Revealing the inventory of type III effectors in Pantoea agglomerans gall-forming pathovars using draft genome sequences and a machine-learning approach

Interference of AHL signal production in the phytophatogen Pantoea agglomerans as a sustainable biological strategy to reduce its virulence

Pantoea agglomerans is considered one of the most ubiquitous and versatile organisms that include strains that induce diseases in various crops and occasionally cause opportunistic infections in humans. To develop effective strategies to mitigate its impact on plant health and agricultural productivity, a comprehensive investigation is crucial for better understanding its pathogenicity. One proposed eco-friendly approach involves the enzymatic degradation of quorum sensing (QS) signal molecules like N-acylhomoserine lactones (AHLs), known as quorum quenching (QQ), offering potential treatment for such bacterial diseases. In this study the production of C4 and 3-oxo-C6HSL was identified in the plant pathogenic P. agglomerans CFBP 11141 and correlated to enzymatic activities such as amylase and acid phosphatase. Moreover, the heterologous expression of a QQ enzyme in the pathogen resulted in lack of AHLs production and the attenuation of the virulence by mean of drastically reduction of soft rot disease in carrots and cherry tomatoes. Additionally, the interference with the QS systems of P. agglomerans CFBP 11141 by two the plant growth-promoting and AHL-degrading bacteria (PGP-QQ) Pseudomonas segetis P6 and Bacillus toyonensis AA1EC1 was evaluated as a potential biocontrol approach for the first time. P. segetis P6 and B. toyonensis AA1EC1 demonstrated effectiveness in diminishing soft rot symptoms induced by P. agglomerans CFBP 11141 in both carrots and cherry tomatoes. Furthermore, the virulence of pathogen notably decreased when co-cultured with strain AA1EC1 on tomato plants.

TSE-ARF: An adaptive prediction method of effectors across secretion system types

Bacterial effector proteins are secreted by a variety of protein secretion systems and play an important role in the interaction between the host and pathogenic bacteria. Therefore, it is important to find a fast and inexpensive method to discover bacterial effectors. In this study, we propose a multi-type secretion effector adaptive random forest (TSE-ARF) to adaptively identify secretion effectors across T1SE-T4SE and T6SE based only on protein sequences. First, we proposed two new feature descriptors by considering some characteristic protein information and fused them with some universal features to form a 290-dimensional feature vector with good versatility. Then, the TSE-ARF model was used to make classification predictions by parameter adaptation of different secretion effectors integrating Shuffled Frog Leaping Algorithm and random forest. The perfect performance in TSE-ARF under different data sets and settings shows its considerable generalization ability, with which more candidate effectors were screened in the whole genome. Source code is available at https://github.com/AIMOVE/TSE-ARF.

Pseudomonas syringae coffee blight is associated with the horizontal transfer of plasmid-encoded type III effectors

The emergence of new pathogens is an ongoing threat to human health and agriculture. While zoonotic spillovers received considerable attention, the emergence of crop diseases is less well studied. Here, we identify genomic factors associated with the emergence of Pseudomonas syringae bacterial blight of coffee. Fifty-three P. syringae strains from diseased Brazilian coffee plants were sequenced. Comparative and evolutionary analyses were used to identify loci associated with coffee blight. Growth and symptomology assays were performed to validate the findings. Coffee isolates clustered in three lineages, including primary phylogroups PG3 and PG4, and secondary phylogroup PG11. Genome-wide association study of the primary PG strains identified 37 loci, including five effectors, most of which were encoded on a plasmid unique to the PG3 and PG4 coffee strains. Evolutionary analyses support the emergence of coffee blight in PG4 when the coffee-associated plasmid and associated effectors derived from a divergent plasmid carried by strains associated with other hosts. This plasmid was only recently transferred into PG3. Natural diversity and CRISPR-Cas9 plasmid curing were used to show that strains with the coffee-associated plasmid grow to higher densities and cause more severe disease symptoms in coffee. This work identifies possible evolutionary mechanisms underlying the emergence of a new lineage of coffee pathogens.

