The supernatant was decanted and the cells were resuspended in 500 mL of infiltration medium sucrose, 44 nM benzylaminopurine, 0.02% Silwet L-77. Invert flowering plants into Agrobacterium solution and swirl for 1 minute making sure that the leaves and flowers were fully submerged. The top of the pots were wrapped with saran wrap and covered for 3 days, after which plants were hand-watered until seeds were fully set. Col-0 wild type, als3-1, sog1-7;als3-1, and suv2-3;als3-1 seedlings were grown in hydroponics for 7 days, then transferred to hydroponic media supplemented with either 0 or 25 μM AlCl3 for 24 hours. Roots were collected and frozen in liquid nitrogen. Total RNA was extracted using TRIzol reagent following the manufacturer’s instructions. RNA yield was measured on a nanodrop and an aliquot of 10 μg of RNA was reserved. Loading buffer was added to 10 μg of total RNA. Total RNA was run on a 1% agarose gel containing 1 X MOPS and 18% formaldehyde . Even loading was visually verified by the relative amount of RNA in each lane by visualized with ethidium bromide staining on a UV light box. RNA was transferred to a Zeta Probe GT nitrocellulose membrane through RNA Capillary Transfer as per manufacturer’s instructions. RNA was cross linked using optimal cross link setting on a SpectroLinker XL-1000 UV Cross linker . The blot was pre-hybridized by incubating at 65°C in prehybridization solution for at least one hour before adding the probe. The probe was made using [32P]- labeled dCTP with the RadPrime kit following manufacturer’s instructions. The probes were cleaned up using an illustra MicroSpin G-50 column following the manufacturer’s instructions.
The probes were boiled,grow bag quick chilled then injected into the prehybridization solution and allowed to hybridize for overnight at 65°C. The blots were then washed in progressively more stringent washes in the following order 2 X SSC, 0.1% SDS; 0.5 X SSC, 0.1% SDS; 0.1% SSC, 0.1% SDS, for 30 minutes each. The blots were exposed to BioMax Light film and developed using a MiniMedical Automatic Film Processor . For real-time PCR analysis, seedlings were grown in the absence or presence of 1.50 mM AlCl3 in a soaked gel environment, after which tissue was collected for RNA extraction using Trizol . RNA samples were DNase treated with RQ1 RNase-free DNase , and cDNA was generated using a SuperScript III kit following the manufacturer’s instructions. Real-time PCR reactions were performed according to Bio-Rad iQ SYBR Green Supermix instructions and run on the Bio-Rad iQ Real-time system under the following conditions: one repeat of 3 min at 95°C, followed by 40 repeats of 30 seconds at 95°C, 40 seconds at 55°C, and 45 seconds at 72°C, followed by a melt curve encompassing 80 steps of 0.5°C from 55 to 95°C. Fluorescence was measured during the 72°C extension step and at each step of the melt curve. Gene expression levels were calculated using the DDCt method as described in the Real-Time PCR Handbook . Mean ± SD values were determined from three technical replicates, and the equations listed below were used for calculations. Arabidopsis EF-1α was used as the reference gene because its expression was found to be Al independent for all genotypes considered . Primer sequences for all genes used can be found in Table 1.
