Lahfa, M. | 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↗

bioRxiv2023

The structural landscape and diversity of Pyricularia oryzae MAX effectors revisited

Magnaporthe AVRs and ToxB-like (MAX) effectors constitute a family of secreted virulence proteins in the fungus Pyricularia oryzae (syn. Magnaporthe oryzae), which causes blast disease on numerous cereals and grasses. In spite of high sequence divergence, MAX effectors share a common fold characterized by a {beta}-sandwich core stabilized by a conserved disulfide bond. In this study, we investigated the structural landscape and diversity within the MAX effector repertoire of P. oryzae. Combining experimental protein structure determination and in silico structure modeling we validated the presence of the conserved MAX effector core domain in 77 out of 94 groups of orthologs (OG) identified in a previous population genomic study. Four novel MAX effector structures determined by NMR were in remarkably good agreement with AlphaFold2 (AF2) predictions. Based on the comparison of the AF2-generated 3D models we propose a classification of the MAX effectors superfamily in 20 structural groups that vary in the canonical MAX fold, disulfide bond patterns, and additional secondary structures in N- and C-terminal extensions. About one-third of the MAX family members remain singletons, without strong structural relationship to other MAX effectors. Analysis of the surface properties of the AF2 MAX models also highlights the high variability within the MAX family at the structural level, potentially reflecting the wide diversity of their virulence functions and host targets. Author summaryMAX effectors are a family of virulence proteins from the plant pathogenic fungus Pyricularia (syn. Magnaporthe) oryzae that share a similar 3D structure despite very low amino-acid sequence identity. Characterizing the function and evolution of these proteins requires a detailed understanding of their structural diversity. With this in mind, we have determined the NMR structures of four new MAX effectors and shown a near-perfect match with the corresponding AlphaFold2 (AF2) models. We then applied a prediction pipeline based on similarity searches with structural modeling using the AF2 software to predict MAX effectors in a collection of 120 P. oryzae genomes. The resulting models and experimental structures revealed that the MAX core while preserved is highly permissive to secondary structure variations and may coexists with extensive structural diversity in terms of structured N- or C-terminal extensions permitting their classification. For a subset of AF2 models, we have also analyzed the physico-chemical properties of the core domain surfaces, adding another, more functional perspective, notably surface electrostatics and stickiness. This work constitutes a major step in understanding the relationships among MAX effectors by analyzing their structural landscape and cataloguing specific physico-chemical properties. It also provides valuable insights for guiding research into the putative targets of these effectors in infected plant hosts.

bioinformatics↗