Features and algorithms: facilitating investigation of secreted effectors in Gram-negative bacteria

Gram-negative bacteria deliver effector proteins through type III, IV, or VI secretion systems (T3SSs, T4SSs, and T6SSs) into host cells, causing infections and diseases. In general, effector proteins for each of these distinct secretion systems lack homology and are difficult to identify. Sequence analysis has disclosed many common features, helping us to understand the evolution, function, and secretion mechanisms of the effectors. In combination with various algorithms, the known common features have facilitated accurate prediction of new effectors. Ensemblers or integrated pipelines achieve a better prediction of performance, which combines multiple computational models or modules with multidimensional features. Natural language processing (NLP) models also show the merits, which could enable discovery of novel features and, in turn, facilitate more precise effector prediction, extending our knowledge about each secretion mechanism.

Comparative sequence analysis of pPATH pathogenicity plasmids in Pantoea agglomerans gall-forming bacteria

Acquisition of the pathogenicity plasmid pPATH that encodes a type III secretion system (T3SS) and effectors (T3Es) has likely led to the transition of a non-pathogenic bacterium into the tumorigenic pathogen Pantoea agglomerans. P. agglomerans pv. gypsophilae (Pag) forms galls on gypsophila (Gypsophila paniculata) and triggers immunity on sugar beet (Beta vulgaris), while P. agglomerans pv. betae (Pab) causes galls on both gypsophila and sugar beet. Draft sequences of the Pag and Pab genomes were previously generated using the MiSeq Illumina technology and used to determine partial T3E inventories of Pab and Pag. Here, we fully assembled the Pab and Pag genomes following sequencing with PacBio technology and carried out a comparative sequence analysis of the Pab and Pag pathogenicity plasmids pPATHpag and pPATHpab. Assembly of Pab and Pag genomes revealed a ~4 Mbp chromosome with a 55% GC content, and three and four plasmids in Pab and Pag, respectively. pPATHpag and pPATHpab share 97% identity within a 74% coverage, and a similar GC content (51%); they are ~156 kb and ~131 kb in size and consist of 198 and 155 coding sequences (CDSs), respectively. In both plasmids, we confirmed the presence of highly similar gene clusters encoding a T3SS, as well as auxin and cytokinins biosynthetic enzymes. Three putative novel T3Es were identified in Pab and one in Pag. Among T3SS-associated proteins encoded by Pag and Pab, we identified two novel chaperons of the ShcV and CesT families that are present in both pathovars with high similarity. We also identified insertion sequences (ISs) and transposons (Tns) that may have contributed to the evolution of the two pathovars. These include seven shared IS elements, and three ISs and two transposons unique to Pab. Finally, comparative sequence analysis revealed plasmid regions and CDSs that are present only in pPATHpab or in pPATHpag. The high similarity and common features of the pPATH plasmids support the hypothesis that the two strains recently evolved into host-specific pathogens.

Complete genome sequence of an Israeli isolate of Xanthomonas hortorum pv. pelargonii strain 305 and novel type III effectors identified in Xanthomonas

Xanthomonas hortorum pv. pelargonii is the causative agent of bacterial blight in geranium ornamental plants, the most threatening bacterial disease of this plant worldwide. Xanthomonas fragariae is the causative agent of angular leaf spot in strawberries, where it poses a significant threat to the strawberry industry. Both pathogens rely on the type III secretion system and the translocation of effector proteins into the plant cells for their pathogenicity. Effectidor is a freely available web server we have previously developed for the prediction of type III effectors in bacterial genomes. Following a complete genome sequencing and assembly of an Israeli isolate of Xanthomonas hortorum pv. pelargonii - strain 305, we used Effectidor to predict effector encoding genes both in this newly sequenced genome, and in X. fragariae strain Fap21, and validated its predictions experimentally. Four and two genes in X. hortorum and X. fragariae, respectively, contained an active translocation signal that allowed the translocation of the reporter AvrBs2 that induced the hypersensitive response in pepper leaves, and are thus considered validated novel effectors. These newly validated effectors are XopBB, XopBC, XopBD, XopBE, XopBF, and XopBG.

