Predication of the Effector Proteins Secreted by Fusarium sacchari Using Genomic Analysis and Heterogenous Expression

Abstract

One of the causative agents of pokkah boeng disease (PBD), which affects sugarcane crops globally, is the fungus Fusarium sacchari. These fungal infections reduce sugar quality and yield, resulting in severe economic losses. Effector proteins play important roles in the interactions between pathogenic fungi and plants. Here, we used bioinformatic prediction approaches to identify 316 candidate secreted effector proteins (CSEPs) in the complete genome of F. sacchari. In total, 95 CSEPs contained known conserved structures, representing 40 superfamilies and 18 domains, while an additional 91 CSEPs contained seven known motifs. Of the 130 CSEPs containing no known domains or motifs, 14 contained one of four novel motifs. A heterogeneous expression system in Nicotiana benthamiana was used to investigate the functions of 163 CSEPs. Seven CSEPs suppressed BAX-triggered programmed cell death in N. benthamiana, while four caused cell death in N. benthamiana. The expression profiles of these eleven CSEPs during F. sacchari infection suggested that they may be involved in sugarcane-F. sacchari interaction. Our results establish a basis for further studies of the role of effector molecules in pathogen–sugarcane interactions, and provide a framework for future predictions of pathogen effector molecules.

Identification of Pathogenicity-Related Effector Proteins and the Role of Piwsc1 in the Virulence of Penicillium italicum on Citrus Fruits

“…These group of proteins were predicted as apoplastic or cytoplasmic effector proteins on the EffectorP-fungi platform. Chen et al [ 66 ] used the A. tumefaciens -mediated Nicotiana benthamiana transient expression system to verify the functions of 3 such effectors in Fusarium sacchari . The results showed that Fs 00367 and Fs 00597 suppressed BAX-induced cell death, while Fs 05897 induced cell death.…”

Functional Characterization of the M36 Metalloprotease FgFly1 in Fusarium graminearum

“…In order to verify whether the FgFly1 signal peptide has a secretory function, we amplified the full-length signal peptide (amino acids 1-23), constructed pSUC2-FgFly1 sp and used the sucrose invertase secretion system of the YTK12 strain to verify the N-terminal signal peptide of FgFly1. It has a secretory function [ 47 ]. As shown in Figure 5 A, the YTK12 strain was unable to synthesize tryptophan with sucrose invertase, so it is not able to grow on CMD-W medium lacking tryptophan and YPRAA, which contains only raffinose as a carbon source.…”

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

“…Recently, with the intention of expanding effector prediction in fungal genomes, Huang et al (2022) [ 13 ], Jaswal et al (2021) [ 14 ] and Zhao et al (2020) [ 15 ] conduced searches based on motifs, a strategy typically used to identify oomycete effectors (the motifs RXLR, ERR, LXL, FLAK, are usually associated with oomycete effectors). Conversely, motif- independent prediction of effectors was recently applied in oomycetes [ 27 ].…”

“…However, effector proteins that differ in one or more of these canonical criteria also exist and we will refer to them as “non-canonical effectors” (NCEs). Non-canonical effectors have been identified based on specific searches for motifs and domains that are associated with other characterized effectors [ 13 , 14 , 15 ], or because of overexpression data observed in transcriptomes of plant-pathogen interactions [ 8 , 16 ]. The effector Pi04314 (PexRD24) was identified while searching for the “RXLR” motif deduced from ESTs of the oomycete Phytophthora infestans during its interaction with potato and tomato.…”

“…Many recent reports continue to base their predictions of effectors on short amino acid lengths and cysteine richness [ 22 , 23 ], but others are searching by other means [ 8 , 13 , 14 , 15 , 16 ]. Available algorithms include the EffectorP machine learning (ML) series, among which the latest version, EffectorP 3.0, is able to classify effectors in the apoplast and cytoplast [ 24 ].…”