Journal of Applied Microbiology最新文献

Aims: To assess bacterial sharing between plants and their water environments by identifying bacteria present both in surrounding water and as plant endophytes in soft rush (Juncus effusus) grown in a full-scale floating wastewater treatment wetland, lettuce (Lactuca sativa) or cress (Lepidium sativum) in commercial hydroponic production systems, and lettuce seeds germinated in tap water inoculated with a blaKPC-positive Escherichia coli strain.

Methods and results: The microbiological analysis included enumeration of coliforms and total heterotrophic bacteria, quantification of the genes 16S rRNA, intI1, and uidA, and bacterial community analysis based on 16S rRNA gene metabarcoding. Of the bacterial genera identified in wastewater (n = 2220) and water (n = 1631 cress; n = 1170 lettuce), at least a quarter were also detected as endophytes in roots, and mainly belonged to the phylum Pseudomonadota. The genes uidA and intI1 were significantly more prevalent (∼1 log-unit/16S rRNA gene) in wastewater than in soft rush roots. In the hydroponic systems, the gene uidA was not detected and the gene intI1, detected in cress but not in lettuce, was significantly more prevalent in water (∼1 log-unit/16S rRNA gene) than in the roots. In lettuce seeds germinated in tap water inoculated with E. coli, uptake values of 11%-48% of the gene blaKPC were observed.

Conclusions: These results suggest that plants share a significant proportion of the bacteria thriving in their external environment, highlighting the importance of microbiological water quality. Antibiotic-resistant bacteria or pathogens can be taken up alongside with natural microbiota, a potentially critical human health hazard for edible crops.

The clustered regularly interspaced short palindrome repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) system has been shown to be an effective genome-editing tool in many organisms, including fungi. It enables precise modifications to the DNA of fungal species, facilitating advancements in research, agriculture, and biotechnology. CRISPR-Cas9-edited non-pathogenic antagonists have emerged as a promising alternative for biocontrol. Several filamentous fungi have been engineered to produce secondary metabolites. Furthermore, the CRISPR-Cas9 system has been used to improve the quality of several edible fungi. However, the application of CRISPR-Cas9 technology for fungal genome editing is still facing some challenges that researchers must address. This review highlights the major approaches and applications of genome editing in fungi, as well as the associated challenges.

Aims: The increasing burden of multidrug-resistant (MDR) Pseudomonas aeruginosa (P. aeruginosa) infections highlights the need for antibiotic-sparing approaches. This study isolated and characterized a lytic bacteriophage active against MDR P. aeruginosa and evaluated its potential for infection control and milk decontamination.

Methods and results: The lytic bacteriophage vB_PaeM_QR7 was isolated from sewage and characterized using morphological, phenotypic, and genomic analyses. Whole-genome sequencing revealed a 45 421-bp linear double-stranded DNA genome with no predicted virulence determinants and antibiotic resistance genes. vB_PaeM_QR7 showed high lytic efficiency (optimal MOI = 1 × 10-5), stability across 30-50°C and pH 4-11, a short latent period, and a burst size of 92.43 ± 52.29 PFU cell-1. The bacteriophage inhibited biofilm formation by 65.88 ± 0.04% and reduced established biofilms by 71.27 ± 0.05%. In milk, vB_PaeM_QR7 reduced bacterial loads by 5.40 ± 0.12 log10 CFU mL-1 , and in the Galleria mellonella infection model, it increased larval survival by 50%.

Conclusions: vB_PaeM_QR7 is a newly identified lytic bacteriophage with activity against 10 MDR P. aeruginosa isolates, including cephalosporin- and carbapenem-resistant strains, supporting its further development as an alternative antimicrobial agent.

Aims: To evaluate the biocontrol of Rhizoctonia solani fungal infection in common bean (Phaseolus vulgaris) by using native Trichoderma spp. from northwestern Argentina.

Methods and results: Eight Trichoderma isolates were assessed for their ability to inhibit AG4 R. solani growth through dual culture. All Trichoderma isolates suppressed fungal growth at 4 days post-inoculation, and completely overgrew on it by exerting high antagonism. Mainly, T. afroharzianum isolates (Th15, Th45, and Th51) reduced the root rot severity (42%-51%) in white common bean (cv. Alubia), and increased the germination index, fresh weight, and root lengths in bioassays (inoculated and non-inoculated with the pathogen). Conidial suspensions of T. afroharzianum isolates (Th15, Th28, and Th51) decreased R. solani infection by 30%-50% in white common bean seedlings and increased stem and root development in greenhouse assays. Moreover, liquid culture of T. afroharzianum Th15 also showed antifungal activity on the growth and infection of R. solani in black common bean (cv. Leales 15). Th15 colonization competed effectively with R. solani by reducing the disease severity index and the inoculum of R. solani in bean roots (the latter of which was assessed by qPCR).

