Application of alignment-free bioinformatics methods to identify an oomycete protein with structural and functional similarity to the bacterial AvrE effector protein

Bacteria deploy water channels to aid infection in plants

Plant pathogens deliver effector proteins into the plant cell to cause disease. Recently, Nomura et al. discovered that the AvrE family of effectors serve as water channels to release water into the apoplast, causing a phenomenon known as 'water soaking'. A chemical called PAMAM G1 blocks these channels and prevents disease symptoms.

Extracellular niche establishment by plant pathogens

The plant extracellular space, referred to as the apoplast, is inhabited by a variety of microorganisms. Reflecting the crucial nature of this compartment, both plants and microorganisms seek to control, exploit and respond to its composition. Upon sensing the apoplastic environment, pathogens activate virulence programmes, including the delivery of effectors with well-established roles in suppressing plant immunity. We posit that another key and foundational role of effectors is niche establishment - specifically, the manipulation of plant physiological processes to enrich the apoplast in water and nutritive metabolites. Facets of plant immunity counteract niche establishment by restricting water, nutrients and signals for virulence activation. The complex competition to control and, in the case of pathogens, exploit the apoplast provides remarkable insights into the nature of virulence, host susceptibility, host defence and, ultimately, the origin of phytopathogenesis. This novel framework focuses on the ecology of a microbial niche and highlights areas of future research on plant-microorganism interactions.

Unraveling pathogen deceptive disguise: from modules to mimicry

Pathogens rely on their effector proteins to colonize host plants. These effectors have diverse functions. A recent study by Li et al. highlights the significance of protein modularity in generating functional diversity among Phytophthora effectors. It underscores the sophisticated tactics that phytopathogens adopt to alter host cellular processes.

Protein phosphatase 2A: a high-value target of virulence factors

Pathogen-encoded virulence factors perturb host physiology and immune function to promote infection. Reinforcing the concept that protein phosphatase 2A (PP2A) is convergently targeted by virulence factors from diverse pathogens, Li et al. demonstrate that PP2A is coopted by members of a modular family of effector proteins from a plant-pathogenic oomycete.

Pathogen protein modularity enables elaborate mimicry of a host phosphatase

Pathogens produce diverse effector proteins to manipulate host cellular processes. However, how functional diversity is generated in an effector repertoire is poorly understood. Many effectors in the devastating plant pathogen Phytophthora contain tandem repeats of the "(L)WY" motif, which are structurally conserved but variable in sequences. Here, we discovered a functional module formed by a specific (L)WY-LWY combination in multiple Phytophthora effectors, which efficiently recruits the serine/threonine protein phosphatase 2A (PP2A) core enzyme in plant hosts. Crystal structure of an effector-PP2A complex shows that the (L)WY-LWY module enables hijacking of the host PP2A core enzyme to form functional holoenzymes. While sharing the PP2A-interacting module at the amino terminus, these effectors possess divergent C-terminal LWY units and regulate distinct sets of phosphoproteins in the host. Our results highlight the appropriation of an essential host phosphatase through molecular mimicry by pathogens and diversification promoted by protein modularity in an effector repertoire.

Pathogen effectors: What do they do at plasmodesmata?

Plants perceive an assortment of external cues during their life cycle, including abiotic and biotic stressors. Biotic stress from a variety of pathogens, including viruses, oomycetes, fungi, and bacteria, is considered to be a substantial factor hindering plant growth and development. To hijack the host cell's defence machinery, plant pathogens have evolved sophisticated attack strategies mediated by numerous effector proteins. Several studies have indicated that plasmodesmata (PD), symplasmic pores that facilitate cell-to-cell communication between a cell and neighbouring cells, are one of the targets of pathogen effectors. However, in contrast to plant-pathogenic viruses, reports of fungal- and bacterial-encoded effectors that localize to and exploit PD are limited. Surprisingly, a recent study of PD-associated bacterial effectors has shown that a number of bacterial effectors undergo cell-to-cell movement via PD. Here we summarize and highlight recent advances in the study of PD-associated fungal/oomycete/bacterial effectors. We also discuss how pathogen effectors interfere with host defence mechanisms in the context of PD regulation.

