The paradigms of legume–rhizobium symbiosis are derived primarily from conserved features of Inverted-Repeat Lacking Clade (IRLC) legumes and closely related species. The Dalbergioids diverged from the IRLC early in legume evolution and possess unique symbiotic features but few genetically tractable models. The small, diploid dalbergioid Aeschynomene americana (American jointvetch) has promise as a genetic model for Dalbergioid-rhizobia symbiosis, yet only a few studies have examined its symbiotic properties. We examined the symbiont range of A. americana from central Florida and characterized a native A. americana nodule isolate, Bradyrhizobium sp. USDA3516. We find that A. americana forms effective symbioses with Bradyrhizobium sp. USDA3516, which is closely related to Thai A. americana symbiont Bradyrhizobium sp DOA9, and with symbionts from the dalbergioids stylo and peanut. Interestingly, several strains that effectively nodulated A. americana exhibited branched bacteroid morphologies, but we found that branching was neither necessary nor sufficient for effective symbiosis. Our study contradicts the prevailing view that bacteroid shape is a major determinant of symbiotic efficiency and presents the A. americana–Bradyrhizobium sp. USDA3516 interaction as an optimal model of A. americana symbiosis.

Phylogenetic trees are the primary framework for conveying evolutionary relationships. While many tools exist for visualizing phylogenetic trees, most are limited to static graphics, require coding expertise, or are developed for a specific website and not easily reusable or extensible. To address these limitations, we developed heat-tree, a collection of software packages in JavaScript, R, and Python for interactive visualization, manipulation, and editing of phylogenetic trees and their associated metadata. Heat-tree allows for the creation of customizable, web-compatible tree visualizations that can be easily embedded in R Markdown, Jupyter Notebooks, and Quarto documents, as well as directly in HTML/JavaScript applications and websites. The package supports radial and rectangular tree layouts, automated translation of metadata values into visual encodings on the tree, interactive tree editing, and export capabilities for publication-quality figures. All visualization parameters are definable programmatically or interactively using the comprehensive graphical user interface included with each visualization. Heat-tree was designed to be a user-friendly software package for interactive tree viewing, manipulation, editing, and self-contained, embeddable visualization across software environments.

Abstract Common scab disease on potato is caused by members of more than 10 pathogenic Streptomyces species. Genome-enabled methods are being increasingly deployed to characterize Streptomyces that cause common scab disease of potato and other tuber and root crops. However, the study of phytopathogenic Streptomyces is constrained by the limited availability of high-quality genome sequences. Here we report improvements to the quality and completeness of genome assemblies for 12 pathogenic type strains of Streptomyces and six closely related non-pathogenic type strains. These assemblies have an average N50 of 7.4 Mbp and with BUSCO scores all greater than 98.5%. Analyses showed that the genomes of phytopathogenic Streptomyces are consistently among the largest Streptomyces genomes sequenced and, relative to those of non-pathogenic strains, are more enriched in genes involved in carbohydrate and amino acid metabolism. Plasmids were not consistently detected across assemblies, suggesting that they are not conserved across species and are not necessary for pathogenicity. Furthermore, comparisons of genome assemblies among both closely and distantly related strains revealed multiple rearrangements within linear chromosomes and reduced synteny near telomeric regions. These improved genome assemblies, many of which correspond to type strains, provide valuable resources for advancing our understanding of the pathogenicity in the genus.

