A Reevaluation of the Role of Arabidopsis NRT1.1 in High-Affinity Nitrate Transport
Notice bibliographique
Résumé
In papers by Wang et al. (1998), Liu et al. (1999), and Liu and Tsay (2003), it was proposed that Arabidopsis thaliana Nitrate Transporter1.1 (AtNRT1.1; CHL1) encodes a dual-affinity nitrate transporter that “plays a major role in high-affinity nitrate uptake.” Here, we evaluate this concept by reexamining the uptake kinetics of Arabidopsis (Arabidopsis thaliana) mutant lines defective in NRT1.1 or other nitrate transporters. The uptake of inorganic ions by plant roots conforms to a pattern of biphasic kinetics. At low external ion concentration, ions are absorbed by saturable high-affinity transport systems (HATS), while at high concentrations, nonsaturating low-affinity transport systems (LATS) operate. Such is the case for K+, NH4+, NO3−, and ClO3− (a NO3− analog; Kochian and Lucas, 1982; Ullrich et al., 1984; Pace and McClure, 1986; Guy et al., 1988; Siddiqi et al., 1990; Aslam et al., 1992). The LATS for 36ClO3− uptake was linear at [ClO3−] down to 200 μm in tobacco (Nicotiana tabacum; Guy et al., 1988) and for nitrate uptake by barley (Hordeum vulgare) down to 100 μm NO3− (Aslam et al., 1992). These concentrations were the lowest examined by the latter authors. In the studies by Pace and McClure (1986), Guy et al. (1988), Siddiqi et al. (1990), and Aslam et al. (1992), LATS fluxes were extremely small at low external [NO3−] and linear at both low and high [NO3−]. In barley, both constitutive HATS (CHATS) and inducible HATS (IHATS) were demonstrated at low [NO3−], while a constitutive LATS (CLATS) failed to saturate even at 50 mm NO3− (Siddiqi et al., 1990). Likewise, CHATS and IHATS for nitrate have been demonstrated in Arabidopsis, as well as CLATS and inducible LATS (ILATS; Tsay et al., 1993; Huang et al., 1999). Doddema and Telkamp (1979) isolated an Arabidopsis B1 mutant that was defective in the LATS for nitrate (but not the HATS) by screening for survival on ClO3−. Tsay et al. (1993) isolated the nitrate-inducible AtNRT1.1 gene that encodes the ILATS. Interestingly, Touraine and Glass (1997) were unable to detect reduced LATS or HATS influxes in AtNRT1.1 mutants grown on KNO3, while Muños et al. (2004) reported increased HATS influx in AtNRT1.1 mutants. Likewise, Remans et al. (2006) failed to detect reduced uptake rates at low (0.5 mm) or high (10 mm) nitrate in AtNRT1.1 mutants. Among eukaryotes, genes encoding IHATS for nitrate were first isolated from Aspergillus nidulans (Unkles et al., 1991) and subsequently from Chlamydomonas reinhardtii (Quesada et al., 1994) and several higher plants (Glass, 2009), and based on the correlations between AtNRT2.1 expression and IHATS influx, it became accepted that IHATS was encoded by AtNRT2.1. This conclusion was supported by the demonstration that transfer DNA mutants disrupted in both AtNRT2.1 and AtNRT2.2 exhibited 67% reduction of HATS but no reduction in LATS function (Filleur et al., 2001). A gene encoding CHATS has not yet been identified, although a mutant with defective CHATS has been isolated (Wang and Crawford, 1996). In summary, it was held that in Arabidopsis, AtNRT2.1 was responsible for IHATS, while AtNRT1.1 and AtNRT1.2 encoded ILATS and CLATS, respectively (Forde, 2000; Li et al., 2007). In papers by Wang et al. (1998), Liu et al. (1999), and Liu and Tsay (2003), it was demonstrated that AtNRT1.1 mutants of Arabidopsis exhibited reduced nitrate uptake even at 10 μm nitrate. The authors concluded that AtNRT1.1 fluxes exhibited saturation kinetics in planta and in Xenopus laevis oocytes and proposed that NRT1.1 encodes a dual-affinity nitrate transporter that “plays a major role in high-affinity nitrate uptake” (Wang et al., 1998). Liu and Tsay (2003) demonstrated that the AtNRT1.1 protein was capable of switching between high- and low-affinity states by phosphorylation of Thr residue 101; under low-nitrogen (N) conditions, phosphorylation mediated via the activation of protein kinase CIPK23 generated a high-affinity transporter (Ho et al., 2009), whereas high-N favored the dephosphorylated low-affinity configuration. In the paper by Wang et al. (1998), AtNRT1.1 mutants had been grown on up to 24 mm NH4+. By subtracting mutant uptake rates from those of the wild type, a difference flux, attributed to NRT1.1, was generated and used to compute a Km of 38 μm using a hyperbolic model. Unfortunately, the wild-type data