World journal of microbiology & biotechnology最新文献

The function of the livestock gut microbiome in driving animal growth, health, and methane emissions is controlled by networks of interactions among microbes. A major challenge is to move beyond simply listing microbial members to understanding these interaction networks, which determine how the community functions as a whole. This review synthesizes how network analysis, combined with multi-omics data, can meet this challenge. We focus on the critical task of identifying keystone species, the disproportionately influential microbes that direct processes like fiber digestion and immune function, yet are often missed by standard surveys. We evaluate a progression of methods, from identifying correlated species to building models that integrate genomic, metabolic, and host data. This integration is key to separating true ecological relationships from statistical noise and to linking microbial presence to function. We highlight how computational techniques like metabolic modeling and machine learning are turning networks into predictive tools. Finally, we outline the path forward: field-ready studies that track microbiomes over time, the development of livestock-specific metabolic models, and analytical standards that will allow research to translate into practical strategies. The goal is to provide a framework for using network science to actively manage the microbiome, enhancing sustainable livestock production.

New Delhi Metallo-β-lactamase-1 (NDM-1) belongs to the carbapenemase family of enzymes, which can hydrolyse a wide range of β-lactam antibiotics. To date, 91 NDM-1 variants have been reported globally. In this study, we generated a novel mutant, NDM-1 D254A, through site-directed mutagenesis to investigate the functional role of non-active site residue Asp254. The wild-type NDM-1 and D254A mutant were cloned, purified, and systematically analyzed using steady-state kinetic assays and circular dichroism spectroscopy. Subsequently, we conducted Insilico studies, which include molecular docking and molecular dynamics (MD) simulations. The D254A mutant has reduced catalytic activity, thus indicating impaired β-lactam hydrolysis. Structural and computational analysis revealed that Asp254 plays an essential role in maintaining the protein stability. These findings illustrate the importance of Asp254 in maintaining the NDM-1 activity and provide the mechanistic insights into the structure-function relationship. This study enhances our understanding of NDM-1 variants and may aid the rational design of targeted inhibitors to counteract the rising global threat of NDM-1 mediated antibiotic resistance.

Psilocybin, a tryptamine-derived alkaloid from Psilocybe mushrooms, has emerged as a high-value biopharmaceutical candidate due to its promising applications in mental health. While clinical studies highlight its rapid and sustained antidepressant effects, current challenges lie in achieving scalable, reproducible, and cost-effective production to meet growing research and therapeutic demand. Traditional extraction from fungal biomass yields low concentrations and requires extensive downstream processing, limiting industrial viability. Chemical synthesis ensures purity but is hindered by high costs and multistep complexity. In contrast, biotechnological approaches have demonstrated significant progress toward sustainable production. Heterologous expression of psilocybin biosynthetic genes in Saccharomyces cerevisiae and Aspergillus nidulans has enabled improved metabolic flux and precursor availability, reaching titers over 200 mg/L under optimized conditions. Moreover, recent engineering Escherichia coli strains has further enhanced catalytic efficiency of key enzymes such as PsiH, achieving production levels up to 2000 mg/L, while simplifying fermentation and purification workflows. These advances establish microbial platforms as a promising route for industrial-scale biosynthesis. Beyond production, psilocybin offers an opportunity to integrate biotechnology with socio-cultural context. In regions where diversity of Psilocybe species and ancestral knowledge converge, the development of biotechnological pipelines could foster innovation in drug discovery, sustainable manufacturing, and policy reform. Overall, psilocybin exemplifies a frontier molecule in biotechnology, where metabolic engineering, synthetic biology, and bioresource valorization converge to transform a natural product into a reproducible, scalable, and globally relevant therapeutic.

