ISME Communications

Phage tail-like elements (PTEs) -- tailocins, bacterial type VI secretion systems (T6SS), and extracellular contractile injection systems (eCIS) -- are contractile nanomachines that bacteria use to kill their neighbors and compete within their micro-ecosystems. PTEs help shape microbial community composition. Most PTE detection tools only detect a single PTE class. Moreover, most tailocin detection methods are largely restricted to Pseudomonas, leaving a key part of tailocin diversity uncharacterized. In this work, we present PhageTAILor (https://github.com/hjcho-bio/PhageTAILor), an integrative and fully automated pipeline that detects and classifies prophages and 3 PTE classes from bacterial genomes. PhageTAILor combines a 6-detector homology-based candidate search (geNomad, tail-gene, PHROGs-tail, SecReT6, eCIStem, and a divergence-tolerant tail-HMM detector) with a LightGBM classifier comprising 1 multiclass and 3 binary heads, trained on 6,501 bacterial genomes carrying 13,082 prophages and PTEs. A phylogeny-free feature matrix used in our model keeps predictions reproducible between model construction and user inference. PhageTAILor performs strongly at the genome level and generalizes beyond its Pseudomonas-rich training set. On a 76-strain cross-clade benchmark, PhageTAILor detected tailocins at F1 = 0.955. Furthermore, it identified 12 of 13 experimentally validated tailocins spanning five genera versus 2 of 13 for a Pseudomonas-restricted tool TattleTail. PhageTAILor also demonstrated sensitivity equivalent to viral detection tool geNomad while avoiding its higher false-positive rate. Applied to 7,925 plant- and soil-associated bacterial isolates, PhageTAILor showed that prophages in the phyllosphere and tailocins in plant-associated bacteria, whereas eCIS are enriched in soil. PhageTAILor is distributed as an open-source, modular pipeline with a command-line interface.

Protists play important roles in food chains and symbioses in soil and aquatic environments, displaying an enormous morphological and functional diversity. While most commonly found protist species are well known to science, our global-scale environmental DNA survey across soil, water, and sediments reveals dozens of novel, phylum-level phylogenetic lineages that remain to be characterized for basic morphology and function. A vast majority of these undescribed taxa occur in marine water and sediments, but some are common in soil. Most of these novel taxa have distinct substrate and habitat preferences and biogeographic patterns. To accord these lineages scientific agency and enable unambiguous scientific communication, we propose formal names for 150 species to phylum-level taxa from 25 deep lineages based on eDNA and rRNA gene long-read sequence information.

Winogradsky columns are a classic model ecosystem for studying microbial biogeochemistry across steep gradients of oxygen and sulfide. They also remain widely used in microbiology education, introducing generations of students to microbial diversity. Yet, the genomic potential of their microbial communities remains uncharacterized. Here, we applied shotgun metagenomic sequencing to a Winogradsky column community at multiple depths, yielding 20 metagenome-assembled genomes (MAGs) representing diverse, largely uncultivated taxa. Genome-resolved analyses revealed metabolically diverse oxygenic and anoxygenic phototrophs that could potentially contribute to carbon and nitrogen fixation across all layers of the column. Most of these phototrophs also encoded one or more pathways for sulfur oxidation, which we speculated may support both energy conservation and/or sulfide detoxification by these populations. Complex carbon degradation capacity was also widespread across the MAGs, suggestive of the potential for the transformation of the column's amended organic matter (shredded coffee filters) into smaller depolymerization products and, through fermentation, organic acids. Together, these findings reveal how distinct microbial guilds might partition interconnected carbon, sulfur, and nitrogen transformations within redox-stratified systems.