Conclusions: Trichoderma afroharzianum Th15 is a biological agent with the potential to protect two cultivars of common bean from the pathogenic attack of R. solani.

Aims: The human gut microbiome is a complex ecosystem whose disruption is implicated in a wide spectrum of diseases, yet translating microbiome research into actionable therapeutics is hindered by a critical trade-off: existing models either prioritize predictive accuracy at the expense of interpretability or sacrifice performance for mechanistic insight, limiting their ability to pinpoint specific disease-driving microbial interactions and taxa.

Methods and results: To address this, we introduce Graph neural network for Interpretable Microbiome (GIM), a graph neural network framework that integrates minimally processed taxonomic metadata as sparse node embeddings within an unweighted complete graph, enabling direct modeling of high-order microbial interactions through message passing. GIM achieves state-of-the-art classification performance on microbiome-disease prediction tasks (e.g. healthy vs. allergic states) while generating finegrained, experimentally validated attributions at the level of taxonomic ranks, driver microbes, and putative microbe-to-microbe interactions.

Conclusions: By bridging the gap between predictive accuracy and biological interpretability, GIM overcomes a key limitation in current approaches, offering a unified framework to both predict dysbiosis-associated disease states and identify actionable microbial targets for therapeutic intervention. This dual capability represents a critical advance toward precision microbiome engineering and scalable hypothesis generation in translational microbiome research.

Aims: To establish a reproducible and consistent zebrafish embryo model for multi-genotype human norovirus (HuNoV) replication, by addressing the critical bottleneck of technical variability in microinjection and systematically characterizing the infection dynamics across genotypes.

Methods and results: We developed a standardized microinjection framework anchored by a hierarchical quantitative evaluation scheme (based on CLSI EP28-A3c) to minimize operator-dependent variability. This system enabled consistent, low-damage delivery of the viral inoculum. The framework's robustness was confirmed by a strong correlation between net injection efficiency and embryo survival (Pearson r = 0.67, P < 0.05). Leveraging this standardized approach, we successfully constructed stable replication models for five HuNoV genotypes (GII.2[P16], GII.4[P31], GII.4[P16], GII.17[P17], and GII.3[P12]), determining the minimum effective inoculum titer and defining the replication kinetics for each.

Conclusions: Our work provides a comprehensive and standardized methodology that significantly enhances the reproducibility of the zebrafish embryo model for HuNoV research. By effectively decoupling technical variability from genuine biological effects, this framework establishes a robust platform for comparative studies of viral pathogenesis, host interactions, and antiviral efficacy across multiple norovirus genotypes.

Aims: Organohalide-respiring bacteria, which utilize organohalides as electron acceptors for energy conservation, play an important role in the global halogen cycle. Organobromine compounds, both natural and anthropogenic, are prevalent in marine habitats, and we therefore aimed to characterize debrominating bacteria from estuarine and marine habitats.

Methods and results: We isolated two anaerobic debrominating bacteria, strain AK and strain HS, of the family Desulfovibrionaceae (in the phylum Thermodesulfobacteriota) from estuarine sediments in New Jersey, USA. Their growth was supported by lactate as a carbon source and 2,6-dibromophenol or sulfate as an electron acceptor, but not lactate alone, indicating that respiratory reductive dehalogenation or sulfate reduction is used for energy generation. In addition to 2,6-dibromophenol, these two strains can also dehalogenate a variety of other brominated compounds. Debrominating activity was not influenced by the presence of sulfate or exogenous cobalamin. Whole genome comparison indicates that these two strains share high similarity with an average nucleotide identity (ANI) of 97.8% and share low similarity (ANI < 90%) with other Halodesulfovibrio species (Halodesulfovibrio marinisediminis, Halodesulfovibrio aestuarii, and Halodesulfovibrio spirochaetisodalis). Whole genome-based phylogenetic analysis indicates that these two strains belong to the genus Halodesulfovibrio and likely represent a new species. Their genomes encode three putative reductive dehalogenase genes and the genes encoding for corrinoid biosynthesis and salvaging. Transcriptional analysis of reductive dehalogenase genes shows that the expression of one reductive dehalogenase gene (rdhA1) is induced by 2,6-dibromophenol, indicating its function in debromination.

