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PubMed2026

Whole-Genome Analysis of Bacillus Licheniformis Ali5 and Synthesis of Lichenysin via Genome Shuffling.

Whole-genome sequencing of Bacillus licheniformis Ali5 was performed via MGI-seq PE150 and Nanopore single-molecule real-time sequencing. The strain has a 4,114,664 bp circular genome encoding 4030 protein-coding genes. Functional annotation across NR, COG, GO, KEGG, CARD, BacMet, and CAZy databases identified 4025, 2812, 988, 1242, 72, 69, and 94 corresponding genes, respectively, and antiSMASH 6.0 revealed multiple antimicrobial biosynthetic gene clusters, including intact lichenysin and lichenicidin VK21 A1/A2 gene clusters. Three rounds of recursive protoplast fusion-based genome shuffling, paired with a dual-index screening system, significantly improved strain growth and lichenysin biosynthesis. Recombinants exhibited shortened lag phase, enhanced proliferation, improved stationary-phase stability, and higher diauxic peak biomass. PP3-176 and PP3-186 showed 4.6%-8.1% higher 12-h shake-flask titer and 3.1%-4.0% higher maximum titer than the parental average, with excellent fermentation stability. 1-L bioreactor validation confirmed strong scale-up potential. PP3-186 achieved 27.2% and 31.6% titer increases at 12 h and 20 h, while PP3-176 yielded 20.4% and 14.6% improvements with robust metabolic performance. This study validates genome shuffling as an effective strategy for enhancing lichenysin production, providing candidate strains and technical support for industrial application.

Bacillus licheniformis↗

PubMed2026

Characterization and genomic analysis of Bacillus halotolerans G3-2: a potential biocontrol agent against apple Alternaria leaf blotch disease.

BACKGROUND: Apple Alternaria leaf blotch (ALB) is a devastating disease threatening the apple industry worldwide. Biocontrol offers an effective and environmentally friendly alternative for disease management. RESULTS: Bacillus strain G3-2 exhibits strong antagonistic activity against Alternaria alternata (a major causal pathogen of ALB). In dual-culture assays, G3-2 inhibited A. alternata by 88.39%; in detached-leaf inoculation assays, it reduced the lesion area by >88%. 16S rRNA sequencing and phylogenetic analysis identified this strain as Bacillus halotolerans. Oxford Nanopore Technology (ONT) sequencing generated a 4.18-Mb complete genome (43.8% G + C) containing 4149 protein-coding genes, 30 rRNAs and 86 tRNAs. CAZy annotation identified 182 genes encoding carbohydrate-active enzymes (CAZymes), including glycoside hydrolases, glycosyltransferase, and carbohydrate esterases, suggesting potential for glycosylated secondary metabolite production. AntiSMASH analysis detected nine biosynthetic gene clusters, including those for surfactin, fengycin, bacillaene and laterocidine. Plate assays confirmed that G3-2 has the ability to produce protease, cellulase and siderophore. Moreover, it exhibits ~70% inhibition against several other phytopathogenic fungi. CONCLUSIONS: These findings demonstrate that G3-2 suppresses A. alternata through antibiosis (lipopeptides and polyketides), nutrient competition (siderophores) and cell-wall degradation (proteases and cellulases). Moreover, our study revealed that it has great potential to be used as a broad-spectrum, environmentally friendly biocontrol agent. © 2026 Society of Chemical Industry.

Alternaria↗

PubMed2026

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 = 5.90; Simpson = 0.98) than in A. cerana (Shannon = 4.01; Simpson = 0.94; p > 0.05), while fungal diversity remained comparable between species (p > 0.05). Beta-diversity analyses revealed strong host-specific clustering for both bacterial (PERMANOVA R2 = 0.7989, p > 0.05) and fungal communities (R2 = 0.7218, p > 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↗

PubMed2026

Comparative profiling of microbial community structure, enzyme potential, metabolic features, and volatile composition in craft and Jiafan Huangjiu processes.

Craft Huangjiu and Jiafan Huangjiu represent two distinct industrial Huangjiu product outcomes with contrasting volatile profiles. This study compared craft Huangjiu (L70) and Jiafan Huangjiu (L79) to characterize their physicochemical, microbial, gene-level functional, metabolic, and volatile features. Because L70 involved mid-fermentation addition of finished Huangjiu, this comparison was not intended to isolate the sole effect of fermentation interruption versus continued fermentation. L79 showed more extensive carbon and nitrogen utilization, with lower residual substrates and higher ethanol and acetic acid contents than L70, whereas L70 retained a less complete fermentation state. At the volatile level, GC-MS and volatile metabolomics consistently showed an ester-enriched profile in L79 and a more alcohol-dominant profile in L70. FlavorDB-based putative annotation and threshold-based OAV analysis further indicated distinct database-assigned descriptor distributions and potential odor-active compounds, with more OAV > 1 ester-related compounds in L79. Metagenomic analysis showed that L70 was dominated by Lactobacillus acetotolerans, whereas L79 contained higher relative abundances of Saccharomyces cerevisiae, Aspergillus oryzae, Aspergillus flavus, and Fructilactobacillus fructivorans. Metagenomic functional annotation showed higher representation of hydrolysis-related CAZy genes and ester-related enzyme annotations in L79. KEGG-based pathway mapping further indicated greater gene-level potential for ethanol-, acetate-, and acetyl-CoA-related metabolism in L79. Accordingly, the L70 profile should be interpreted as the integrated final-product outcome of process intervention, exogenous input, and subsequent fermentation. The findings provide a comparative basis for future flavor regulation and process optimization in Huangjiu and other fermented alcoholic beverages.