ABSTRACT The type VI secretion system (T6SS) enables Gram-negative bacteria to inject toxic effectors into neighboring cells, mediating contact-dependent antagonism and interbacterial competition. How the T6SS-mediated attack responds to environmental cues varies and remains unclear among different bacteria. Here, using Agrobacterium fabrum C58, a soil-borne phytopathogenic bacterium, we investigated the impact of osmolarity, moisture, surface stiffness, and glucose on T6SS-mediated antagonism. We show that these abiotic factors influenced the production of two polysaccharides, cyclic-β-(1,2)-glucan (CβG) and succinoglycan (SG), and modulated the T6SS-killing outcome. Mechanistically, high osmolarity inhibits CβG production, thereby enhancing the expression and secretion of the T6SS. In contrast, SG biosynthesis, in response to moisture, surface stiffness, and glucose, does not impact T6SS expression and function but decreases T6SS-mediated killing efficacy. Electron microscopy revealed that SG creates a physical barrier between bacterial cells. Such physical distancing not only hinders the T6SS attack from Agrobacterium , but also confers protection against other competitors at both intra- and inter-species levels. Our results unravel the complexity of how specific environmental factors modulate the contact-dependent antagonism and highlight a balance between offensive and defensive behaviors. Significance Statement Bacteria live in polymicrobial communities where they often need to fight off competitors to survive. One well-characterized weapon is the type VI secretion system (T6SS), a nanomachine mediating contact-dependent antagonism. In this study, we aim to study how the T6SS attack is influenced by environmental cues. We discovered that carbon sources, osmolarity, and surface stiffness modulate the T6SS efficacy through the secretion of sugar chains outside the cell. This sugar secretion increases the physical distance between cells, protecting against T6SS-mediated attack. However, such physical distancing also hinders the efficacy of the T6SS attack originating from Agrobacterium itself. Our results reveal a previously understudied offense-defense tradeoff between EPS production and T6SS-mediated attack. This finding underscores the intricate balance between bacterial offense and defense strategies.

Agrobacterium is not only a costly plant pathogen but is also an essential tool for plant transformation. Though Agrobacterium-mediated transformation (AMT) has been heavily studied, its polygenic nature and complex transcriptional regulation make identification of the genetic basis of transformational efficiency difficult through traditional genetic and bioinformatic approaches. Here, we use a bottom-up synthetic approach to systematically engineer the tumor-inducing plasmid (pTi), wherein the majority of virulence machinery is encoded. Using a validated toolkit to control Agrobacterium gene expression in planta, we perform a quantitative dissection of AMT to investigate the contributions of critical vir-genes at different expression levels. We construct a synthetic pTi capable of transient plant and stable fungal transformation and characterize bottlenecks and solutions for complex polygenic synthetic pTi designs. Our reductionist approach demonstrates how bottom-up engineering can be used to dissect and elucidate the genetic underpinnings of complex biological traits, laying the foundation for future engineering to establish full synthetic control over the critical process of AMT.

John M. McDowell, a leader in the field of molecular plant-microbe interactions, friend and colleague of many scientists in the molecular plant-microbe community, and a dedicated member of the International Society of Molecular Plant-Microbe Interactions, passed away in December 2024. John was known to many, not just because of his own seminal scientific discoveries, but because of his ability to synthesize the progress made in the field of molecular plant-microbe interactions, and in particular, the interplay between oomycete pathogens and the plant immune system, which led to many outstanding reviews. His ability to zoom out from minute details to the big picture also made him an effective mentor, teacher, editor in chief of the MPMI journal, NSF program director, and a great colleague, who would always be ready to ask the illuminating questions that helped you in deciding where to direct future efforts or provide sensitive hypotheses to test next. And in whatever he did, in whatever situation he was, he was always supportive, encouraging, lifting people up, and making them feel good about themselves and getting everybody even more excited about the research they were doing. He was the most even-keeled, kind-hearted person, an example to all of how to be better - not just as a scientist but as a human. [Formula: see text] Copyright © 2025 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Large-scale analyses of bacterial genomic datasets contribute to the comprehensive characterization of complex microbial dynamics among different strains and species. Such analyses often include open reading frame extraction, orthogroup inference, phylogeny reconstruction, and functional annotation of proteins. We have previously developed the M1CR0B1AL1Z3R web server, a “one-stop shop” for conducting comparative analyses of microbial genomes. Here, we present M1CR0B1AL1Z3R 2.0, an enhanced version that includes a new user-friendly web interface and an improved, optimized, and more versatile pipeline. The following features were added: (i) a computationally efficient inference of orthogroups, which allows the analysis of up to 2000 bacterial genomes; (ii) genome completeness analysis; (iii) lists of orphan genes per genome; (iv) genome numeric representation that allows detecting genomic rearrangement events; (v) codon bias analysis; (vi) annotation of orthogroups with KEGG Orthology numbers; and (vii) a map of pairwise average nucleotide identity values. M1CR0B1AL1Z3R 2.0 is freely available at https://microbializer.tau.ac.il/.

