Biotechnology Reports最新文献

Characterization of the temperature effects on the abundance and richness of the microbiota of Lutzomyia longipalpis, insect vector of Leishmania infantum in America, is an aspect of pivotal importance to understand the interactions between temperature, bacteria, and Leishmania infection. We developed and used a customized device with a temperature gradient (21–34 °C) to assess the temperature preferences of wild females of Lu. longipalpis collected in a rural area (Ricaurte, Cundinamarca, Colombia). Each replicate consisted of 50 females exposed to the gradient for an hour. At the end of the exposure time, insects were collected and separated by the temperature ranges selected varying from 21 °C to 34 °C. They were organized in 17 pools from which total DNA extracts were obtained, and samples were subjected to 16S rRNA amplicon sequencing analyzes. The most abundant phyla across the different temperature ranges were Proteobacteria (17.22–90.73 %), Firmicutes (5.99–77.21 %) and Actinobacteria (1.56–59.85 %). Results also showed an abundance (30 % to 57.36 %) of Pseudomonas (mainly at temperatures of 21–29 °C and 34 °C) that decreased to 6.55 %-13.20 % at temperatures of 31–33 °C, while Bacillus increase its abundance to 67.24 % at 29–33 °C. Serratia also had a greater representation (49.79 %), specifically in sand flies recovered at 25–27 °C. No significant differences were found at α-diversity level when comparing richness using the Shannon-Wiener, Simpson, and Chao1 indices, while β-diversity differences were found using the Bray-Curtis index (F-value of 3.5073, p-value < 0.013, R-squared of 0,4889), especially in the groups of Lu. longipalpis associated at higher temperatures (29–33 °C). It was also possible to detect the presence of endosymbionts such as Spiroplasma and Arsenophonus in the range of 29–33 °C. Rickettsia was only detected in Lu. longipalpis sand flies recovered between 25–27 °C. It was possible to characterize Lu. longipalpis microbiota in response to intraspecific temperature preferences and observe changes in bacterial communities and endosymbionts at different ranges of said environmental variable, which may be important in its vector competence and environmental plasticity to adapt to new climate change scenarios.

The oil contents and fatty acid composition of three non-edible seed oils extracted using Soxhlet extraction with hexane as the solvent were presented. The physical and chemical properties of the oils were determined from which cetane number, biofuel potential, higher heating values, and antimicrobial activities were assessed. The dominant fatty acids were 49 % linoleic acid, 37 % pentadecenoic acid, and 38 % cis-10-heptadecenenoic acid for Hura crepitans (HC), Thevetia nerifolia (TN) and Trichosanthes cucumerina (TC), respectively. The seed oils were majorly unsaturated, with HC having the highest degree of unsaturation. Acid value, saponification value, iodine value, and free fatty acids were low compared to many reported values in literature. The cetane values were generally high because the oils have a reasonable amount of saturated fatty acid, with TN having the highest cetane number. The low iodine value and saponification value make the biofuel potential and higher heating value to be high with TN having the highest in both and thus the best seed oil for biofuel. However, TN and HC have no antimicrobial activity to Klebsiella pneumoniae (gram -ve), Staphylococcus aureus (gram +ve), Escherichia coli (gram -ve), Bacillus subtilis, Enterobacter aerogenes, Candida albican, Rhizopus stolonifer, Fusarium Solani, Aspergillus flavus and Candida tropicalis, while TC has broad spectrum of activity against all tested bacteria and fungi, except Klebsiella pneumoniae.

Plants have an impact on the economy because they are used in the food and medical industries. Plants are a source of macro- and micronutrients for the health of humans and animals; however, the rise in microbial diseases has put plant health and yield at risk. Because there are insufficient controls, microbial infections annually impact approximately 25 % of the world's plant crops. Alternative strategies, such as biocontrol, are required to fight these illnesses. This review discusses the potential uses of recently discovered microorganisms because they are safe, effective, and unlikely to cause drug resistance. They have no negative effects on soil microbiology or the environment because they are environmentally benign. Biological control enhances indigenous microbiomes by reducing bacterial wilt, brown blotch, fire blight, and crown gall. More research is required to make these biocontrol agents more stable, effective, and less toxic before they can be used in commercial settings.

Outer membrane vesicles (OMVs), non-replicating spherical liposomes derived from Gram-negative bacteria, are a promising vaccine platform and multifunctional delivery systems. Their ability to be modified via genetic engineering for the incorporation and display of heterologous proteins enhances their functionality. In this study, we demonstrated a bio-ligation approach to display single-chain variable fragments (scFv) on the OMV surface using the SpyTag/SpyCatcher system. SpyTag-fused scFv, expressed by mammalian cells, bound to OMVs with SpyCatcher-fused Lpp'OmpA after a simple incubation. Biophysical analysis indicated that the conjugated OMVs maintained their physicochemical properties. We used an scFv targeting mucin 1 protein (MUC1) for specific cell targeting. Confocal microscopy revealed that conjugated OMVs specifically bound to and were internalized by MUC1-presenting cells, but not by MUC1-deficient cells. In conclusion, this rapid and efficient bio-ligation system facilitates the display of functional scFv on OMV surfaces, offering a promising approach for targeted delivery to MUC1-expressing cancer cells.

Fusarium wilt of Banana (FWB) caused by Fusarium oxysporum f. sp. cubense (Foc) poses a significant threat to the banana industry, with current inadequate control measures. This study evaluated the antifungal potential of nine Streptomyces strains isolated from Antarctic soil samples, using Casein-Starch media to stimulate the production of antifungal compounds. The inhibition spectrum against Foc was assessed under laboratory conditions using the well diffusion on Mueller-Hinton agar, with antifungal activity measured in arbitrary units (AU/mL) and minimum inhibitory concentration (MIC) tested using ethyl acetate extracts. Among the nine isolates, K6 and E7 were closely related to Streptomyces polyrhachis and Streptomyces fildesensis, exhibited significant antifungal activity, with K6 and E7 showing 320 and 80 AU/mL, and MIC values of 250 and >500 ppm, respectively. These findings highlight K6 and E7 as potential biocontrol agents against Foc, offering new avenues for sustainable Fusarium wilt management in banana cultivation.

The You Only Look Once (YOLO) deep learning model iterations—YOLOv7–YOLOv8—were put through a rigorous evaluation process to see how well they could recognize oil palm plants. Precision, recall, F1-score, and detection time metrics are analyzed for a variety of configurations, including YOLOv7x, YOLOv7-W6, YOLOv7-D6, YOLOv8s, YOLOv8n, YOLOv8m, YOLOv8l, and YOLOv8x. YOLO label v1.2.1 was used to label a dataset of 80,486 images for training, and 482 drone-captured images, including 5,233 images of oil palms, were used for testing the models. The YOLOv8 series showed notable advancements; with 99.31 %, YOLOv8m obtained the greatest F1-score, signifying the highest detection accuracy. Furthermore, YOLOv8s showed a notable decrease in detection times, improving its suitability for comprehensive environmental surveys and in-the-moment monitoring. Precise identification of oil palm trees is beneficial for improved resource management and less environmental effect; this supports the use of these models in conjunction with drone and satellite imaging technologies for agricultural economic sustainability and optimal crop management.