ISME Communications

Agriculture is a major source of anthropogenic greenhouse-gas emissions, being the largest source of nitrous oxide (N2O), an extremely potent greenhouse gas and ozone-depleting agent. Soil N2O emissions are largely driven by microbial nitrification, in which ammonia-oxidizing microorganisms catalyze the rate-limiting oxidation of ammonia to nitrite. Nitrification not only mediates N2O fluxes but also reduces fertilization efficiency and contributes to eutrophication through nitrate leaching. Bacteriophage (phage)-based control of microbial communities is rapidly garnering interest in a number of fields; however, phages infecting ammonia-oxidizers are largely uncharacterized, with only one lytic phage having been described, limiting the potential for phage-mediated nitrification inhibition. Here, we show the largest set of phages infecting ammonia-oxidizing bacteria (AOB) to date: 45 dsDNA phages identified from urban wastewater, infecting four AOB species, with 16 demonstrating cross-genus host ranges and capable of eliminating nitrification activity in liquid cultures. Phylogenetic and taxonomic analyses revealed six proposed families of Caudoviricetes and numerous monophyletic clades, likely representing higher-level lineages. Structure-guided genome annotation revealed these phages to carry diverse and seldom-seen auxiliary metabolic genes, ranging from a complete ABC transporter cassette to a large antimicrobial resistance gene cluster. These results unveil the previously unrecognized diversity of AOB phages and their potential to alter host physiology. Our data demonstrates a broad taxonomic and functional repertoire of cultured AOB phages, greatly expanding the panel of known AOB phages, suggesting that viruses play a more significant and complex role in nitrification than previously understood. Moreover, we outline an effective methodological framework for isolating AOB phages from environmental samples. These results will help reframe our understanding of environmental nitrification and enable intensified selection and use of phages for its control.

Coastal marine environments are increasingly recognised as reservoirs of antimicrobial-resistant (AMR) pathogens. However, it remains challenging to recover high-quality genomes of clinically relevant bacteria present at low abundance from complex natural systems. Here, we applied culture-enriched metagenomics to systematically track the diversity and dynamics of major AMR pathogens within the coastal marine system of St. Johns Island, Singapore, as a model ecosystem for pathogen surveillance. Selective media-based enrichment recovered 773 metagenome-assembled genomes (MAGs) from 92 multi-matrix environmental samples, which includes coastal water, sediment, and seaweed, capturing diverse AMR ESKAPE and Vibrio species. Distinct bacterial signatures and dispersal patterns were observed in each niche, for example, microbes that signal human impact was detected at the beach, while fish-associated pathogens were present at the aquaculture facility outlet. Notably, the high-quality MAGs enabled subspecies-level identification and supported the AMR gene detection across six distinct coastal habitats. Detailed differences in the recovery of specific pathogens across enrichment media were also identified, demonstrating the methods efficacy in finding media suitable for surveillance of specific organisms, such as deciding between liquid or solid formulations. MAGs recovered from culture-enriched metagenomics were highly similar to genomes obtained from pure isolates, as demonstrated for Klebsiella pneumoniae. The preserved culture-enriched stocks were capable of recovering organisms of interest when individual isolates were required for further study. Overall, our findings highlight the utility of culture-enriched metagenomics as a cost-effective, sensitive approach to uncovering the genomic landscape of pathogens with environmental reservoirs, with implications for AMR surveillance and ecological risk assessment.

Viruses of the phylum Nucleocytoviricota are paradigm-shifting entities due to their exceptionally large genomes and complex gene repertoires, which blur the lines between viral and cellular life. Previous research has leveraged computational approaches to map their extensive diversity, while experimental work has started to elucidate the intricate networks they form with hosts, bacterial and other symbionts, co-infecting virophages and other mobile genetic elements. Here, we analyzed deeply sequenced metagenomes sampled from wastewater treatment plants in Denmark, an environment with rapid abiotic changes and known to be a hotbed of dense microbial communities. We discovered 61 novel nucleocytoviruses, 15 virophages and 14 polinton-like viruses. By integrating them with microbial contigs into a multilayered interaction network, we explore the role of these entities on a mesocosm scale. We demonstrate the centrality of nucleocytoviruses, positioning them as important players shaping microbial community structure and evolution in wastewater treatment plants.