European foulbrood (EFB) is a severe bacterial disease of honey bee brood often leading to significant declines in colony health and honey production. The dearth of data on this disease in the United States (US) complicates response efforts. In 2021 and 2022 we conducted a two-year cross-sectional surveillance study among Michigan beekeepers to establish baseline pathogen and disease prevalence. We combined this surveillance with molecular epidemiology to investigate genetic diversity, and transmission dynamics of Melissococcus plutonius, the causative agent of EFB, in US honey bee colonies. PCR screening detected M. plutonius in all 15 migratory and stationary beekeeping operations and in 6 of 14 hobby beekeeping operations. Infection and disease were found to be seasonal, with prevalence of both peaking in June when over half the colonies were infected, and over 20% had clinical EFB. Whole genome, single nucleotide polymorphism analysis revealed wide genetic diversity even within a single hive. Operations often had multiple genotypes present which varied from year to year, consistent with high rates of transmission and reinfection. Prevalence and whole genome data provided here will be critical in tracking the efficacy of mitigation efforts and underscore the necessity of additional epidemiological investigations.

MOTIVATION:Type III secretion systems are used by many Gram-negative bacteria to inject type 3 effectors (T3Es) directly into eukaryotic cells, promoting disease or provoking immune response. Because of these opposing evolutionary forces, T3E repertoires often vary within taxonomic groups. Identifying the full effector gene repertoire in genomes of related individuals is crucial for determining core and specialized effectors, understanding the disease dynamics, and developing appropriate management strategies against pathogens. It can also help uncover novel T3Es that have recently emerged in a population. Our previously published Effectidor web server successfully addressed the challenge of identifying T3Es in a single bacterial genome. Here, we enriched the web server with various novel capabilities, including the identification of T3Es from multiple genome sequences simultaneously. RESULTS:We present Effectidor II, a web server that relies on machine learning to predict T3E-encoding genes within bacterial pan-genomes. We demonstrate the benefit of learning based on features extracted from the entire sequences comprising the pan-genome and report a novel T3E discovered by it in Xanthomonas euroxanthea. AVAILABILITY AND IMPLEMENTATION:Effectidor II is available at: https://effectidor.tau.ac.il and the source code is available at: https://github.com/naamawagner/Effectidor. A stand-alone version of Effectidor II is available at: https://github.com/naamawagner/Effectidor/tree/StandAlone. The source code for the standalone version and the data used in this work are also provided in https://doi.org/10.5281/zenodo.15081636.

Members of the Phytophthora genus are responsible for many important diseases in agricultural and natural ecosystems. Phytophthora ramorum causes devastating diseases of oak, and tanoak stands in US forests and larch in the UK. The four evolutionary lineages involved express different virulence phenotypes on plant hosts, and characterization of gene content is foundational to understanding the basis for these differences. Recent discovery of P. ramorum at its candidate center of origin in Asia provides a new opportunity for investigating the evolutionary history of the species. We assembled, high-quality genome sequences of six P. ramorum isolates representing three lineages from Asia and three causing epidemics in western US forests. The six genomes were assembled into 13 putative chromosomes. Analysis of structural variation revealed multiple chromosome fusion and fission events. Analysis of putative virulence genes revealed variations in effector gene composition among the sequenced lineages. We further characterized their evolutionary history and inferred a contraction of crinkler-encoding genes in the subclade of Phytophthora containing P. ramorum. There were losses of multiple families and a near complete loss of paralogs in the largest core crinkler family in the ancestor of P. ramorum and sister species P. lateralis. Secreted glycoside hydrolase enzymes showed a similar degree of variation in abundance among genomes of P. ramorum lineages as that observed among several Phytophthora species. We found plasticity among genomes from multiple lineages in a Phytophthora species and provide insights into the evolutionary history of a class of anciently conserved effector genes.

