npj Biofilms and Microbiomes

Biofilm represents a complex aggregation of bacteria embedded within a self-produced extracellular polymeric substance (EPS). We investigated the characteristics of mycobacterial biofilm using Mycobacterium smegmatis (Msm) as model organism. By combining transcriptomic (RNA-seq) and proteomic (LC-MS) analyses, the research captures dynamic changes during the establishment and maturation of the biofilm. Transcriptomics analysis showed a distinct gene expression profile as compared to its planktonic form. Interestingly, clear differences were seen between initial (~2-day old) and mature (~5-day old) biofilm stages, highlighting phasic gene expression throughout biofilm development. Marked alteration in oxidative stress-related genes and energy metabolism from ATP to NADH was observed. Furthermore, quantitative mass spectrometry-based proteome examination of EPS showed an abundance of cytoplasmic proteins present differentially between initial and mature biofilm stages. Pathway enrichment revealed enhanced oxidative stress responses and metabolic shifts in mature biofilms, including upregulation of NADH dehydrogenase and downregulation of ATP synthase, indicating altered energy metabolism. Our findings thus provide insights into the molecular adaptations, including production of mycofactocin, occurring during mycobacterial biofilm establishment and maturation, and advance our understanding of mycobacterial biofilm physiology.

Periodontitis, a chronic inflammatory disease affecting approximately 40% of U.S. adults aged 30 years and older, is characterized by dysbiosis of the dental plaque microbiome. However, although scaling and root planing (SRP) is the cornerstone of periodontal treatment, its effects on the taxonomic composition and functional potential of the dental plaque microbiome remain incompletely understood. In this study, we used whole-metagenome shotgun sequencing to characterize taxonomic composition and functional potential in dental plaque microbiomes collected from 39 patients with Stage II or III generalized periodontitis before and 3-4 months after SRP. Consistent with clinical improvement, periodontal therapy significantly reduced bleeding on probing and plaque index. Whole-metagenome shotgun sequencing identified 3.18 million non-redundant genes and 12,353 microbial species across 78 samples, revealing increased gene and species richness after treatment, along with a significant restructuring of microbial community. Established periodontal pathogens, including Porphyromonas gingivalis and Tannerella forsythia, as well as the emerging pathogen Escherichia coli, decreased following treatment, whereas health-associated early colonizers, including multiple Actinomyces species and Streptococcus cristatus, increased. Functional annotation using the Carbohydrate-Active Enzymes (CAZy) database identified treatment-associated differences in several carbohydrate-active enzymes, including multiple glycosyltransferases, indicating remodeling of the predicted functional potential of the dental plaque microbiome. These findings demonstrate that successful SRP promotes coordinated taxonomic and predicted functional remodeling of the dental plaque microbiome and highlight the value of shotgun metagenomic sequencing for characterizing both taxonomic and functional recovery following periodontal therapy.

The architecture of Bacillus subtilis biofilms is influenced by the coordinated regulation of cellular specialization, matrix assembly, and metabolism. B. subtilis can form different types of biofilm in diverse physical and chemical environments. Understanding the molecular mechanisms that drive biofilm heterogeneity and adaptation to different environmental niches is crucial for developing more effective strategies to control their formation. In this study, we developed a tightly dual-regulated CRISPR interference (CRISPRi) system and employed multi-scale imaging to investigate the functions of individual genes in two distinct biofilm models: the floating pellicle and the intricate, three-dimensionally structured macrocolony, which develop at the liquid-air and solid-air interfaces, respectively. Our findings validated the CRISPRi approach as a powerful method for studying biofilm development over extended periods and revealed that numerous small non-coding RNAs are involved in regulating biofilm growth dynamics and architecture. The CRISPRi approach was also applied to a pool of 507 genes and transcription units, including protein-coding genes and non-coding RNAs, to screen for cell fitness in these two biofilm models. We discovered that, while both biofilm forms rely on fundamental processes such as cell wall synthesis and nucleotide metabolism, they exhibit different genetic dependencies with regard to matrix composition, motility, and signaling. Exopolysaccharide production, motility, and chemotaxis are crucial for pellicle formation. In contrast, macrocolony development is influenced by {gamma}-polyglutamate synthesis and nutrient acquisition functions. Genes of unknown function were also identified to play a differentially important role in the two biofilm forms. Additionally, the CRISPRi screens revealed further non-coding RNAs regulating biofilm architecture and growth dynamics, adding to the existing layers of post-transcriptional control. Collectively, these results demonstrate that biofilm formation at different physical interfaces is governed by a combination of shared and unique genetic pathways tailored to the specific biofilm environment, thereby opening research avenues into the molecular mechanisms specific to the solid-air and liquid-air interfaces.

