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Ecological and methodological insights from genetic and coprological profiling of gastrointestinal communities in wild howler monkeys.

The gastrointestinal tract hosts a complex community of microorganisms and helminth parasites that collectively contribute to host health and fitness. Analysis of these communities provides insight into diverse aspects of host dietary ecology, immunity, nutrition, and host-parasite interactions. However, research methodologies, such as sample preservation and sequencing approach, can influence how we understand and characterize these features. Here, we profiled the gastrointestinal microbial and helminth communities in different groups of wild Costa Rican mantled howler monkeys (Alouatta palliata palliata). We compared samples stored in ethanol versus directly flash frozen, and contrasted conclusions drawn from 16S versus shotgun sequencing approaches. Bacterial, archaeal, and eukaryotic taxa associated with the digestion of plant material dominated the GI communities. Storage and sequencing methods influenced microbial profiles: ethanol-stored samples exhibited higher diversity than frozen samples, and 16S sequencing detected lower diversity than shotgun. Helminths were detected via coprological microscopy in 71% of individuals, whereas metagenomic detection was inconsistent. This study provides new data on the microorganisms and their putative digestive functions in the gut of a folivorous primate, and highlights the pros and cons of different methodological choices when profiling host-microbiome and host-parasite interactions.

Animals

Spatial scaling of metagenomic diversity reveals ecological disruption in the gut microbiome of gout patients.

Gout, a painful inflammatory arthritis, is characterized by hyperuricemia and monosodium urate crystal deposition, with growing evidence linking its pathogenesis to gut microbiome dysbiosis. However, traditional diversity metrics fail to capture the complex spatial organization of microbial communities. This study addresses this gap by applying the novel metagenomic Diversity-Area Relationship (m-DAR) model to investigate scaling laws in the gout microbiome-quantifying how metagenomic diversity changes with the number of individuals sampled. Our analysis of gut microbiomes from gout patients and healthy controls revealed fundamental ecological disruptions. We found that gout microbiomes exhibited significantly altered scaling patterns: they showed greater inter-individual dissimilarity (higher z-values) at the level of rare genes (q = 0), but weaker scaling of dominant genes (q = 1-3) compared to healthy controls. Crucially, the maximal accrual diversity (MAD) was substantially lower in gout patients, indicating a severely constrained potential for total microbial gene diversity. Furthermore, profiling of metagenomic functional gene clusters (MFGCs) uncovered widespread functional perturbations, including increased diversity scaling for carbohydrate-active enzymes (CAZy) but decreased scaling in essential metabolic pathways (KEGG, KO). These results demonstrate that the gout gut microbiome is defined by a loss of ecological structure, featuring reduced homogeneity in dominant taxa, expanded rare biosphere variation, and an overall collapsed diversity capacity. This work introduces an ecological framework for characterizing dysbiosis in gout that complements traditional diversity metrics and may inform the development of microbiome-based therapeutic strategies. Further research is needed to translate these ecological patterns into clinical applications.

Humans

Longitudinal development of infant oral ecosystem: salivary metabolomic, bacteriome, and virome dynamics in early infancy.

This prospective cohort study investigated the longitudinal development of the salivary bacteriome, virome, and metabolome during early infancy. We assessed the associations between oral bacteria, viruses, and metabolites from 10 mother-infant dyads, with oral samples collected at 1 and 2 years of age. Forty saliva and plaque samples underwent untargeted metabolomic analysis, and infant saliva samples underwent metagenomic sequencing. Maternal salivary and plaque metabolomic profiles remained largely stable, whereas infant profiles were clearly separated from maternal profiles and changed with age. Notably, infant dental plaque metabolism underwent more substantial changes from year 1 to year 2 than saliva, with age-dependent metabolite shifts mainly involving energy, amino acid, nucleotide, and lipid metabolic pathways. Our findings also revealed significant developmental shifts in salivary bacteriome, virome, and functional pathway profiles during early childhood. The most abundant oral bacteria in early life, comprising over 75% of total abundance, included Veillonella, Streptococcus, Rothia, Prevotella, Neisseria, and Actinomyces species. While human viruses like Roseolovirus were detected, bacteriophages constituted the majority of the virome. Comparing infants at year 1 and year 2, we identified differentially abundant bacteria, viruses, metabolic functional pathways, and specific metabolites. We observed associations between bacteria and viruses, noting that these cross-kingdom relationships attenuated as infants grew. The study results underscore the complex and dynamic development of the oral microbiome, virome, and metabolome during early childhood.IMPORTANCEThe human oral cavity undergoes substantial microbial and metabolic development during early childhood, yet the temporal changes in the infant oral ecosystem remain incompletely understood. In this study, we longitudinally profiled the salivary metabolome, bacteriome, and virome of infants at 1 and 2 years of age. We demonstrated that the infant oral metabolome undergoes substantial developmental shifts, particularly in pathways related to energy, amino acid, and lipid metabolism; whereas maternal metabolic profiles remained stable over the same period. Furthermore, our results revealed the dynamic assembly of infant salivary virome and bacteriome and their associations with the functional pathways and metabolites. These findings provide new insights into the complex and dynamic development of the oral microbiome, virome, and metabolome in early infancy.

