Transcription factor module NLP–NIGT1 fine-tunes NITRATE TRANSPORTER2.1 expression

• Published in: Plant physiology (Bethesda) 2023-11, Vol.193 (4), p.2865-2879
• Main Authors: Ueda, Yoshiaki, Yanagisawa, Shuichi
• Format: Article
• Language: English
• ISSN: 0032-0889; 1532-2548
• DOI: 10.1093/plphys/kiad458

Abstract Arabidopsis (Arabidopsis thaliana) high-affinity NITRATE TRANSPORTER2.1 (NRT2.1) plays a dominant role in the uptake of nitrate, the most important nitrogen (N) source for most terrestrial plants. The nitrate-inducible expression of NRT2.1 is regulated by NIN-LIKE PROTEIN (NLP) family transcriptional activators and NITRATE-INDUCIBLE GARP-TYPE TRANSCRIPTIONAL REPRESSOR1 (NIGT1) family transcriptional repressors. Phosphorus (P) availability also affects the expression of NRT2.1 because the PHOSPHATE STARVATION RESPONSE1 transcriptional activator activates NIGT1 genes in P-deficient environments. Here, we show a biology-based mathematical understanding of the complex regulation of NRT2.1 expression by multiple transcription factors using 2 different approaches: a microplate-based assay for the real-time measurement of temporal changes in NRT2.1 promoter activity under different nutritional conditions, and an ordinary differential equation (ODE)-based mathematical modeling of the NLP- and NIGT1-regulated expression patterns of NRT2.1. Both approaches consistently reveal that NIGT1 stabilizes the amplitude of NRT2.1 expression under a wide range of nitrate concentrations. Furthermore, the ODE model suggests that parameters such as the synthesis rate of NIGT1 mRNA and NIGT1 proteins and the affinity of NIGT1 proteins for the NRT2.1 promoter substantially influence the temporal expression patterns of NRT2.1 in response to nitrate. These results suggest that the NLP–NIGT1 feedforward loop allows a precise control of nitrate uptake. Hence, this study paves the way for understanding the complex regulation of nutrient acquisition in plants, thus facilitating engineered nutrient uptake and plant response patterns using synthetic biology approaches. Luciferase-based analysis and mathematical modeling suggest that a transcriptional network structure stabilizes the expression of the NITRATE TRANSPORTER2.1 under various concentrations of nitrate.