bioRxivPlant Biology
Molecular mechanism for the recognition of sequence-divergent CIF peptides by the plant receptor kinases GSO1/SGN3 and GSO2.
S. Okuda, S. Fujita, A. Moretti, U. Hohmann, V. G. Gonzalez Doblas, Y. Ma, A. Pfister, B. Brandt, N. Geldner, M. Hothorn
Abstract
Plants use leucine-rich repeat receptor kinases (LRR-RKs) to sense sequence diverse peptide hormones at the cell surface. A 3.0 [A] crystal structure of the LRR-RK GSO1/SGN3 regulating Casparian strip formation in the endodermis reveals a large spiral-shaped ectodomain. The domain provides a binding platform for 21 amino-acid CIF peptide ligands, which are tyrosine sulfated by the tyrosylprotein sulfotransferase TPST/SGN2. GSO1/SGN3 harbors a binding pocket for sulfotyrosine and makes extended backbone interactions with CIF2. Quantitative biochemical comparisons reveal that GSO1/SGN3 - CIF2 represents one of the strongest receptor-ligand pairs known in plants. Multiple missense mutations are required to block CIF2 binding in vitro, and GSO1/SGN3 function in vivo. Using structure-guided sequence analysis we uncover novel CIF peptides conserved among higher plants. Quantitative binding assays with known and novel CIFs suggest that the homologous LRR-RKs GSO1/SGN3 and GSO2 have evolved unique peptide binding properties to control different developmental processes. A quantitative biochemical interaction screen, a CIF peptide antagonist and genetic analyses together implicate SERK LRR-RKs as essential co-receptor kinases required for GSO1/SGN3 and GSO2 receptor activation. 0ur work provides a mechanistic framework for the recognition of sequence-divergent peptide hormones in plants.\n\nSignificance StatementTwo sequence-related plant membrane receptor kinases and their shape-complementary co-receptors are shown to selectively sense members of a small family of secreted peptide hormones to control formation of an important diffusion barrier in the plant root.
- organism: plant (other)
- assay: structural biology
- research focus: cell type annotation
- research focus: protein folding & dynamics
- approach: experimental assay
- approach: biophysical modeling
- approach: statistical model
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