BackgroundCloud water harbors diverse microbial communities despite its extreme oligotrophic conditions. However, the ecological and evolutionary dynamics of viruses in these transient atmospheric habitats remain poorly understood. Clouds have traditionally been regarded primarily as passive carriers of microorganisms rather than as active ecological environments supporting microbial interactions. In this study, cloud water was sampled at Mount Verde, Cape Verde Islands (744 m a.s.l.). We performed metagenomic analyses of iron-flocculated cloud water alongside genome analyses of a bacterial isolate and metagenome-assembled genomes using established bioinformatic approaches. Viral diversity, virus-host interactions, metabolic functions, genetic adaptations, and viral population dynamics across cloud events were investigated. In addition, UV-B resistance experiments were conducted for a novel cloud-water isolate. ResultsWe isolated 24 cloud water bacteria, including four novel species lineages, and recovered 62 high-quality metagenome-assembled genomes, including 10 novel species lineages. We identified 458 viral operational taxonomic units and 237 virus-host linkages across diverse prokaryotic hosts, revealing active viral predation across diverse bacterial taxa. In addition, CRISPR spacer matches from isolates of novel bacterial lineages such as Deinococcus nubigenus MPC36 were found. Viruses carried genes involved in host adaptation to environmental stressors, including cold-shock response, UV radiation resistance, and osmotic stress. In addition, viral populations exhibited SNP-level microdiversity and shifts in single-nucleotide variant composition across temporally proximate cloud events, indicating rapid population turnover. Experimental characterization of the cloud isolate Curtobacterium nubigenum MPC39 further revealed pronounced resistance to UV-B radiation and the presence of an inducible prophage, Curtobacterium phage vB_CnuS_Cirrus1 assigned to the new viral family Nebulaviridae, which could be validated in transmission electron microscopy. Reconstructed genomes from cloud-associated bacteria encoded carbon monoxide dehydrogenase genes and UV resistance genes, suggesting trace gas metabolism and enhanced UV protection as survival strategies in oligotrophic cloud droplets. In silico replication rates estimated using iRep were consistent with active bacterial replication at the time of sampling. ConclusionsTogether, these findings demonstrate that clouds are not merely passive carriers of microorganisms, but dynamic atmospheric ecosystems in which virus-host interactions shape microbial diversity and contribute to microbial turnover, atmospheric dispersal, and cloud-water biogeochemistry.

Background.Mycoviruses infect fungal cells and represent important components of the global virome with potential biological control applications. The rice blast pathogen Pyricularia oryzae causes devastating crop losses worldwide, yet its mycovirus diversity remains understudied. While traditional dsRNA extraction remains a standard method for virus discovery, recent advancements, such as monoclonal antibody (mAb)-based dsRNA enrichment, offer improved specificity and sensitivity for viral detection. Methods.We developed the monoclonal anti-dsRNA antibody-based metagenomics (MADAM) approach, integrating dsRNA enrichment using 2G4 monoclonal antibody, sequence-independent reverse transcription-PCR with random octamer primers, and Oxford Nanopore Technologies sequencing. Total RNA was extracted from four P. oryzae isolates collected from Yuanyang rice terraces (Yunnan, China). After nuclease treatment, dsRNA was enriched using anti-dsRNA antibodies, followed by strand-switching cDNA synthesis, PCR amplification, and MinION sequencing. Genome gaps and terminal sequences were resolved through targeted RT-PCR and modified 3' RACE approaches. Results.MADAM achieved high viral read recovery rates (46.9-72.7%) and identified 18 P. oryzae-associated RNA viruses across seven families: Botourmiaviridae, Deltaormycoviridae, Mymonaviridae, Partitiviridae, Polymycoviridae, Splipalmiviridae, and Ambiguiviridae. Nearly complete to complete genomes (ranging from 1,226 to 6,085 nucleotides) were recovered, with sequence coverage spanning 88-100%. Co-infections occurred in three out of four isolates. Notable discoveries included the first deltaormycovirus in P. oryzae, a putative novel Botourmiaviridae member, and an additional genomic segment of a polymycovirus. The method detected positive-sense, negative-sense ssRNA, and dsRNA viruses, demonstrating broad applicability.

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.