Blood banks represent highly controlled healthcare environments where microbiological surveillance has traditionally focused on blood products rather than environmental microbial reservoirs. Despite their critical role in transfusion safety, the ecology of surface-associated microorganisms and the persistence traits that enable their long-term survival remain poorly understood. Here, we combined scanning electron microscopy, culture-based microbiology, phenotypic characterization, MALDI-TOF mass spectrometry, and whole-genome sequencing to investigate whether surfaces within a public blood bank facility constitute reservoirs of environmentally derived bacteria with enhanced persistence potential. Samples collected from a public blood bank in Tucuman, Argentina yielded 37 culturable bacterial isolates, predominantly Gram-positive environmental taxa together with a limited number of opportunistic Gram-negative species. More than 30% of the isolates exhibited multidrug resistance, while several strains displayed strong biofilm formation, amyloid-like fiber production, motility, and hemolytic activity, indicating multiple phenotypic strategies associated with long-term surface persistence. Whole-genome sequencing of six representative isolates confirmed species identity, identified genes related to antimicrobial resistance, adhesion, biofilm formation, stress adaptation, and cytotoxicity, and revealed frequent genotype-phenotype discordance, highlighting the importance of integrating genomic and phenotypic analyses. Notably, one isolate exhibited less than 92% average nucleotide identity with publicly available genomes, suggesting the presence of a previously undescribed environmental species. Thus, blood bank surfaces function as selective ecological niches favoring bacteria with persistence-associated traits rather than simply reflecting contamination from blood products. These microorganisms may constitute latent biosafety hazards if environmental barriers fail, particularly in facilities handling biological materials intended for vulnerable patients. Our results support the incorporation of integrated bioimaging, phenotypic characterization, and genome-resolved environmental surveillance into infection prevention strategies and transfusion biosafety programs within a One Health framework.

Wastewater metagenomic sequencing (WW-MGS) enables simultaneous detection of hundreds of pathogens, but its use for quantitative pathogen tracking has not been robustly validated. Like wastewater PCR (WW-PCR), WW-MGS is affected by biases from variable fecal dilution and sample processing, but must additionally contend with the compositional structure of sequencing data, where a taxon's apparent abundance depends on the abundance of every other taxon in the sample. Simple summaries such as a pathogen's fraction of total reads may therefore be poorly suited to quantitative use. We retrospectively evaluated seven normalization approaches that attempt to control for these sources of bias against a baseline of total read relative abundance, using 1,425 samples from the CASPER consortium spanning 25 U.S. sites. Each approach was compared against WW-PCR and clinical data across eight total pathogens. Among the normalization strategies we evaluated, tobamovirus markers, diet-derived plant viruses abundant in human stool, performed best. Normalizing WW-MGS data by tobamovirus-genus counts improved median site concordance for 18 of 19 pathogen and comparison-source combinations. Gains were largest for year-round-circulating SARS-CoV-2 and norovirus and smaller for sharply seasonal pathogens such as influenza and respiratory syncytial virus, where baseline concordance was already high. Tobamovirus normalization rarely degraded concordance, with median gains roughly five times larger than median losses. Tobamovirus-normalized WW-MGS reached clinical concordance comparable to targeted WW-PCR, supporting its use as a quantitative trend-monitoring tool alongside pathogen-agnostic detection.