Viral infection is a major yet poorly quantified driver of microbial interactions and biogeochemical fluxes in the ocean. In diatoms, which are key contributors to marine primary production, the extent to which viruses reprogram host cell metabolism and alter elemental cycling remains largely unresolved. Here, we investigated how infection by a lytic single-stranded RNA virus reshapes carbon (C) and nitrogen (N) fluxes in the ecologically relevant nanoplanktonic diatom Mediolabrus comicus. Using controlled infection experiments coupled with flow cytometry, electron microscopy, PAM fluorimetry, and stable isotope probing, we resolved infection-driven changes from the population to the cellular scale. Infection induced rapid optical shifts and cellular reorganization, including the formation of membrane-bound viral replication compartments. These changes coincided with early impairment of plastidial functions, as shown by disruption of photosystem II functionality and a concomitant decline in photosynthetic carbon fixation. In contrast, nitrogen uptake was maintained and strongly enhanced during late stages of infection, indicating sustained resource acquisition to support viral replication. This decoupling led to dynamic changes in cellular stoichiometry and, overall, to substantial reductions in population-level carbon and nitrogen assimilation due to growth inhibition. Together, these findings demonstrate that diatom RNA virus infection reshapes host carbon and nitrogen metabolism, with cascading effects on elemental cycling. Our results identify diatom RNA viruses as important drivers of marine biogeochemical processes, with implications for primary production and the fate of organic matter in the ocean.

Intertidal mudflats are low hydrodynamic energy environments hosting microphytobenthic communities that experience strong spatiotemporal variability in light regimes, including changes in spectral quality and light intensity that can lead to cellular photooxidative stress. To cope with these fluctuations, autotrophs exhibit diverse and highly plastic adaptations that are often species-dependent and shaped by their ecological niches. This study investigates photophysiological responses and metabolic remodeling in a diatom assemblage originating from a natural winter microphytobenthic biofilm under contrasting red and blue light intensities. To this end, photosynthetic parameters were monitored alongside changes in lipophilic metabolites, including untargeted lipids and lipophilic pigments. While few metabolites showed temporal remodeling, rapid and contrasting changes were observed within 30 minutes in response to both spectral quality and light intensity. Red light treatments induced broader remodeling of lipophilic metabolites than blue light, whereas blue light appeared to have a greater impact on photosynthetic parameters. Moreover, red light induced xanthophyll-cycle responses comparable to those observed under blue light at equivalent incident intensity. We discuss these metabolic responses in relation to diatom photoadaptive strategies, placing these findings within the intertidal environmental framework. This work further underlines the importance of understanding rapid metabolic plasticity in coping with light fluctuations, providing new insights into the photoregulatory strategies of natural microphytobenthic communities.

Diatoms are major contributors to marine primary production, yet current approaches for monitoring their abundance and function rely on coarse satellite chlorophyll estimates or sparse cell count and carbon fixation measurements. Molecular markers are a promising approach for high-resolution measurement of both abundance and metabolic activity through analysis of environmental DNA (eDNA) and RNA (eRNA). We present an isothermal quantitative recombinase polymerase amplification (qRPA) assay targeting rbcL gene copies and transcripts of marine diatoms, operating at low temperature and producing results in less than 15 min. We demonstrate specificity and calibration across diverse diatom taxa, then apply the assay to eDNA and eRNA samples from the Mare Chiara Long-Term Ecological Research site in the Bay of Naples, Italy, alongside microscopy, chlorophyll, physicochemical, and carbon-fixation data. Diatom rbcL DNA tracked abundance across five orders of magnitude despite seasonal shifts in community composition. Combining molecular and optical data revealed increased cellular rbcL copies and chlorophyll in low-light winter populations, suggesting enhanced photosynthetic capacity despite lower abundance. Furthermore, rbcL RNA reflected total carbon fixation rates and identified populations with differing carbon fixation activity. These results support rapid, RPA-based rbcL quantification as a robust approach for biomolecular ocean observing.

Marine diatoms contribute to about 20% of global primary production. We present the first basin-scale, multiyear assessment of diatom communities in the North Pacific, combining taxonomically high-resolution RuBisCO large subunit gene (rbcL) metabarcoding with concurrent environmental measurements. Using a nine-year time series of daily samples resolved at the species level via ~500 bp rbcL fragments, we performed multivariate analyses across biogeographic provinces, identifying significant correlations between community structure and environmental drivers such as temperature and macronutrient availability. We report the prevalence of a previously overlooked centric diatom species in the North Pacific, Eunotogramma lunatum, which appears to be near-dominant even in subarctic high-nitrate, low-chlorophyll waters where pennate diatoms are typically favored. These results demonstrate the power of rbcL for large-scale ocean monitoring and provide a critical baseline for future studies of diatom population dynamics, climate change impacts, and ecosystem resilience in a key marine region.