Viruses are abundant and ecologically important in soils, yet the persistence and production dynamics of extracellular virions remain poorly understood. We applied a genome-resolved stable isotope probing viromics (SIP-viromics) approach, combining H 18O labeling with viral metagenomics, to track virion turnover in seasonally dry grassland soils following rewetting. We identified 354 viral populations (vOTUs) using individual-sample and combined metagenome assemblies. Only 22% of vOTUs exhibited significant 18O enrichment, indicating active replication and new virion production during the 1-week incubation; the majority (78%) persisted without detectable replication, consistent with a viral seed bank. Active vOTUs accounted for 4.76-5.15% of total virions per gram of soil, with viral loads ranging from 3.15 x 1010 to 6.59 x 1010 virions per gram. Probabilistic and deterministic sensitivity analyses spanning viral DNA fraction and genome length reinforced that persistent virions represented the majority of the extracellular viral pool post-wet-up, regardless of parameter assumptions. Host predictions linked both active and persistent vOTUs primarily to Actinomycetota and Pseudomonadota--bacterial groups known to rapidly resuscitate following rewetting--suggesting that some viruses exhibit rapid turnover while others persist over longer timescales, forming a stable viral pool capable of reinitiating infections during favorable conditions. These results demonstrate that SIP-viromics can distinguish newly produced from persistent virions and reveal host-associated patterns of lytic infection and virion production. Our findings advance understanding of soil virus-host interactions and highlight the ecological role of persistent virions as a genetic reservoir contributing to microbial turnover and biogeochemical cycling following environmental disturbance. ImportanceUnderstanding the persistence and production dynamics of soil viruses is critical for elucidating their roles in microbial community dynamics and nutrient cycling, yet these processes have remained largely uncharacterized due to methodological limitations. By integrating stable isotope probing with viromics, this study provides a robust framework for directly distinguishing newly produced from persistent virions in situ. Unlike conventional viromics, which only catalogs viral diversity, SIP-viromics enables quantification of active viral replication and persistence under natural soil conditions. Our results demonstrate that most virions in a seasonally dry soil persisted through a rewetting event, with active replication limited to a minority of viral populations. Persistent virions were primarily linked to dominant bacterial groups, indicating that host ecophysiology and environmental stability strongly influence lytic infection. Collectively, these findings highlight viruses as long-term reservoirs of genetic material, capable of shaping microbial dynamics and ecosystem processes over time. This work establishes SIP-viromics as a powerful approach for studying virus-host interactions and their ecological significance in terrestrial environments.

Aquaculture is an essential food production sector for meeting the global demand for high-quality protein. However, the sector faces significant challenges from bacterial pathogens, particularly Vibrio anguillarum, which causes vibriosis in numerous commercially important fish species. Current disease management strategies rely heavily on antibiotics, leading to antimicrobial resistance and environmental concerns. Microalgal microbiomes represent promising alternatives for sustainable pathogen control, yet the molecular mechanisms underlying their inhibitory activity remain poorly understood. Here, we employed an integrated multi-omics approach to elucidate the mechanisms by which the microbiome of microalga Isochrysis galbana inhibits the highly virulent fish pathogen V. anguillarum strain 90-11-286. Using a GFP-based inhibition assay, we confirmed potent pathogen suppression by the algal microbiome, achieving complete inhibition at a 1:1000 ratio of pathogen to microbiome. Through 16S rRNA gene amplicon sequencing, metagenomics, metatranscriptomics, and metabolomics, we characterized community composition, genomic potential, gene expression patterns, and metabolite production during pathogen challenge. The inhibitory microbiome was dominated by Alteromonas macleodii and Vreelandella alkaliphila, with high-quality metagenome-assembled genomes revealing substantial secondary metabolite biosynthetic potential. Metatranscriptomic analysis revealed active expression of biosynthetic gene clusters encoding, for example, non-ribosomal peptide synthetases, particularly a siderophore gene cluster in V. alkaliphila. Metabolomic profiling confirmed the production of hydroxamate siderophores in the microbiome, including desferrioxamine analogues, proferrioxamine G1t, and tenacibactin D, which accumulated during pathogen inhibition, as well as 10 putative new compounds. Notably, siderophore production was constitutive rather than pathogen-induced, suggesting iron competition as the primary inhibitory mechanism. Our findings demonstrate that iron sequestration through siderophore production represents a key strategy for pathogen suppression in marine microbial communities. This work provides molecular evidence for microbiome-mediated disease control and establishes a foundation for developing rationally designed multi-strain probiotic consortia for sustainable aquaculture applications, offering an environmentally friendly alternative to antibiotic-based pathogen management strategies.

