Remote homology clustering identifies lowly conserved families of effector proteins in plant-pathogenic fungi

Template-Based Modelling of the Structure of Fungal Effector Proteins

The discovery of new fungal effector proteins is necessary to enable the screening of cultivars for disease resistance. Sequence-based bioinformatics methods have been used for this purpose, but only a limited number of functional effector proteins have been successfully predicted and subsequently validated experimentally. A significant obstacle is that many fungal effector proteins discovered so far lack sequence similarity or conserved sequence motifs. The availability of experimentally determined three-dimensional (3D) structures of a number of effector proteins has recently highlighted structural similarities amongst groups of sequence-dissimilar fungal effectors, enabling the search for similar structural folds amongst effector sequence candidates. We have applied template-based modelling to predict the 3D structures of candidate effector sequences obtained from bioinformatics predictions and the PHI-BASE database. Structural matches were found not only with ToxA- and MAX-like effector candidates but also with non-fungal effector-like proteins-including plant defensins and animal venoms-suggesting the broad conservation of ancestral structural folds amongst cytotoxic peptides from a diverse range of distant species. Accurate modelling of fungal effectors were achieved using RaptorX. The utility of predicted structures of effector proteins lies in the prediction of their interactions with plant receptors through molecular docking, which will improve the understanding of effector-plant interactions.

Surface frustration re-patterning underlies the structural landscape and evolvability of fungal orphan candidate effectors

Pathogens secrete effector proteins to subvert host physiology and cause disease. Effectors are engaged in a molecular arms race with the host resulting in conflicting evolutionary constraints to manipulate host cells without triggering immune responses. The molecular mechanisms allowing effectors to be at the same time robust and evolvable remain largely enigmatic. Here, we show that 62 conserved structure-related families encompass the majority of fungal orphan effector candidates in the Pezizomycotina subphylum. These effectors diversified through changes in patterns of thermodynamic frustration at surface residues. The underlying mutations tended to increase the robustness of the overall effector protein structure while switching potential binding interfaces. This mechanism could explain how conserved effector families maintained biological activity over long evolutionary timespans in different host environments and provides a model for the emergence of sequence-unrelated effector families with conserved structures.

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

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.

Fungal Effectoromics: A World in Constant Evolution

Effectors are small, secreted molecules that mediate the establishment of interactions in nature. While some concepts of effector biology have stood the test of time, this area of study is ever-evolving as new effectors and associated characteristics are being revealed. In the present review, the different characteristics that underly effector classifications are discussed, contrasting past and present knowledge regarding these molecules to foster a more comprehensive understanding of effectors for the reader. Research gaps in effector identification and perspectives for effector application in plant disease management are also presented, with a focus on fungal effectors in the plant-microbe interaction and interactions beyond the plant host. In summary, the review provides an amenable yet thorough introduction to fungal effector biology, presenting noteworthy examples of effectors and effector studies that have shaped our present understanding of the field.