Organosulfur compounds are the predominant sulfur source in terrestrial environments, requiring bacteria to use enzymes for their assimilation. Most described organosulfur-assimilating enzymes require oxygen, and enzymes that function under anoxic conditions remain poorly understood. Recently, methylthio-alkane reductase (Mar), a nitrogenase-like enzyme that reduces the volatile organic sulfur compounds (VOSCs) methylthio ethanol (MT-EtOH), dimethyl sulfide (DMS), and ethyl methyl sulfide (EMS) under anoxic conditions, was identified in the purple nonsulfur bacterium Rhodospirillum rubrum. However, another purple nonsulfur bacterium, Rhodopseudomonas palustris, has three loci of nitrogen fixation-like (NFL) genes with high sequence similarity to Mar, suggesting additional Mar-like enzymes with distinct roles. Here, we tested whether these NFL genes are required for VOSC assimilation in R. palustris. RNA-seq analysis revealed that all three NFL loci are upregulated under sulfur limitation, supporting a role in sulfur assimilation. Only disruption of the NFL genes encoded by RPA2634-37, renamed marBHDK1, caused fitness defects with EMS, DMS, and dimethylsulfoniopropionate (DMSP) as sulfur sources, indicating a functional Mar enzyme. The NFL genes RPA2347-48 and RPA2353-54, renamed marKD2 and marHB2, were required for activity with MT-EtOH or ethanethiol but not DMS, EMS, or DMSP. No activity was observed for the third locus, RPA2363-64, renamed nflDK. Overall, two Mar homologs in R. palustris are capable of VOSC reduction, one specialized for simple VOSCs and the other preferring a substrate with an additional functional group.

Water availability is critical for plants and their microbial communities, including pathogens. The plant pathogen Phytophthora cinnamomi persists in soils with fluctuating moisture, yet cellular responses to water limitation remain poorly understood in Phytophthora and oomycetes more broadly. Although we recently characterized the proteomic response of P. cinnamomi to NaCl-induced osmotic and ionic stress, its response to PEG-mediated water limitation remains poorly understood, leaving a critical gap in our understanding of drought-relevant stress adaptation. Here, we quantified mycelial growth and profiled time-resolved proteome dynamics of P. cinnamomi during polyethylene glycol (PEG-3350)-treatment, simulating moderate water limiting conditions. Treatment with 5% PEG-3350 enhanced radial mycelial growth relative to controls, with no early growth inhibition observed. Label-free proteomics identified 1,097 protein groups, with 880 proteins shared between conditions and an asymmetric abundance profile dominated by decreasing protein abundance over time. Only a small subset of proteins increased, mainly enzymes involved in redox buffering (e.g., thioredoxin and glutaredoxin-like proteins) and mitochondrial/metabolic regulation (e.g., alternative oxidase) and mitochondrial/metabolic regulation. Hierarchical clustering revealed a potential three-phase temporal program: early translational and regulatory remodeling (1-6 HPT), sustained metabolic adjustment (6-12 HPT), and delayed engagement of redox and proteostasis functions (12-24 HPT). Network analysis demonstrated that redox-associated function was integrated throughout this adaptation, with individual clusters further specialized by cofactor preference (NADP- versus NAD-dependent enzymes) and distinct metabolic roles (malate dehydrogenase, CoA-ligase activity). This coordinated, multi-phase reorganization sustained mycelial growth despite moderate osmotic stress, indicating that P. cinnamomi employs active proteomic adaptation rather than passive stress tolerance. These findings reveal the cellular mechanisms underlying drought persistence in this invasive pathogen and suggest molecular targets for disease management under water-limited conditions.