Understanding the ecology of pathogens is important for disease management. Recently, a devastating canker disease was found on red alder (Alnus rubra) planted as landscape trees. Bacteria were isolated from two groups of symptomatic trees located approximately 1 km apart, and one strain from each group was used to complete Koch's postulates. The results showed that these bacteria can cause disease not only on red alder but also on two other alder species. Unexpectedly, analyses of genome sequences of bacterial strains identified them as Lonsdalea quercina, a pathogenic species previously known to cause dieback of oak species, but not alder. Additionally, a core genome phylogeny clustered bacterial strains isolated from red alder within a subclade of L. quercina strains isolated from symptomatic oak trees. Consistent with the close phylogenetic relationship, there was no obvious evidence for divergence in genome composition of strains isolated from red alder and oak. Altogether, the findings indicate that L. quercina is a potential threat to Alnus species.

Whole genome sequencing (WGS) offers a comprehensive, organism-agnostic method that effectively meets the need for efficient, reliable, and standardized responses to emerging threats from pathogens and pests. Here, we present PathogenSurveillance , an open-source and automated Nextflow pipeline for population genomic analyses of WGS data. It is designed with features tailored for biosurveillance and is suitable for in-field or point-of-care diagnostics. PathogenSurveillance is flexible, accommodating short- and long-read datasets and mixed samples of prokaryotes and/or eukaryotes. It automates all steps, including reference identification and retrieval from the NCBI Assembly database, and produces customizable interactive reports with summaries, phylogenetic trees, and minimum spanning networks that enable species and subspecies level identification. It also outputs quality control metrics and organizes genomic data hierarchically to facilitate downstream analyses. The pipeline runs on any Linux-based system and minimizes the need for advanced computational expertise. Source code is available on GitHub under the open-source MIT license. The pipeline expands the toolkit for real-time biosurveillance, enabling rapid detection and monitoring of pathogens and pests for rapid response to novel variants. Interpretive summary PathogenSurveillance is a new open-source tool that helps scientists quickly and reliably detect and monitor harmful organisms like pathogens and pests. It works by analyzing their genetic material, offering a fast and standardized way to respond to emerging biological threats. This tool is designed to be easy to use, even outside of traditional lab settings, such as in the field or at point-of-care locations. It can handle different types of genetic data, including those from bacteria, fungi, and other organisms, and works with both short and long DNA sequences. PathogenSurveillance automatically identifies reference genomes from public databases and generates interactive reports that include summaries, evolutionary trees, and network diagrams. These features help users identify organisms down to the species or subspecies level. It also checks data quality and organizes results to support further analysis. Importantly, it runs on any Linux-based system and doesn’t require advanced computing skills. The source code is freely available on GitHub under the MIT license, making it accessible to researchers and public health professionals worldwide. Overall, it adds a powerful tool to the biosurveillance toolkit, enabling faster responses to new and evolving biological threats. ### Competing Interest Statement The authors have declared no competing interest. USDA Agricultural Research Service, 2072-22000-045-000-D National Institute of Food and Agriculture, https://ror.org/05qx3fv49, 2021-67021-34433, 2023-67013-39918

European foulbrood (EFB) is a severe bacterial disease of honey bee brood often leading to significant declines in colony health and honey production. The dearth of data on this disease in the United States (US) complicates response efforts. In this study, we combine surveillance and molecular epidemiology to investigate prevalence, diversity, and transmission dynamics of Melissococcus plutonius , the causative agent of EFB, in US honey bee colonies. Rates of infection and disease were found to be seasonal, with prevalence peaking in June when over half the colonies screened were infected. Whole genome, single nucleotide polymorphism analysis revealed wide genetic diversity even within a single hive. Operations often had multiple genotypes present which varied from year to year, consistent with high rates of transmission and reinfection. Prevalence and whole genome data provided here will be critical in tracking the efficacy of mitigation efforts and underscore the necessity of additional epidemiological investigations. ### Competing Interest Statement The authors have declared no competing interest.