Natural language processing approach to model the secretion signal of type III effectors

Type III effectors are proteins injected by Gram-negative bacteria into eukaryotic hosts. In many plant and animal pathogens, these effectors manipulate host cellular processes to the benefit of the bacteria. Type III effectors are secreted by a type III secretion system that must "classify" each bacterial protein into one of two categories, either the protein should be translocated or not. It was previously shown that type III effectors have a secretion signal within their N-terminus, however, despite numerous efforts, the exact biochemical identity of this secretion signal is generally unknown. Computational characterization of the secretion signal is important for the identification of novel effectors and for better understanding the molecular translocation mechanism. In this work we developed novel machine-learning algorithms for characterizing the secretion signal in both plant and animal pathogens. Specifically, we represented each protein as a vector in high-dimensional space using Facebook's protein language model. Classification algorithms were next used to separate effectors from non-effector proteins. We subsequently curated a benchmark dataset of hundreds of effectors and thousands of non-effector proteins. We showed that on this curated dataset, our novel approach yielded substantially better classification accuracy compared to previously developed methodologies. We have also tested the hypothesis that plant and animal pathogen effectors are characterized by different secretion signals. Finally, we integrated the novel approach in Effectidor, a web-server for predicting type III effector proteins, leading to a more accurate classification of effectors from non-effectors.

Opposite Sides of Pantoea agglomerans and Its Associated Commercial Outlook

Multifaceted microorganisms such as the bacterium Pantoea colonize a wide range of habitats and can exhibit both beneficial and harmful behaviors, which provide new insights into microbial ecology. In the agricultural context, several strains of Pantoea spp. can promote plant growth through direct or indirect mechanisms. Members of this genus contribute to plant growth mainly by increasing the supply of nitrogen, solubilizing ammonia and inorganic phosphate, and producing phytohormones (e.g., auxins). Several other studies have shown the potential of strains of Pantoea spp. to induce systemic resistance and protection against pests and pathogenic microorganisms in cultivated plants. Strains of the species Pantoea agglomerans deserve attention as a pest and phytopathogen control agent. Several of them also possess a biotechnological potential for therapeutic purposes (e.g., immunomodulators) and are implicated in human infections. Thus, the differentiation between the harmful and beneficial strains of P. agglomerans is mandatory to apply this bacterium safely as a biofertilizer or biocontroller. This review specifically evaluates the potential of the strain-associated features of P. agglomerans for bioprospecting and agricultural applications through its biological versatility as well as clarifying its potential animal and human health risks from a genomic point of view.

Beneficial Effect and Potential Risk of Pantoea on Rice Production

Bacteria from the genus Pantoea have been reported to be widely distributed in rice paddy environments with contradictory roles. Some strains promoted rice growth and protected rice from pathogen infection or abiotic stress, but other strain exhibited virulence to rice, even causing severe rice disease. In order to effectively utilize Pantoea in rice production, this paper analyzed the mechanisms underlying beneficial and harmful effects of Pantoea on rice growth. The beneficial effect of Pantoea on rice plants includes growth promotion, abiotic alleviation and disease inhibition. The growth promotion may be mainly attributed to nitrogen-fixation, phosphate solubilization, plant physiological change, the biosynthesis of siderophores, exopolysaccharides, 1-aminocyclopropane-1-carboxylic acid deaminase and phytohormones, including cytokinin, indole-3-acetic acid (IAA), auxins, abscisic acid and gibberellic acid, while the disease inhibition may be mainly due to the induced resistance, nutrient and spatial competition, as well as the production of a variety of antibiotics. The pathogenic mechanism of Pantoea can be mainly attributed to bacterial motility, production of phytohormones such as IAA, quorum sensing-related signal molecules and a series of cell wall-degrading enzymes, while the pathogenicity-related genes of Pantoea include genes encoding plasmids, such as the pPATH plasmid, the hypersensitive response and pathogenicity system, as well as various types of secretion systems, such as T3SS and T6SS. In addition, the existing scientific problems in this field were discussed and future research prospects were proposed.

Biocontrol of Candida albicans by Antagonistic Microorganisms and Bioactive Compounds

Candida albicans is an endogenous opportunistic pathogenic fungus that is harmless when the host system remains stable. However, C. albicans could seriously threaten human life and health when the body’s immune function declines or the normal flora is out of balance. Due to the increasing resistance of candidiasis to existing drugs, it is important to find new strategies to help treat this type of systemic fungal disease. Biological control is considered as a promising strategy which is more friendly and safer. In this review, we compare the bacteriostatic behavior of different antagonistic microorganisms (bacteria and fungi) against C. albicans. In addition, natural products with unique structures have attracted researchers’ attention. Therefore, the bioactive nature products produced by different microorganisms and their possible inhibitory mechanisms are also reviewed. The application of biological control strategies and the discovery of new compounds with antifungal activity will reduce the resistance of C. albicans, thereby promoting the development of novel diverse antifungal drugs.