Volatile Organic Compounds↗

PubMed2026

Integrated electronic nose, GC-MS, and metagenomic analyses reveal volatile flavor and microbial community differences in heap-fermented grains of Jiangxiangxing Baijiu across different fermentation degrees.

The fermentation degree of heap-fermented grains in Jiangxiangxing Baijiu production is a critical factor influencing base Baijiu quality. However, conventional assessment methods largely rely on empirical experience and therefore suffer from limited objectivity and accuracy. In this study, integrated volatile profiling and metagenomic approaches were employed to investigate volatile characteristics and microbial functional potential differentiation in fermented grains with different fermentation degrees (under-fermented, normally fermented, and over-fermented). Significant differences in physicochemical properties were observed among fermentation degrees, particularly in acidity and reducing sugar content. Electronic nose analysis revealed distinct sensor response patterns among different fermentation degrees, indicating differences in overall volatile odor fingerprint patterns. A total of 81 volatile compounds were identified by HS-SPME-GC-MS, with aldehydes, ketones, and pyrazines showing pronounced variations among fermentation degrees, and acetaldehyde exhibiting strong discriminatory potential. LEfSe analysis identified 18 microbial taxa as potential biomarkers associated with different fermentation degrees, including Pichia kudriavzevii, Lentibacillus daiqui, and Acetobacter pasteurianus. Correlation analysis revealed significant positive associations between acetaldehyde levels and Acetobacter abundance. Furthermore, KEGG, CAZy, and eggNOG analyses revealed differentiated functional potentials among fermentation degrees, providing insights into the potential metabolic basis associated with flavor differentiation. Overall, these findings highlight that fermentation degree differentiation is closely associated with coordinated changes in physicochemical conditions, microbial communities, and functional potentials, providing ecological insights into flavor differentiation and theoretical support for objective fermentation degree evaluation and quality control of Jiangxiangxing Baijiu production.

Fermentation↗

PubMed2026

Comprehensive profiling of antibiotic resistance genes and functional clusters of orthologous groups annotation of gut microbiota in Indonesian Kedu chickens.

Antibiotic resistance is a growing global health concern, with poultry systems acting as important reservoirs of antibiotic resistance genes (ARGs). However, resistome and functional profiles of indigenous chickens raised under traditional systems remain underexplored. This study aimed to characterize the antibiotic resistome, virulence factor genes, and metabolic potential of gut microbiota in Indonesian Kedu chickens using a shotgun metagenomic approach. Digesta samples from five gastrointestinal segments of 21 healthy adult chickens were analyzed through high-throughput sequencing. ARGs were identified using the Comprehensive Antibiotic Resistance Database (CARD) and Antibiotic Resistance Genes Databases (ARDB), while virulence factors and functional genes were annotated using Virulence Factor Database (VFDB), Clusters of Orthologous Groups (COG), and Carbohydrate-Active EnZymes (CAZy) databases. Results revealed a diverse resistome dominated by multidrug resistance and efflux pump mechanisms, with prominent genes associated with fluoroquinolone, tetracycline, β-lactam, and glycopeptide resistance. The detection of clinically relevant ARGs suggests that genetic determinants associated with antimicrobial resistance are present in the gut microbiota of traditionally raised Kedu chickens, although metagenomic data alone cannot determine whether these genes are actively expressed or confer phenotypic resistance. Virulence factor analysis showed functions related to adherence, immune evasion, iron acquisition, quorum sensing, and efflux activity, reflecting strong microbial adaptability. Functional profiling demonstrated enrichment in translation, carbohydrate and amino acid metabolism, genome maintenance, and cell envelope biogenesis. Additionally, CAZyme analysis indicated a high capacity for complex polysaccharide degradation, supporting efficient utilization of fiber-rich traditional diets. In conclusion, this study provides a comprehensive metagenomic overview of antibiotic resistance and functional potential in Kedu chicken gut microbiota, emphasizing the importance of incorporating indigenous poultry into antimicrobial resistance surveillance within a One Health framework.

Antibiotic resistance genes↗

PubMed2025

16S rRNA and Metagenomic Datasets of Gastrointestinal Microbiota in Fetal and 7-Day-Old Goat Kids.