bacteriome

Characteristics and assembly mechanisms of tobacco-associated bacteria in typical tobacco-planting regions across China.

INTRODUCTION: Plant-associated microbiota critically modulates host growth and environmental adaptation, yet assembly mechanisms, niche differentiation, and ecological strategies of bacterial communities inhabiting tobacco microhabitats remain poorly elucidated across geographical gradients. METHODS: Here, we systematically characterized bacterial microbiome assembly across five tobacco-associated niches (bulk soil, rhizosphere soil, root, stem, and leaf) from seven typical tobacco-planting regions using 16S rRNA amplicon sequencing, genome annotation, and niche breadth analysis. The independent and interactive effects of geographical location and host compartment on community structure, and further compared genomic traits, functional profiles, and life-history strategies between specialist and generalist bacterial populations were quantified. RESULTS: The results revealed a deterministic soil-plant continuum stratification of bacterial communities and diversity, with progressively simplified communities and decreasing alpha diversity from bulk soil to above-ground tissues, accompanied by progressive dominance of Proteobacteria. Geographical factors predominantly structured soil microbial communities via divergent edaphic properties, while host filtering acted as a universal dominant driver shaping endophytic microbiome assembly. Niche differentiation analysis demonstrated that niche-specialized bacterial ASVs overwhelmingly dominated all microhabitats and geographical sites, whereas generalist taxa only constituted auxiliary populations. Although specialist and generalist microbes exhibited highly conserved core genomic architectures and overall functional repertoires, they displayed distinct niche-specific functional divergence in metabolic pathways, stress resistance, and secondary metabolism across host compartments. Life-history strategy analysis further revealed that Y-strategist represented the core adaptive bacterial population, especially enriched in above-ground tobacco tissues. DISCUSSION: Our study establishes a hierarchical dual-filtering assembly model for tobacco microbiota, clarifies the ecological differentiation and functional adaptation of specialist and generalist bacteria, and provides fundamental insights into the assembly rules and adaptive mechanisms of crop-associated microbiomes for future microbial resource utilization and agricultural microbiome regulation.

biogeography

Identification and Classification of Expressed Orphan Genes, Spurious Orphan Genes, and Conserved Genes in the Human Gut Microbiome.

Orphan genes (OGs)-genes lacking detectable homologs outside a species-are widespread in microbial genomes and are thought to contribute to their adaptation and molecular innovation. However, not all predicted OGs may represent novel functional coding sequences. False positive OGs, also called spurious OGs, can arise from gene prediction errors. We reason that OGs lacking detectable expression are more likely to be spurious. To test this, we combined large-scale metatranscriptomic profiling of the human gut microbiome with machine learning to distinguish expressed OGs from spurious ones and compare them with conserved genes (CGs) found in multiple species. Using nearly 5,000 metatranscriptome libraries, we identified ∼218,000 OGs supported by expression evidence, while ∼330,000 predicted OGs lacked detectable expression and were classified as spurious. We extracted 154 features for sequence, structural, and evolutionary properties for each gene and trained XGBoost classifiers while accounting for genomic representation. The models achieved an area under the receiver operating characteristic curve (AUC) of 0.82 in distinguishing expressed OGs from spurious OGs and an AUC of 0.93 in distinguishing expressed OGs from CGs. Interpretation based on SHAP (SHapley Additive exPlanations) revealed clear biological signals. Particularly, expressed orphans were present in more genomes than spurious ones, and expressed OGs were shorter than CGs. This work improves OG discovery and suggests that expressed OGs differ systematically from CGs and spurious OGs in sequence composition, structural constraints, and evolutionary signals.

