ABSTRACT Endophytic bacteria are key components of plant microbiomes, enhancing host growth, stress tolerance, and defence mechanisms. Ten cultivable strains affiliated with Bacillaceae, including putative novel Priestia and Bacillus species, were previously isolated from Galium aparine L.'s tissues. All tolerated diverse levels of abiotic stresses, produced ammonia and auxins, as well as all exhibited strong hydrolytic enzyme activities (amylase, protease, xylanase, and pectinase), indicating robust metabolic versatility. These bacteria stand out as prolific producers of industrially relevant compounds. Priestia megaterium GR4 demonstrated high production of hydrolytic enzymes and biosurfactants, and most strains synthesized and accumulated polyhydroxyalkanoates (PHA), highlighting their potential as sustainable bioplastic producers. UPLC‐MS/MS confirmed koranimine production by Peribacillus frigoritolerans GR2. Previous genome mining studies revealed diverse biosynthetic gene clusters, including those for surfactin and fengycin. Overall, G. aparine endophytes represent powerful biological factories capable of producing a wide range of valuable compounds, including enzymes, biosurfactants and biopolymers, with strong potential for applications in industrial biotechnology, sustainable agriculture, and biocontrol.
ABSTRACT Antimicrobial resistance (AMR) is a major threat to global health and resistant bacterial populations have been observed to develop and spread in and around wastewater. However, in vitro studies on AMR development are typically conducted in ideal rich media conditions, which can differ in composition and nutrient density from wastewater. In this study, we compare the growth and AMR development of E. coli in a synthetic wastewater recipe to autoclaved wastewater samples from the Massachusetts Water Resources Authority (MWRA). We found that synthetic wastewater and real wastewater samples both supported less bacterial growth compared to LB broth and had similar susceptibility profiles to antibiotic pressure from Doxycycline, Ciprofloxacin and Streptomycin. More importantly, unlike in LB broth, AMR development over time during continuous passaging under subinhibitory antibiotic pressure in pH‐adjusted synthetic wastewater was similar in fold change to real wastewater samples. Thus, we suggest that synthetic wastewater is a more accurate predictor of both E. coli growth and antibiotic resistance development in wastewater systems than standard nutrient broths such as LB. The validation of synthetic wastewater as a better proxy for real wastewater will allow for further recapitulation of the wastewater environment in future in vitro studies of AMR in these conditions.
ABSTRACT Microbiomes are increasingly understood as interconnected ecological systems spanning soil, water, plants, animals, humans and engineered environments rather than as isolated host‐associated communities. This microbiome continuum provides a mechanistic perspective for One Health by linking microbial cells with the movement of metabolites, genes, signalling molecules and ecological functions across environmental boundaries. Here, we critically examined the biological processes that maintain this continuity, including dispersal, horizontal gene transfer (HGT), metabolic exchange, environmental exposure and host–microbe communication. We consider how climate change and anthropogenic disturbance reshape these interactions and influence antimicrobial resistance (AMR), non‐communicable disease, ecosystem function and pathogen emergence. We further evaluate how artificial intelligence (AI), including machine learning and deep learning, can integrate multi‐omics and longitudinal data, while emphasizing that predictive performance does not establish causality and that AI remains dependent on data quality, biological knowledge and experimental validation. Engineered microbiomes offer opportunities for targeted intervention, but ecological stability, biosafety, HGT and translational uncertainty remain important constraints. We propose a One Health Microbiome Intelligence Framework (OH‐MIF) as a conceptual architecture for cross‐domain integration, with emphasis on standardized data, causal validation, equitable participation and human oversight.
ABSTRACT Biosurfactants are eco‐friendly surface‐active compounds produced by microorganisms that lower surface and interfacial tensions, enhancing the bioavailability of hydrophobic compounds. The study reports the isolation and characterization of biosurfactant‐producing bacteria from industrial waste effluent in a river near Dhaka, Bangladesh. Using diesel‐enriched media, bacterial strains were isolated and screened for biosurfactant production using oil displacement, emulsification index (E24%), and drop‐collapse assays. The microbial cultures were characterized based on biochemical activities and 16S rRNA sequencing. Biosurfactant characterization was carried out using chromatographic techniques. Six cultures passed the drop‐collapse and oil‐displacement tests with E24% ranging from 9% to 41%. The CTAB agar assay confirmed the anionic nature of the biosurfactants. The potential biosurfactant producers belong mostly to the Bacillus and Stutzerimonas groups, with one low‐biosurfactant‐producing isolate from the Enterobacteriaceae group. The presence of two consortia, Bacillus‐Acinetobacter and Bacillus‐Stutzerimonas , was also observed. The isolates and consortia exhibited varying levels of antibacterial, antifungal, adherence, and plant growth‐promoting activity. Biosurfactant production capacity under extreme conditions has been characterized by pH stability (pH 2–pH 11), salinity tolerance (2%–10% NaCl), and temperature tolerance (40°C–100°C). Overall, they provide a green and economical alternative to synthetic surfactants, with low toxicity and potential applications in bioremediation, biocontrol, and plant growth promotion.
ABSTRACT Tank bromeliads in the neotropics harbour complex communities of invertebrates and even provide food, water and shelter to various vertebrate species. However, few studies have sequenced the microbial communities within epiphytic bromeliad phytotelmata. We sequenced the 16S rRNA subunit extracted from swabs rubbed at the base within the central phytotelm of the epiphytic bromeliads Aechmea hoppii and A. nidularioides . We tested factors that we suspected could influence the alpha diversity and beta‐diversity of prokaryotic communities in bromeliads. Height on the tree and size of the bromeliad influenced the alpha‐diversity within plants. Height from the ground and pH of the phytotelm explained small proportions of the variation among communities, regardless of whether quantitative or qualitative distances were calculated. We used FAPROTAX to assign taxa to functional groups and found that a complex picture of correlations between function and variables emerged, with height on the tree, pH, plant size and species, forest type and sampling season correlating with different functional groups. This relatively large metabarcoding study of bromeliad phytotelmata prokaryotes contributes to the growing knowledge of these highly diverse and complex systems.