Effectidor: an automated machine-learning-based web server for the prediction of type-III secretion system effectors

MOTIVATION

Type-III secretion systems are utilized by many Gram-negative bacteria to inject type-3 effectors (T3Es) to eukaryotic cells. These effectors manipulate host processes for the benefit of the bacteria and thus promote disease. They can also function as host-specificity determinants through their recognition as avirulence proteins that elicit immune response. Identifying the full effector repertoire within a set of bacterial genomes is of great importance to develop appropriate treatments against the associated pathogens.

RESULTS

We present Effectidor, a user-friendly web server that harnesses several machine-learning techniques to predict T3Es within bacterial genomes. We compared the performance of Effectidor to other available tools for the same task on three pathogenic bacteria. Effectidor outperformed these tools in terms of classification accuracy (area under the precision-recall curve above 0.98 in all cases).

AVAILABILITY AND IMPLEMENTATION

Effectidor is available at: https://effectidor.tau.ac.il, and the source code is available at: https://github.com/naamawagner/Effectidor.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Recent Advancements in Tracking Bacterial Effector Protein Translocation

Bacteria-host interactions are characterized by the delivery of bacterial virulence factors, i.e., effectors, into host cells where they counteract host immunity and exploit host responses allowing bacterial survival and spreading. These effectors are translocated into host cells by means of dedicated secretion systems such as the type 3 secretion system (T3SS). A comprehensive understanding of effector translocation in a spatio-temporal manner is of critical importance to gain insights into an effector’s mode of action. Various approaches have been developed to understand timing and order of effector translocation, quantities of translocated effectors and their subcellular localization upon translocation into host cells. Recently, the existing toolset has been expanded by newly developed state-of-the art methods to monitor bacterial effector translocation and dynamics. In this review, we elaborate on reported methods and discuss recent advances and shortcomings in this area of tracking bacterial effector translocation.

Synergistic interaction between the type III secretion system of the endophytic bacterium Pantoea agglomerans DAPP-PG 734 and the virulence of the causal agent of olive knot Pseudomonas savastanoi pv. savastanoi DAPP-PG 722

The endophytic bacterium Pantoea agglomerans DAPP-PG 734 was previously isolated from olive knots caused by infection with Pseudomonas savastanoi pv. savastanoi DAPP-PG 722. Whole-genome analysis of this P. agglomerans strain revealed the presence of a Hypersensitive response and pathogenicity (Hrp) type III secretion system (T3SS). To assess the role of the P. agglomerans T3SS in the interaction with P. savastanoi pv. savastanoi, we generated independent knockout mutants in three Hrp genes of the P. agglomerans DAPP-PG 734 T3SS (hrpJ, hrpN, and hrpY). In contrast to the wildtype control, all three mutants failed to cause a hypersensitive response when infiltrated in tobacco leaves, suggesting that P. agglomerans T3SS is functional and injects effector proteins in plant cells. In contrast to P. savastanoi pv. savastanoi DAPP-PG 722, the wildtype strain P. agglomerans DAPP-PG 734 and its Hrp T3SS mutants did not cause olive knot disease in 1-year-old olive plants. Coinoculation of P. savastanoi pv. savastanoi with P. agglomerans wildtype strains did not significantly change the knot size, while the DAPP-PG 734 hrpY mutant induced a significant decrease in knot size, which could be complemented by providing hrpY on a plasmid. By epifluorescence microscopy and confocal laser scanning microscopy, we found that the localization patterns in knots were nonoverlapping for P. savastanoi pv. savastanoi and P. agglomerans when coinoculated. Our results suggest that suppression of olive plant defences mediated by the Hrp T3SS of P. agglomerans DAPP-PG 734 positively impacts the virulence of P. savastanoi pv. savastanoi DAPP-PG 722.