Humans

Pilot metaproteomic profiling reveals bacterial diversity and potential medical and veterinary relevance of tick microbiomes in northern Algeria.

Ticks are major ectoparasites and vectors of pathogens affecting humans, livestock, and wildlife. They harbor diverse microbial communities that may influence tick biology and interactions with microorganisms; however, functional information on tick-associated microbiomes remains limited, particularly in North Africa. In this pilot study, we applied a metaproteomic approach based on high-resolution tandem mass spectrometry to characterize bacterial communities associated with three tick species collected in Algeria: Rhipicephalus sanguineus sensu lato, Hyalomma aegyptium, and Hyalomma dromedarii. Peptide spectra were assigned to taxa using a two-step database search strategy based on NCBInr, and bacterial composition and relative abundance were compared across tick species and sampling locations. A total of 40 bacterial genera belonging to 32 families and four phyla were identified. Microbiome composition differed significantly between tick genera and collection locations, suggesting an influence of species-specific and geographical factors on microbial community structure. Dominant genera included Streptomyces, Bacillus, Clostridium, Escherichia, Flavobacterium, Paenibacillus, and Providencia. Peptides related to Coxiella spp. were frequently detected, consistent with previous reports of Coxiella-like endosymbionts in ticks. This pilot study provides a first metaproteomic characterization of tick-associated communities in Algeria. The results reveal species- and location-associated differences in microbial composition and highlight the potential of metaproteomics for exploring tick-associated microbiomes in North Africa.

Animals

Metagenomic profiling of gut microbiome in post-cholecystectomy patients with diarrhea: a nested case-control study.

BACKGROUND: Cholecystectomy can cause diarrhea, with an incidence as high as 57.2%, seriously impacting patient prognosis. To investigate the gut dysbiosis following cholecystectomy and identify microbial biomarkers and functional genomics associated with post-cholecystectomy diarrhea (PCD), we conducted a nested case-control study within a prospective cohort. METHODS: We enrolled a cohort of 160 patients. At follow-up completion, 30 patients who developed PCD were matched with 30 non-PCD (NPCD) controls. 16 S rRNA sequencing was used to analyze gut microbiota structure and diversity (mainly at genus level). Representative fecal samples underwent metagenomic sequencing for species level and genetic differential analysis. RESULTS: The potentially pathogenic bacterial species Coprococcus comes and Blautia sp. were significantly enriched in the gut microbiota of PCD patients, with their abundance positively correlated with the degree of intestinal inflammation. In contrast, the potentially beneficial bacterial species Bacteroides intestinalis and Prevotella copri, known to contribute to lipid metabolism and play a role in modulating gut immunity and suppressing inflammatory responses, were found to be significantly depleted in PCD patients. Further metagenomic functional analysis revealed significant enrichment of pathways related to cell motility, membrane transport, and sulfur metabolism in PCD patients. CONCLUSIONS: This work identified potential beneficial and pathogenic bacterial species associated with the onset of PCD, as well as significantly enriched functional pathways within the intestinal microbiota. These findings provide a scientific basis for elucidating the relationship between PCD and gut microbiota, and provide candidate microbial signatures and functional pathways that may inform future microbiota-targeted strategies, pending external and mechanistic validation.

Humans

Resistant starch types 2 and 4 induce distinct and reversible changes in the human gut microbiome.