Lactobacillus gallinarum Y86, isolated from broiler ileal mucosa under strict anaerobiosis (85% N₂/10% CO₂/5% H₂), demonstrates significant potential as a microbial feed additive for antibiotic-free farming. 16 S rRNA sequencing (99.79% identity to L. gallinarum ATCC 33199; GenBank ON248243) confirmed its taxonomy. Stationary-phase cultures secreted a heat-stable antimicrobial that produced inhibition zones of 21.53 ± 0.34 mm against Salmonella enterica serovar pullorum and 11.90 ± 0.52 mm against Staphylococcus aureus, retaining 87.30% activity after 120 °C for 15 min; sensitivity to trypsin and lipase indicates a proteolipid nature. Y86 endured pH 2.0 for 3 h (63.37% survival) before programmed lysis at 4 h, then recovered to 92.44% viability under intestinal conditions and maintained 45.36% viability in 0.5% bile. High surface hydrophobicity (85.71%) drove auto-aggregation to 97.99% within 24 h, supporting strong epithelial adhesion. The strain was susceptible to β-lactams, macrolides, and vancomycin, intrinsically resistant to tetracyclines and quinolones, and non-haemolytic, meeting EFSA-QPS safety criteria. Collectively, its thermostable antimicrobial production, timed gastric lysis, intestinal resilience, and proven safety identify Y86 as an industrially compatible candidate for antibiotic-free poultry feeds, advancing microbiota-based alternatives to growth-promoting antibiotics.

Bacterial soft rot is a major vegetable disease of global significance, predominantly associated with Pectobacterium species; however, new reports indicate that novel, emerging pathogens are contributing to disease incidence. This study identified a novel pathogen, Enterobacter cloacae, as a causal agent of radish soft rot. Two isolates, RDH1 and RDH3, were isolated from 20 decaying radish taproots collected from Kolar, Karnataka, India, where a 12% disease incidence was recorded. Biochemical and physiological characterization, alongside comparison with E. cloacae ATCC 13047, confirmed the genus identity. Molecular analysis of 16S rRNA sequences revealed 99.56 and 99.87% similarity of RDH1 and RDH3, respectively, to known E. cloacae strains. Pathogenicity assay confirmed the pathogenicity of both isolates, and semi-quantitative assessment of plant cell wall degrading enzymes showed RDH1 producing clearance zones of 12.00, 10.33, and 8.00 mm, while RDH3 exhibited zones of 12.00, 10.00, and 7.67 mm, of pectin lyase, polygalacturonase, and cellulase, respectively. Host range assays on 10 vegetable crops revealed RDH3 as more virulent, particularly in radish, carrot, and cabbage, with the hypodermal syringe method showing broader infectivity compared to minimal infection via coir-enrichment seedling inoculation. Further, whole genome sequencing of RDH3 revealed a 4.8 Mb genome, 55% GC content, a single plasmid, and 99% ANI similarity to E. cloacae GGT036, containing T6SS, T4SS, ICEs, prophages, genomic islands, and 12 horizontal gene transfer events. These findings underscore the emerging role of E. cloacae in vegetable soft rot and highlight the need for further research on its pathogenic mechanisms and management strategies.

Bacterial detection and identification is paramount as it plays a key role in safeguarding human health, food safety and security. Over the past decade, biosensors have emerged as a powerful tool for bacterial detection due to their ability to provide rapid, sensitive, specific and cost-effective monitoring of bacteria. Biosensors rely on the interaction between the target analyte and biological recognition elements, which triggers a measurable signal that can be quantified, thus enabling the detection of bacteria. In recent years, nanoparticles have become a focal point in biosensor research due to their unique physical and chemical properties, enhancing their sensitivity, specificity and functionality. Artificial intelligence, microfluidics and wearable biosensor technologies are shaping the next-generation real-time bacterial monitoring tools. AI-based biosensors interpret complex biological signals and provide automated detection of bacterial pathogens. Similarly, wearable biosensors are emerging as a promising option for non-invasive detection and monitoring of wound infections. Additionally, the integration of CRISPR/Cas systems into biosensing platforms has revolutionized molecular diagnostics by enabling highly specific detection of pathogenic bacteria. In forensic sciences, biosensors are being explored for the identification of body fluids based on their unique bacterial signatures, which can assist in crime scene reconstruction and post-mortem interval estimation. Most studies that have reported on biosensors for detection of bacteria, have targeted a single analyte or bacterial species. Given the growing interest and demand for multiplexed biosensors, future research should focus on developing biosensors capable of detecting multiple bacteria simultaneously, without compromising the accuracy. Biosensors with dual functionality will be instrumental in providing an integrated solution to detect, manage and control bacterial pathogens, thereby mitigating any potential threat to human health.