WideEffHunter: An Algorithm to Predict Canonical and Non-Canonical Effectors in Fungi and Oomycetes

Abstract

Newer effectorome prediction algorithms are considering effectors that may not comply with the canonical characteristics of small, secreted, cysteine-rich proteins. The use of effector-related motifs and domains is an emerging strategy for effector identification, but its use has been limited to individual species, whether oomycete or fungal, and certain domains and motifs have only been associated with one or the other. The use of these strategies is important for the identification of novel, non-canonical effectors (NCEs) which we have found to constitute approximately 90% of the effectoromes. We produced an algorithm in Bash called WideEffHunter that is founded on integrating three key characteristics: the presence of effector motifs, effector domains and homology to validated existing effectors. Interestingly, we found similar numbers of effectors with motifs and domains within two different taxonomic kingdoms: fungi and oomycetes, indicating that with respect to their effector content, the two organisms may be more similar than previously believed. WideEffHunter can identify the entire effectorome (non-canonical and canonical effectors) of oomycetes and fungi whether pathogenic or non-pathogenic, unifying effector prediction in these two kingdoms as well as the two different lifestyles. The elucidation of complete effectoromes is a crucial step towards advancing effectoromics and disease management in agriculture.

Novel Insights into Phytoplasma Effectors

“…This list of phytoplasma effectors comprises membrane-bound proteins such as IdpA, Imp, VmpA and Amp. Based on more traditional descriptions of effectors as "no TMD, secreted proteins", these proteins should be excluded, but it is known that the Amp protein interacts with the actin of insect vectors [99], and recently, Wang et al (2023) [26] showed that the expression of this protein in Nicotiana tabacum inhibits plant host defense and promotes infection by the rice orange leaf phytoplasma, validating this protein as a true effector.…”

PhyEffector, the First Algorithm That Identifies Classical and Non-Classical Effectors in Phytoplasmas

“…The search for effectors based on homology was also used in the prediction of fungal and oomycete effectors by WideEffHunter and demonstrated to improve its accuracy on real tests beyond positive control [49].…”

Pseudocercospora fijiensis Conidial Germination Is Dominated by Pathogenicity Factors and Effectors

“…Effector prediction and filtering were performed using WideEffHunter [49] and EffHunter algorithms [39]. The criteria to identify the canonical effectors were (1) protein length ≤ 400 amino acids, (2) extracellular localization, (3) the presence of a signal peptide, (4) at least 4 cysteine residues, and (5) absence of transmembrane domains.…”

“…Recently, the EffHunter algorithm was created and was shown to have the highest F1 score among fungal effector predictors when identifying these canonical or classical effectors [39]. A novel algorithm with the ability to identify non-canonical fungal effectors was published, Wide-EffHunter, which simultaneously possesses the ability of EffectorP 1.0 to predict effectors in non-pathogenic organisms, and the added ability of Effector P 2.0 to predict effectors in pathogenic fungi [49]. Here, 40 effector candidates (less than 10% of the effectorome) meet the classical characteristics, and this proportion coincides with WideEffHunter findings when fungal effectoromes were mined [49].…”

“…A novel algorithm with the ability to identify non-canonical fungal effectors was published, Wide-EffHunter, which simultaneously possesses the ability of EffectorP 1.0 to predict effectors in non-pathogenic organisms, and the added ability of Effector P 2.0 to predict effectors in pathogenic fungi [49]. Here, 40 effector candidates (less than 10% of the effectorome) meet the classical characteristics, and this proportion coincides with WideEffHunter findings when fungal effectoromes were mined [49]. Thirty-five of these canonical effectors were previously predicted in the P. fijiensis genome by Arango-Izaza et al [75].…”