Nitrogen sensing and regulatory networks: it's about time and space.
Carly M ShanksKarin RothkegelMatthew D BrooksChia-Yi ChengJosé Miguel AlvarezSandrine RuffelGabriel KroukRodrigo A GutierrezGloria M CoruzziPublished in: The Plant cell (2024)
A plant's response to external and internal nitrogen signals/status relies on sensing and signaling mechanisms that operate across spatial and temporal dimensions. From a comprehensive systems biology perspective, this involves integrating nitrogen responses in different cell types and over long distances to ensure organ coordination in real time and yield practical applications. In this prospective review, we focus on novel aspects of nitrogen (N) sensing/signaling uncovered using temporal and spatial systems biology approaches, largely in the model Arabidopsis. The temporal aspects span: transcriptional responses to N-dose mediated by Michaelis-Menten kinetics, the role of the master NLP7 transcription factor as a nitrate sensor, its nitrate-dependent TF nuclear retention, its "hit-and-run" mode of target gene regulation, and temporal transcriptional cascade identified by "network walking." Spatial aspects of N-sensing/signaling have been uncovered in cell type-specific studies in roots and in root-to-shoot communication. We explore new approaches using single-cell sequencing data, trajectory inference, and pseudotime analysis as well as machine learning and artificial intelligence approaches. Finally, unveiling the mechanisms underlying the spatial dynamics of nitrogen sensing/signaling networks across species from model to crop could pave the way for translational studies to improve nitrogen-use efficiency in crops. Such outcomes could potentially reduce the detrimental effects of excessive fertilizer usage on groundwater pollution and greenhouse gas emissions.
Keyphrases
- transcription factor
- single cell
- artificial intelligence
- machine learning
- big data
- heavy metals
- rna seq
- gene expression
- drinking water
- deep learning
- risk assessment
- human health
- type diabetes
- stem cells
- particulate matter
- climate change
- heat shock
- health risk assessment
- body mass index
- physical activity
- mesenchymal stem cells
- skeletal muscle
- bone marrow
- aqueous solution