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Azcue, J. M.

Publications and source records attributed to Azcue, J. M..

2 recordsLinked to original sources

Convergent recognition of tobamovirus movement proteins by phylogenetically distinct NLR immune receptors

The tobamovirus Tomato brown rugose fruit virus (ToBRFV) has rapidly emerged as a major threat to tomato production worldwide, overcoming the widely deployed Tm-22-mediated resistance and challenging current strategies for tobamovirus disease control. The tomato coiled-coil nucleotide-binding leucine-rich repeat (CC-NLR) immune receptor HREZ confers resistance to ToBRFV. However, the activation mechanism underlying HREZ recognition of ToBRFV remains unclear. Here, we show that HREZ is activated by the movement protein (MP) of ToBRFV and induces hypersensitive cell death. Upon activation, HREZ assembles into a higher-order oligomeric complex, with AlphaFold 3 modelling supporting a pentameric resistosome model. Phylogenetic analysis places HREZ in a CC-NLR lineage distinct from the canonical tobamovirus resistance receptor Tm-22, consistent with convergent evolution of tobamovirus MP recognition. Comparative analysis of eight MPs from the family Virgaviridae reveals that HREZ and Tm-22 have distinct recognition spectra. Four distinct tobamovirus MPs that activate HREZ also promote its assembly into a higher-order oligomeric complex. Together, these findings show how phylogenetically distinct CC-NLRs can converge on the same viral target while retaining distinct recognition breadth and provide a foundation for developing resistance strategies against current and emerging tobamoviruses.

plant biology↗

AI-guided discovery of atypical protein assemblies

Artificial intelligence (AI) systems such as AlphaFold have transformed structural biology by enabling accurate prediction of protein structures. However, their capacity to uncover new classes of macromolecular assemblies remains largely untapped. We developed the Structural Novelty Index (SNI), a quantitative framework for identifying protein complexes that diverge from canonical architectures. As one implementation of SNI, we developed SNINRC-Hexa, to identify unconventional resistosomes formed by nucleotide-binding, leucine-rich repeat immune receptors (NLRs). We used it to analyze AlphaFold 3 models of 637 non-redundant NRC proteins from 346 genomes representing 85 plant species. This analysis identified candidates with predicted architectures distinct from the canonical hexameric resistosomes of NRC proteins. Biochemical purification and negative-stain transmission electron microscopy of NRC7 orthologs from multiple species supported the SNI prediction and revealed an unexpected undecameric (11-mer) assembly. Our results establish SNI as a scalable approach for discovering atypical protein complexes.

bioinformatics↗