Resistant starch (RS) can confer benefits for the gut microbiome and host cardiometabolic health. However, different types of resistant starch can differentially affect gut microbiome composition and functional capacity, especially given interindividual variability in responses, thus limiting the application of resistant starch in dietary strategies. We used shotgun metagenomics to perform a secondary analysis of samples collected during a previously reported randomized clinical trial to determine the effects of dietary supplementation with two types of resistant starch (RS2 and RS4) and a digestible starch (control) on the gut microbiome. Both resistant starch types induced distinct but transient alterations in the gut microbial community. RS2 enriched the keystone degrader, Ruminococcus bromii, and Blautia glucerasea, whereas RS4 favored Parabacteroides distasonis and known but uncharacterized microbial species such as a Lachnospiraceae bacterium. Moreover, we detected strain-level differences in the response of Bifidobacterium adolescentis to resistant starch. Microbial functional profiling revealed an enhanced capacity for complex carbohydrate utilization following resistant starch intake, including increased abundance of specific α-amylases, glycoside hydrolases, starch utilization systems, and other currently uncharacterized genes. Identifying the bacterial strains and genes that respond to different RS types will help to more accurately predict who will benefit from a given RS type. Our findings demonstrate that RS2 and RS4 differentially shape microbial ecology and metabolic capacity and provide a foundation for microbiome-informed personalization of resistant starch-based dietary interventions.IMPORTANCEDietary intake influences human health by modulating metabolism, partly by shaping the microbiota inhabiting the gut. Resistant starch (RS), a dietary fiber, is associated with metabolic improvements. While previous research has explored how RS alters the gut microbiome, RS comprises five types with differing physical and chemical characteristics, and the distinct impacts of each type on the microbiome and host health have not been fully characterized, particularly using high-resolution approaches such as shotgun metagenomics. In this secondary analysis of samples from a longitudinal crossover intervention study, we link dietary supplementation with RS2 and RS4 with distinct and transient changes in the composition and functional potential of the human gut microbiome. Specifically, we identify species that increase in abundance with each RS type, accompanied by increases in genes and pathways involved in complex carbohydrate utilization. The findings support the development of precision nutrition strategies utilizing RS supplementation to improve metabolic health.This study is registered with ClinicalTrials.gov as NCT05743790.

Humans

SetBERT: the deep learning platform for contextualized embeddings and explainable predictions from high-throughput sequencing.

MOTIVATION: High-throughput sequencing (HTS) is a modern sequencing technology used to profile microbiomes by sequencing thousands of short genomic fragments from the microorganisms within a given sample. This technology presents a unique opportunity for artificial intelligence to comprehend the underlying functional relationships of microbial communities. However, due to the unstructured nature of HTS data, nearly all computational models are limited to processing DNA sequences individually. This limitation causes them to miss out on key interactions between microorganisms, significantly hindering our understanding of how these interactions influence the microbial communities as a whole. Furthermore, most computational methods rely on post-processing of samples which could inadvertently introduce unintentional protocol-specific bias. RESULTS: Addressing these concerns, we present SetBERT, a robust pre-training methodology for creating generalized deep learning models for processing HTS data to produce contextualized embeddings and be fine-tuned for downstream tasks with explainable predictions. By leveraging sequence interactions, we show that SetBERT significantly outperforms other models in taxonomic classification with genus-level classification accuracy of 95%. Furthermore, we demonstrate that SetBERT is able to accurately explain its predictions autonomously by confirming the biological-relevance of taxa identified by the model. AVAILABILITY AND IMPLEMENTATION: All source code is available at https://github.com/DLii-Research/setbert. SetBERT may be used through the q2-deepdna QIIME 2 plugin whose source code is available at https://github.com/DLii-Research/q2-deepdna.

Deep Learning

Lesion-specific oral microbiome signatures and predicted carcinogenic pathways in oral squamous cell carcinoma: a paired-site study in Pakistan.

BACKGROUND: Oral squamous cell carcinoma accounts for over 90% of oral neoplasms. Despite therapeutic advances, the lack of reliable, non-invasive biomarkers and delayed diagnosis continues to impede effective clinical management. By combining paired lesion and non-lesion sampling with predictive metagenomics analysis, our study addresses this gap and advances the current understanding of microbiome&#x2012;tumor interactions. METHODS: We analyzed 92 buccal swab samples from 39 OSCC patients and 14 healthy controls using 16S rRNA gene (V3-V4) sequencing. Taxonomic profiling was conducted using QIIME2 and SILVA/eHOMD databases, functional pathways were predicted using PICRUSt2, and hub taxa were identified through co-abundance network analysis. RESULTS: Microbial community structure differed significantly across lesion, non-lesion, and healthy sites (PERMANOVA, p&#x2009;=&#x2009;0.001). Lesions were enriched with Selenomonas infelix and Treponema vincentii, while healthy controls harbored Streptococcus oralis and Gemella haemolysans. Co-abundance network analysis revealed lesion-specific hub species, notably T. vincentii, strongly correlated with predicted activation of pyrimidine biosynthesis pathways (r&#x2009;=&#x2009;0.69, q&#x2009;<&#x2009;1E-6), suggesting predicted metabolic alterations in the tumor microenvironment. Non-lesion sites were also characterized by two hub species, Prevotella melaninogenica and Segatella oulorum. CONCLUSION: Our findings define a lesion-specific microbial signature of OSCC characterized by the depletion of health-associated taxa, enrichment of pro-inflammatory pathobionts, and predicted associations with metabolic pathways implicated in carcinogenesis. These alterations reflect a predicted functionally altered tumor microenvironment.