Background: Early-onset colorectal cancer (EOCRC) is increasing globally, particularly among Hispanic/Latino (H/L) populations, yet the contribution of tumor-colonizing microbiota to age-associated colorectal cancer (CRC) biology remains poorly understood. Most microbiome studies have focused on fecal communities or non-Hispanic populations, leaving the intratumoral microbial landscape of H/L patients largely unexplored. Methods: We performed an exploratory characterization of tumor-colonizing microbiota using whole-exome sequencing (WES) data from four primary colorectal tumors obtained from H/L patients treated at City of Hope, including two EOCRC (<50 years) and two late-onset colorectal cancer (LOCRC; [&ge;]50 years) cases. Following removal of host-derived sequences, microbial taxonomic profiling was conducted at the family, genus, and species levels, and microbial metabolic pathways were inferred. Clinical and pathological data were integrated to evaluate age-associated differences in microbial composition and predicted function. Results: Family-, genus-, and species-level analyses consistently demonstrated greater microbial diversity in LOCRC than EOCRC. LOCRC contained more than twice the number of unique bacterial families, nearly three times as many unique genera, and more than twice as many unique bacterial species. A conserved core microbiota, including Fusobacteriaceae, Prevotellaceae, Fusobacterium, and Prevotella, was identified across both age groups, whereas LOCRC was enriched in CRC-associated taxa including Fusobacterium nucleatum, Bacteroides fragilis, Parvimonas micra, Porphyromonas asaccharolytica, and Dialister pneumosintes. Species-level analyses revealed only a single shared bacterial species between EOCRC and LOCRC, indicating progressive microbial divergence with increasing taxonomic resolution. In contrast, functional profiling identified 11 predicted microbial metabolic pathways, of which nine were shared between age groups, two were unique to EOCRC, and none were exclusive to LOCRC. Core metabolic pathways involved in energy metabolism, amino acid biosynthesis, phospholipid metabolism, and central carbon metabolism exhibited comparable abundance across both groups, demonstrating substantial functional conservation despite pronounced taxonomic differences. Conclusions: Tumor-colonizing microbiota differ markedly between EOCRC and LOCRC in H/L patients, with late-onset tumors exhibiting substantially greater microbial richness and taxonomic complexity. Despite these compositional differences, microbial metabolic functions remain largely conserved, supporting the concept of functional redundancy within the colorectal tumor microenvironment (TME). Although exploratory, this proof-of-concept study provides one of the first characterizations of intratumoral microbiota in H/L EOCRC and establishes a foundation for larger multi-omics investigations aimed at identifying microbiome-based biomarkers and therapeutic targets for precision oncology.

Biofilms on aquaculture infrastructure harbor diverse microbial communities that may influence water quality and fish health, yet the temporal dynamics of these communities remain poorly characterized. Here, we used 16S rRNA gene amplicon sequencing to profile biofilm communities on concrete raceway surfaces across an 80-day rainbow trout (Oncorhynchus mykiss) indoor hatch-house production period. One hundred twenty-three wall swab samples from 19 raceways at six time points (9, 23, 38, 53, 65, and 80 days) were analyzed after stringent quality control. Beta diversity analyses revealed that biofilm communities at each time point were significantly distinct (PERMANOVA, p < 0.001 for all pairwise comparisons), with early communities exhibiting greater variability than late-stage biofilms. Total bacterial load increased approximately 2.5-fold from early to late stages (qPCR, p < 0.001). Differential abundance testing (ANCOM-BC) identified 57 differentially abundant genera between early-and late-stage biofilms, and random forest classification distinguished early from late communities with over 93% test accuracy. A clear successional trajectory emerged: early biofilms were dominated by pioneer taxa including Pseudomonas, Caulobacter, and Flavobacterium; mid-succession communities featured predatory Bdellovibrio and the methylotroph Methylotenera; and mature biofilms were enriched in saprophytic Saprospiraceae and Haliscomenobacter, polysaccharide-degrading Verrucomicrobiaceae, and cooperative predatory myxobacteria. Flavobacterium columnare, a pathogen of concern in aquaculture, was detected at low levels throughout the production period. These results demonstrate predictable ecological succession in freshwater built environment biofilms and provide a foundation for understanding the role of surface-associated microbial communities in hatchery management.

