Alphafold-multimer predicts cross-kingdom interactions at the plant-pathogen interface

biorxiv(2023)

引用 0|浏览39
暂无评分
摘要
Adapted plant pathogens from various microbial kingdoms produce hundreds of unrelated small secreted proteins (SSPs) with elusive roles. Some of these SSPs might be inhibitors targeting the most harmful hydrolases secreted by the host. Here, we used Alphafold-Multimer (AFM) to screen 1,879 SSPs of seven tomato pathogens for interacting with six defence-related hydrolases of tomato that accumulate to high levels in the apoplast during infection. This screen of 11,274 protein pairs identified 15 SSPs that are predicted to obstruct the active site of chitinases and proteases with an intrinsic fold. Four SSPs were experimentally verified to be inhibitors of pathogenesis-related subtilase P69B, including extracellular protein-36 (Ecp36) and secreted-into-xylem-15 (Six15) of the fungal tomato pathogens Cladosporium fulvum and Fusarium oxysporum , respectively. Together with a novel P69B inhibitor from the bacterial pathogen Xanthomonas perforans and the previously reported Kazal-like inhibitors of the oomycete pathogen Phytophthora infestans , P69B emerges as an important effector hub targeted by different microbial kingdoms, consistent with the presence of a hyper-variant residue in P69B orthologs and gene duplication and diversification of P69B paralogs that could avoid inhibitor binding. This study demonstrates the power of artificial intelligence to accurately predict novel cross-kingdom interactions at the plant-pathogen interface. ### Competing Interest Statement The authors have declared no competing interest.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要