16S rRNA gene

Two Bacillus PGPB Strains in Wheat and Soybean: Wheat Growth Promotion Without Detectable Rhizosphere Microbiome Restructuring.

Plant growth-promoting bacteria (PGPB) are increasingly deployed as biofertilizers, yet the link between an inoculant's genomic potential and its realized effect on the plant is rarely assessed within an integrative framework that jointly captures the rhizosphere microbiome, plant phenotype, and strain genome. Two Bacillus strains-B. halotolerans 1453 and B. pumilus 630-were applied to wheat and soybean in a factorial pot experiment (2 strains &#xd7; 2 application methods &#xd7; 3 frequencies + control, 3-4 replicates). Rhizosphere samples (n = 67 after filtering) were profiled by 16S rRNA sequencing with PICRUSt2 functional prediction and compositional validation (Aitchison PERMANOVA, ALDEx2, ANCOM-BC2). The PGPB gene repertoire was characterized by genome mining (481 marker genes, 14 categories). Wheat phenotype (six traits) and soybean height were analyzed with models appropriate for count data (Negative Binomial and binomial GLMs) for treatment-vs.-control comparisons, and with factorial ANOVA for decomposition into main effects and interactions. Crop identity was the dominant factor shaping both microbiome structure and function (PERMANOVA R2 = 14.7% taxonomically and R2 = 7.8% functionally, both p < 0.001), with biologically meaningful taxonomic differences between wheat and soybean; strain, application count and method had no significant effect on community composition (R2 < 4% each), and co-occurrence networks showed no reliable differences between crops once read depth and sample size were controlled for. Despite this neutrality at the microbiome level, inoculation significantly increased wheat spike count (NB-GLM, all 12 treatments vs. control, padj 0.0002-0.031), ear weight, and stem count, with application count the strongest source of variability and a pronounced strain &#xd7; application count. Strain 1453 outperformed 630 in spike count (+23.1%, p = 0.012) and ear weight (+20.4%, p = 0.023); we hypothesize that this may be related to its more complete DNRA pathway (narGHI + nirB-nirD) and biocontrol genes (bacE, srfAA). Strain 630 produced a less pronounced effect than strain 1453 but was subject to smaller fluctuations across replicates (CV &#x2248; 16-21% vs. &#x2248;24-26% for 1453), which may reflect better resilience to environmental fluctuations, possibly due to its confirmed rsbV/rsbW stress-tolerance regulon. Rhizosphere microbiome composition differed clearly by crop (wheat vs. soybean) but showed no detectable response to strain, application method, or application count. Despite this lack of a microbiome signal, inoculation significantly increased wheat spike count and ear weight, with the magnitude and stability of this effect differing by strain. We hypothesize that this strain-dependent difference relates to underlying genomic differences-particularly in nitrogen metabolism (DNRA pathway) and stress-tolerance genes-though this link has not been tested directly and remains a hypothesis for future work.

Triticum

Microbial and functional shifts between flare and remission in a single-center cohort of children with inflammatory bowel disease.