The perinatal period (from late gestation to the neonatal stage) in ruminants is a critical phase for fetal organ maturation, where ecological succession of gastrointestinal microbial communities significantly impacts livestock production efficiency. However, research remains insufficient regarding the distribution patterns and functional annotation of microbial communities across different gastrointestinal compartments during this period. This study characterized early microbiota dynamics in Hutianshi Goats using 16S rRNA sequencing (4 fetal goats at 90 ± 10 gestational days) and metagenomics (3 7-day-old goat kids). The fetal goat group generated 852,694 valid reads, yielding 688,277 high-quality reads after chimera removal for downstream analysis. The 7-day-old goat kids group produced 1,081,588,182 final valid reads, after data processing and assembly, 8,561,345 contigs were generated. Gene prediction identified 6,095,352 genes. Multi-database annotations (NR, KEGG, CAZy, etc.) revealed functional potential and antimicrobial resistance traits. The public release of this dataset facilitates academic understanding of microbial community dynamics and host-microbe interactions during this developmental stage, providing both theoretical foundations and data resources for ruminant developmental biology and precision breeding regulation.

Animals↗

PubMed2026

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↗

PubMed2026

Gut microbiota dynamics and metabolic pathways associated with bleomycin-induced pulmonary fibrosis progression.

BACKGROUND: Pulmonary fibrosis (PF) is a progressive respiratory disease characterized by epithelial injury, aberrant repair and excessive extracellular matrix deposition. Although the gut-lung axis is increasingly implicated in respiratory disorders, stage-resolved characterization of gut microbiota taxonomic and functional potential during PF development is limited. METHODS: We established a bleomycin-induced murine PF model and performed cross-sectional shotgun metagenomic sequencing of fecal samples from separate cohorts at three defined stages: baseline (control), day 7 (early fibrosis; M7), and day 14 (established fibrosis; M14). Microbial taxonomy, alpha/beta diversity, and predicted functional capacity were inferred using Kyoto Encyclopedia of Genes and Genomes (KEGG) and Carbohydrate-Active enZymes (CAZy) annotations; associations were assessed using Procrustes and Spearman correlation analyses. RESULTS: Histopathology and immunohistochemistry confirmed progressive fibrogenesis with increased TGF-β1 and α-SMA expression. Compared with baseline, bleomycin-treated groups exhibited stage-specific shifts in gut microbial composition, including depletion of mucin-associated taxa (e.g., Prevotella, Akkermansia muciniphila) and expansion of Muribaculaceae- and Clostridiaceae-affiliated taxa. Alpha and beta diversity metrics differed across groups. KEGG/CAZy-based annotations revealed predicted, stage-dependent changes in microbial metabolic potential, including early reductions in pathways related to amino acid and glycan metabolism (M7) and later increases in predicted starch/sucrose catabolism, phosphotransferase system (PTS) representation, and secondary bile acid biosynthesis (M14). Correlation analyses linked compositional shifts to these predicted functional changes. CONCLUSION: In a stage-resolved, cross-sectional study, bleomycin-associated pulmonary fibrosis was accompanied by compositional and predicted functional alterations in the gut microbiota. These data identify candidate taxa and predicted pathways for follow-up mechanistic testing, but functional (metabolomic) and causality experiments are required to confirm whether and how microbial changes contribute to PF pathogenesis.

Animals↗

PubMed2026

Vibrio phycocola sp. nov. and Vibrio phycohabitans sp. nov., Isolated from the Phycosphere of Marine Algae.

Two Gram-stain-negative, facultatively aerobic, oxidase- and catalase-positive, motile (by means of a polar flagellum) rod-shaped bacterial strains, designated BS-M-Sm-2T and MA40-2T, were isolated from marine algae. Growth was optimal at pH 7.0-8.0 and 2.0-3.0% (w/v) NaCl, with temperature optima of 25°C for BS-M-Sm-2T and 25-30°C for MA40-2T. Ubiquinone-8 was the sole respiratory quinone. The major fatty acids common to both strains were C16:0, summed feature 3 (C16:1 ω7c and/or C16:1 ω6c), and summed feature 8 (C18:1 ω7c and/or C18:1 ω6c), while BS-M-Sm-2T additionally contained C12:0 and C14:0. The predominant polar lipids were phosphatidylethanolamine and phosphatidylglycerol, with diphosphatidylglycerol also detected in strain MA40-2T. The DNA G+C contents of strains BS-M-Sm-2T and MA40-2T were 44.2 and 39.8 mol%, respectively. The 16S rRNA gene sequence similarity, average nucleotide identity (ANI), and digital DNA-DNA hybridization (dDDH) values between the two strains were 93.8%, 71.4%, and 23.2%, respectively. Phylogenetic and phylogenomic analyses placed both strains within the genus Vibrio, forming distinct lineages. Comparisons with closely related Vibrio type strains yielded ANI and dDDH values below 91.6% and 44.3%, respectively, further supporting their classification as novel species. Genome analyses revealed genes potentially involved in algal symbiosis, including those for polysaccharide degradation and vitamin biosynthesis. Based on comprehensive genomic, phylogenetic, phenotypic, and chemotaxonomic evidence, strains BS-M-Sm-2T and MA40-2T represent two novel species, for which the names Vibrio phycocola sp. nov. (BS-M-Sm-2T =KACC 24066T =DSM 119941T) and Vibrio phycohabitans sp. nov. (MA40-2T =KACC 24064T = DSM 119942T) are proposed.

RNA, Ribosomal, 16S↗