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NRT1.1 as central signaling hub orchestrating plant growth and stress trade-offs

Sep 2026 · Frontiers in Plant Science · Vol 17 · 0 citations · 82 references
Medicine

Abstract

Plants must continuously balance nitrogen-dependent growth with adaptation to environmental stresses. The nitrate transporter AtNRT1.1 in Arabidopsis thaliana and its rice ortholog OsNRT1.1B have been reported to integrate nitrogen- and stress-related signals in their respective species. This review synthesizes how NRT1.1 orthologs coordinate nitrate and stress signaling. Experimentally characterized NRT1.1 forms a homodimer, and phosphorylation of a key threonine residue (Thr101) acts as a molecular switch, toggling between high- and low-affinity nitrate transport modes. OsNRT1.1B also functions as a high-affinity ABA receptor in rice. NRT1.1 orthologs may integrate nitrate and ABA signals via allosteric regulation and ligand competition. Signaling triggers cellular responses via calcium signatures and kinase cascades, driving transcriptional reprogramming through NLP transcription factors, including AtNLP2/7 in Arabidopsis and OsNLP3/4 in rice. These responses include root architecture remodeling, rhizosphere homeostasis, nitrogen-phosphorus coordination, and shoot-root developmental synchronization. This review also discusses the evolution of the NRT1.1 signaling, highlighting experimentally supported core functions and lineage-specific innovations. The nitrate transport/signaling module discussed here is supported primarily by studies of AtNRT1.1 in Arabidopsis, whereas the ABA-receptor module is supported mainly by studies of OsNRT1.1B in rice. However, whether mechanisms established in Arabidopsis are conserved and agronomically relevant in other crop species remains to be fully established. Although nitrate- and ABA-related NRT1.1 functions have both been investigated in rice, direct experimental evidence that the two proposed modules operate coordinately within a single species remains limited. Accordingly, this model should be viewed as a comparative and hypothesis-generating framework rather than a universally validated mechanism. Understanding this network may provide a basis for identifying targets to improve nutrient use efficiency, stress resilience, and yield stability, pending validation in target crops.

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