BACKGROUND: Gut microbial dysbiosis is central to the pathogenesis of inflammatory bowel disease (IBD). While gut microbiome differences between patients with and without IBD are well established, microbiome changes associated with disease activity and remission remain limited, particularly in paediatric populations. AIM: To examine intra-individual taxonomic and functional gut microbiome changes during transition from active flare to remission under maintenance immunosuppression in a pilot single-center Singapore cohort of children with IBD. METHODS: Paired stool samples and clinical data were collected from seven patients with paediatric IBD [5 Crohn's disease (CD), 2 ulcerative colitis; &#x2264; 18 years] during active disease/flare (visit 1; Pediatric CD Activity Index/Pediatric Ulcerative Colitis Activity Index &#x2265; 10) and subsequent clinical remission (visit 2; Pediatric CD Activity Index/Pediatric Ulcerative Colitis Activity Index < 10). Samples underwent shotgun metagenomic sequencing for high-resolution taxonomic profiling and functional annotation of Kyoto Encyclopaedia of Genes and Genomes pathways. RESULTS: Gut microbial diversity was reduced during flare compared to remission, with Actinobacteria abundance significantly higher in remission. Two distinct microbial clusters differentiated flare and remission states: The remission cluster was enriched with Bifidobacterium adolescentis, Bifidobacterium dentium, Lactobacillus gasseri, Faecalibacterium prausnitzii, while the flare state showed increased Klebsiella pneumoniae. Remission was further characterized by a downregulation of pathogenic microbes and an upregulation of beneficial microbes including a higher abundance of the butyrate producer Anaerostipes hadrus (P = 0.046). Microbial functional genes enriched in remission were predominantly associated with metabolic pathways including vitamin and cofactor biosynthesis, as well as carbohydrate, amino acid, and lipid metabolism. CONCLUSION: The transition from flare to remission in Singaporean children with IBD is characterized by functional remodeling of the gut microbiome, which may contribute to recovery processes related to intestinal barrier integrity, cellular maintenance, and tissue repair. Targeted modulation of the gut microbiome may help sustain remission in paediatric IBD.

Functional shift

Enhancing the fiber degradation efficiency in dairy cattle rumen through engineered bacterial communities.

BACKGROUND: The rumen functions as an anaerobic fermentation chamber, housing microorganisms with cellulolytic and proteolytic capabilities that facilitate feed utilization. Fiber-degrading bacteria possess the capability to enhance the productivity of cellulolytic feed. The application of omics technologies has greatly improved our understanding of the rumen microbiome. Determining microbial composition and functional patterns in the rumen does not equate to a comprehensive exploration of rumen microbial resources and their mechanisms of action. This study seeks to integrate high throughput 16S rRNA data with information on culturomics, cellulolytic activities, nutrition, and synthetic microbial communities (SynCom) engineering. The objective is to evaluate the relationship between rumen microbial activity and fiber utilization efficiency in cattle, ultimately aiming to develop a more powerful intervention strategy for the ruminant industry. RESULTS: The enrichment culture with various carbon sources led to significant alterations in the composition and structure of rumen microbiota, particularly enhancing those associated with carbohydrate metabolism. Employing the culturomics methodology, 896 strains from 78 species (including 8 novel species) were isolated, resulting in a 10.1% isolation rate relative to the rumen bacterial community. Among them, 35 strains demonstrated boosted cellulose-degrading capability on plates, while 25 exhibited the ability to degrade hemicellulose as well. SynComs of these candidates were prepared based on the ratio observed in rumen microbiota exhibiting high cellulolytic performance. SynCom&#xa0;3 improved the neutral detergent fiber degradation (NDFD) by 20.39%&#xa0;averagely. Additionally, both in vitro and in situ assessments indicated that the optimization of dose/strain in SynCom&#xa0;3 significantly improved the in vitro NDFD by 20.56% and increased the in situ NDFD by 7.81%, along with the acidic detergent fiber (ADF,&#xa0;+&#x2009;11.47%). Genomic analysis revealed that the SynCom&#xa0;3 functioned well in fiber degradation through the synergistic action of key carbohydrate-active enzymes. CONCLUSIONS: This study strengthens rumen microbiome research by integrating omics and SynCom engineering within a microbiota-bacteria-enzymes-genes framework, revealing the significance of enzymatic synergy in carbohydrate metabolism. The findings establish a framework for utilizing low-abundance microbes and engineering functional consortia, which are crucial for improving ruminant feed utilization and biomass conversion. Future research should investigate the transcriptomic profiles and the metabolic cross-feeding mechanisms of fiber-degrading strains in the rumen. Video Abstract.

Animals

From bacterial to microbiome-derived vesicles: genome-informed identity, source qualification, and translational quality for skin-directed cosmetics.

