Phytobiomes Journal

Antibiotic use in agricultural systems can unintentionally disrupt beneficial rhizosphere microorganisms, yet the consequences of this dysbiosis for plant fitness remain insufficiently understood. Building on previous findings that application of streptomycin to the roots decreases cyanobacteria and increases tomato plant susceptibility to foliar Xanthomonas infection, this study aimed to determine whether this relationship reflects causation or correlation. We evaluated whether targeted inoculation with the filamentous nitrogen-fixing cyanobacterium Cylindrospermum sp. (CI) or a complex rhizosphere microbiome transplant (RMT) could mitigate antibiotic-induced dysbiosis. As expected, streptomycin treatment significantly increased bacterial spot disease severity and reduced microbial richness in the rhizosphere, marked by a pronounced decline in cyanobacterial and Cylindrospermum operational taxonomic units. Co-occurrence network analysis revealed that this dysbiotic state was defined by reduced community connectivity and increased negative associations, indicating a breakdown in cooperative microbial relationships. Notably, both CI and RMT reduced plant disease severity, though they caused distinct rhizosphere community reassembly outcomes. While RMT relied on microbial functional redundancy, the targeted CI approach achieved more robust colonization and effectively "patched" the functional gap left by dysbiosis. Microbiome restoration directly influenced host physiology, significantly reducing the overactivation of ethylene-mediated defense genes, such as ERF1, and partially reinstating auxin-responsive signaling pathways (IAA21) that were disrupted under dysbiosis. These findings suggest that targeted microbial inoculation could reverse dysbiosis and enhance plant resilience under pathogen pressure as effectively as complex microbial transplants. This work highlights a shift in microbiome management: from the complex rebuilding of communities to the strategic repair of specific functional gaps.

Common bean (Phaseolus vulgaris) is an important crop in Canada and globally. Like other legumes, common bean (Phaseolus vulgaris) establishes symbiotic interactions with nitrogen fixing bacteria called rhizobia. However, nitrogen fixation by rhizobia in association with common bean is often suboptimal, constraining its productivity and necessitating the application of nitrogen fertilizer. To support the development of high-performing, locally adapted rhizobial inoculants for Ontario common bean growers, we isolated 216 common bean-nodulating rhizobia from southern Ontario soils using a nodule trapping approach with four common bean cultivars. Whole genome sequencing followed by phylogenomic analyses of the 216 rhizobial isolates revealed substantial diversity, assigning them to 11 Rhizobium species, including two novel species. Nearly all isolates belong to the symbiovar phaseoli, spanning the nodC {gamma}-a, {gamma}-b, and alleles, with four isolates belonging to the symbiovar gallica. Soil origin had a significant impact on the species-level community composition recovered during the nodule trapping experiments, indicative of biogeographical structuring of common bean-nodulating rhizobia across southern Ontario. In contrast, host trapping cultivar had only a minor influence of the recovered Rhizobium population diversity. Greenhouse assays demonstrated that one of the novel Rhizobium species exhibited the highest average symbiotic effectiveness, although high-quality isolates were found across multiple species. Together, these results revealed a diverse and genomically variable Rhizobium community capable of forming effective symbioses with common bean in southern Ontario soils. Importantly, our genome-sequenced Rhizobium collection will serve as a valuable resource for identifying competitive and high-quality strains for the development of inoculants tailored to Ontario common bean production. IMPORTANCECommon bean is a globally important food crop, yet its productivity is often limited by suboptimal nitrogen fixation, forcing growers to rely on synthetic fertilizers. Consequently, identifying high-performing, locally adapted inoculant strains is essential for reducing dependence on synthetic nitrogen fertilizers and improving the sustainability of temperate agroecosystems. Our study provides a genome-sequenced collection of common bean-nodulating Rhizobium from southern Ontario, revealing substantial species and genomic diversity across sampling locations. Greenhouse studies allowed us to identify multiple isolates, including isolates from a novel Rhizobium species, that consistently fix nitrogen with, and enhance the growth of, common bean plants. Our findings highlight strong biogeographical structuring of rhizobial communities and demonstrate that Ontario soils already harbour strains with high symbiotic potential. In addition, our Rhizobium collection represents a foundational resource to support future inoculant development and enables future work on the ecology, evolution, and applied optimization of legume-rhizobium symbioses.