Protistan predators are key regulators of microbial food webs, yet most are considered to occupy relatively narrow trophic niches. Here, we demonstrate that Mayorella spp. (Amoebozoa), isolated from marine and freshwater environments, exhibits exceptional trophic breadth spanning multiple trophic levels. Live-cell imaging revealed predation on bacteria, algae, dinoflagellates, diatoms, flagellates, ciliates, and multicellular prey including rotifers. Large or filamentous prey were engulfed whole or mechanically fragmented during ingestion. Notably, Mayorella consumed both trophozoites and cysts of free-living amoebae (Naegleria and Acanthamoeba), with clear digestion of cyst contents. Dense cultures showed aggregation around large prey and facultative cannibalism. Ingestion of microplastic-like particles occurred without evidence of digestion. Predator cell size and population density increased markedly when feeding on protist or mixed prey relative to bacterial diets, indicating pronounced trophic plasticity. These findings establish Mayorella as a broad-spectrum, cross-trophic predator with the capacity to exert top-down effects across microbial food webs and suggest a previously underappreciated role in the suppression of pathogenic free-living amoebae.

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.

1Consortia of archaea and partner bacteria couple the anaerobic oxidation of alkanes to sulfate reduction. While catabolic pathways in anaerobic alkane-oxidizing archaea (ANKA) are increasingly understood, their anabolic capacities remain poorly characterized. Here, we examined nine enrichment cultures dominated by ANKA and their partner bacteria for small-molecular compounds using solvent extraction and gas chromatographic analysis of derivatized extracts. All hydrocarbon-degrading cultures contained substantial amounts of disaccharides in their metabolite pools. Cold-adapted methane-oxidizing cultures dominated by ANME-2c and Seep-SRB2 contained up to 1.5 mg of trehalose per mg soluble protein. Trehalose was also abundant in ethane-oxidizing cultures of Candidatus Ethanoperedens and its distinct partner SRBs, accounting for up to 75 % of the extracted metabolites. In contrast, thermophilic ANKA cultures dominated by ANME-1 or Ca. Syntropharchaeum and Ca. Desulfofervidus contained an abundant as-yet-unidentified glucose-containing disaccharide. Metagenomic analysis revealed widespread trehalose metabolism genes among partner Desulfobacterota and in ANME-2c and Ca. Ethanoperedens, but a lower potential in ANME-1 and Syntropharchaeum, consistent with metabolite profiles. If exogenous trehalose was added to the Ethane50 culture, we observed rapid metabolization by heterotrophic microorganisms, but poor assimilation by the Ca. Ethanoperedens/ Ca. Desulfofervidus core community, indicating that ANKA/SRB consortia do not consume externally supplied trehalose. Instead, Ca. Ethanoperedens/ Ca. Desulfofervidus, as well as other ANKA/SRB consortia, may use the disaccharides as energy-storage molecules, osmolytes, or components of the extracellular matrix. Notably, the disaccharides produced by the consortia also sustain ancillary heterotrophs, thereby linking alkane oxidation to broader sedimentary carbon cycling.

Global change drivers are reshaping agroecosystems and their sustained functions worldwide. While soil microorganisms underpin the resilience of these systems, the individual and interactive effects of multiple anthropogenic stressors on microbial community structure and function using large-scale field experiments remain poorly understood. Here, we utilize a full-factorial field experiment in a subtropical agroecosystem to investigate how land-use intensity, cattle grazing intensity, and altered precipitation regimes interact to shape soil microbiomes. Combining microbiome sequencing with network analyses and functional bioinformatics, we evaluated effects of these drivers on prokaryotic and fungal diversity, composition, predicted functional profiles, and community structure. Land-use intensity emerged as the primary driver of microbial responses, explaining 25% and 13% of the total variation in community composition for prokaryotes and fungi, respectively. Compared to intensively managed pastures, semi-natural pastures had significantly different community composition for prokaryotes and fungi and exhibited 22% higher fungal diversity. Semi-natural pastures were enriched with decomposer-associated taxa and metabolic pathways related to energy and lipid metabolism indicating enhanced microbial activity. Surprisingly, intensively managed pastures showed higher network modularity but lower network richness, suggesting a trade-off between community compartmentalization and complexity under intensive land management. Grazing and precipitation manipulations induced core microbiome changes within land-use intensities but had no impact on overall community structure and no significant interactions with land-use. Together, these findings suggest that long-term land-use legacies exert a persistent influence on soil microbial community structure, function, and organization, shaping the context within which other global change drivers operate in subtropical agroecosystems.