With the rapid expansion of global food demand, aquaculture has become a critical pillar for future food security. However, aquaculture systems remain highly vulnerable to pathogenic bacteria, and rapid identification of antagonistic microbes is essential for sustainable disease control. Conventional evaluation approaches rely on fluorescence labeling or post-culture assays, limiting the ability to quantify dynamic interactions in mixed microbial populations in a real-time and label-free manner. Here, we propose a computational framework for classifying the mixing ratio of Vibrio harveyi and environmental bacteria using time-series motion features extracted from microscopy videos. We defined 24 interpretable motility descriptors and employed a Temporal Convolutional Network (TCN) to learn their temporal structure. The proposed method achieved a classification accuracy of 93.3%, outperforming conventional static statistical approaches and alternative machine learning models. These findings indicate that mixture discrimination in microbial communities is governed not by absolute motility magnitude, but by collective alignment and its temporal stability. Our study establishes a time-resolved computational framework for quantifying dynamic collective order in mixed microbial populations and highlights its potential for label-free automated screening and robotic microbiological applications.

The human gut microbiome harbours a diverse community of microeukaryotes, predominantly fungi, which may potentially play important roles in gut ecology and homeostasis. Despite their potential, the study of gut microeukaryotes has been hampered by the limited sensitivity of standard sequencing approaches, which struggle to capture DNA from low-abundance microorganisms against the overwhelming background of bacterial biomass. To address this, we developed a method to selectively enrich for microeukaryotic cells in human faecal samples by depleting bacterial cells prior to metagenomic sequencing. Through systematic comparison and optimisation at each processing step, we established a robust standard operating procedure (SOP) for microeukaryotic cell enrichment. By benchmarking this SOP across eight human faecal samples with three technical replicates each, we showed that it consistently increased microeukaryote representation in metagenomic libraries, greater microeukaryotic taxonomic diversity, and a reduced proportion of unclassified taxa. Together, these improvements enabled substantially deeper characterisation of the microeukaryotic fraction of the human gut microbiome.

Background: Urinary tract infections (UTIs) rank among the most common infections globally, with many linked to indwelling urinary catheters. Our prior culture-based longitudinal evaluation of long-term catheterized nursing home residents revealed persistent asymptomatic colonization by pathogens and demonstrated that CAUTI onset was not necessarily due to new pathogen acquisition. In this study, we optimized metagenomics methods to examine the ecological structure underlying persistent colonization and the transition to infection. Results: We present a comprehensive longitudinal metagenomic analysis of catheterized urine specimens, revealing colonization dynamics of 69 microbial species across 198 samples from 9 individuals. Descriptive ecological metrics were combined with Bayesian mixed-effects models that accounted for repeated within-participant sampling to identify clusters of co-occurring species, determine the impact of perturbations such as antibiotic exposure and catheter changes on community structure, and identify taxa predictive of infection sign and symptom onset. Longitudinal specimens clustered into three main ecological phenotypes: 1) moderate diversity, unstable communities (3 participants); 2) high diversity, stable communities that resisted disruption even after multiple catheter changes (3 participants); and 3) low diversity, pathogen-dominated communities (3 participants). Catheter changes alone did not significantly disrupt community composition, while antibiotic exposures induced major shifts often followed by re-colonization with the same genera within subsequent weeks. Six clusters of species were identified for which relative abundances correlated across perturbations to the microbial community, including a mutually exclusive Enterobacterales cluster and fastidious-anaerobe group cluster. 24 species were found to correlate with onset of signs and symptoms of infection, 11 of which were missed by standard urine culture. Conclusions. The catheterized urinary tract represents a novel ecosystem that is resilient to disruption by catheter changes but susceptible to antibiotic perturbation. Antibiotic exposure did deplete all species associated with signs and symptoms but also depleted potentially benign microbes. Our findings have direct implications for catheter management protocols and antibiotic stewardship in long-term catheterized patients. Prospective evaluation using this framework in a larger cohort can help translate these ecological insights into clinical decision-making tools.