Phyllosphere microbiomes are increasingly recognized as key regulators of plant health and stress responses, although they are also known to change considerably over both space and time. In the phyllosphere, members of the genus Methylobacterium are often abundant and ecologically important as plant growth promoting bacteria. However, knowledge about the temporal abundances and community dynamics of Methylobacterium in agricultural systems remains limited. To address this gap, we characterized seasonal shifts in Methylobacterium-specific and total phyllosphere bacterial loads and community structure on two common summer crops and one overwintering cover crop. Leaf samples of Zea mays (corn), Glycine max (soybean), and Thlaspi arvense L. (pennycress) plants were collected over one year in Minnesota, USA and analyzed with host-associated microbial PCR (hamPCR). Microbial loads and community composition varied strongly among hosts and across growing seasons. Corn supported the highest Methylobacterium and total bacterial loads, increasing towards senescence, while pennycress exhibited the lowest loads and the most distinct communities. While there were strong host-specific patterns, a group of most abundant genera were shared across all crops (Methylobacterium, Sphingomonas, Pseudomonas, and Massilia) and the most abundant Methylobacterium amplicon sequence variants were present on all three hosts. Our findings highlight how microbial loads and community composition change during phyllosphere assembly across diverse summer and overwintering crops, with a small core of versatile taxa dominating multiple agricultural hosts. Understanding these host and season-linked patterns provides a foundation of harnessing Methylobacterium strains to enhance crop productivity and resilience.

Understanding how host-microbiome interactions influence tree disease is critical for understanding forest resilience. Here, we present foliar microbiome ITS2 metabarcoding transcriptomic datasets from Pinus sylvestris to investigate susceptibility to Dothistroma needle blight (DNB), a globally important foliar disease caused by Dothistroma septosporum. We hypothesised that host genotype shapes foliar microbial communities and their interactions, thereby influencing disease outcomes. Samples were collected from a progeny-provenance field trial in the south of Scotland representing a broad spectrum of disease susceptibilities. The dataset comprises ITS2 metabarcoding samples from 200 genotypes across three timepoints and RNAseq samples from 48 genotypes across two timepoints. Sampling captured key stages of pathogen exposure and disease progression. Both standardised and bespoke protocols were used for nucleotide extraction, sequencing, and quality control, including multiple negative and positive controls. These datasets, available in the European Nucleotide Archive (project accession PRJEB88228), enable analysis of temporal dynamics in foliar fungal communities, host-microbiome transcriptional responses, and genotype-dependent variation in disease susceptibility.

Ralstonia pseudosolanacearum (Rps) belongs to the Ralstonia solanacearum species complex (RSSC). It is a vascular pathogen that causes lethal bacterial wilt disease in many plants, including tomato and eggplant. In this study, we infiltrated tomato leaves with the phytopathogenic bacterium at 109 CFU/mL and observed the development of necrotic scars in the infiltrated area at 48 hours post-infiltration. Interestingly, this response was followed by petiole bending toward the ground of the compound leaf. This was followed by the gradual senescence of the infiltrated leaflet only. In addition, the terminal leaflet infiltrated with the pathogen exhibited epinasty. None of the above symptoms were observed in leaves infiltrated with the known virulent deficient hrpB::{Omega} mutant. Surprisingly, all of the above symptoms were observed in leaves infiltrated with another well-known virulence-deficient mutant phcA::{Omega}. It indicated that the necrotic lesion caused in tomato leaves was hrp-dependent. Infiltration in eggplant leaves caused necrotic scarring and leaf senescence, which were relatively delayed. Necrotic scarring without petiole bending or senescence in tomato leaves was also observed due to infiltration of Pseudomonas aeruginosa SPT08, a tomato endophyte having plant growth promotion activity. The patho-phenotypes such as petiole bending, epinasty, and senescence observed in the case of tomato in this study were not reported earlier. We believe these phenotypes produced in tomato after leaf infiltration may be useful to study the virulence of this pathogen.

