are normalized using MAS5. Only genes displaying an affymetrix signal value >75 at least in one sample are used. For each probe, the affymetrix signal value of each microarray is normalized by the mean of signal values from all microarrays constituting one dataset. Pearson coefficient correlation values between gene expression are calculated from the auxin matrix (three datasets) cytokinin matrix (two datasets) and carbon matrix (two datasets), separately. Only gene expression correlation values greater than 0.7 or less than –0.7 are kept for network building using Cytoscape (Smoot et al., 2011). The thicker the edge between two genes, the more the correlation value is closed to 1 or –1. Plain and dash lines indicate positive and negative correlation, respectively. (GSE numbers are GEO accessions available at http://www.ncbi.nlm.nih.gov/geo/ and E-MEXP numbers are available at http://www.ebi.ac.uk/ arrayexpress/).

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