Replication efficiencies of RT-PCR primers were generated from standard curves produced from RT-PCR reactions as described above with 500, 100, 50, 10, 5, 1, 0.5, and 0.1 ng of Arabidopsis cDNA template. Log values of template quantity were graphed against the Ct values as determined from three technical replicates to generate a standard curve for each primer set, the slope, and R2 values, from which were used to calculate reaction efficiencies . Only efficiencies between 95 and 105% and standard curve R2 > 0.98 were accepted. Nitrogen is a vital macro-nutrient for plant growth and development.In agricultural systems, high-yield of crops relies on application of nitrogen fertilizers. But a large part of nitrogen deposited in the soil can’t be absorbed by plants and is lost to the environment, resulting in severe environmental and ecological pollution. Improving the nitrogen use efficiency of crops is the key to solve these problems. Studying the genes and mechanisms involved in regulating nitrogen uptake and assimilation can be a prerequisite for improving NUE of crops, therefore it is of great importance for sustaining agriculture. Nitrate and ammonium are the main nitrogen forms used by plants and most crops, like maize and wheat, take up nitrate as the major nitrogen source. In addition to its nutrient role, nitrate acts also as a signaling molecule for plants. It regulates the expression levels of many genes, including genes directly involved in nitrate assimilation, namely NIAs, NiR, and some NRTs . It is also involved in many adaptive responses of plants, such as root development and architecture, seed dormancy, flowering time, circadian system, leaf development, stomatal movements, and auxin transportation. Nitrate is taken up into plants by nitrate transporters and high affinity and low affinity nitrate uptake systems have been identified. Four gene families have been identified that encode nitrate transporters in Arabidopsis: NRT1/PTR , NRT2 , CLC , and SLAC1/SLAH .
Among these families, NRT1/PTR belongs to the low affinity transport system, and NRT2 belongs to the high affinity transport system. NRT1.1 , which belongs to NRT/PTR family, functions in nitrate uptake as both high affinity and low affinity transporter.In addition to the nitrate transport systems, genes involved in nitrate signaling have also been identified. Most of these genes were found to function in root architecture or primary nitrate responses. Te genes functioning in root architecture include the ANR1, the first molecular component isolated by classic molecular genetics approach, is a MADS box transcription factor and positively regulates lateral root branching under sufficient nitrate condition. miR393/AFB3 and NAC4 have been demonstrated to regulate the root system architecture in nitrate signaling using systems approach. Te split-root assays indicated that TCP20 was involved in systemic nitrate signaling for root foraging. Recently, TCP20 was found to regulate root meristem growth under nitrogen starvation and to interact with NLP6&7. HHO1 and HRS1 are two nitrate-responsive transcription factors isolated by genome-wide analyses. They function in the repression of primary root growth under both phosphate starvation and nitrate supply conditions. During last several years, the nitrate regulatory factors involved in the primary nitrate response have been identified. NRT1.1, in addition to its transport function, was identified to work as a nitrate sensor. Te study on the crystal structure of NRT1.1 has demonstrated that Tr101 phosphorylation is essential for nitrate transport rate and provides further insights into its transport mechanisms. CIPK8 and CIPK23 which belong to CBL-interacting protein kinase family are important players in responding to primary nitrate. CIPK8 works positively while CIPK23 functions negatively in nitrate regulation. Te expression of both CIPK8 and CIPK23 is regulated by NRT1.1. Recently, NRG2 which is an essential nitrate regulatory gene was isolated by forward genetics screen. NRG2 acts as a positive nitrate regulatory factor and modulates NRT1.1 expression and can interact with NLP7. Additionally,grow bag gardening several transcription factors were identified to be involved in primary nitrate response, for example, NLP6, NLP7, LBD37/38/39, TGA1, TGA4, and SPL9. NLP7 is NIN-like protein and acts as an important nitrate positive regulator. NLP7 was isolated by reverse genetics strategy and the nlp7 mutants exhibit a nitrogen-starved phenotype. Te nitrate condition can affect the NLP7′s nuclear retention. Previous studies have demonstrated that the nitrate response cis-element NRE can be bound by NLPs and contain a DNA-binding domain RWP-PK and protein-protein interaction domains typeI/II Phox and Ben1p. ChIP-chip assays showed that NLP7 could bind 851 genes containing NRT1.1, NRT2.1, LBD37/38.