O_LISymbiosis between legumes and rhizobia is beneficial on nutrient-poor soils, as it enables the fixation of atmospheric N2. To establish this symbiosis, gene expression in both the host plant and the symbiont has to be regulated. To understand the underlying RNA-mediated regulation of host gene expression, we designed experiments to identify competing endogenous networks involving circular RNA, microRNA, and linear transcripts during symbiosis, using wt and symbiosis-deficient Lotus japonicus mutants with the rhizobium Mesorhizobium loti (M. loti). C_LIO_LICircRNA, miRNA, and linear transcripts were identified from Lotus japonicus wildtype and CCamK mutant (ccamk-13; snf-1) seedlings without inoculation or with M. loti inoculation using deep short-read sequencing with rRNA-depletion and random primers. C_LIO_LIDifferentially expressed miRNAs showed negative correlations to predicted target genes and may regulate symbiotic processes. The symbiosis essential iron-sensor LjnsRING/BRUTUS expresses a circRNA which was upregulated in symbiotic treatments. This circRNA may act as a target mimic and contribute to nodule longevity. CircRNAs are predicted to act predominantly as trans-regulatory molecules with similar frequencies in Arabidopsis thaliania, Oryza sativa, and Lotus japonicus. C_LIO_LIWe identified novel miRNAs, long noncoding RNAs, and circRNAs, and nominated several as potential new regulatory non-coding RNAs that may act as target mimics to stabilize genes and support symbiosis. C_LI SummarySymbiosis between Lotus japonicus and Mesorhizobium loti involves treatment-specific regulation of competing endogenous RNA networks involving circular RNA, miRNA, and linear transcripts.

Ectomycorrhizal (EcM) fungi are well-recognized symbionts impacting tree health and ecosystem functioning globally, yet understanding of their timing of proliferation in soils across seasons and years remains limited. We analyzed monthly patterns of EcM fungal abundance and community structure over two years in five temperate monodominant forest plots via quantitative PCR and Illumina sequencing. We found that the phenological dynamics of EcM fungi differed significantly by host tree leaf habit, fungal exploration type, fungal genus, and soil moisture. Overall, total EcM fungal abundances based on qPCR consistently peaked in autumn, and were more dynamic in evergreen than deciduous plots, supporting ideas of surplus carbon and asymmetric above-belowground dynamics. Longer-distance exploration types peaked earlier and were more stable than shorter-distance types, suggesting an independent and supportive role in releasing spring nutrients. About half of 20 focal taxa consistently peaked in either autumn, summer, or spring, while others were either host- and/or year-dependent. Our findings highlight that phenology is a key EcM fungal trait best explained by both host and fungal contributions, and future studies across biomes should consider seasonal shifts and sampling to elucidate phenological traits. Summary- The timing of belowground production and seasonal community dynamics remain poorly understood for ectomycorrhizal (EcM) fungi. - We collected soils monthly for two years from five temperate monodominant forest plots. - Fungal production peaked in autumn, shorter-distance and evergreen-associated spanned wider ranges, and half of focal fungal genera showed seasonal preference, emphasizing autumn surplus carbon and spring nutrients from long-distance types. - Future studies should consider seasonal shifts when sampling EcM fungal communities, and forest carbon models should include asymmetric above-belowground phenology. Translated Summary (Spanish)- La fenologia de la produccion y composicion de comunidades de hongos ectomicorrizicos (EcM) es poco estudiada. - Recolectamos suelos mensualmente por dos anos de cinco parcelas mono-dominantes templados. - Produccion maxima de hongos ocurrio en otono, hongos asociados con arboles siempreverdes y de exploracion de corta-distancia observaron rangos mas amplios, y la mitad de generos de hongos focales observaron preferencia estacional, enfatizando extra carbono en otono y nutrientes en primavera de tipos larga-distancia. - Estudios deben considerar cambios estacionales para el muestreo de hongos EcM, y modelos de carbono deben incluir fenologia asimetrica entre hojas y hongos. Plain language summaryEctomycorrhizal fungi are critical for the global carbon cycle, but their seasonal and inter-annual growth patterns remain unclear. We sample soil DNA monthly over two years across five different monodominant temperate forest stands. We find an overall belowground peak in autumn, with significantly later growth under wetter conditions, more dynamism with evergreen trees, and distinct spring growth by longer-distance fungi.

