Transceptor NRT1.1 and receptor-kinase QSK1 complex controls PM H+-ATPase activity under low nitrate.

NRT1.1, a nitrate transceptor, plays an important role in nitrate binding, sensing, and nitrate-dependent lateral root (LR) morphology. However, little is known about NRT1.1-mediated nitrate signaling transduction through plasma membrane (PM)-localized proteins. Through in-depth phosphoproteome profiling using membranes of Arabidopsis roots, we identified receptor kinase QSK1 and plasma membrane H+-ATPase AHA2 as potential downstream components of NRT1.1 signaling in a mild low-nitrate (LN)-dependent manner. QSK1, as a functional kinase and molecular link, physically interacts with NRT1.1 and AHA2 at LN and specifically phosphorylates AHA2 at S899. Importantly, we found that LN, not high nitrate (HN), induces formation of the NRT1.1-QSK1-AHA2 complex in order to repress the proton efflux into the apoplast by increased phosphorylation of AHA2 at S899. Loss of either NRT1.1 or QSK1 thus results in a higher T947/S899 phosphorylation ratio on AHA2, leading to enhanced pump activity and longer LRs under LN. Our results uncover a regulatory mechanism in which NRT1.1, under LN conditions, promotes coreceptor QSK1 phosphorylation and enhances the NRT1.1-QSK1 complex formation to transduce LN sensing to the PM H+-ATPase AHA2, controlling the phosphorylation ratio of activating and inhibitory phosphorylation sites on AHA2. This then results in altered proton pump activity, apoplast acidification, and regulation of NRT1.1-mediated LR growth.

Comparison of path-based centrality measures in protein-protein interaction networks revealed proteins with phenotypic relevance during adaptation to changing nitrogen environments.

Plants must rapidly adapt to changes in nutrient conditions. Especially adaptations to changing nitrogen environments are very complex involving also major adjustments on the protein level. Here, we used a size-exclusion chromatography-coupled to mass spectrometry approach to study the dynamics of protein-protein interactions induced by transition from full nutrition to nitrogen starvation. Comparison of interaction networks established for each nutrient condition revealed a large overlap of proteins which were part of the protein-protein interaction network, but that same set of proteins underwent different interactions at each treatment. Network topology parameter betweenness centrality (BC) was found to best reflect the relevance of individual proteins in the information flow within each network. Changes in BC for individual proteins may therefore indicate their involvement in the cellular adjustments to the new condition. Based on this analysis, a set of proteins was identified showing high nitrogen-dependent changes in their BC values: The receptor kinase AT5G49770, co-receptor QSK1, and proton-ATPase AHA2. Mutants of those proteins showed a nitrate-dependent root growth phenotype. Individual interactions within the reconstructed network were tested using FRET-FLIM technology. Taken together, we present a systematic strategy comparing dynamic changes in protein-protein interaction networks based on their network parameters to identify regulatory nodes. SIGNIFICANCE: Protein-protein interactions are known to be important in cellular signaling events, but the dynamic changes in interaction networks induced by external stimuli are still rarely studied. We systematically analyzed how changes in the nutrient environment induced a rewiring of protein-protein interactions in roots. We observed small changes in overall protein abundances, but instead a rewiring of pairwise protein-protein interactions. Betweenness centrality was found to be the optimal network topology parameter to identify protein candidates with high relevance to the information flow in the (dynamic) network. Predicted interactions of those relevant nodes were confirmed in FLIM/FRET experiments and in phenotypic analysis. The network approach described here may be a useful application in dynamic network analysis more generally.

Classification and Interactions of LRR Receptors and Co-receptors Within the Arabidopsis Plasma Membrane - An Overview.

Receptor kinases (RK) constitute the largest protein kinase family in plants. In particular, members of the leucine-rich repeat-receptor kinases (LRR-RKs) are involved in the perception of various signals at the plasma membrane. Experimental evidence over the past years revealed a conserved activation mechanism through ligand-inducible heterodimer formation: a ligand is recognized by a receptor kinase with a large extracellular domain (ECD). This ligand binding receptor directly interacts with a so-called co-receptor with a small ECD for ligand fixation and kinase activation. A large proportion of LRR-RKs is functionally still uncharacterized and the dynamic complexity of the plasma membrane makes it difficult to precisely define receptor kinase heterodimer pairs and their functions. In this review, we give an overview of the current knowledge of LRR receptor and co-receptor functions. We use ECD lengths to classify the LRR receptor kinase family and describe different interaction properties of ligand-binding receptors and their respective co-receptor from a network perspective.

Global Identification of Protein Complexes within the Membrane Proteome of Arabidopsis Roots Using a SEC-MS Approach.

Biological processes consist of several consecutive and interacting steps as, for example, in signal transduction cascades or metabolic reaction chains. These processes are regulated by protein-protein interactions and the formation of larger protein complexes, which also occur within biological membranes. To gain a large-scale overview of complex-forming proteins and the composition of such complexes within the cellular membranes of Arabidopsis roots, we use the combination of size-exclusion chromatography and mass spectrometry. First, we identified complex-forming proteins by a retention shift analysis relative to expected retention times of monomeric proteins during size-exclusion chromatography. In a second step we predicted complex composition through pairwise correlation of elution profiles. As result we present an interactome of 963 proteins within cellular membranes of Arabidopsis roots. Identification of complex-forming proteins was highly robust between two independently grown root proteomes. The protein complex composition derived from pairwise correlations of coeluting proteins reproducibly identified stable protein complexes (ribosomes, proteasome, mitochondrial respiratory chain supercomplexes) but showed higher variance between replicates regarding transient interactions (e.g., interactions with kinases) within membrane protein complexes.