Evolutionarily conserved bacterial effectors hijack abscisic acid signaling to induce an aqueous environment in the apoplast

High atmospheric humidity levels profoundly impact host-pathogen interactions in plants by enabling the establishment of an aqueous living space that benefits pathogens. The effectors HopM1 and AvrE1 of the bacterial pathogen Pseudomonas syringae have been shown to induce an aqueous apoplast under such conditions. However, the mechanisms by which this happens remain unknown. Here, we show that HopM1 and AvrE1 work redundantly to establish an aqueous living space by inducing a major reprogramming of the Arabidopsis thaliana transcriptome landscape. These effectors induce a strong abscisic acid (ABA) signature, which promotes stomatal closure, resulting in reduced leaf transpiration and water-soaking lesions. Furthermore, these effectors preferentially increase ABA accumulation in guard cells, which control stomatal aperture. Notably, a guard-cell-specific ABA transporter, ABCG40, is necessary for HopM1 induction of water-soaking lesions. This study provides molecular insights into a chain of events of stomatal manipulation that create an ideal microenvironment to facilitate infection.

AvrE1 and HopR1 from Pseudomonas syringae pv. actinidiae are additively required for full virulence on kiwifruit

Pseudomonas syringae pv. actinidiae ICMP 18884 biovar 3 (Psa3) produces necrotic lesions during infection of its kiwifruit host. Bacterial growth in planta and lesion formation are dependent upon a functional type III secretion system (T3S), which translocates multiple effector proteins into host cells. Associated with the T3S locus is the conserved effector locus (CEL), which has been characterized and shown to be essential for the full virulence in other P. syringae pathovars. Two effectors at the CEL, hopM1 and avrE1, as well as an avrE1-related non-CEL effector, hopR1, have been shown to be redundant in the model pathogen P. syringae pv. tomato DC3000 (Pto), a close relative of Psa. However, it is not known whether CEL-related effectors are required for Psa pathogenicity. The Psa3 allele of hopM1, and its associated chaperone, shcM, have diverged significantly from their orthologs in Pto. Furthermore, the CEL effector hopAA1-1, as well as a related non-CEL effector, hopAA1-2, have both been pseudogenized. We have shown that HopM1 does not contribute to Psa3 virulence due to a truncation in shcM, a truncation conserved in the Psa lineage, probably due to the need to evade HopM1-triggered immunity in kiwifruit. We characterized the virulence contribution of CEL and related effectors in Psa3 and found that only avrE1 and hopR1, additively, are required for in planta growth and lesion production. This is unlike the redundancy described for these effectors in Pto and indicates that these two Psa3 genes are key determinants essential for kiwifruit bacterial canker disease.

Wavelength Selection Method Based on Partial Least Square from Hyperspectral Unmanned Aerial Vehicle Orthomosaic of Irrigated Olive Orchards

