Concordance between SIVA, IVAN, and VAMPIRE software tools for semi-automated analysis of retinal vessel caliber

We aimed to compare measurements from three of the most widely used software packages in the literature and to generate conversion algorithms for measurement of the central retinal artery equivalent (CRAE) and central retinal vein equivalent (CRVE) between SIVA and IVAN and between SIVA and VAMPIRE. We analyzed 223 retinal photographs from 133 human participants using both SIVA, VAMPIRE and IVAN independently for computing CRAE and CRVE. Agreement between measurements was assessed using Bland–Altman plots and intra-class correlation coefficients. A conversion algorithm between measurements was carried out using linear regression, and validated using bootstrapping and root-mean-square error. The agreement between VAMPIRE and IVAN was poor to moderate: The mean difference was 20.2 µm (95% limits of agreement, LOA, −12.2–52.6 µm) for CRAE and 21.0 µm (95% LOA, −17.5–59.5 µm) for CRVE. The agreement between VAMPIRE and SIVA was also poor to moderate: the mean difference was 36.6 µm (95% LOA, −12.8–60.4 µm) for CRAE, and 40.3 µm (95% LOA, 5.6–75.0 µm) for CRVE. The agreement between IVAN and SIVA was good to excellent: the mean difference was 16.4 µm (95% LOA, −4.25–37.0 µm) for CRAE, and 19.3 µm (95% LOA, 0.09–38.6 µm) for CRVE. We propose an algorithm converting IVAN and VAMPIRE measurements into SIVA-estimated measurements, which could be used to homogenize sets of vessel measurements obtained with different software packages

A bacterial cysteine protease effector protein interferes with photosynthesis to suppress plant innate immune responses

The bacterial pathogen Pseudomonas syringae pv tomato DC3000 suppresses plant innate immunity with effector proteins injected by a type III secretion system (T3SS). The cysteine protease effector HopN1, which reduces the ability of DC3000 to elicit programmed cell death in non-host tobacco, was found to also suppress the production of defence-associated reactive oxygen species (ROS) and callose when delivered by Pseudomonas fluorescens heterologously expressing a P. syringae T3SS. Purified His 6 -tagged HopN1 was used to identify tomato PsbQ, a member of the oxygen evolving complex of photosystem II (PSII), as an interacting protein. HopN1 localized to chloroplasts and both degraded PsbQ and inhibited PSII activity in chloroplast preparations, whereas a HopN1 D299A non-catalytic mutant lost these abilities. Gene silencing of NtPsbQ in tobacco compromised ROS production and programmed cell death

Experimental Evolution of a Plant Pathogen into a Legume Symbiont

Following acquisition of a rhizobial symbiotic plasmid, adaptive mutations in the virulence pathway allowed pathogenic Ralstonia solanacearum to evolve into a legume symbiont under plant selection

Bacteria establish an aqueous living space in plants crucial for virulence

High humidity has a strong influence on the development of numerous diseases affecting the above-ground parts of plants (the phyllosphere) in crop fields and natural ecosystems, but the molecular basis of this humidity effect is not understood. Previous studies have emphasized immune suppression as a key step in bacterial pathogenesis. Here we show that humidity-dependent, pathogen-driven establishment of an aqueous intercellular space (apoplast) is another important step in bacterial infection of the phyllosphere. Bacterial effectors, such as Pseudomonas syringae HopM1, induce establishment of the aqueous apoplast and are sufficient to transform non-pathogenic P. syringae strains into virulent pathogens in immunodeficient Arabidopsis thaliana under high humidity. Arabidopsis quadruple mutants simultaneously defective in a host target (AtMIN7) of HopM1 and in pattern-triggered immunity could not only be used to reconstitute the basic features of bacterial infection, but also exhibited humidity-dependent dyshomeostasis of the endophytic commensal bacterial community in the phyllosphere. These results highlight a new conceptual framework for understanding diverse phyllosphere–bacterial interactions

Meta-analytic approach to the accurate prediction of secreted virulence effectors in gram-negative bacteria

<p>Abstract</p> <p>Background</p> <p>Many pathogens use a type III secretion system to translocate virulence proteins (called effectors) in order to adapt to the host environment. To date, many prediction tools for effector identification have been developed. However, these tools are insufficiently accurate for producing a list of putative effectors that can be applied directly for labor-intensive experimental verification. This also suggests that important features of effectors have yet to be fully characterized.</p> <p>Results</p> <p>In this study, we have constructed an accurate approach to predicting secreted virulence effectors from Gram-negative bacteria. This consists of a support vector machine-based discriminant analysis followed by a simple criteria-based filtering. The accuracy was assessed by estimating the average number of true positives in the top-20 ranking in the genome-wide screening. In the validation, 10 sets of 20 training and 20 testing examples were randomly selected from 40 known effectors of <it>Salmonella enterica </it>serovar Typhimurium LT2. On average, the SVM portion of our system predicted 9.7 true positives from 20 testing examples in the top-20 of the prediction. Removal of the N-terminal instability, codon adaptation index and ProtParam indices decreased the score to 7.6, 8.9 and 7.9, respectively. These discrimination features suggested that the following characteristics of effectors had been uncovered: unstable N-terminus, non-optimal codon usage, hydrophilic, and less aliphathic. The secondary filtering process represented by coexpression analysis and domain distribution analysis further refined the average true positive counts to 12.3. We further confirmed that our system can correctly predict known effectors of <it>P. syringae </it>DC3000, strongly indicating its feasibility.</p> <p>Conclusions</p> <p>We have successfully developed an accurate prediction system for screening effectors on a genome-wide scale. We confirmed the accuracy of our system by external validation using known effectors of <it>Salmonella </it>and obtained the accurate list of putative effectors of the organism. The level of accuracy was sufficient to yield candidates for gene-directed experimental verification. Furthermore, new features of effectors were revealed: non-optimal codon usage and instability of the N-terminal region. From these findings, a new working hypothesis is proposed regarding mechanisms controlling the translocation of virulence effectors and determining the substrate specificity encoded in the secretion system.</p

Roadmap for future research on plant pathogen effectors

Bacterial and eukaryotic plant pathogens deliver effector proteins into plant cells to promote pathogenesis. Bacterial pathogens containing type III protein secretion systems are known to inject many of these effectors into plant cells. More recently, oomycete pathogens have been shown to possess a large family of effectors containing the RXLR motif, and many effectors are also being discovered in fungal pathogens. Although effector activities are largely unknown, at least a subset suppress plant immunity. A plethora of new plant pathogen genomes that will soon be available thanks to next-generation sequencing technologies will allow the identification of many more effectors. This article summarizes the key approaches used to identify plant pathogen effectors, many of which will continue to be useful for future effector discovery. Thus, it can be viewed as a ‘roadmap’ for effector and effector target identification. Because effectors can be used as tools to elucidate components of innate immunity, advances in our understanding of effectors and their targets should lead to improvements in agriculture