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It is estimated that nearly five billion people do not have access to surgical care. Approximately 94% of individuals in low- and middle-income countries (LMICs) lack access to surgery in comparison to 14.9% in high-income countries (HICs). There are several urologic conditions requiring surgical intervention that are not treated because of the limited number of expert urologists in LMICs. Telesurgery is a concept that connects patients and surgeons in different locations through the use of a robotic surgery system. In this review, we explain the origins of telesurgery as well as the benefits and obstacles to its global implementation. Telesurgery can reduce travel times and the dangers associated with traveling for surgical care in LMICs. Additionally, telesurgery allows patients in LMICs to gain access to expert urologists while also providing effective training to upcoming surgeons. However, LMICs require substantial investment to improve digital infrastructure that will support urologic telesurgery. There will also be ethical, legal, and policy considerations that will need to be resolved for safe and equitable urologic telesurgery to occur. There have been multiple successful applications of urologic telesurgery, suggesting that the technology for this to become routine is already available. The time for international collaboration must begin now to reduce global disparities in access to urologic surgery.

Activating the expression of host susceptibility (S) genes is one of the strategies plant pathogens employed to promote infection of their host. Here, the authors show that targeted methylation at the TAL20 effector binding element of the cassava SWEET10a gene lead to resistance to Xanthomonas phaseoli.

Cassava mosaic disease is caused by geminiviruses and suppresses cassava yields throughout the tropics. Here, the authors show that mutations in MePOLD1, encoding DNA polymerase δ subunit 1, co-segregate with CMD2, the major source of genetic resistance for this disease.

Abstract Background Methods to accurately quantify disease severity are fundamental to plant pathogen interaction studies. Commonly used methods include visual scoring of disease symptoms, tracking pathogen growth in planta over time, and various assays that detect plant defense responses. Several image-based methods for phenotyping of plant disease symptoms have also been developed. Each of these methods has different advantages and limitations which should be carefully considered when choosing an approach and interpreting the results. Results In this paper, we developed two image analysis methods and tested their ability to quantify different aspects of disease lesions in the cassava-Xanthomonas pathosystem. The first method uses ImageJ, an open-source platform widely used in the biological sciences. The second method is a few-shot support vector machine learning tool that uses a classifier file trained with five representative infected leaf images for lesion recognition. Cassava leaves were syringe infiltrated with wildtype Xanthomonas, a Xanthomonas mutant with decreased virulence, and mock treatments. Digital images of infected leaves were captured overtime using a Raspberry Pi camera. The image analysis methods were analyzed and compared for the ability to segment the lesion from the background and accurately capture and measure differences between the treatment types. Conclusions Both image analysis methods presented in this paper allow for accurate segmentation of disease lesions from the non-infected plant. Specifically, at 4-, 6-, and 9-days post inoculation (DPI), both methods provided quantitative differences in disease symptoms between different treatment types. Thus, either method could be applied to extract information about disease severity. Strengths and weaknesses of each approach are discussed.

Environmental variability poses a major challenge to any field study. Researchers attempt to mitigate this challenge through replication. Thus, the ability to detect experimental signals is determined by the degree of replication and the amount of environmental variation, noise, within the experimental system. A major source of noise in field studies comes from the natural heterogeneity of soil properties which create microtreatments throughout the field. In addition, the variation within different soil properties is often nonrandomly distributed across a field. We explore this challenge through a sorghum field trial dataset with accompanying plant, microbiome, and soil property data. Diverse sorghum genotypes and two watering regimes were applied in a split-plot design. We describe a process of identifying, estimating, and controlling for the effects of spatially distributed soil properties on plant traits and microbial communities using minimal degrees of freedom. Importantly, this process provides a method with which sources of environmental variation in field data can be identified and adjusted, improving our ability to resolve effects of interest and to quantify subtle phenotypes.