Microbes play a vital role in plant development, health, and resilience, yet relatively little is known about the specific metabolic mechanisms driving interactions in these host-associated communities. Systems biology models enable a computational approach to understanding metabolic interactions, which can be difficult to pinpoint experimentally; however, these methods cannot yet accommodate the large number of species in natural communities. Synthetic communities (SynComs) provide a more tractable alternative to explore targeted interactions. Here, we investigated metabolite exchange in a seven-member maize root-associated SynCom, specifically accounting for plant host context by designing a customized exudate medium. We constructed metabolic models for each bacterial species and curated them with in vitro phenotyping data to reflect experimentally based carbon uptake potential. Flux balance analysis of individual species demonstrated that integrating phenotype data and changing medium type had substantial impacts on predicted growth rates, which in turn shaped potential interspecies interactions. In silico community growth optimization of the seven-member community model showed that the exudate medium supported a more diverse community composition compared to minimal medium, with predictions of community member abundance closely aligned to literature-derived experimental results. Predicted metabolite exchange in the root exudate environment showed Enterobacter ludwigii as a community hub, and cross-feeding of indole suggested a potential effect of bacterial community interactions on the plant host. Our in silico findings indicate the host plays an important role in structuring microbial interactions and cross-feeding at the metabolic level, underscoring the importance of considering environmental context from both theoretical and experimental perspectives. IMPORTANCETrue understanding of a system is marked by the ability to predict its behavior. The complexity of natural host-microbe systems represents a frontier of knowledge that scientists are working to understand, and elucidating principles of interactions within multi-partite microbial communities remains a challenge in microbial ecology. Synthetic communities provide a tractable starting point for investigating interaction mechanisms, and computational approaches complement laboratory experiments by systematically evaluating multiple possibilities for metabolic pathway processing, thereby allowing us to comprehensively study the interconnected metabolic networks of host-associated microbiota. The model we developed for the seven-member maize root-associated bacterial community presents a step toward predicting plant-microbe behavior, providing hypotheses for future experimental testing and serving as a template for expanding model complexity to more members and other systems.

Beneficial interactions between plants and microorganisms strongly influence plant health and productivity, and root exudates play a central role in shaping these associations. This study analyzed the transcriptional responses of the bacterial endophytes Enterobacter asburiae RCA24 and Kosakonia sacchari RCA25 to root exudates from two commercial Italian rice accessions (Oryza sativa Baldo and Vialone Nano) and from an accession of the wild progenitor of tropical rice, Oryza rufipogon. Bacterial transcriptome analyses revealed that RCA24 responds differently to O. sativa varieties and that RCA25 was more stimulated by O. rufipogon. Changes in bacterial gene expression were mainly related to central metabolism, stress response, and signal transduction, highlighting a precise pattern of interaction. On the other hand, transcriptome analysis of inoculated rice revealed that RCA24 triggered broader transcriptional changes in plants than RCA25. Differentially expressed genes were related, especially in shoots, to defense responses, hormone-mediated signaling, and ribosome biogenesis, revealing that plants discriminate bacterial strains in a genotype-specific manner at the transcriptional level. Our findings suggest that traits beneficial to plant-soil microbiota interactions present in O. rufipogon and lost during domestication and diversification could be identified and reintroduced into modern rice varieties to improve sustainable field performance through beneficial microbial associations.

Scalable soil microbiome monitoring requires sampling methods that are reproducible across operators, field sites, and logistical constraints. Here, we evaluated three key methodological choices that commonly limit comparability in agricultural rhizosphere studies: how the rhizosphere sampling unit is operationally defined, sample pooling strategies, and preservation methods. We introduce the RhizoCore, a standardized root-zone soil core defined by core diameter, depth, position relative to the plant, and subsample volume, as a practical proxy for traditional rhizosphere sampling. The RhizoCore method captured more than 92% of the sequencing depth found in traditional rhizosphere samples, with differences limited predominantly to low-abundance taxa. Preservation methods significantly affected bacterial communities, while sample pooling showed greater impact on fungal diversity and substantially reduced within-group variability across all treatments. Despite these effects, differential abundance analysis revealed minimal compositional changes, with only a small fraction of microbial taxa significantly affected by either pooling or preservation method. Our findings demonstrate that the RhizoCore method provides a reproducible, and scalable approach for rhizosphere sampling that balances scientific rigor with practical field implementation, offering a framework for large-scale soil microbiome monitoring programs and for improving comparability among agricultural microbiome studies across diverse environmental conditions.