Microbial communities are dynamic, adaptive ecosystems whose collective behavior emerges from metabolic interactions such as cross-feeding, competition, and cooperation, rather than taxonomic diversity or individual metabolic potential alone. This distinction is clinically significant in the postmenopausal urinary tract, where recurrent urinary tract infections (rUTIs) are associated with complex, persistent infection dynamics including multiple contributing bacterial species. The ability of resident microbial communities to prevent pathogen establishment, known as colonization resistance, is increasingly attributed to the metabolic interactions within the urobiome itself rather than any single resident species. However, current approaches, such as taxonomic profiling and classical differential abundance analysis, can only partially describe the presence or maintenance of such interactions. Consequently, the community-level metabolic architecture determining pathogen resistance remains incompletely understood. To address this gap, we developed PhenoRewire, a network-based framework that quantifies how metabolite co-variation is rewired between biological states using untargeted metabolomics data. We applied this framework to an induced pluripotent stem cell (iPSC) urothelial organoid-derived barrier co-cultured with synthetic urobiome communities as a model of urobiome-pathogen dynamics relevant to rUTIs in two approaches. In an infection model, clinically isolated uropathogens Escherichia coli and Enterococcus faecalis, were co-cultured with a three-member urobiome community consisting of Lactobacillus gasseri, Lactobacillus crispatus, and Gardnerella vaginalis. Here we show how E. coli drove the metabolic reorganization, while E. faecalis amplified it disproportionately. PhenoRewire disentangled the 6-fold metabolic network amplification mediated by E. faecalis as a metabolic facilitator, revealing an emergent urobiome-pathogen co-variation architecture (1,781 vs 227 edges) not recapitulated by either community alone. Moreover, in a six-member urobiome single-strain dropout experiment, we revealed that removal of the sole Actinomycete Winkia anitrata caused significant network collapse (Louvain modularity falls from 0.707 to 0.038), identifying it as the single non-redundant keystone of the community. More broadly, these results demonstrate how untargeted metabolomics co-variation network analysis can be applied to defined synthetic urobiomes in combination with a urothelial host model to elucidate community dynamics. This framework provides a template that can be extended beyond the urobiome to investigate any complex microbial community where ecological behavior remains an open question.

Genetic variation among microbial strains of the same species can profoundly influence their phenotypes, ecological functions, and impacts on human health. Traditionally, the relative abundance of a species has been used to identify associations between the microbiome and disease. However, this approach overlooks intra-species genetic variation and is susceptible to spurious correlations arising from the compositional nature of abundance data and microbial load. Fast, k-mer-based algorithms can now accurately estimate strain-level Average Nucleotide Identity (ANI) in metagenomes. Despite its value as an orthogonal metric for strain-level analysis, methods for conducting ANI-based association studies remain limited. To address this, we developed StrainSpy, a statistical algorithm that identifies associations between containment ANI and variables of interest across a wide range of study designs, including longitudinal and multi-cohort designs. Re-analysis of a study examining gut microbiota recovery in 12 healthy adults following antibiotic exposure revealed novel strain-level associations, including a reduction in strain-level diversity despite species persistence. Applying StrainSpy to a multi-cohort analysis of 3,414 colorectal cancer metagenomes identified novel strain-level associations with colorectal cancer. However, in a separate collection of microbiome-immunotherapy studies, no individual strain was consistently associated across cohorts. Importantly, across both datasets, StrainSpy informed containment ANI-based machine learning models achieved comparable accuracy to traditional abundance-based methods. StrainSpy is publicly available as an R package github.com/gtonkinhill/strainspy.

