Journal of Basic Microbiology最新文献

Petrochemicals have emerged as an environmental hazard requiring innovative, sustainable remediation strategies. Bioremediation, specifically by genetically modified microorganisms (GMMs), is well known to produce surfactants that have emerged as a promising source to catalyze the efficiency of hydrocarbon degradation. The surfactant produced by GMMs facilitates the emulsification and dispersion of petroleum hydrocarbons. This review discusses the current state of biodegradation research, specifically on GMMs engineered to synthesize surfactant, which play an important role in enhancing the solubility of hydrophobic contaminants, such as oil components, thereby enhancing microbial access for degradation. The GMMs explored to optimize surfactant production and tailor their bioremediation efficiency. Furthermore, highlights the environmental benefits of utilizing GMMs for surfactant production, emphasizing the potential for a sustainable and cost-effective remediation strategy. Challenges and ethical considerations associated with the release of genetically modified organisms into the environment are also discussed, underscoring the importance of thorough risk assessments and regulatory frameworks. In conclusion, the integration of GMMs capable of producing surfactants presents a promising avenue for addressing petrochemicals through efficient and environmentally conscious bioremediation strategies. Future research should focus on optimizing the performance and safety of these engineered organisms to ensure their successful application in real-world environmental scenarios.

Cordycepin, a nucleoside analog derived from Cordyceps militaris, is a bioactive compound with potent pharmacological properties and growing relevance in functional food and pharmaceutical industries. However, its production is highly variable depending on cultivation conditions, making real-time and scalable prediction essential for efficient process control. This study aimed to develop a machine learning-based predictive model to estimate cordycepin content based on measurable cultivation parameters. Three machine learning algorithms—XGBoost, Random Forest, and Support Vector Machine—were trained using experimental data encompassing environmental and nutritional factors. Model validation was conducted using Tropsha's statistical criteria, and model explainability was achieved through SHAP analysis. A user-friendly GUI was also developed for real-time prediction and application. Among the models, XGBoost demonstrated the highest performance with a cross-validated Q² of 0.9087 and an R² of 0.9544, satisfying all statistical requirements for reliability. SHAP analysis identified light wavelength and carbon/nitrogen ratio as the most influential factors in cordycepin biosynthesis. The developed GUI enables end-users to input cultivation conditions and receive immediate predictions, facilitating data-driven decision-making. This approach offers a scalable and interpretable framework for optimizing bioactive compound production in edible fungi, with potential application in smart bioprocessing and precision fermentation.

Pathogen-host interactions can involve cooperation or synergy, as well as competition and coexistence among different species. The host plant can also influence the competition among pathogens through defense mechanisms that target one or multiple pathogens, either in an active or passive manner. Nonetheless, typically, more virulent pathogens manage to bypass the host's defence strategies to establish infection. Research on plant-pathogen interactions primarily focuses on the model systems of a single host being infected by a single disease and model systems like Arabidopsis thaliana or Nicotiana benthamiana infected with pathogen have been generally used to identify genetic and molecular mechanism involved in plant immunity. However, in natural environments, microbes exist within complex communities, and plant infections often involve multiple genotypes, introducing complexities that the single host-single disease model cannot adequately clarify. In this discussion, we explore the latest insights into the interactions between hosts and multiple pathogens, as well as their impacts on both host resistance and vulnerability. We emphasize recent developments in co-infection systems and examine their potential implications for the epidemiology and management of plant diseases.

The emergence of multidrug-resistant (MDR) bacteria is facilitated by the excessive and inappropriate use of antibiotics in aquaculture. This study assessed antibiotic resistance profiles and heavy metal responses of bacteria isolated on Thiosulfate Citrate Bile Salts Sucrose (TCBS) agar from six sample types across three fish farms, yielding 51 isolates belonging to nine genera and 12 bacterial classes, with Staphylococcus being the most predominant genus. Although they appeared as Gram-positive on TCBS agar, 16S rRNA sequencing confirmed their taxonomic identity, indicating that TCBS selectivity requires reevaluation. Half of the isolates were multidrug-resistant (50.98%), and MDR and MAR index >0.2 were more frequent in Gram-negative (71%) than in Gram-positive isolates (33%). The most prevalent resistance determinants were tetM (62.7%) and tetA (54.9%), while only one isolate carried a carbapenemase gene. Biofilm formation was observed in 80.4% of isolates. Heavy metal susceptibility followed the order Cd²⁺ > Cr⁶⁺ > Zn²⁺ > Pb²⁺, and co-exposure to Cd²⁺, Zn²⁺, and Cr⁶⁺ (40 ppm) significantly increased resistance to imipenem. These findings indicate that aquaculture environments may act as reservoirs for co-resistant pathogens, posing potential risks to food safety and public health.