Forest and Trees: Exploring Bacterial Virulence with Genome-wide Association Studies and Machine Learning

The advent of inexpensive and rapid sequencing technologies has allowed bacterial whole-genome sequences to be generated at an unprecedented pace. This wealth of information has revealed an unanticipated degree of strain-to-strain genetic diversity within many bacterial species. Awareness of this genetic heterogeneity has corresponded with a greater appreciation of intraspecies variation in virulence. A number of comparative genomic strategies have been developed to link these genotypic and pathogenic differences with the aim of discovering novel virulence factors. Here, we review recent advances in comparative genomic approaches to identify bacterial virulence determinants, with a focus on genome-wide association studies and machine learning.

Type III secretion system effectors form robust and flexible intracellular virulence networks

Infections with many Gram-negative pathogens, including Escherichia coli, Salmonella, Shigella, and Yersinia, rely on type III secretion system (T3SS) effectors. We hypothesized that while hijacking processes within mammalian cells, the effectors operate as a robust network that can tolerate substantial contractions. This was tested in vivo using the mouse pathogen Citrobacter rodentium (encoding 31 effectors). Sequential gene deletions showed that effector essentiality for infection was context dependent and that the network could tolerate 60% contraction while maintaining pathogenicity. Despite inducing very different colonic cytokine profiles (e.g., interleukin-22, interleukin-17, interferon-γ, or granulocyte-macrophage colony-stimulating factor), different networks induced protective immunity. Using data from >100 distinct mutant combinations, we built and trained a machine learning model able to predict colonization outcomes, which were confirmed experimentally. Furthermore, reproducing the human-restricted enteropathogenic E. coli effector repertoire in C. rodentium was not sufficient for efficient colonization, which implicates effector networks in host adaptation. These results unveil the extreme robustness of both T3SS effector networks and host responses.

Bacterial nucleomodulins: A coevolutionary adaptation to the eukaryotic command center

Through long-term interactions with their hosts, bacterial pathogens have evolved unique arsenals of effector proteins that interact with specific host targets and reprogram the host cell into a permissive niche for pathogen proliferation. The targeting of effector proteins into the host cell nucleus for modulation of nuclear processes is an emerging theme among bacterial pathogens. These unique pathogen effector proteins have been termed in recent years as "nucleomodulins." The first nucleomodulins were discovered in the phytopathogens Agrobacterium and Xanthomonas, where their nucleomodulins functioned as eukaryotic transcription factors or integrated themselves into host cell DNA to promote tumor induction, respectively. Numerous nucleomodulins were recently identified in mammalian pathogens. Bacterial nucleomodulins are an emerging family of pathogen effector proteins that evolved to target specific components of the host cell command center through various mechanisms. These mechanisms include: chromatin dynamics, histone modification, DNA methylation, RNA splicing, DNA replication, cell cycle, and cell signaling pathways. Nucleomodulins may induce short- or long-term epigenetic modifications of the host cell. In this extensive review, we discuss the current knowledge of nucleomodulins from plant and mammalian pathogens. While many nucleomodulins are already identified, continued research is instrumental in understanding their mechanisms of action and the role they play during the progression of pathogenesis. The continued study of nucleomodulins will enhance our knowledge of their effects on nuclear chromatin dynamics, protein homeostasis, transcriptional landscapes, and the overall host cell epigenome.

Show me your secret(ed) weapons: a multifaceted approach reveals a wide arsenal of type III-secreted effectors in the cucurbit pathogenic bacterium Acidovorax citrulli and novel effectors in the Acidovorax genus