Amplicon sequencing of the 16S rRNA gene is the most widely used approach for profiling bacterial communities, but its taxonomic resolution is typically limited to the genus level. Many species carry multiple divergent 16S rRNA alleles that overlap across species boundaries, an ambiguity that even full-length, long-read sequencing cannot fully resolve. Shotgun metagenomics achieves species-level resolution but remains costly, particularly when only a single genus is of interest. Amplicon sequencing of rapidly evolving, protein-coding housekeeping genes offers a cost-effective alternative, yet no tool exists to identify suitable primer sets for a given target taxon. Here we present AmPair, a Snakemake pipeline that, given a target genus and one or more candidate housekeeping genes, designs and ranks primer pairs binding conserved regions while flanking a variable region capable of species-level discrimination, and validates them in silico across all available genomes. Using the genus Bacillus and the housekeeping gene tuf as a case study, the primer set recommended by AmPair amplified 99% of 2,392 genomes; only 0.04% carried multiple alleles and none showed inter-species allele overlap, compared with 91.41% and 69.49%, respectively, for the standard 16S rRNA V1-V9 region. Applied to a Bacillus community profiled by Nanopore sequencing, the same primers resolved closely related species. AmPair thus offers a generalizable and accessible route to species-level community profiling.

Enterococcus faecalis is an opportunistic pathogen and facultative anaerobe that primarily relies on fermentative metabolism to colonize a wide range of aerobic and anaerobic environments. In the presence of exogenous heme, E. faecalis can assemble a minimal electron transport chain consisting of membrane-associated primary dehydrogenases, demethylmenaquinone, and the terminal cytochrome bd oxidase (CydAB). This respiratory chain is thought to generate a proton motive force to drive ATP synthesis via the F-type ATP synthase, thereby improving energy conservation under aerobic conditions. However, a cytosolic NADH oxidase (Nox) also consumes NADH and oxygen, potentially competing with the electron transport chain for reducing equivalents and terminal electron acceptors; but the relative physiological contributions of these two oxygen-reducing pathways remain poorly understood. To define the roles of CydAB and Nox under normoxic and hypoxic conditions, we constructed {Delta}cydAB and {Delta}nox mutants. Real-time, in situ measurements revealed {Delta}cydAB had no significant effect on oxygen utilization while in the {Delta}nox it was significantly reduced; revealing Nox as the major consumer of oxygen. Semi-untargeted metabolomic analysis further revealed oxidase-specific alterations in central metabolism with the {Delta}nox causing pronounced shifts in the ATP and NADH ratios; highlighting Nox as a key determinant of intracellular redox and energy homeostasis. Finally, single-cell fluorescence microscopy showed that membrane potential, a component of proton motive force, was substantially diminished only in the absence of both CydAB and Nox, or the F-type ATP synthase. These findings indicate that the F-type ATP synthase is a major generator of proton motive force, even upon aerobic growth, and demonstrate a complementary role for the electron transport chain and Nox in the bioenergetics of E. faecalis.

Antibiotic-induced disruption of plant-associated microbiomes has the potential to alter host health beyond the directly exposed generation, yet whether the effects of dysbiosis are transmitted through the seed microbiome remains unknown. Here, we investigated the intergenerational impacts of streptomycin-induced dysbiosis in tomato (Solanum lycopersicum), demonstrated that seed microbiome transfer (SMT) restores progeny microbiome function and disease resistance, and characterized the underlying physiological and genetic mechanisms. Parental streptomycin exposure altered the composition of progeny rhizosphere bacterial communities, reduced expression of defense-associated genes, and increased susceptibility to Xanthomonas perforans. Suppression of immune gene expression was strongly associated with increased disease severity, indicating that parental dysbiosis impaired progeny plants ability to mount effective immune responses. Transfer of the seed microbiome from healthy plant donors partially restored rhizosphere community composition, reduced disease severity and recovered defense gene expression of three genes. Together, our findings demonstrated that antibiotic exposure microbiome disturbance generates intergenerational legacy effects that influence plant immunity and disease susceptibility and seed microbiome transfer can counteract this dysbiosis across generations.