Abstract Background This study aims to describe the short-term reactogenicity of the AS03-adjuvanted H5N1 vaccine expressed through adverse events (AEs) and quality-adjusted life-day (QALD) scores. The AEs are likely to be short-term and therefore the quality of life (QoL) questionnaire, SF-36v2, was administered daily to record changes over seven days. A more sensitive application of this instrument should allow for a better understanding of short-term tolerability of adjuvanted vaccines. Methods Participants (N = 50) received a 2-dose vaccination schedule. Solicited (collected daily: days 0 to 7 [post dose 1] and 21 to 28 [post dose 2]) and unsolicited (collected weekly until day 21) AEs were collected via diary cards. The QoL questionnaires were completed daily (days 0–6) and weekly (days 0, 6, 21, 27) after dose one. Questionnaire data were transformed into SF-6D scores to report QALDs. It was hypothesized post-hoc that the QALD and daily AEs scores should correlate if discrete QoL-changes were captured. Results Pain (92%) and muscle ache (66%) were the most commonly reported solicited local and general AEs respectively, neither increased in intensity nor in frequency after dose 2. No safety concerns were identified during the study. A correlation between the daily AEs and QALD scores existed (correlation coefficient, − 0.97 (p

AbstractResearch on a few model plant–pathogen systems has benefitted from years of tool and resource development. This is not the case for the vast majority of economically and nutritionally important plants, creating a crop improvement bottleneck. Cassava bacterial blight (CBB), caused by Xanthomonas axonopodismanihotisXamManihot esculentain vivoSMeSWEET10aMeSWEET10a-GFP

Abstract High‐throughput phenotyping (HTP) has emerged as one of the most exciting and rapidly evolving spaces within plant science. The successful application of phenotyping technologies will facilitate increases in agricultural productivity. High‐throughput phenotyping research is interdisciplinary and may involve biologists, engineers, mathematicians, physicists, and computer scientists. Here we describe the need for additional interest in HTP and offer a primer for those looking to engage with the HTP community. This is a high‐level overview of HTP technologies and analysis methodologies, which highlights recent progress in applying HTP to foundational research, identification of biotic and abiotic stress, breeding and crop improvement, and commercial and production processes. We also point to the opportunities and challenges associated with incorporating HTP across food production to sustainably meet the current and future global food supply requirements.

The zig-zag model of host-pathogen interaction describes the relative strength of defense response across a spectrum of pathogen-induced plant phenotypes. A stronger defense response results in increased resistance. Here, we investigate the strength of pathogen virulence during disease and place these findings in the context of the zig-zag model. Xanthomonas vasicola pv. holcicola (Xvh) causes sorghum bacterial leaf streak. Despite being widespread, this disease has not been described in detail at the molecular level. We divided diverse sorghum genotypes into three groups based on disease symptoms: water-soaked lesions, red lesions, and resistance. Bacterial growth assays confirmed that these three phenotypes represent a range of resistance and susceptibility. To simultaneously reveal defense and virulence responses across the spectrum of disease phenotypes, we performed dual RNA-seq on Xvh-infected sorghum. Consistent with the zig-zag model, the expression of plant defense-related genes was strongest in the resistance interaction. Surprisingly, bacterial virulence genes related to the type III secretion system (T3SS) and type III effectors (T3Es) were also most highly expressed in the resistance interaction. This expression pattern was observed at multiple time points within the sorghum-Xvh pathosystem. Further, a similar expression pattern was observed in Arabidopsis infected with Pseudomonas syringae for effector-triggered immunity via AvrRps4 but not AvrRpt2. Specific metabolites were able to repress the Xvh virulence response in vitro and in planta suggesting a possible signaling mechanism. Taken together, these findings reveal multiple permutations of the continually evolving host-pathogen arms race from the perspective of host defense and pathogen virulence responses.

Size‐based selectivity for metal ions based on highly preorganized five‐membered chelate rings is discussed. Metal ion complexation by the tetra‐pyridyl ligand EBIP ((8,9‐dihydro‐diquino[8,7‐b:7′,8′‐j][1,10]phenanthroline) is investigated, Formation constants (log K1) are reported for EBIP with 28 metal ions in 50 % CH3OH/H2O (v/v). The shift in size‐selectivity toward large metal ions and against small metal is demonstrated. Log K1 for the EBIP complexes shows a steady increase from La(III) to Lu(III), with a strong local maximum at Sm(III), and strong local minimum at Gd(III). This difference in log K1 between Sm(III) and Gd(III) for the tetra‐pyridyls is shown to depend largely on the level of preorganization of the ligand, being at a maximum for EBIP and a minimum for quaterpyridine. Log K1 for the Y(III) complex is invariably lower than for the similarly‐sized Ho(III) for all ligands that contain any nitrogen donors. Lower log K values for Y(III) are due to stabilization of the Ln(III) complexes with nitrogen donors by participation of the 5d orbitals, and to a lesser extent the 4 f orbitals, of the Ln(III) ions in M−L bonding. A DFT analysis of selectivity of tetra‐pyridyls for metal ions shows that Y(III) complexes should be less stable than similarly‐sized Ho(III) complexes. [ABSTRACT FROM AUTHOR]

