 Computational studies reveal structural characterization and novel families of Puccinia striiformis f. sp. tritici effectorsRaheel Asghar, Nan Wu, Noman Ali, Yulei Wang and Mahinur Akkaya PLOS Computational Biology, 2025, vol. 21, issue 3, 1-26 Abstract: Understanding the biological functions of Puccinia striiformis f. sp. tritici (Pst) effectors is fundamental for uncovering the mechanisms of pathogenicity and variability, thereby paving the way for developing durable and effective control strategies for stripe rust. However, due to the lack of an efficient genetic transformation system in Pst, progress in effector function studies has been slow. Here, we modeled the structures of 15,201 effectors from twelve Pst races or isolates, a Puccinia striiformis isolate, and one Puccinia striiformis f. sp. hordei isolate using AlphaFold2. Of these, 8,102 folds were successfully predicted, and we performed sequence- and structure-based annotations of these effectors. These effectors were classified into 410 structure clusters and 1,005 sequence clusters. Sequence lengths varied widely, with a concentration between 101-250 amino acids, and motif analysis revealed that 47% and 5.81% of the predicted effectors contain known effector motifs [Y/F/W]xC and RxLR, respectively highlighting the structural conservation across a substantial portion of the effectors. Subcellular localization predictions indicated a predominant cytoplasmic localization, with notable chloroplast and nuclear presence. Structure-guided analysis significantly enhances effector prediction efficiency as demonstrated by the 75% among 8,102 have structural annotation. The clustering and annotation prediction both based on the sequence and structure homologies allowed us to determine the adopted folding or fold families of the effectors. A common feature observed was the formation of structural homologies from different sequences. In our study, one of the comparative structural analyses revealed a new structure family with a core structure of four helices, including Pst27791, PstGSRE4, and PstSIE1, which target key wheat immune pathway proteins, impacting the host immune functions. Further comparative structural analysis showed similarities between Pst effectors and effectors from other pathogens, such as AvrSr35, AvrSr50, Zt-KP4-1, and MoHrip2, highlighting a possibility of convergent evolutionary strategies, yet to be supported by further data encompassing on some evolutionarily distant species. Currently, our initial analysis is the most one on Pst effectors’ sequence, structural and annotation relationships providing a novel foundation to advance our future understanding of Pst pathogenicity and evolution.Author summary: Stripe rust, caused by the fungus Puccinia striiformis f. sp. tritici (Pst), is a major threat to wheat crops worldwide. The fungus uses special proteins, called effectors, to bypass the plant’s immune defenses and establish infection. To better understand how these effectors work, we used a computational tool, AlphaFold2, to predict the structures of over 15,000 Pst effector proteins. Interestingly, some of the effectors resemble proteins found in other plant pathogens, suggesting that different fungi may evolve analogously. Our research offers new insights into the combatting strategies of Pst and could lead to new methods for protecting wheat from stripe rust. Date: 2025 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1012503 DOI: 10.1371/journal.pcbi.1012503 Access Statistics for this article More articles in PLOS Computational Biology from Public Library of Science |
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