The cucurbit pathogenic bacterium Acidovorax citrulli requires a functional type III secretion system (T3SS) for pathogenicity. In this bacterium, as with Xanthomonas and Ralstonia spp., an AraC-type transcriptional regulator, HrpX, regulates expression of genes encoding T3SS components and type III-secreted effectors (T3Es). The annotation of a sequenced A. citrulli strain revealed 11 T3E genes. Assuming that this could be an underestimation, we aimed to uncover the T3E arsenal of the A. citrulli model strain, M6. Thorough sequence analysis revealed 51 M6 genes whose products are similar to known T3Es. Furthermore, we combined machine learning and transcriptomics to identify novel T3Es. The machine-learning approach ranked all A. citrulli M6 genes according to their propensity to encode T3Es. RNA-Seq revealed differential gene expression between wild-type M6 and a mutant defective in HrpX: 159 and 28 genes showed significantly reduced and increased expression in the mutant relative to wild-type M6, respectively. Data combined from these approaches led to the identification of seven novel T3E candidates that were further validated using a T3SS-dependent translocation assay. These T3E genes encode hypothetical proteins that seem to be restricted to plant pathogenic Acidovorax species. Transient expression in Nicotiana benthamiana revealed that two of these T3Es localize to the cell nucleus and one interacts with the endoplasmic reticulum. This study places A. citrulli among the 'richest' bacterial pathogens in terms of T3E cargo. It also revealed novel T3Es that appear to be involved in the pathoadaptive evolution of plant pathogenic Acidovorax species.

Two Pantoea agglomerans type III effectors can transform nonpathogenic and phytopathogenic bacteria into host-specific gall-forming pathogens

Pantoea agglomerans (Pa), a widespread commensal bacterium, has evolved into a host-specific gall-forming pathogen on gypsophila and beet by acquiring a plasmid harbouring a type III secretion system (T3SS) and effectors (T3Es). Pantoea agglomerans pv. gypsophilae (Pag) elicits galls on gypsophila and a hypersensitive response on beet, whereas P. agglomerans pv. betae (Pab) elicits galls on beet and gypsophila. HsvG and HsvB are two paralogous T3Es present in both pathovars and act as host-specific transcription activators on gypsophila and beet, respectively. PthG and PseB are major T3Es that contribute to gall development of Pag and Pab, respectively. To establish the minimal combinations of T3Es that are sufficient to elicit gall symptoms, strains of the nonpathogenic bacteria Pseudomonas fluorescens 55, Pa 3-1, Pa 98 and Escherichia coli, transformed with pHIR11 harbouring a T3SS, and the phytopathogenic bacteria Erwinia amylovora, Dickeya solani and Xanthomonas campestris pv. campestris were transformed with the T3Es hsvG, hsvB, pthG and pseB, either individually or in pairs, and used to infect gypsophila and beet. Strikingly, all the tested nonpathogenic and phytopathogenic bacterial strains harbouring hsvG and pthG incited galls on gypsophila, whereas strains harbouring hsvB and pseB, with the exception of E. coli, incited galls on beet.

Modeling for Survival of Clostridium perfringens in Saeng-sik, a Powdered Ready-to-Eat Food with Low Water Activity

HIGHLIGHTS

We developed a mathematical model to predict the survival of C. perfringens in food. C. perfringens vegetative cells and spores were inoculated into dried powder food. The a_w of saeng-sik was below 0.1. Weibull and Davey models can successfully describe the survival of C. perfringens. The developed model can be applied to samples with different microbial communities.

Assessing the Ability of Salmonella enterica to Translocate Type III Effectors Into Plant Cells

Salmonella enterica serovar Typhimurium, a human enteric pathogen, has the ability to multiply and survive endophytically in plants. Genes encoding the type III secretion system (T3SS) or its effectors (T3Es) may contribute to its colonization. Two reporter plasmids for T3E translocation into plant cells that are based on hypersensitive response domains of avirulence proteins from the Pantoea agglomerans-beet and Xanthomonas euvesicatoria-pepper pathosystems were employed in this study to investigate the role of T3Es in the interaction of Salmonella ser. Typhimurium 14028 with plants. The T3Es of Salmonella ser. Typhimurium, SipB and SifA, which are translocated into animal cells, could not be delivered by Salmonella ser. Typhimurium into cells of beet roots or pepper leaves. In contrast, these effectors were translocated into plant cells by the phytopathogenic bacteria P. agglomerans pv. betae, Erwinia amylovora, and X. euvesicatoria. Similarly, HsvG, a T3E of P. agglomerans pv. gypsophilae, and XopAU of X. euvesicatoria could be translocated into beet roots and pepper leaves, respectively, by the plant pathogens but not by Salmonella ser. Typhimurium. Mutations in Salmonella ser. Typhimurium T3SS genes invA, ssaV, sipB, or sifA, did not affect its endophytic colonization of lettuce leaves, supporting the notion that S. enterica cannot translocate T3Es into plant cells.