High-throughput phenotyping has emerged as a powerful method for studying plant biology. Large image-based datasets are generated and analyzed with automated image analysis pipelines. A major challenge associated with these analyses is variation in image quality that can inadvertently bias results. Images are made up of tuples of data called pixels, which consist of R, G, and B values, arranged in a grid. Many factors, for example image brightness, can influence the quality of the image that is captured. These factors alter the values of the pixels within images and consequently can bias the data and downstream analyses. Here, we provide an automated method to adjust an image-based dataset so that brightness, contrast, and color profile is standardized. The correction method is a collection of linear models that adjusts pixel tuples based on a reference panel of colors. We apply this technique to a set of images taken in a high-throughput imaging facility and successfully detect variance within the image dataset. In this case, variation resulted from temperature-dependent light intensity throughout the experiment. Using this correction method, we were able to standardize images throughout the dataset, and we show that this correction enhanced our ability to accurately quantify morphological measurements within each image. We implement this technique in a high-throughput pipeline available with this paper, and it is also implemented in PlantCV.

Cotton bacterial blight (CBB), an important disease of (Gossypium hirsutum) in the early 20th century, had been controlled by resistant germplasm for over half a century. Recently, CBB re-emerged as an agronomic problem in the United States. Here, we report analysis of cotton variety planting statistics that indicate a steady increase in the percentage of susceptible cotton varieties grown each year since 2009. Phylogenetic analysis revealed that strains from the current outbreak cluster with race 18 Xanthomonas citri pv. malvacearum (Xcm) strains. Illumina based draft genomes were generated for thirteen Xcm isolates and analyzed along with 4 previously published Xcm genomes. These genomes encode 24 conserved and nine variable type three effectors. Strains in the race 18 clade contain 3 to 5 more effectors than other Xcm strains. SMRT sequencing of two geographically and temporally diverse strains of Xcm yielded circular chromosomes and accompanying plasmids. These genomes encode eight and thirteen distinct transcription activator-like effector genes. RNA-sequencing revealed 52 genes induced within two cotton cultivars by both tested Xcm strains. This gene list includes a homeologous pair of genes, with homology to the known susceptibility gene, MLO. In contrast, the two strains of Xcm induce different clade III SWEET sugar transporters. Subsequent genome wide analysis revealed patterns in the overall expression of homeologous gene pairs in cotton after inoculation by Xcm. These data reveal important insights into the Xcm-G. hirsutum disease complex and strategies for future development of resistant cultivars.

The gene-for-gene concept has historically been applied to describe a specific resistance interaction wherein single genes from the host and the pathogen dictate the outcome. These interactions have been observed across the plant kingdom and all known plant microbial pathogens. In recent years, this concept has been extended to susceptibility phenotypes in the context of transcription activator-like (TAL) effectors that target SWEET sugar transporters. However, because this interaction has only been observed in rice, it was not clear whether the gene-for-gene susceptibility was unique to that system. Here, we show, through a combined systematic analysis of the TAL effector complement of Xanthomonas axonopodis pv. manihotis and RNA sequencing to identify targets in cassava, that TAL20Xam668 specifically induces the sugar transporter MeSWEET10a to promote virulence. Designer TAL effectors (dTALE) complement TAL20Xam668 mutant phenotypes, demonstrating that MeSWEET10a is a susceptibility gene in cassava. Sucrose uptake–deficient X. axonopodis pv. manihotis bacteria do not lose virulence, indicating that sucrose may be cleaved extracellularly and taken up as hexoses into X. axonopodis pv. manihotis. Together, our data suggest that pathogen hijacking of plant nutrients is not unique to rice blight but also plays a role in bacterial blight of the dicot cassava.

[This corrects the article DOI: 10.1371/journal.pgen.1006049.].

Systemic acquired resistance, mediated by the Arabidopsis NPR1 gene and the rice NH1 gene, confers broad-spectrum immunity to diverse pathogens. NPR1 and NH1 interact with TGA transcription factors to activate downstream defense genes. Despite the importance of this defense response, the signaling components downstream of NPR1/NH1 and TGA proteins are poorly defined. Here we report the identification of a rice mutant, snim1, which suppresses NH1-mediated immunity and demonstrate that two genes encoding previously uncharacterized cysteine-rich-receptor-like kinases (CRK6 and CRK10), complement the snim1 mutant phenotype. Silencing of CRK6 and CRK10 genes individually in the parental genetic background recreates the snim1 phenotype. We identified a rice mutant in the Kitaake genetic background with a frameshift mutation in crk10; this mutant also displays a compromised immune response highlighting the important role of crk10. We also show that elevated levels of NH1 expression lead to enhanced CRK10 expression and that the rice TGA2.1 protein binds to the CRK10 promoter. These experiments demonstrate a requirement for CRKs in NH1-mediated immunity and establish a molecular link between NH1 and induction of CRK10 expression.