Conclusions: This study expands our knowledge about the organohalide respiring potential of marine and estuarine Thermodesulfobacteriota.

Aims: Pyrazinamide (PZA) resistance in Mycobacterium tuberculosis challenges tuberculosis management, primarily through pncA mutations, while broader transcriptional adaptations remain unclear. This study aimed to characterize the transcriptomic adaptations associated with PZA resistance using a PZA-resistant clinical strain carrying a 10-nucleotide deletion in pncA (positions 118-127) that abolishes PZA activation (PZAR), in comparison with drug susceptible laboratory strain H37Rv under PZA treated (RvT) and untreated (UTRv) conditions.

Methods and results: Strain specific PZA concentrations was established at 200 µg mL-1 for the PZA-resistant strain (PZAR) and 12.5 µg mL-1 for the H37Rv strain (RvT). Untreated H37Rv strain was used as a reference for comparison. RNA-sequencing identified 3413 differentially expressed genes (Padj ≤ 0.05), including 1428 upregulated and 1360 downregulated genes, while the remaining 625 genes showed moderate but statistically significant expression changes. Functional enrichment was most pronounced in PZAR vs RvT comparison, followed by PZAR vs UTRv, whereas no significant enrichment was observed in RvT vs UTRv, indicating a strong association between the pncA mutation and PZA-responsive transcriptomic profiles. Ribosomal machinery genes (rplC, rplD, and rpsH) were significantly enriched and strongly upregulated in the resistant strain under treatment but only mildly regulated in the laboratory strain. Several anti-TB drug targets (katG, ethA, atpE, panD) were downregulated, while efflux pump genes (Rv1258, Rv3008, Rv3756c) were upregulated, reflecting a coordinated transcriptional response across drug targets. Network analysis identified 19 gene clusters, with prominent modules comprising polyketide synthases, phthiocerol dimycocerosate synthesis genes, fatty acid β-oxidation enzymes, and ESAT-6 (ESX) secretion system.

Conclusion: These findings uncover mutation-associated and PZA-responsive transcriptomic signatures that reveal adaptive pathways involved in tolerance under drug pressure and provide a framework for future functional and therapeutic investigations.

Aims: Food-grade titanium dioxide (E171) is widely used as a food additive, yet concerns persist regarding potential gastrointestinal effects, possibly mediated by interactions with the gut microbiome. This study aimed to investigate the physicochemical behavior of E171 under different digestive contexts and to assess its effects on gut microbial composition and metabolic activity.

Methods and results: The dynamic in vitro colon model TIM-2 was used to expose human fecal microbiota to E171 under fasted (aqueous suspension; E171-aq) and fed (yogurt matrix; E171-yog) conditions. Particle size distribution, reactive oxygen species formation, microbiome composition (16S rRNA gene sequencing), and short-chain fatty acid production were analyzed. Larger aggregates were observed under fasted conditions (mean diameter ∼210 nm), whereas digestion in yogurt produced smaller aggregates (mean diameter ∼167 nm) and a higher nanoparticle fraction, reaching up to 20%. No ROS production was detected following fermentation. Both E171-aq and E171-yog significantly increased butyrate levels, indicating altered microbial metabolic activity. Microbiome profiling revealed compositional shifts, including a decreased relative abundance of Blautia and an increased relative abundance of Lachnospiraceae, taxa associated with inflammatory and metabolic responses.

Conclusions: E171 undergoes distinct physicochemical transformations depending on the digestive context, with enhanced nanoparticle formation under fed conditions. E171 exposure also modulates gut microbiome composition and function, notably by stimulating butyrate production.

Aims: Microbial communities have recently emerged as promising biomarkers for forensic applications, offering novel perspectives to complement traditional approaches. This review aims to synthesise current evidence on how microbiome signals can be translated into usable forensic intelligence across crime-scene investigation and medico-legal casework.

Methods and results: This review summarizes advances in three key areas: soil evidence tracing, postmortem interval (PMI) estimation, and individual identification in sexual assault cases. Soil microbiome, shaped by geography and environment, provides distinctive signatures that can link evidence to specific locations. Dynamic microbial succession during decomposition provides a temporal indicator for PMI estimation, while human microbiota, with their site-specific and relatively stable features, show potential for identifying individuals and inferring physical contact. Alongside these applications, this review also briefly discusses past and current microbiome analysis techniques, as well as machine learning models.

Conclusions: Despite rapid advances, major obstacles remain, including instability of microbial communities and risks of contamination. Addressing these challenges will require validated protocols and robust to support reliable interpretation in forensic practice.