Pre-harvest litter management is a key determinant of broiler production conditions, influencing NH3; generation, pathogen exposure, nutrient retention, and microbial reservoirs that accumulate across production cycles. Conventional chemical and physical management strategies can support flock health, but their effects on pathogen-associated bacterial populations are often transient and may not account for the microbial interactions that govern persistence, exclusion, and community succession. Here, we evaluated an alternative litter management strategy combining IndigoLT pre-/postbiotic with reduced-rate NaHSO4; across two broiler growouts, with litter sampled at the end of each flock to determine impact on prokaryotic microbiome structure, physicochemistry, and Enterococcus abundance. Alternative management influenced observed richness, phylogenetic diversity, community composition, and co-occurrence network structure while reducing the relative abundance of Enterococcus, including E. cecorum and E. hirae. Digital PCR corroborated sequencing-based Enterococcus abundance patterns, although 16S-based treatment effects were not always reflected as lower absolute copy number at terminal sampling, consistent with reduced proportional dominance rather than sustained absolute suppression. Complementary biofilm- and growth-inhibition assays performed with IndigoLT demonstrated context-dependent antibiofilm and bacteriostatic activity against reference and poultry-derived Enterococcus isolates, with stronger responses for E. cecorum than E. hirae and bactericidal-level reductions in viable recovery at higher exposure levels. These findings demonstrate that biologic-based litter management can alter microbiome structure and pathogen-associated taxa under commercial production conditions, providing a basis for microbiome-informed amendment strategies aimed at reducing pathogen load and supporting broiler health.

Biocontainment systems designed to attenuate the spread of mobile DNA are challenging to evaluate within microbiomes of engineered environments. To better understand how toxin-based biocontainment systems affect horizontal gene transfer (HGT) in a microbiome, we evaluated the host range of pairs of plasmids using orthogonal catalytic RNA (cat-RNA) that amend distinct barcodes to 16S rRNA following HGT. We show that mobilizable (5 kb) and self-mobilizable (60 kb) plasmids, which use the same RP4 transfer machinery but different origins of replication, overlap in their host range when conjugated in parallel into a wastewater community, with 127 of the 143 amplicon sequence variants (ASVs) presenting barcoding signals from both plasmids (89%). We also find that mobilizable plasmids with or without the Escherichia coli CcdB toxin overlap in host range in a wastewater community. Among the two most abundant orders, CcdB attenuated the barcoding signal in Aeromonadales more consistently than Enterobacteriales, which have F plasmids containing the CcdB-CcdA toxin-antitoxin system used for biocontainment. Also, CcdB decreased the abundance of the mobilizable plasmid by >100-fold and yielded mutations in 85% of the reads. Together, these findings reveal how pairs of plasmids expressing orthogonal cat-RNA can be used to monitor the effects of plasmid-encoded traits on mobile DNA persistence following HGT. They also highlight challenges when using biocontainment systems containing genes related to those found in the microbiomes targeted for engineering.

Consumption of ultra-processed foods is rising globally and has been implicated in inflammation and metabolic dysfunction, yet the impact of specific food additives on the human gut microbiota remains poorly understood. Using dietary data from the Food & You study (approximately 1000 participants in Switzerland), we identified 257 unique additives from 4,119 unique packaged products to quantify each participant's daily additive exposure. Higher exposure to a combination of high intensity sweeteners and sugar polyols, commonly found in low calorie products, was independently associated with reduced gut microbial Shannon diversity (beta = -0.39, p < 0.001), after adjustment for demographics, diet quality, BMI and bowel movement frequency. At a broader level, total additive exposure and fast food consumption were each negatively associated with gut microbial diversity; however, additive exposure remained independently associated and also specifically attenuated the diversity benefits of vegetable rich diets. Furthermore, microbial log ratio signatures linked to additive exposure showed strong negative correlations with Shannon diversity, including emulsifiers and thickeners (r = -0.66) and preservatives and antioxidants (r = -0.56). Integrating additive exposure with healthy dietary components such as HEI, fruits, or vegetables strengthened associations with gut microbial diversity; for example, vegetable linked correlations with Shannon diversity increased from r = 0.52 to r = 0.65 when contrasted against preservative-antioxidant exposure. Concordantly, microbial signatures associated with the sweeteners and sugar polyols additive combination showed depletion of fiber associated commensal taxa, and enrichment of pathways involved in polyol and aromatic compound metabolism. Notably, these associations emerged despite packaged foods representing only approximately 15% of logged dietary intake, underscoring the sensitivity of gut microbial diversity to limited exposure, and demonstrating that without integrating additive and processed-food metrics, one of the largest effect-size phenomena in human gut microbiota diversity would remain undetected.