Bacterial extracellular vesicles (BEVs) are increasingly proposed as materials for skin-directed cosmetics, yet rapid adoption of "exosome" terminology has outpaced clarity on their origin, composition, and manufacturing quality. This review argues that the value of BEVs depends on scientific discipline rather than marketing appeal, and that they are promising because they are biologically potent, not because they are intrinsically benign. We retain BEVs as the scientific umbrella term for vesicles released by bacteria and we propose the term microbiome-derived vesicles (MDVs) as the consumer-facing designation for qualified commensal BEVs - a surface term that avoids the difficulty of "bacterial" while its definition preserves bacterial provenance. We develop a three-axis framework for BEV identity that integrates compositional analysis, producer-strain genomics, and functional or safety profiling, and we position whole-genome sequencing (WGS) as decisive for source qualification and mechanistic interpretation but insufficient to prove the efficacy of a purified preparation. Building on this framework, we summarize isolation, purification, and analytical characterization requirements; interpret current skin-efficacy evidence in light of its methodological limits; and discuss formulation, cosmetic application, regulatory positioning, and manufacturable quality. We conclude that transparent bacterial provenance, reproducible preparation, and evidence proportionate to the claims made are prerequisites for evaluating commensal BEVs, described for skin applications as MDVs, as a scientifically defined cosmetic platform.

Bacterial extracellular vesicles

Species-specific structuring of gut bacterial and fungal communities in honey bees Apis cerana and Apis mellifera.

Honey bee gut microbiome studies have primarily emphasized bacteria, leaving fungal communities comparatively overlooked despite their ecological and functional importance. Whole-genome shotgun metagenomics of Apis cerana and Apis mellifera revealed fungal assemblages dominated by Ascomycota, with Basidiomycota and Microsporidia in minor proportions, alongside gut bacterial communities composed mainly of Pseudomonadota, Bacillota, and Actinomycetota. The bacterial diversity was markedly higher in A. mellifera (Shannon&#x2009;=&#x2009;5.90; Simpson&#x2009;=&#x2009;0.98) than in A. cerana (Shannon&#x2009;=&#x2009;4.01; Simpson&#x2009;=&#x2009;0.94; p&#x2009;>&#x2009;0.05), while fungal diversity remained comparable between species (p&#x2009;>&#x2009;0.05). Beta-diversity analyses revealed strong host-specific clustering for both bacterial (PERMANOVA R2&#x2009;=&#x2009;0.7989, p&#x2009;>&#x2009;0.05) and fungal communities (R2&#x2009;=&#x2009;0.7218, p&#x2009;>&#x2009;0.05), indicating distinct microbial organization driven by host species. Bacterial-fungal co-occurrence patterns exhibited host-specific structuring, suggesting differential inter-kingdom community organization between A. cerana and A. mellifera. Linear Discriminant Analysis Effect Size (LEfSe) identified 93 discriminatory fungal taxa (45 enriched in A. cerana, 48 in A. mellifera), highlighting yeast-dominated signatures in A. mellifera and Basidiomycota-affiliated enrichments in A. cerana. KEGG and CAZy profiling revealed host- and kingdom-specific functional differences, with bacterial communities of A. mellifera showing distinct representation of carbohydrate metabolism and nutrient-cycling functions, while fungal communities exhibited a comparatively narrower functional repertoire. Together, these findings provide a high-resolution view of honey bee bacterial and fungal microbiomes, highlighting strong host-driven divergence in taxonomy, function, and cross-kingdom interactions.

Animals

Farming reshapes the gut resistome, virulome, and mobilome of Cervidae.