Ctenophores and placozoans arose early in metazoan evolution and are characterized by traits associated with key aspects of animal evolution. Despite the evolutionary significance of ctenophores and placozoans, their RNA viromes are poorly understood. To determine the diversity and evolution of RNA virome in these organisms, particularly whether the viruses present with these ancient host lineages similarly occupy basal phylogenetic positions, we analysed publicly available transcriptome data from the Sequence Read Archive (SRA). Accordingly, we identified 26 putative novel viruses classified into 11 virus groups, including members of the families Flaviviridae and Chuviridae. The novel viruses clustered with those previously identified in vertebrates, invertebrates, plants and fungi. Notably, some virus sequences within the Flaviviridae, Chuviridae, Lispiviridae and Marnaviridae were highly divergent, branching deeply relative to their closest known relatives or forming distinct lineages, in some cases suggesting a divergence early in metazoan evolution. In contrast, viruses within the Birnaviridae, Endornaviridae, Mymonaviridae, Narnaviridae, Phasmaviridae, Orthomyxoviridae, Orthototiviridae, and some viruses within the Picornavirales, exhibited patterns consistent with more recent diversification and host jumping. In addition, RNA viruses were detected across multiple species and tissues within the Ctenophora (including whole organisms and embryos) and Placozoa, expanding their host range and highlighting a largely uncharacterized diversity. Together, these findings expand the known diversity and host range of several virus groups, and shed light on virus evolution in early metazoans, demonstrating both host jumping within aquatic environments and virus host-associations that may span the entirety of animal evolution.

Zinc is an essential micronutrient at low concentrations, yet it becomes toxic at slightly higher ones. This is exploited by plants as an effective defensive strategy. However, the molecular components that are involved zinc-mediated immunity remain poorly defined. Here, we show that mixed-linked {beta}-1,3/1,4-glucans naturally occurring in microbial and grass cell walls and used as an agrobiological solution, trigger zinc accumulation in the Arabidopsis apoplast and upregulate the expression of the zinc transporters HMA2 and HMA4. This response occurs independently of salicylic acid, jasmonic acid and ethylene-mediated signalling pathways, but it requires the LysM receptor kinases CERK1, LYK4 and LYK5, indicating a specific pattern triggered immunity-associated mechanism. We further demonstrate that hma2hma4 mutants display constitutive activation of a broad set of defence-related genes, yet this transcriptional reprogramming is insufficient to confer resistance against the necrotrophic fungus Plectosphaerella cucumerina BMM. Moreover, metabolomic profiling highlights the contribution of specialized metabolites to this defective defence output. Altogether, our findings reveal that zinc-mediated toxicity constitutes a defence mechanism integrated into the immune response triggered by specific microbial or damage associated molecular patterns.

Rinsing-dependent dental hygiene presents a significant public health challenge in water-scarce environments. This study investigated combinations of xylitol (Xyl), chitosan (Chi), glycyrrhizin (Gly), epigallocatechin gallate (EGCG), dicalcium phosphate (DCP), and nano-hydroxyapatite (nHA) on the primary bacteria behind dental caries, S. mutans. These combinations were assessed for markers of dental caries by biofilm reduction, bacterial killing, and acid buffering against S. mutans when applied to an in vitro simulated enamel model using glass bead surfaces for biofilm formation, and gene expression was subsequently examined via RT-qPCR. Separately, mineral retention was also quantified. The EGCG-DCP-Xyl film demonstrated the highest overall efficacy, achieving a significant reduction in biofilm concentration compared to the untreated control and performing similarly in magnitude to the positive toothpaste control. Dead fluorescence staining confirmed that the EGCG-DCP-Xyl film induced the highest rate of non-viable cells, followed by the Chi-Gly film and the Gly-Xyl film. During 10-day pH cycling, the EGCG-DCP-Xyl and DCP-Xyl formulations buffered pH the most, consistently maintaining mean pH levels safely above the demineralization threshold of pH 5.5. The EGCG-DCP-Xyl also optimized mineral stability with the highest retained calcium concentration, significantly outperforming the Chi-Xyl film. At the transcript level, the EGCG-DCP-Xyl film induced substantial downregulation of key virulence genes, yielding decreases in expression for glucosyltransferase B (gtfB), associated with biofilm synthesis, collagen-binding protein (cnm), associated with tissue invasion, and lactate dehydrogenase (ldh), associated with lactic acid production, compared to the untreated control, with effects comparable in magnitude to the positive toothpaste control. This research suggests that targeting bacterial pathways and mineral loss through a portable film may have potential for preventing dental caries, especially in environments where water is limited. However, additional studies are necessary to evaluate real-world effectiveness.