Multiple replication sequences in a genome can provide multiple integration sites, thus increasing target gene integration efficiency. In this study, in the Escherichia coli BL21(DE3) genome, we identified 19 multicopy sequences including rDNA sites and insAB repeats that occurred 28 times and had the highest copy number. For target gene integration, at least 15/28 insAB sites underwent target gene integration with no concomitant effects on cell growth. In addition, lacZ activity at insAB sites reached approximately 4000 U/mg and was ten times that of rDNA sites. From our data, multicopy insAB sequences had favorable sites for target gene integration in E. coli. Therefore, using insAB sites, targeted gene expression in the E. coli genome can be conveniently adjusted to high levels.

A novel Gram-stain positive bacterial strain, GB16_1_BI, with 70.3% G+C content was isolated from rice roots cultivated in the Madhyamgram field station of Bose Institute, West Bengal, India. GB16_1_BI is a nonmotile, nitrate reducing, ammonium releasing and plant growth promoting bacteria. The average nucleotide identity-analysis of GB16_1_BI showed highest identity with Microbacterium enclense NIO-1002^T (ANIb: 82.55%; ANIm: 87.51%) and Microbacterium phycohabitans KSW2-29^T (ANIb: 82.53%; ANIm: 86.79%). Type strain genome server comparison of whole genome sequence of GB16_1_BI with genomes sequences for other species of the genus predicted that GB16_1_BI as a novel species with the digital DNA-DNA hybridization values of < 30% with its closest phylogenetic relatives. The 16S rRNA sequence of GB16_1_BI showed 98.72% similarity with Microbacterium proteolyticum RZ36^T, 98.42% similarity with Microbacterium phycohabitans KSW2-29^T and 98.43% with M. enclense NIO-1002^T. Whole cell fatty acid analyses showed iso-C16:0, anteiso-C17:0 and anteisoC15:0 as the predominant fatty acids. The strain was designated as Microbacterium bengalense sp. nov GB16_1_BIT (=MTCC 13245=JCM 37885).

Aphis gossypii Glover (Hemiptera: Aphididae) poses a major threat to okra cultivation, causing significant yield losses worldwide. This study evaluated the efficacy of the entomopathogenic fungus Lecanicillium fusisporum strain NBAIR-Vl8 against A. gossypii in both laboratory and field environments, along with Metarhizium anisopliae NBAIR-Ma4 and Beauveria bassiana NBAIR-Bb5a. L. fusisporum NBAIR-Vl8 exhibited high virulence, with an LC₅₀ of 4.22 × 10⁴ spores/mL and LT₅₀ and LT₉₀ values of 60.45 h and 86.97 h, respectively. Over 2 years of field trials, there were significant reductions in aphid (73.65%) and leafhopper, Amrasca biguttula biguttula (67.93%) populations and increased yield (6.64 q ha⁻¹) compared to untreated plots (3.98 q ha⁻¹). LC-MS/MS and GC-MS analyses of NBAIR-Vl8 identified important bioactive metabolites, including penitrem D, zwittermicin A, β-sitosterol, curcumin, and (1 R,2S)-naphthalene 1,2-oxide. To explore potential molecular targets, homology models of A. gossypii nicotinic acetylcholine receptor (nAChR) and chemosensory protein CSP8, as well as A. biguttula biguttula ribosomal protein L13 and tubulin beta chain, were developed and validated. Molecular docking using AutoDock Vina revealed that penitrem D had the highest binding affinities (−8.9 kcal/mol for nAChR), surpassing the commercial insecticide thiamethoxam (−5.4 kcal/mol for nAChR). β-sitosterol and curcumin also demonstrated strong interactions with CSP8 and structural proteins. These targets are essential for neurotransmission, olfaction, protein synthesis, and cytoskeletal integrity, indicating a multitarget mechanism of action of the drug. NBAIR-Vl8 shows significant biocontrol potential, supported by in vitro, field, and in silico evidence, highlighting its potential as a broad-spectrum microbial pesticide for integrated pest management.

Paramyrothecium roridum has recently emerged as a notable foliar pathogen of cotton in India, yet information on its population diversity remains limited. This study provides the first integrated assessment of the morpho-genetic diversity of P. roridum across traditional and non-traditional cotton-growing regions of Haryana. Thirty isolates collected from diseased cotton leaves exhibited clear phenotypic variability in colony appearance, sporodochial structures, growth patterns, and conidial dimensions, indicating considerable morphological plasticity within the species. ITS rRNA sequencing grouped all isolates into a single major clade with a small internal subgroup, reflecting overall genetic coherence with minor evolutionary divergence. Analysis of 544 nucleotide sites identified 20 segregating sites, demonstrating measurable polymorphism among isolates. Non-traditional cotton regions displayed greater genetic variability and more segregating sites than traditional areas, suggesting a broader genetic base and the influence of distinct ecological or agronomic selection pressures. Despite this variability, the low genetic differentiation coefficient indicated that all isolates constitute a largely panmictic population with unrestricted gene flow across cotton-growing zones. By combining morphological and molecular characterization, this study enhances understanding of P. roridum diversity, its dispersal potential, and evolutionary dynamics within Haryana. To the best of our knowledge, this is the first detailed investigation of P. roridum population structure in Haryana's cotton ecosystem.