The rapid expansion of cervid farming raises concerns about antimicrobial resistance (AMR) dissemination, yet its impact on the Cervidae gut microbiome remains poorly characterized. We integrated 89 newly sequenced fecal metagenomes with 599 publicly available datasets, comprising 285 metagenomes from farmed cervids and 370 from wild cervids, to construct a catalog of 15,494 non-redundant metagenome-assembled genomes (MAGs) representing 2,401 species. Our analysis demonstrates that farming profoundly reshapes the gut microbiome's functional composition. Specifically, farmed cervids exhibited significantly higher relative abundance, diversity, and heterogeneity of antimicrobial resistance genes (ARGs) compared to wild counterparts. We observed a robust synergistic relationship between ARGs, virulence factor genes, and mobile genetic element (MGE)-associated genes, identifying 70 ARG-MGE combinations as evidence of potential horizontal gene transfer. Plasmid profiling further suggested that a subset of ARGs may be associated with conjugative plasmids, with plasmid-associated ARGs being significantly more abundant in farmed than in wild cervids. Virome analyses indicated that bacteriophages, particularly Siphoviridae, may serve as mobile reservoirs for ARGs. Notably, Cervidae shared 268 ARG types with humans, including 23&#xa0;high-risk genes associated with resistance to clinically important antibiotics (e.g. tetX1, vanRD, and bla-CTX-M-178), with Escherichia coli as a key cross-host carrier. These findings highlight that human-impacted cervid gut microbiomes are significant environmental reservoirs of clinically relevant AMR, underscoring the necessity for enhanced antibiotic stewardship and resistance surveillance in managed wildlife within a One Health framework.

Animals

Host-independent metagenomics reveal gut bacteria contribution to Delia antiqua growth by vitamin B6 provision.

Insect guts host a diverse and abundant array of microorganisms. These microbes improve host fitness by extensively involving in a range of crucial physiological processes, which have mainly been revealed by high-throughput sequencing, particularly metagenomics. However, it is almost impossible to make an accurate and complete distinction between the genetic functions of microbial symbionts and insect hosts without host genome data. By comparing metagenomic data from gut germ-free and nonaxenic larvae, we accurately identified the data belonging to the gut microbiome of the onion maggot Delia antiqua (Diptera: Anthomyiidae). Besides, a correlation between bacteria of the genus Wohlfahrtiimonas (Gammaproteobacteria: Pseudomonadaceae) and vitamin B6 metabolism was detected through collinearity analysis. Furthermore, in vitro tests confirmed that the gut bacterium Wohlfahrtiimonas larvae contributed to the growth of D. antiqua larvae via the independent synthesis of vitamin B6. This study provides a comprehensive view of the gut bacterial diversity in D. antiqua and reveals a functional profile that is strictly specific to the gut microbiota of this species. It has preliminarily revealed the functional differentiation between insect hosts and their symbiotic microorganisms. This study also offers a technical reference for the study of microbial symbiotic functions in other insect-microbe symbioses without host genomic data.

Animals

The mechanism by which long-term exposure to TDCIPP promotes cognitive impairment in 3&#x202f;&#xd7;Tg-AD mice: Insights from multi-omics studies.

Tri(1,3-dichloro-2-propyl) phosphate (TDCIPP) is a commonly used organophosphate ester that has the potential to adversely affect human health. Although previous studies have closely associated TDCIPP with cognitive impairment, the underlying mechanisms remain unclear. To elucidate the neurotoxic effects of TDCIPP and its mechanistic contribution to cognitive impairment in 3&#x202f;&#xd7;Tg-AD mice, a multi-omics approach incorporating proteomics, untargeted metabolomics, and 16S ribosomal RNA (rRNA) gene sequencing was employed to evaluate the impact of TDCIPP exposure on neurobehavioral function. TDCIPP exposure promoted cognitive impairment in 3&#x202f;&#xd7;Tg-AD mice. Proteomic analyses revealed that this promotion is associated with disturbances in the hippocampal mitochondrial autophagy pathway. Furthermore, TDCIPP may interfere with the PINK1/Parkin-mediated mitophagy pathway at the functional level, without altering PINK1 protein abundance. Untargeted metabolomic analysis of urine samples demonstrated that TDCIPP exposure altered the metabolic profile of 3&#x202f;&#xd7;Tg-AD mice, with 58 metabolites upregulated and 11 downregulated. Additionally, 16S rRNA sequencing revealed substantial modifications in gut microbiome composition following exposure to TDCIPP. Notably, significant correlations were identified between the perturbed bacterial genera and the differential metabolites. In conclusion, exposure to TDCIPP promotes cognitive impairment in 3&#x202f;&#xd7;Tg-AD mice, which is associated with the interference with the PINK1/Parkin-mediated mitophagy pathway, as well as alterations in the urinary metabolome and gut microbiota. These findings suggest the potential to mitigate such cognitive impairment by targeting the microbiota-gut-brain axis.

Animals