Black Sigatoka is a disease that occurs in banana plantations worldwide. This disease is caused by the hemibiotrophic fungus Pseudocercospora fijiensis, whose infection results in a significant reduction in both product quality and yield. Therefore, detection and identification in the early stages of this pathogen in plants could help minimize losses, as well as prevent the spread of the disease to neighboring cultures. To achieve this, a highly sensitive SPR immunosensor was developed to detect P. fijiensis in real samples of leaf extracts in early stages of the disease. A polyclonal antibody (anti-HF1), produced against HF1 (cell wall protein of P. fijiensis) was covalently immobilized on a gold-coated chip via a mixed self-assembled monolayer (SAM) of alkanethiols using the EDC/NHS method. The analytical parameters of the biosensor were established, obtaining a limit of detection of 11.7 µg mL⁻¹, a sensitivity of 0.0021 units of reflectance per ng mL⁻¹ and a linear response range for the antigen from 39.1 to 122 µg mL⁻¹. No matrix effects were observed during the measurements of real leaf banana extracts by the immunosensor. To the best of our knowledge, this is the first research into the development of an SPR biosensor for the detection of P. fijiensis, which demonstrates its potential as an alternative analytical tool for in-field monitoring of black Sigatoka disease.

Pathogens are able to deliver small-secreted, cysteine-rich proteins into plant cells to enable infection. The computational prediction of effector proteins remains one of the most challenging areas in the study of plant fungi interactions. At present, there are several bioinformatic programs that can help in the identification of these proteins; however, in most cases, these programs are managed independently. Here, we present EffHunter, an easy and fast bioinformatics tool for the identification of effectors. This predictor was used to identify putative effectors in 88 proteomes using characteristics such as size, cysteine residue content, secretion signal and transmembrane domains.

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.

Effectors are small, secreted molecules that alter host cell structure and function, thereby facilitating infection or triggering a defense response. Effectoromics studies have focused on effectors in plant–pathogen interactions, where their contributions to virulence are determined in the plant host, i.e., whether the effector induces resistance or susceptibility to plant disease. Effector molecules from plant pathogenic microorganisms such as fungi, oomycetes and bacteria are major disease determinants. Interestingly, the effectors of non-pathogenic plant organisms such as endophytes display similar functions but have different outcomes for plant health. Endophyte effectors commonly aid in the establishment of mutualistic interactions with the plant and contribute to plant health through the induction of systemic resistance against pathogens, while pathogenic effectors mainly debilitate the plant’s immune response, resulting in the establishment of disease. Effectors of plant pathogens as well as plant endophytes are tools to be considered in effectoromics for the development of novel strategies for disease management. This review aims to present effectors in their roles as promotors of health or disease for the plant host.

The coconut palm (Cocos nucifera L.) is a common crop in pantropical areas facing various challenges, one of them being the control of diseases and pests. Diseases such as bud rot caused by Phytophthora palmivora, lethal yellowing caused by phytoplasmas of the types 16SrIV-A, 16SrIV-D or 16SrIV-E, among others, and pests like the coconut palm weevil, Rhynchophorus vulneratus (Coleoptera: Curculionidae), and the horned beetle, Oryctes rhinocerus (Coleoptera: Scarabaeidae), are controlled by applying pesticides, pheromones and cultural control. These practices do not guarantee eradication since some causal agents have become resistant or are imbedded in infected tissues making them difficult to eradicate. This review condenses the current genomics, transcriptomics, proteomics and metabolomics studies which are being conducted with the aim of understanding the pathosystems associated with the coconut palm, highlighting the findings generated by omics studies that may become future targets for the control of diseases and pests in the coconut crop.