Bacterial spot is a consistent threat to global tomato and pepper productions; however, Ohios fresh market production currently lacks the updated surveillance data necessary to provide accurate management solutions. While traditional diagnostics focus on identification of a single causal agent, shotgun metagenomic sequencing (MGS) offers a comprehensive view of the infection court. An assignment-first MGS workflow was developed and validated in this study, utilizing Kraken2 databases to extract Xanthomonas species associated with bacterial spot and to characterize the microbial communities of bacterial spot in Ohio production systems. Through in silico spiking experiments, thresholds were established for bacterial spot identification. Species and pathovar identification via average nucleotide identity (ANI) remained accurate at abundance as low as 0.1%. A minimum of 2% Xanthomonas reads were required for high genome completeness (BUSCO >90%) and 3% for reliable type III secretion system (T3SS) effector profiling. Analysis of 63 samples from fresh-market production fields identified Xanthomonas hortorum pv. gardneri, Xanthomonas euvesicatoria pv. euvesicatoria, and Xanthomonas arboricola residing in symptomatic samples, alongside other taxa including Pseudomonas and Stenotrophomonas. Phylogenetic comparisons of metagenome-assembled genomes (MAGs) were comparable to whole genome sequences (WGS) from the same samples, supporting the reliability of culture-independent diagnostics. These results provide a robust framework for utilizing metagenomics as a diagnostic tool, expanding our knowledge of bacterial spot population structure in Ohio, and uncovering the bacterial communities associated with bacterial spot.

There is disagreement on whether secondary endosymbionts are found in the major cereal pest aphid, Rhopalosiphum padi. Some papers report a diversity of secondary bacterial endosymbionts while others have failed to find evidence of these bacteria in this species. Here we revisit this issue by summarizing the relevant literature and through additional sampling of the species in Australia, China and Denmark using a combination of molecular approaches. We find a general absence of secondary endosymbionts beyond the obligate endosymbiont Hamiltonella defensa in R. padi. While the inconsistency in survey results may reflect rapid changes in endosymbiont turnover in populations and/or the impact of ecological factors such as host plant type on endosymbiont diversity, we are concerned that technical issues may be at least partly responsible for inconsistencies in the literature. This leads us to emphasize the importance of multiple sources of evidence required to establish and characterize endosymbiont infections, including PCR and qPCR assays, DNA Sanger sequencing and 16SrRNA gene metabarcoding. We note that several major aphid pests show a low incidence of secondary endosymbionts which raises issues about the importance of these endosymbionts in aphids that constitute pests, even though endosymbionts can in some cases increase host fitness and therefore pest impact.

Aridification and climate stress threaten global plant productivity, but the survival strategies of desert plants remain only partly understood. In this study, we examined how the microbiome of Citrullus colocynthis, a hardy desert cucurbit valued for its ecological and medicinal benefits, may influence the plants ability to withstand harsh conditions. Using 16S rRNA amplicon sequencing, shotgun metagenomics, and culture-based methods, we analyzed microbiome changes across two regions of the UAE during the rainy and dry seasons. Leaf and root bacterial communities showed clear seasonal shifts, with greater richness in winter and higher evenness in summer, while soil microbiomes remained stable. Dominant bacterial groups, Actinomycetota and Pseudomonadota, varied seasonally, indicating trade-offs between stress tolerance and metabolic flexibility. Fungal communities (mainly Ascomycota and Basidiomycota) were stable at the phylum level but reorganized by order between seasons; archaeal populations showed little change. Among 24 cultured bacterial isolates, including three potential new species, we identified multiple stress tolerance and plant growth-promoting traits. Genomic data revealed biosynthetic clusters for antimicrobial and stress-protective functions, as well as adaptation genes in Pseudomonas orientalis. These results demonstrate that the dynamic, functionally diverse microbiome of C. colocynthis enhances its resilience to desert stress, offering potential for arid-land agriculture.

The Digital Pedon (DP) is an open-source Python framework that represents a soil profile as a continuously updated digital twin, bridging three persistent gaps in soil science: disconnected models and observations, cross-database interoperability, and the inference gap between raw sensor signals and agronomically meaningful variables. Integrating real-time sensor streams, model-based solver chains (Model-Zoo), GLOSIS-compliant ontology mapping, and a novel LLM agentic interface layer enabling natural language soil queries, the DP supports applications spanning precision agriculture, digital soil mapping, and environmental sustainability assessment. Four proof-of-concept experiments confirm automatic profile initialisation fidelity, solver chain consistency, ontology compliance, and user-defined solver extensibility.