The gut microbiota is crucial for immune development and overall health in chickens. In commercial production, birds routinely receive multiple vaccines during early life. While individual vaccines are known to affect microbial composition, the impact of complex, multi-vaccine programs, as used in the poultry industry, is not well understood. This longitudinal study examined the impact of multiple live and inactivated vaccines, given at commercially relevant times from an early age, on gut microbial diversity and composition in layer chickens. We characterised microbiota profiles using 16S rRNA gene sequencing at pre- and post-vaccination timepoints across different vaccine groups. Overall, microbial diversity remained stable across most vaccines, indicating strong resilience of the gut microbiota to repeated immunological interventions. Differential abundance analyses identified changes in selected bacterial taxa following vaccination, with responses varying among vaccine groups. Notably, these changes were not sustained, as the gut microbial community returned to a stable state after the vaccination schedule. These findings underscore the robustness of the chicken gut ecosystem and lay a foundation for future research into microbiome-vaccine interactions and their implications for poultry health, immunity, and production efficiency.

Intra-species genomic variation results from diversity-generating processes and supplies the raw material for subsequent natural selection. Environmental stress can be regarded as the ultimate accelerator of these processes, especially for microorganisms, which can alter their DNA if presented with nutrient limitation, toxins, or pathogen attack. Chronic intestinal inflammation, as in inflammatory bowel diseases (IBD), may be regarded as prolonged environmental stress for gut commensal bacteria, bringing a large number of enteric species down to undetectable levels. However, it remains unclear how the microbes that survive the IBD gut environment actually respond to IBD stress, and whether their stress response may leave a transient or permanent signature in their genomes. To investigate whether IBD stress induces and selects for certain genetic diversity, we performed metagenomic analyses on gut species in IBD patients and Controls. We focused on strain diversity within a single individual, which might be the result of more recent diversification processes under stress. We found measurable differences at the genome level between IBD and Controls, yet this was species-dependent. We then investigated gene-level diversity and found that certain functions were more likely to be enriched with either neutral divergence, functional divergence, or both. Functions that were enriched in IBD with both kinds of diversity were associated with motility and iron-scavenging, among others. These results may point towards functions that are under selection in the context of IBD stress, and could inform future mechanistic work, exploring previously unknown routes of bacterial diversification and adaptation to stress in the gut microbiome.

The ability of current spatial transcriptomics platforms to sensitively and specifically detect tissue-resident microbes alongside the whole host transcriptome remains limited. Here we present HOst MicrobE Spatial-seq (HOMES-seq), a Visium-based workflow for joint spatial profiling of microbial species and the host transcriptome in formalin-fixed paraffin-embedded (FFPE) colorectal tumours. HOMES-seq incorporates an analytical framework to distinguish contaminant-derived signals from bona fide tissue-resident microbes while improving detection sensitivity and reducing sequencing costs relative to existing approaches.

Caldimonas thermodepolymerans is a thermophilic polyhydroxyalkanoate (PHA)-producing bacterium with strong potential for sustainable bioplastic production. Besides serving as intracellular carbon and energy storage compounds, PHAs are increasingly associated with bacterial stress resistance and cellular robustness. This study aimed to investigate the physiological and transcriptomic response of C. thermodepolymerans to osmotic stress induced by elevated NaCl concentrations. Growth analysis demonstrated tolerance up to a supplementation of 2% NaCl, while moderate salt concentrations enhanced PHA accumulation, reaching 65% cell dry weight at 1.5% NaCl supplementation. To better understand the bacterial response to osmotic stress, RNA sequencing was performed under sublethal salt stress conditions. Differential expression analysis revealed major changes in genes related to osmoprotection, trehalose metabolism and type VI secretion systems, whereas motility and chemotaxis genes were strongly repressed. Phenotypic assays confirmed increased biofilm formation and reduced swarming motility under salt-induced osmotic stress. Although canonical PHA biosynthesis genes were not significantly differentially expressed, increased polymer accumulation suggests other underlying mechanisms linked to osmoadaptation. Together, these findings demonstrate that osmotic stress induces metabolic, physiological and regulatory responses in C. thermodepolymerans, highlighting the importance of PHA in stress adaptation besides its industrial applicability.