Bacterial spot disease of pepper and tomato is caused by four distinct Xanthomonas species and is a severely limiting factor on fruit yield in these crops. The genetic diversity and the type III effector repertoires of a large sampling of field strains for this disease have yet to be explored on a genomic scale, limiting our understanding of pathogen evolution in an agricultural setting. Genomes of sixty-seven Xanthomonas euvesicatoria (Xe), Xanthomonas perforans (Xp), and Xanthomonas gardneri (Xg) strains isolated from diseased pepper and tomato fields in the southeastern and midwestern United States were sequenced in order to determine the genetic diversity in field strains. Type III effector repertoires were computationally predicted for each strain, and multiple methods of constructing phylogenies were employed to understand better the genetic relationship of strains in the collection. A division in the Xp population was detected based on core genome phylogeny, supporting a model whereby the host-range expansion of Xp field strains on pepper is due, in part, to a loss of the effector AvrBsT. Xp-host compatibility was further studied with the observation that a double deletion mutant of AvrBsT and XopQ in Xp experiences a host gain for Nicotiana benthamiana. Extensive sampling of field strains and an improved understanding of effector content will aid in efforts to design disease resistance strategies targeted against highly conserved core effectors.

Wheat bran (WB) from Triticum aestivum has many beneficial effects on human health. To the best of our knowledge, very little has been published about its ability to prevent pathogenic bacterial adhesion in the intestine. Here, a WB extract was fractionated using different strategies, and the obtained fractions were tested in different in vitro methodologies to evaluate their interference in the attachment of enterotoxigenic Escherichia coli (ETEC) K88 to intestinal porcine epithelial cells (IPEC-J2) with the aim of identifying the putative anti-adhesive molecules. It was found that a proteinaceous compound in the >300-kDa fraction mediates the recognition of ETEC K88 to IPEC-J2. Further fractionation of the >300-kDa sample by size-exclusion chromatography showed several proteins below 90 kDa, suggesting that the target protein belongs to a high-molecular-weight (MW) multi-component protein complex. The identification of some relevant excised bands was performed by mass spectrometry (MS) and mostly revealed the presence of various protease inhibitors (PIs) of low MW: Serpin-Z2B, Class II chitinase, endogenous alpha-amylase/subtilisin inhibitor and alpha-amylase/trypsin inhibitor CM3. Furthermore, an incubation of the WB extract with ETEC K88 allowed for the identification of a 7S storage protein globulin of wheat, Globulin 3 of 66 kDa, which may be one of the most firmly attached WB proteins to ETEC K88 cells. Further studies should be performed to gain an understanding of the molecular recognition of the blocking process that takes place. All gathered information can eventually pave the way for the development of novel anti-adhesion therapeutic agents to prevent bacterial pathogenesis.

Rice NH1 (NPR1 homolog 1) is a key mediator of innate immunity. In both plants and animals, the innate immune response is often accompanied by rapid cell death at the site of pathogen infection. Over-expression of NH1 in rice results in resistance to the bacterial pathogen, Xanthomonas oryzae pv. oryzae (Xoo), constitutive expression of defense related genes and enhanced benzothiadiazole (BTH)- mediated cell death. Here we describe a forward genetic screen that identified a suppressor of NH1-mediated lesion formation and resistance, snl6. Comparative genome hybridization and fine mapping rapidly identified the genomic location of the Snl6 gene. Snl6 is a member of the cinnamoyl-CoA reductase (CCR)-like gene family. We show that Snl6 is required for NH1-mediated resistance to Xoo. Further, we show that Snl6 is required for pathogenesis-related gene expression. In contrast to previously described CCR family members, disruption of Snl6 does not result in an obvious morphologic phenotype. Snl6 mutants have reduced lignin content and increased sugar extractability, an important trait for the production of cellulosic biofuels. These results suggest the existence of a conserved group of CCR-like genes involved in the defense response, and with the potential to alter lignin content without affecting development.