Interactions between amoebae and bacteria are increasingly viewed as key drivers of zoonotic pathogen emergence in rodent-dwelling burrows, yet the environmental factors shaping these interactions remain poorly understood. Here, we analyzed soil characteristics and used absolute quantitative high-throughput sequencing to assess microbial communities in active burrow, inactive burrow, and off-burrow soils across four rodent species (marmot, squirrel, gerbil, and vole) in the Hulunbuir grassland of Inner Mongolia, China. This study demonstrates that rodent activity creates chemically distinct soil microhabitats, with nitrate (NO --N) enrichment in active burrow soils consistently observed across rodent species. Elevated soil NO3--N was associated with reduced microbial phylogenetic diversity and reorganization of amoeba-co-occurring bacterial assemblages. Both absolute abundance-based correlations and functional prediction of co-occurring bacteria indicated that amoebae were primarily associated with nitrogen-cycling bacteria in off-burrow soils. In burrow soils, amoebae increasingly interacted with bacterial taxa associated with pathogenicity while retaining ties to nitrogen-cycling taxa. Structural equation modeling and mediation analysis revealed that NO3--N enrichment indirectly linked to increased infectious disease-related functional potential by amoeba-associated bacterial restructuring and coordinated shifts in nitrogen cycling, independent of changes in bacterial abundance. Together, our findings highlight the importance of rodent-driven soil heterogeneity in shaping amoeba-bacteria interactions and suggest that rodent-mediated NO --N enrichment may promote the emergence and persistence of potentially pathogenic bacteria, with broader implications for soil ecosystem functioning and disease-related processes in terrestrial ecosystems.

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.

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.

The 16S rRNA gene is the most widely used genetic marker for microbial community profiling, but its limited sequence divergence often prevents species-level identification. The RNA polymerase {beta}-subunit gene (rpoB) offers higher sequence variability, single-copy occurrence, and stronger phylogenetic consistency, yet its adoption in metataxonomic studies has been constrained by the lack of universal primer sets. Here, we present a novel universal primer pair that amplifies an [~]1,800 bp rpoB region (rpoB_MV) compatible with long-read sequencing platforms. In silico evaluation across 17683 bacterial reference genomes demonstrated high universality, with over 86% of genomes predicted to amplify. Compared with full-length and partial 16S rRNA gene markers, the rpoB_MV amplicon exhibited significantly greater inter-species sequence divergence and improved phylogenetic concordance with core-genome trees. Sequencing of two complementary mock communities confirmed superior species-level identification accuracy, with misclassification rates below 0.01% and no reads assigned to unresolved species clusters. These results establish rpoB_MV as a robust alternative to 16S rRNA gene-based profiling for high-resolution metataxonomic applications. IMPORTANCEMicrobial community studies increasingly require species-level resolution because species within the same genus can differ substantially in pathogenicity, ecological function, and metabolic capacity. Current 16S rRNA gene-based methods frequently fail to distinguish closely related species, collapsing biologically distinct organisms into the same taxonomic assignment and obscuring community differences that matter for clinical diagnostics, food safety, and environmental monitoring. The rpoB_MV primer pair presented here overcomes this limitation by targeting a longer, more variable region of the rpoB gene, enabling accurate species-level identification across diverse bacterial phyla. Combined with advances in long-read sequencing, this approach provides researchers with a practical tool to resolve microbial communities at the species-level.

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.