Plant growth promoting microbes enhance developmental progression of the host by influencing its nutrient availability or by deploying secondary metabolites responsible for manipulating the hormonal crosstalk. Microbacterium bengalense sp. nov. GB16_1_BI (Accession number: SRX9280401), a newly identified ammonium releasing Actinomycetota, could enhance plant growth by manipulating rhizosphere bacteria. Amplicon sequencing of the 16S rRNA V3-V4 region from the rhizosphere of the black rice (Chakhao Poireiton) showed that GB16_1_BI could inhibit most bacteria. However, GB16_1_BI inoculation encouraged the growth of rare bacteria specific to waterlogged rice rhizosphere. Analysis of the OTUs using PICRUSt2 (Phylogenetic investigation of communities by reconstruction of unobserved states) showed increased abundance in the marker genes for nitrogen cycling (nifH, nrfA and nrt) but not for nifD or nifK which was also reflected in the ANOSIM analysis in the OTUs of the N-fixing bacteria. Marker genes for methane metabolism (comA, comB, cofG and cofH) were also more abundant in the inoculated plants than the control; however, ANOSIM studies did not support this observation in the OTUs of methane cycling bacteria. Both Methylosinus and Methylocystis, the two most abundant methanotrophic OTUs, are also known to be nitrogen fixers. Hence, GB16_1_BI could influence plant growth predominantly by manipulating nitrogen cycling microbes. The genome sequence as well as untargeted metabolome analyses of GB16_1_BI showed abundance of secondary metabolites with probable antimicrobial activity. GB16_1_BI could utilize varied carbohydrates and amino acid as energy source and form persister-like cells may help it to survive in the soil in absence of the host plant.

Pennycress (Thlaspi arvense L.) is an intermediate winter oilseed crop that has only recently been domesticated for agronomic use. Improving agronomic traits requires sources of genetic variation, and mutagenesis is frequently used to help overcome the limitations of natural populations. We investigate the impact of Ethyl methanesulfonate (EMS) on genetically effective cells (GECs) to characterize the intra-individual genetic variation of EMS mutagenesis in pennycress. We identified that pennycress contains at least 4 GECs which, when treated with EMS, create unique mutations across different branches within the same individual plant. We then propagated the M2 plants for whole genome sequencing, providing extensive characterization of the EMS mutation profile and developing a gene index as a resource for future reverse genetic screenings. Article SummaryPennycress is an emerging winter oil seed crop in the American Midwest. Domestication efforts have advanced rapidly through a combination of genetic techniques. One of the most successful methods has been the use of a mutant gene index, a large collection of pennycress seed where new genetic variation has been created through Ethyl methanesulfonate (EMS). EMS mutations are not uniform however, and a single treated seed can have wide genetic variation within the resulting plant. We investigate the role of genetically effective cells on EMS variation, and present the full EMS population as a resource for further pennycress domestication efforts.

Soft rot Pectobacteriaceae (SRP) are among the most economically important plant pathogenic bacteria and are especially known to be problematic in potato production. The epidemiology of disease transmission has been investigated for almost a century, and several aspects have been highlighted as plausible infection routes. However, it is generally accepted that the major source of disease is the latently infected mother tuber, but several parameters are still influencing disease prevalence including contaminated equipment, soil water status as well as temperature. Management of the disease is limited to hygiene practices, dry storage and seed certification systems but several studies have also proven biocontrol agents such as bacteriophages (phages) as promising tools. Despite the severity of SRP on potato production, little is known about the genetic diversity of SRPs in Denmark, and since only few isolates are available, the possibility to design a broadly effective phage cocktail is limited. Here we describe a three-year field study utilizing an agri-citizen science approach where Danish farmers provided symptomatic potato plants or tubers, together with metadata such as date, location, potato variety and origin. By using whole genome sequencing (Illumina and Nanopore) together with metadata we were able to investigate and monitor the epidemiological disease spread across the country using 103 complete genomes, sampled across all three years. In this study we provide epidemiological evidence of disease origins and a suite of phages that could be used as a biocontrol tool for early disease intervention. Our results revealed several clonal clades across diverse locations (SNPs < 20) which strongly indicate common origin. A total of 17 Pectobacterium phages were tested and did target > 80% of clonal clades. Based on the clonality across the soft rot isolates we propose the possibility to set in early on using phages targeting strains relevant for soft rot development, with the possibility of a surveillance program together with customizing the phage preference.