presented by Wang et al. (1998; Fig. 2B) are not hyperbolic. A linear fit of these data generated r2 = 0.85, while a Hofstee analysis for hyperbolae (V against V/S, where V represents uptake velocity, and S represents nitrate concentration) gave r2 = 0.26. Likewise, the difference fluxes give a linear fit with r2 = 0.76, compared with a hyperbolic fit where r2 = 0.11. Using the more comprehensive data sets of Wang et al. (1998; Fig. 5, A and B), linear regressions for difference fluxes gave r2 = 0.97 and 0.9, respectively, compared with 0.72 and 0.21 for a hyperbolic model. Clearly, a linear model is superior to a hyperbolic fit at low nitrate concentration. The absence of hyperbolic fluxes results from prior growth on N levels that suppress AtNRT2.1 expression (Zhuo et al., 1999) and reduce measured fluxes to abnormally low values. As an example, in wild-type plants grown on 25 mm NH4+, Ho et al. (2009) reported a 15NO3− influx of approximately 0.2 μmol g−1 dry weight h−1. By contrast, Orsel et al. (2006) reported a value of 120 μmol g−1 dry weight h−1 for plants grown on 0.2 mm nitrate. The papers by Liu et al. (1999) and Liu and Tsay (2003) confirmed the observations of Wang et al. (1998) and provided convincing evidence that, when expressed in X. laevis oocytes, NO3− uptake by AtNRT1.1 was biphasic, exhibiting saturation below 1 mm NO3− and between 5 and 30 mm NO3−. This saturation of low-affinity fluxes is contrary to the observed patterns of linear in planta low-affinity fluxes. Fluxes due to AtNRT1.1 were also determined in Arabidopsis (Liu and Tsay, 2003), but with an insufficient range of concentrations to distinguish between linear and hyperbolic models. The lack of agreement between the X. laevis and in planta data may be due to the long-term (1.5–3 h) incubations employed to measure 15NO3− fluxes in the former. Short-term flux measurements in our plant studies using 13NO3− are typically of 5 to 10 min duration to characterize influx uncompromised by confounding effects such as efflux or saturation of the sink. Also, X. laevis oocytes and plant cells differ significantly in membrane chemistry and surface-volume ratios. Therefore, fluxes derived from such heterologous systems should be interpreted with caution. IHATS influx in Arabidopsis thaliana Nitrate Assimilation Related2.1 (AtNAR2.1) knockout mutants is reduced by more than 96%, and mutants fail to survive on low-nitrate medium, due to loss of the AtNRT2.1 polypeptide from plasma membranes (Okamoto et al., 2006; Orsel et al., 2006; Wirth et al., 2007; Yong et al., 2010). Yet, AtNRT1.1 expression, growth on 2.5 mm nitrate, and 13NO3− or 15NO3− influx due to LATS were normal. The plants used for this influx study were N deprived; hence, AtNRT1.1 should have been in its high-affinity mode. Yet, the contribution to low-concentration influx by AtNRT1.1 was only 4% (or less) of the wild-type flux. Figure 1 shows 13NO3− influx data determined for Atnar2.1 mutant plants, as described by Okamoto et al. (2006). The measured flux is extremely low, and linear regression gave an r2 value of 0.92, compared with 0.48 for a hyperbolic regression. Poor growth on low nitrate and reduced HATS influx were also observed in Atnrt2.1-nrt2.2 mutants, despite normal AtNRT1.1 expression and LATS influx (Filleur et al., 2001; Orsel et al., 2004; Li et al., 2007). Clearly, in the absence of AtNRT2.1 or AtNAR2.1, NRT1.1 is incapable of absorbing sufficient NO3− to sustain growth on low nitrate. Nitrate influx into roots of AtNAR2.1 mutants. Plants were grown hydroponically for 4 weeks on 1 mm NH4NO3, then deprived of N for 1 week before 6 h of induction with 1 mm KNO3. Influx was for 5 min in 100 μm KNO3. FW, Fresh weight. In summary, (1) We contend (based on statistical evaluation of kinetic models) that in planta fluxes through NRT1.1, at both low and high nitrate, exhibit a linear concentration dependence, and dual-affinity transport applies only to the X. laevis oocyte system. (2) Diminished nitrate uptake at low NO3− concentrations in AtNRT1.1 mutants results because influx is so suppressed by prior growth on very high levels of N that even a very small AtNRT1.1 flux is demonstrable. Under normal conditions of N provision, the AtNRT1.1 contribution to influx is trivial. (3) Notwithstanding the normal expression of AtNRT1.1 in Atnar2.1 mutants and the normal growth and nitrate influx at high nitrate, at low nitrate these mutants (lacking NRT2.1 