Methane is a powerful greenhouse gas. Typically, a large fraction of the methane formed in coastal sediments is removed via anaerobic methane oxidation (AOM). Here, we demonstrate the potential for a range of AOM pathways in brackish coastal sediments by ANME-2a archaea. At our study site, geochemical profiles indicate that AOM is primarily restricted to a shallow, metal-oxide-rich sulfate-methane transition zone (SMTZ). ANME-2a were the sole methanotrophs detected, and metatranscriptomics showed the highest expression levels of the ANME-2a genes in the SMTZ. AOM activity was observed in sediment incubations with various electron acceptors, including sulfate, metal oxides, and the organic matter analogue graphene oxide. Highest potential rates were observed in sediments from below the SMTZ, pointing towards fast stimulation of the deeper methanotrophic community when alleviating the electron acceptor limitation. The variety of AOM pathways and persistence of methanotrophs below the SMTZ likely contribute to the resilience of the microbial methane filter in brackish coastal sediments.

Acinetobacter baumannii is a highly adaptable nosocomial pathogen with extensive antibiotic resistance, a disproportionately large accessory genome, and high genomic plasticity. Owing to these features, the World Health Organisation (WHO) classifies A.baumannii as a critical-priority pathogen. In this study, we analyzed 47 isolates from our VUB (Vrije Universiteit Brussel) collection and applied distance-based species-delimitation algorithms - Automatic Barcode Gap Discovery (ABGD) and Assemble Species by Automatic Partitioning (ASAP) - for the first time at the bacterial core-genome scale. By integrating conspecificity matrices, we extended these traditionally single-locus methods into a multi-locus framework, which we term Core-Gene Consensus Delimitation (CGCD). Across a range of gene-level co-occurrence thresholds, CGCD consistently recovered 11 stable groups using both ABGD and ASAP. Larger-scale validation using 856 A. baumannii genomes recovered the same 11 well-separated groups were recovered, demonstrating the robustness and reliability of our clustering approach. Mapping these groups onto a core-genome phylogeny revealed that each group forms a distinct clade, indicating that they represent evolutionarily independent lineages rather than arbitrary clusters. We further constructed a clustering tree based on accessory gene presence-absence patterns. In this tree, only one strain (AB231-VUB) clustered within group 11; otherwise, the groups remained tightly cohesive, sharing characteristic sets of accessory genes. Together, these results show that the groups defined by CGCD are genomically, evolutionarily, and functionally distinct, supporting their interpretation as separate species. Our findings highlight CGCD as a powerful, high-resolution framework for species delimitation. CGCD is threshold-free, gene-based, and universally applicable--the first species-delimitation approach that can be applied across all domains of life, from bacteria to animals and plants.

Glyphosate, the worlds most widely used herbicide, targets the enzyme 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS), which is conserved across plants and many bacteria. While its environmental effects are increasingly recognized, its role on antimicrobial resistance (AMR) remains incompletely understood. In particular, the link between intrinsic glyphosate sensitivity and AMR gene content or evolutionary dynamics has not been systematically explored. We examined the relationship between bacterial sensitivity to glyphosate, AMR profiles, and the evolution of AMR genes. We analyzed genome datasets from the human gut microbiota and the Alignable Tight Genomic Clusters (ATGC). EPSPS sequences were identified via BLAST and annotations and classified based on the intrinsic sensitivity to glyphosate using the EPSPSClass webserver. AMR genes, including associated drug classes and resistance mechanisms, were annotated using the Comprehensive Antibiotic Resistance Database (CARD). Across datasets, glyphosate-sensitive bacteria carried a greater diversity of AMR genes and mechanisms. In contrast, probabilistic modeling revealed that glyphosate-resistant bacteria accumulate AMR genes at significantly higher rates. Phylogenetic birth-and-death analyses and stochastic mapping further revealed elevated AMR gene gain, loss, expansion, and reduction in resistant strains. These results indicate a decoupling between AMR gene diversity and evolutionary dynamics: sensitive bacteria maintain more resistance genes, whereas resistant bacteria display accelerated AMR gene turnover. This suggests that glyphosate resistance is linked to increased genome dynamics, potentially enhancing bacterias adaptability under combined herbicide and antimicrobial pressures. Given glyphosates extensive agricultural use and potential human exposure, these findings highlight an underappreciated link between herbicide resistance and the evolution of AMR in bacterial populations.