Constructing microbial association networks is a common strategy for exploring relationships among taxa in microbiome studies. Although marginal correlation methods are easy to implement and allow formal inference, they can produce spurious edges driven by indirect associations through other taxa. Conditional graphical-modeling methods aim to recover direct associations, but many rely on Gaussian or linear assumptions and often provide limited uncertainty quantification. We propose a conditional, nonparametric approach based on the scaled expected conditional covariance (SEcov). SEcov measures population-level conditional association by residualizing each taxon with respect to the remaining taxa and scaling the resulting expected conditional covariance. The resulting estimator can incorporate flexible machine-learning methods for conditional-mean estimation and admits asymptotic normal inference, enabling p-values and confidence intervals for taxon-pair associations. We demonstrate through simulation studies that our proposed approach improves network recovery relative to other methods, and we illustrate the new method via construction of a co-occurrence network for the vaginal microbiome during pregnancy. IMPORTANCEHigh-throughput sequencing has made it possible to characterize microbial communities at large scale, and network analysis is widely used to summarize relationships among taxa. However, networks based on marginal correlations may include indirect associations, whereas many conditional graphical models rely on assumptions that may be difficult to justify for sparse, zero-inflated, compositional microbiome data. SEcov offers a practical alternative by estimating conditional associations nonparametrically and attaching inferential uncertainty to individual edges. This allows investigators to construct microbiome networks using statistically interpretable evidence for taxon-pair associations, rather than relying solely on arbitrary correlation cutoffs or regularization tuning parameters.

The Bacillus cereus group comprises bacteria of biotechnological interest, but also raises health concerns. Some bacteria in this group are opportunistic human pathogens, mainly causing foodborne gastrointestinal infections. As of today, the presence, sequence variability, or expression of genes encoding toxins or other virulence factors are insufficient to predict the potential of a given isolate to cause the diarrheal form of the disease. To address this limitation, we developed a sandwich ELISA to quantify the NheA and Sphingomyelinase (SMase) proteins in culture supernatants to test them as markers of pathogenic potential. Application of the assay to a collection of B. cereus group isolates revealed that strains associated with food poisoning outbreaks produce significantly more NheA and SMase than those isolated from the environment or from commercial products. Statistical analyses show that the combined quantification of NheA and SMase provides robust discrimination between pathogenic and non-pathogenic (environmental and commercial) profiles. These results demonstrate that the quantitative assessment of both NheA and SMase production can serve as a reliable biomarker for distinguishing diarrheic food poisoning isolates from harmless strains.

1. Forest canopies harbour strong microclimatic gradients that shape plant performance, species interactions and ecosystem processes. Yet, despite renewed interest sparked by global change, forest canopies remain difficult-to-access experimental spaces. 2. With the goal to expand access to tree canopies as experimental arenas, we designed, built, and tested TreeTOP, a standardized experimental platform that opens canopy space for manipulative ecological experiments, specifically with potted plants. TreeTOP features lightweight aluminum frames placed in mature tree canopies non-invasively, allowing potted plants to be placed in three different heights, ground level, shade canopy, and sun canopy. 3. We implemented TreeTOP using two contrasting infrastructure concepts to demonstrate its applicability in both highly equipped canopy research facilities and forests without permanent canopy infrastructure. One installation relied on a canopy crane, grid power and fully automated irrigation, whereas the second was built by certified tree climbers and was equipped with an autonomous solar-powered, battery-operated irrigation system. At both sites, environmental sensor networks monitor the experiment. 4. TreeTOP successfully reproduced characteristic canopy microclimatic gradients, including increasing light availability, daytime air temperatures and thermal extremes with canopy height. Despite differing infrastructures, both implementations generated comparable microclimatic patterns, demonstrating that standardized canopy experiments are feasible in forests with or without permanent canopy access. By opening canopy space for manipulative experiments, TreeTOP provides a transferable framework for investigating plant performance, phenology, species interactions and microbiome assembly under realistic forest conditions.