Diseases severely impact plant growth and productivity. Here, we sought to identify new products for preventing agrobacteria from causing crown gall disease, which can affect many agriculturally important crop species. To this end, we characterized bacteria that fortuitously contaminated and antagonized a culture of plant-pathogenic bacterial species unrelated to agrobacteria. Analysis of genome sequences suggested that many of the isolated strains are members of the operational group Bacillus amyloliquefaciens. Of those tested, three strongly inhibited growth in a culture of agrobacteria. We focused on strain Z062 and showed that partially purified broth extracts inhibited growth in a culture of agrobacterial strains representative of taxonomic and virulence plasmid diversity. One of the inhibiting products was purified and identified as a mixture of plipastatin analogs, cyclic lipopeptides better known as antifungal products. Importantly, we demonstrated that broth extracts containing plipastatins or a mixture of plipastatins protected plants against crown gall disease. Last, the findings suggest that purified individual analogs of plipastatin vary in efficacy, as those with shorter fatty acid chains were generally more effective in a culture against agrobacteria. Plipastatins have potential as a preventive product to protect crop species against diverse genotypes of pathogenic agrobacteria.Copyright (c) 2025 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Natural products derived from Allium spp., such as garlic oil, garlic powder, and diallyl disulfide (DADS), are strong elicitors of sclerotia germination in the fungus Sclerotium cepivorum (syn. Stromatinia cepivora), the causal agent of Allium white rot. However, these compounds can also have broad antimicrobial activity against a wide range of bacteria, oomycetes, and other fungi when they are applied to soil. The objective of this study was to determine the potential impacts that DADS application has on soil microbial communities. DADS was applied to two soil types and incubated under aerobic and anaerobic conditions. Metabarcodes for bacterial, fungal, and oomycete communities were analyzed to identify changes. A significant effect of DADS treatment on the overall compositions of bacterial, fungal, and oomycete communities was observed compared with the mock-treated control. Soil type and incubation conditions did not have a significant effect on soil microbial communities, and significant interactions were not observed with DADS treatment in this study. Potential changes in soil microbial communities should be considered when applying DADS to field soils.

Metabarcoding is a widely used approach relying on short DNA sequences to identify organisms present in a community. Although established workflows exist for analysis of single metabarcodes, these are cumbersome when multiple metabarcodes are required to study diverse taxa, such as those in plant- and soil-associated microbial communities, or when analyzing newly developed metabarcodes. To address this, we developed demulticoder, an R package automating the use of DADA2 to analyze data derived from multiple metabarcodes. It has novel capabilities that streamline data analysis by reducing the number of manual input steps and enabling automated processing of multiplexed metabarcodes. Additionally, demulticoder modularizes data processing to allow for iterative quality control and reformats data for downstream analyses. We also updated the oomycete-specific rps10 barcode database by revising the taxonomic information of select entries based on updates to the classifications within the NCBI Taxonomy database. A multiplex sequenced dataset consisting of ITS1 and rps10 metabarcodes from 162 samples and 12 controls was analyzed to compare demulticoder against a standard analysis workflow. Demulticoder required manual input at only four steps in comparison with 28 steps required for the standard workflow. Data quality and results from downstream exploratory, diversity, and differential abundance analyses were comparable to those from the standard workflow. Demulticoder is versatile and can be used to analyze datasets consisting of single metabarcodes, multiplexed and pooled metabarcode types, and different metabarcode types generated in separate experiments. The demulticoder R package, example datasets, and instructions are publicly accessible and open source.