Aphanomyces euteiches, the causative agent of Aphanomyces root rot (ARR), is of major concern for pea and other legume crops globally. This oomycete pathogen causes substantial decreases in crop yields, is unaffected by most fungicides, and persists in the soil for many years via its resilient oospores. Given the significance of pea crops in sustainable agriculture, namely the ability to fix nitrogen and act as a sustainable protein source, solutions to ARR are of high importance. We used RNA-seq in a novel strain of Pseudomonas donghuensis to identify two biosynthetic gene clusters under GacA/S control that are involved in producing bioactive molecules capable of inhibiting A. euteiches. Based on similarity to other reported clusters in Pseudomonas, the first is predicted to encode for a pseudoiodinine compound, while the second is predicted to produce the siderophore 7-hydroxytropolone. Individual knockouts of each cluster showed loss of inhibitory action of P. donghuensis NRC29 against A, euteiches in vivo. This is the first report highlighting the potential of P. donghuensis and the products of the two identified biosynthetic pathways as biocontrol agents for A. euteiches. Further investigations into the efficacy of P. donghuensis NRC29 and its metabolites in inhibiting A. euteiches in field trials will be of high value in developing sustainable strategies for ARR mitigation. ImportanceModern fungicidal treatments for control of root rot in pulse crops are ineffective for control of A. euteiches, leaving limited strategies for management of A. euteiches infected fields. We describe a novel P. donghuensis strain with potential for biocontrol against this persistent pathogen. Given the economic value of peas and other pulses globally, further work into harnessing the bioactive metabolites produced by this strain into a practical in-field treatment will be valuable.

Microbiome science is increasingly important in modern biology education because microbial communities influence human health, ecosystems, and environmental processes. However, undergraduate microbiome instruction is often limited by the high cost and technical complexity of sequencing-based workflows, restricting opportunities for authentic student-driven research. To address this challenge, we developed a low-cost, inquiry-based curriculum that enables undergraduate students to conduct complete microbiome studies using 16S rRNA gene sequencing. The module integrates project design, environmental sample collection, microbial cell processing, PCR amplification, sequencing, and bioinformatic analysis using open-source tools such as QIIME 2. Cost-reduction strategies included centrifugation-based cell collection and a surfactant-assisted direct PCR workflow that eliminated the need for commercial DNA extraction kits. Students designed independent research projects investigating microbial communities in local environments, including campus water sources and gym equipment surfaces. Assessment data from post-course surveys, knowledge checks, and student research products demonstrated strong learning gains in microbiome concepts, molecular biology techniques, scientific communication, and computational analysis. Students reported high confidence in PCR, experimental design, and microbiome interpretation, while also identifying bioinformatics as the most challenging yet rewarding component of the curriculum. All participants expressed increased interest in future research in microbiology or bioinformatics. Overall, this curriculum provides an accessible, scalable framework for integrating next-generation sequencing into undergraduate education while promoting inquiry-driven learning, student ownership, and engagement in authentic scientific research.

BackgroundThe exponential growth of public metagenomic datasets offers an unprecedented opportunity to explore microbial diversity. However, analyzing this vast amount of data presents significant computational challenges. While shotgun metagenomics provides deep functional and taxonomic resolution, its high cost still limits its application. On the other hand, 16S rRNA gene sequencing remains a cost-effective and widely used alternative, but tools are needed to maximize its discovery potential. Traditional clustering is not scalable, obstructing the creation of a comprehensive and continuously updated catalog of microbial life from 16S data. MethodsWe developed a reproducible and scalable Snakemake pipeline for the incremental clustering of 16S rRNA amplicons. The workflow begins by constructing a reference database from bacterial and archaeal genomes. It then processes 16S rRNA samples sequentially. For each new sample, sequences are first mapped against the existing cluster centroids. Sequences that match known centroids are assigned accordingly, while unmapped sequences are clustered independently to form novel operational taxonomic units (OTUs). These new centroids are then merged with the existing database, allowing it to grow dynamically without the need for computationally prohibitive all-at-once re-clustering. ResultsOur pipeline enables the efficient and continuous expansion of a 16S rRNA cluster database. By processing a large corpus of public 16S rRNA samples, we generated a comprehensive atlas of tens of thousands of OTUs. A significant fraction of these clusters, particularly at the genus and family levels, were classified as unknown. ConclusionsThis work provides a powerful, open-source tool for large-scale analysis of 16S rRNA samples. The incremental clustering strategy overcomes the scalability limitations of traditional methods, allowing researchers to leverage public data and discover novel microbes in their own microbiome samples.