On their own, probiotics do not entirely eliminate pathogens during infection and disease. Instead, they often serve as adjuncts that rely on distinct mechanisms to reduce the presence of harmful bacteria. Our prior research indicates that an isolated Aeromonas dhakensis strain A603 kills pathogenic Vibrio strains through two antibacterial mechanisms: the type VI secretion system (T6SS) and phenazine (AdPhen). Here, we investigate A603 as a standalone probiotic for a shrimp disease model. This study shows that A603 prevents mortality from acute hepatopancreatic necrosis disease (AHPND) in shrimp caused by pathogenic Vibrio spp. that produce the PirAB toxin. AHPND infection alters the shrimp microbiota by increasing pathogen abundance and decreasing beneficial bacterial abundance prior to death. As both a prophylactic and treatment, A603 removes pathogenic Vibrio from shrimp and reverses such alterations in the microbiota using both T6SS and AdPhen. Collectively, our findings show that A603 antibacterial mechanisms prevent AHPND.

The human gut, containing 100 trillion microbes, is also considered the "second brain," having control over the different functions of the physiological system. With advancements in bioinformatics and the development of sequencing technologies, researchers are able to explore the diversity and functional implications of gut microbiota (GM), which have become strongly associated with a variety of diseases. Microbial imbalance, or dysbiosis, acts as a biomarker for early detection and prognosis of a disease. Artificial Intelligence and Machine Learning (AI/ML) methods, although extensively used in predicting GM associated diseases, are seldom translated to having practical real-world outcomes, necessitating the design of robust AI/ML models applicable in real-world scenario. We have therefore come up with designing stacking-based ensemble architectures (EM1 and EM2), developed by integrating multiple ML-based learning algorithms for improving disease prediction accuracy. The GM datasets, after split into training and test sets, were eventually fed into the proposed two-layer ensemble models, which combines the output from standardized base learners via a meta-classifier, strengthening classification robustness as well as ensuring consistency in optimized performance across diverse datasets. Both the proposed hybrid ensemble models have emerged to be superior performers over all baseline and deep learning models, with an average accuracy of 0.87 and 0.84 respectively. By combining multiple learners, the proposed ensemble models outperform traditional single-algorithm-based approaches to attain higher accuracy and robustness on complex GM datasets. Key messagesO_LIDevelopment of stacking-based hybrid ensemble models (EM), which can be employed to integrate different AI/ML algorithms with better prediction accuracy of gut microbiome (GM)-associated diseases. C_LIO_LIUse of independent GM datasets with preprocessing methods such as SMOTE and PCA to address class imbalance and high dimensionality. C_LIO_LIAll the proposed EM architectures are mostly superior to the existing state-of-the-art AI/ML methods (highest prediction accuracy: 0.87 and 0.84 with EM1 and EM2 models respectively) for GM diseases predictions. C_LIO_LIThe cross-cohort validation demonstrates high prediction accuracy and robustness, (AUC values close to 0.98 and 0.99, for EM1 and EM2). C_LIO_LIThese therefore demonstrate the effectiveness of EM frameworks for GM associated disease prediction, paving the way for corresponding applications in precision medicine. C_LI

The rhizosphere microbiome plays fundamental roles in plant health and productivity, yet the ecological rules governing microbiome assembly remain poorly understood. Here, we investigated early rhizosphere community assembly in tomato using a replicated combinatorial community coalescence framework, in which seven distinct natural bacterial communities were inoculated individually and in all possible pairwise and triplet combinations. Single inoculum communities clustered according to inoculum identity, indicating a strong effect of source community composition on assembly trajectories. However, when all communities were analyzed jointly, samples formed a continuous compositional landscape with no clear evidence of discrete community states. Despite major differences in source community composition, rhizosphere communities consistently converged toward the same uneven rank abundance structure, with two ASVs accounting for 50% and a median of nineteen ASVs for 90% of total abundance. While assembly was dominated by a very small number of Pseudomonas ASVs, limited evidence of alternative dominant states was observed. Increasing inoculum complexity did not increase stochasticity but instead promoted stronger convergence toward a global rhizosphere compositional centroid. Moreover, dominance hierarchies emerging from community coalescence closely mirrored the distance of source communities to this centroid. Communities derived from orchard soils consistently showed the highest dominance, suggesting that historical contingency and prior adaptation to horticultural crop rhizospheres may influence competitive success. Together, these results support the existence of a canonical rhizosphere attractor in both community composition and abundance architecture, with patterns consistent with assembly occurring under a limited number of dominant ecological niches imposed by the tomato rhizosphere.