Caves are a unique ecosystem that harbor diverse microorganisms, and provide a challenging environment to the dwelling microbial communities, which may boost gene expression and can lead to the production of inimitable bioactive natural products. In this study, we obtained 59 actinobacteria from four different caves located in Bahadurkhel, District Karak, Pakistan. On the basis of taxonomic characteristics, 30 isolates were selected and screened for secondary metabolites production and bioactivity profiling. The extracts of all the isolates exhibited promising antibacterial activity against several pathogenic bacteria, with the best outcome seen in the extract of isolate SNK 21. The metabolomic analysis of the extracts by LC-MS/MS-based molecular networking and whole genome sequencing (WGS) followed by antiSMASH analysis revealed the presence of diverse secondary metabolites and biosynthetic gene clusters (BGCs) in SNK 21. Purification of compounds by manual chromatography, HPLC, and characterization by NMR, HR-MS, led to the identification of the active compounds, actinomycin D and its isomer. In addition, metabolomic analysis and genome mining of morphologically distinct isolates, SNK 202 and SNK 329, also showed diverse secondary metabolites and BGCs, underscoring the potential of actinobacteria from undisturbed caves in Pakistan as a new source of bioactive compounds.

Intense competition for resources among microorganisms imposes strong selective pressure for traits that provide a competitive advantage, including traits that harm others. The type VI secretion system (T6SS) is a versatile contractile injection apparatus encoded by many Gram-negative bacteria. This system is best known for its lethal use in deploying effectors toxic to neighboring bacteria. However, T6SSs can also be used to secrete effectors into the environment to influence nutrient acquisition. Additionally, for some bacteria, T6SSs deploy effectors toxic to eukaryotic hosts and are involved in virulence, which, however, has not been demonstrated for plant-associated bacteria. Here, we review the diverse functions and evolutionary basis of T6SSs. We discuss the potential ecological impacts of T6SSs in plant-associated communities. Understanding outcomes is important for finding the best approaches for using bacteria in sustainable management of plant agricultural systems.

Listeria monocytogenes is a foodborne pathogen of concern in dairy processing facilities, with the potential to cause human illness and trigger regulatory actions if found in the product. Monitoring for Listeria spp. through environmental sampling is recommended to prevent establishment of these microorganisms in dairy processing environments, thereby reducing the risk of product contamination. To inform on L. monocytogenes diversity and transmission, we analyzed genome sequences of L. monocytogenes strains (n = 88) obtained through the British Columbia Dairy Inspection Program. Strains were recovered from five different dairy processing facilities over a 10 year period (2007-2017). Analysis of whole genome sequences (WGS) grouped the isolates into nine sequence types and 11 cgMLST types (CT). The majority of isolates (93%) belonged to lineage II. Within each CT, single nucleotide polymorphism (SNP) differences ranged from 0 to 237 between isolates. A highly similar (0-16 SNPs) cluster of over 60 isolates, collected over 9 years within one facility (#71), was identified suggesting a possible persistent population. Analyses of genome content revealed a low frequency of genes associated with stress tolerance, with the exception of widely disseminated cadmium resistance genes cadA1 and cadA2. The distribution of virulence genes and mutations within internalin genes varied across the isolates and facilities. Further studies are needed to elucidate their phenotypic effect on pathogenicity and stress response. These findings demonstrate the diversity of L. monocytogenes isolates across dairy facilities in the same region. Findings also showed the utility of using WGS to discern potential persistence events within a single facility over time.

The landscape of scientific publishing is experiencing a transformative shift toward open access, a paradigm that mandates the availability of research outputs such as data, code, materials, and publications. Open access provides increased reproducibility and allows for reuse of these resources. This article provides guidance for best publishing practices of scientific research, data, and associated resources, including code, in The American Phytopathological Society journals. Key areas such as diagnostic assays, experimental design, data sharing, and code deposition are explored in detail. This guidance aligns with that observed by other leading journals. We hope the information assembled in this paper will raise awareness of best practices and enable greater appraisal of the true effects of biological phenomena in plant pathology.