In addition, overexpression of NLP7 can increase plant biomass, nitrogen uptake, total nitrogen content, and expression levels of genes involved in nitrogen assimilation and signaling. Moreover, NLP7 can control plant root growth under both N-limited and N-rich conditions. NLP6 also functions positively in nitrate regulation, is retained in the nucleus in nitrate-treated plants and can activate the expression of nitrate-responsive genes. LBD37/38/39 are negative regulators in nitrate signaling. Tey are involved in primary nitrate response and can affect nitrogen status, growth, and nitrogen-dependent shoot branching. TGA1, TGA4, and SPL9 were isolated by systems approach. TGA1 and TGA4 belong to bZIP transcription factor family and TGA1 can bind to the promoters of NRT2.1 and NRT2.2. SPL9 is demonstrated to be a nitrate regulatory hub. Although these nitrate regulatory genes have been identified, our understanding of the nitrate regulatory gene network is still incomplete. For example, both NLP7 and NRT1.1 play essential roles in regulating nitrate signaling and ChIP-chip assay showed that NLP7 might bind NRT1.1, however, their relationship and underlining mechanism remain unclear. In this paper, we investigated the relationship between NRT1.1 and NLP7 in nitrate regulation. Our analyses reveal that NLP7 acts as a positive regulatory factor upstream of NRT1.1 when NH4 + is present and modulates the nitrate signaling function of NRT1.1. NLP7 might function in another pathway to regulate nitrate signaling independent of NRT1.1. In addition, transcriptome data showed that four GO terms related to nitrogen were regulated by NRT1.1 as well as NLP7 in nitrate signaling, providing more evidence to support our above conclusion. Furthermore, the ChIP and EMSA assays indicated that NLP7 could bind to specifc regions of the NRT1.1 promoter. Our findings not only further elucidate the relationship between NRT1.1 and NLP7, but also provide insights into the network of the nitrate regulatory genes.To study the relationship between NLP7 and NRT1.1, the expression levels of NRT1.1 was detected firstly under potassium nitrate and ammonium nitrate conditions. Figure 1a showed that the transcript levels of NRT1.1 in the nlp7 mutants were not notably changed under potassium nitrate condition, but was significantly decreased in mutant plants under ammonium nitrate condition . This indicates that the expression levels of NRT1.1 can be modulated by NLP7 in the presence of NH4 +. In order to test if NLP7 is regulated by NRT1.1, we tested NLP7 expression in chl1-5 and chl1-13 mutants in potassium nitrate and ammonium nitrate mediums. Te expression of NLP7 was not changed in the nrt1.1 mutants . This result indicates that NRT1.1 may not regulate the expression of NLP7. We also tested the NRT1.1 expression response to nitrate in WT and the nlp7 mutants. qPCR results showed that the induction of NRT1.1 by nitrate was notably decreased in the nlp7 mutants, indicating that NLP7 affects the response of NRT1.1 to nitrate .To elucidate the relationship between NLP7 and NRT1.1, the single mutants: nlp7-4 and chl1-13 which contain the nitrate-responsive NRP-YFP transgene, both of which were isolated by our mutant screens described previously were crossed to obtain the double mutant chl1-13 nlp7-4. Te YFP signal levels in the roots of WT, two single mutants, and double mutants were detected. Te results showed that the YFP signal of the two single mutants under the ammonium nitrate condition was much weaker than that of WT while the double mutant chl1-13 nlp7-4 exhibited significantly weaker YFP signal than the nlp7-4 mutant and similar to the chl1-13 mutant . At the same time, we detected the YFP signal of the plants under the potassium nitrate condition without NH4 +. Te results showed that the YFP levels of the double mutant chl1-13 nlp7-4 were much lower than those of WT and the chl1-13 mutant, and similar to those of the nlp7-4 mutant . Remarkably, the YFP signal of the chl1-13 mutant was mildly weaker than WT. This result is consistent with previous studies demonstrating that NRT1.1 is a key player in the nitrate regulation when NH4 + is present and functions poorly when NH4 + is absent. Because we don’t observe any additive effects in the double mutant, these evidences indicate that NLP7 and NRT1.1 may participate in nitrate signaling in the same pathway. In order to find physiological evidences for the relationship between NLP7 and NRT1.1, we investigated the nitrate content and nitrate reductase activity in plants. Figure 2c showed higher nitrate content in the nlp7 mutants while lower in the chl1 plants than that in WT .