transporters) demonstrate virtually no nitrate uptake, exhibit linear concentration dependence (Fig. 1), and fail to survive. If, as we conclude, NRT1.1 normally makes only a very minor contribution to nitrate uptake at low nitrate concentration, then what is its role? The literature suggests that NRT1.1 is multifunctional (Wang et al., 2012). In short-term experiments using seedling plants, NRT1.1 absorbs nitrate at high external concentration, as well as peptides, amino acids, and even auxin (Gojon et al., 2011). Yet, in long-term studies, ryegrass (Lolium perenne) tissue N and growth were independent of external nitrate concentration between 14.3 μm and 14.3 mm (Clement et al., 1978), suggesting a suppression of LATS. Likewise, long-term patterns of NO3− uptake in maize (Zea mays) grown in 0.5 or 2.5 mm NO3− were best correlated with the transcript abundance of NRT2.1 and NRT2.2 rather than NRT1.1A, NRT1.1B, or NRT1.2 (Garnett et al., 2013). While NRT1.1 is highly expressed at the root tip, NRT2.1 is more highly expressed distal to the root tip (Huang et al., 1999; Guo et al., 2001; Nazoa et al., 2003). The higher nitrate concentrations of fresh soil are first encountered by the advancing root tip, and NRT1.1 transporters would best capture this nitrate, reducing ambient concentrations to those matching the kinetics of NRT2 transporters (Garnett et al., 2013). Seasonal and local variations in nitrate availability demand that plants sense and respond adaptively to this availability by activating genes encoding NO3− transport systems and many enzyme systems (Crawford, 1995; Stitt, 1999; Wang et al., 2004; Ho et al., 2009; Krouk et al., 2010; Castaings et al., 2011; Gojon et al., 2011). NRT1.1 and NRT2.1 have been proposed as potential nitrate sensors for this nitrate signaling pathway (Gojon et al., 2011). In Arabidopsis, the elongation of lateral roots into high-NO3− patches is under the control of the transcription factor ANR1 (Zhang and Forde, 1998; Remans et al., 2006). Disruption of ANR1 or AtNRT1.1 expression diminishes this response, and AtNRT1.1 mutants exhibit decreased ANR1 expression (Remans et al., 2006). Hence, AtNRT1.1 has been referred to as a transceptor, a membrane protein that serves transport and signaling functions (Gojon et al., 2011). The normal down-regulation of NRT2.1 and NAR2.1 expression in response to NO3− assimilates (e.g. NH4+ or Gln) is suppressed in NRT1.1 mutants, resulting in elevated HATS activity (Muños et al., 2004; Krouk et al., 2006). Thus, it appears that NRT1.1 normally acts to suppress IHATS activity when high concentrations of alternative N sources are present. Therefore, down-regulation of HATS is achieved by feedback from N metabolites and from NRT1.1 activity. Guo et al. (2003) demonstrated that AtNRT1.1 is strongly expressed in guard cells, while AtNRT1.1 mutants accumulate lower levels of NO3− in guard cells, exhibit reduced stomatal opening, and transpire less than wild-type plants. Other anions may serve this osmotic function, but when NO3− is available to guard cells, NRT1.1 is an important component of stomatal opening. Treatment of wild-type parent plants with 1 to 50 mm NO3− increased subsequent seed germination rates in a dose-dependent manner, whereas seeds from AtNRT1.1 mutants pretreated with 1 mm NO3− failed to show increased germination, although plants did respond to 10 mm NO3− (Alboresi et al., 2005). This germination response is mediated by NRT1.1. The increased dormancy of seeds from plants previously grown on low NO3− might serve to prevent germination under less favorable conditions. The authors acknowledge that different formulations of the Michaelis-Menten equation (e.g. Lineweaver-Burk, Eadie-Hofstee, etc.) may give different results for regression. Accordingly, as well as the Hofstee evaluations used in the body of this paper, we also applied the Hanes-Wolfe and a nonlinear regression to the data for NRT1.1 fluxes. The nonlinear regression failed to discriminate between linear and hyperbolic models, but the Hanes-Wolfe analysis confirmed the superiority of linear over hyperbolic models. We thank TRI-University Meson Facility for providing 13NO3−. high-affinity transport systems low-affinity transport systems constitutive high-affinity transport systems inducible high-affinity transport systems constitutive low-affinity transport systems inducible low-affinity transport systems nitrogen
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».