Identifying and mapping irrigated areas is essential for a variety of applications such as agricultural planning and water resource management. Irrigated plots are mainly identified using supervised classification of multispectral images from satellite or manned aerial platforms. Recently, hyperspectral sensors on-board Unmanned Aerial Vehicles (UAV) have proven to be useful analytical tools in agriculture due to their high spectral resolution. However, few efforts have been made to identify which wavelengths could be applied to provide relevant information in specific scenarios. In this study, hyperspectral reflectance data from UAV were used to compare the performance of several wavelength selection methods based on Partial Least Square (PLS) regression with the purpose of discriminating two systems of irrigation commonly used in olive orchards. The tested PLS methods include filter methods (Loading Weights, Regression Coefficient and Variable Importance in Projection); Wrapper methods (Genetic Algorithm-PLS, Uninformative Variable Elimination-PLS, Backward Variable Elimination-PLS, Sub-window Permutation Analysis-PLS, Iterative Predictive Weighting-PLS, Regularized Elimination Procedure-PLS, Backward Interval-PLS, Forward Interval-PLS and Competitive Adaptive Reweighted Sampling-PLS); and an Embedded method (Sparse-PLS). In addition, two non-PLS based methods, Lasso and Boruta, were also used. Linear Discriminant Analysis and nonlinear K-Nearest Neighbors techniques were established for identification and assessment. The results indicate that wavelength selection methods, commonly used in other disciplines, provide utility in remote sensing for agronomical purposes, the identification of irrigation techniques being one such example. In addition to the aforementioned, these PLS and non-PLS based methods can play an important role in multivariate analysis, which can be used for subsequent model analysis. Of all the methods evaluated, Genetic Algorithm-PLS and Boruta eliminated nearly 90% of the original spectral wavelengths acquired from a hyperspectral sensor onboard a UAV while increasing the identification accuracy of the classification.

Oomycetes Used in Arabidopsis Research

Arabidopsis plants in their natural environment are susceptible to infection by oomycete pathogens, in particular to downy mildew and white rust diseases. These naturally occurring infectious agents have imposed evolutionary pressures on Arabidopsis populations and are therefore highly relevant for the study of host-pathogen co-evolution. In addition, the study of oomycete diseases, including infections caused by several Phytophthora species, has led to many scientific discoveries on Arabidopsis immunity and disease. Herein, we describe the major oomycete species used for experiments on Arabidopsis, and how these pathosystems have been used to provide significant insights into mechanistic and evolutionary aspects of plant-oomycete interactions. We also highlight understudied aspects of plant-oomycete interactions, as well as translational approaches, that can be productively addressed using the reference pathosystems described in this article.

Bastion3: a two-layer ensemble predictor of type III secreted effectors

MOTIVATION

Type III secreted effectors (T3SEs) can be injected into host cell cytoplasm via type III secretion systems (T3SSs) to modulate interactions between Gram-negative bacterial pathogens and their hosts. Due to their relevance in pathogen-host interactions, significant computational efforts have been put toward identification of T3SEs and these in turn have stimulated new T3SE discoveries. However, as T3SEs with new characteristics are discovered, these existing computational tools reveal important limitations: (i) most of the trained machine learning models are based on the N-terminus (or incorporating also the C-terminus) instead of the proteins' complete sequences, and (ii) the underlying models (trained with classic algorithms) employed only few features, most of which were extracted based on sequence-information alone. To achieve better T3SE prediction, we must identify more powerful, informative features and investigate how to effectively integrate these into a comprehensive model.

RESULTS

In this work, we present Bastion3, a two-layer ensemble predictor developed to accurately identify type III secreted effectors from protein sequence data. In contrast with existing methods that employ single models with few features, Bastion3 explores a wide range of features, from various types, trains single models based on these features and finally integrates these models through ensemble learning. We trained the models using a new gradient boosting machine, LightGBM and further boosted the models' performances through a novel genetic algorithm (GA) based two-step parameter optimization strategy. Our benchmark test demonstrates that Bastion3 achieves a much better performance compared to commonly used methods, with an ACC value of 0.959, F-value of 0.958, MCC value of 0.917 and AUC value of 0.956, which comprehensively outperformed all other toolkits by more than 5.6% in ACC value, 5.7% in F-value, 12.4% in MCC value and 5.8% in AUC value. Based on our proposed two-layer ensemble model, we further developed a user-friendly online toolkit, maximizing convenience for experimental scientists toward T3SE prediction. With its design to ease future discoveries of novel T3SEs and improved performance, Bastion3 is poised to become a widely used, state-of-the-art toolkit for T3SE prediction.

AVAILABILITY AND IMPLEMENTATION

http://bastion3.erc.monash.edu/.

CONTACT

selkrig@embl.de or wyztli@163.com or or trevor.lithgow@monash.edu.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.