Mammri, L. | bioRxiv Science

bioRxiv2024

Zymoseptoria tritici proteins structurally related to UmV-KP4 and UmV-KP6 are toxic to fungi, and define novel structural families of fungal effectors

Fungal effectors play crucial roles in plant infection. Despite low sequence identity, effectors were recently classified into structural families. In this study, we have elucidated the structures of Zt-NIP1 and Mycgr3-91409 effectors of the wheat fungal pathogen Zymoseptoria tritici, using X-ray crystallography and NMR. These effectors displayed a structural homology with, respectively, KP4 and KP6 killer toxins, from UmV dsRNA viruses infecting the corn fungal pathogen Ustilago maydis. Consequently, Zt-NIP1 and Mycgr3-91409 were renamed Zt-KP4-1 and Zt-KP6-1. Orthologs and paralogs of Zt-KP4-1 and Zt-KP6-1 were identified in Zymoseptoria, but not in other fungi, except Ecp2 effectors related to Zt-KP4-1. Assessment of the biological activities of Zt-KP6-1 and Zt-KP4-1 revealed their toxicity to fungi such as Botrytis cinerea and Z. tritici, but not to wheat. A novel pipeline relying on Foldseek and cysteine-pattern constrained HMM searches of AlphaFold2 predicted structures from Uniprot generated a comprehensive inventory of KP4 and KP6 proteins in fungi and plants. A structure-based classification of these proteins revealed four KP4 and three KP6 structural super families. This classification provided far-reaching hypotheses on their biological function and evolution. This unifying structural framework highlights the power of structure determination for the classification of effectors, and their functional investigation.

biochemistry↗

bioRxiv2021

Design of a new effector recognition specificity in a plant NLR immune receptor by molecular engineering of its integrated decoy domain

Plant nucleotide-binding and leucine-rich repeat domain proteins (NLRs) are immune sensors that specifically recognize pathogen effectors and induce immune responses. Designing artificial NLRs with new effector recognition specificities is a promising prospect for sustainable, knowledge-driven crop protection. However, such strategies are hampered by the complexity of NLR function. Here, we tested whether molecular engineering of the integrated decoy domain (ID) of an NLR could extend its recognition spectrum to a new effector. To this aim, we relied on the detailed molecular knowledge of the recognition of distinct Magnaporthe oryzae MAX (Magnaporthe AVRs and ToxB-like) effectors by the rice NLRs RGA5 and Pikp-1. For both NLRs, effector recognition involves physical binding to their HMA (Heavy Metal-Associated) IDs. However, AVR-PikD, the effector recognized by Pikp-1, binds to a completely different surface of the HMA domain compared to AVR-Pia and AVR1-CO39, recognized by RGA5. By introducing into the HMA domain of RGA5 the residues of the Pikp-1 HMA domain involved in AVR-PikD binding, we created a high-affinity binding surface for this new effector. In the Nicotiana benthamiana heterologous system, RGA5 variants carrying this engineered binding surface still recognize AVR-Pia and AVR1-CO39, but also perceive the new ligand, AVR-PikD, resulting in the activation of immune responses. Therefore, our study provides a proof of concept for the design of new effector recognition specificities in NLRs through molecular engineering of IDs. However, it pinpoints significant knowledge gaps that limit the full deployment of this NLR-ID engineering strategy and provides hypotheses for future research on this topic.

plant biology↗