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Biosynthesis of silver nanoparticles using actinomycetes, phytotoxicity on rice seeds, and potential application in the biocontrol of phytopathogens.

Ingrid P ZwarCaterina do Valle TrottaAna B S ZiottiMilton Lima NetoWelington L AraújoItamar S de MeloCristiane A OttoniAna Olívia de Souza
Published in: Journal of basic microbiology (2022)
To find effective silver nanoparticles (AgNPs) for control of phytopathogens, in this study, two strains of actinomycetes isolated from the soil of the Brazilian biome Caatinga (Caat5-35) and from mangrove sediment (Canv1-58) were utilized. The strains were identified by using the 16S rRNA gene sequencing as Streptomyces sp., related to Streptomyces mimosus species. The obtained AgNPs were coded as AgNPs 35 and AgNPs 58 and characterized by size and morphology using dynamic light scattering, zeta potential, transmission electron microscopy, and Fourier transformed infrared (FTIR). The antifungal activity of the AgNPs 35 and AgNPs 58 was evaluated in vitro by the minimal inhibitory concentration (MIC) assay on the phytopathogens, Alternaria solani, Alternaria alternata, and Colletotrichum gloeosporioides. The phytotoxic effect was evaluated by the germination rate and seedling growth of rice (Oryza sativa). AgNPs 35 and AgNPs 58 showed surface plasmon resonance and average sizes of 30 and 60 nm, respectively. Both AgNPs presented spherical shape and the FTIR analysis confirmed the presence of functional groups such as free amines and hydroxyls of biomolecules bounded to the external layer of the nanoparticles. Both AgNPs inhibited the growth of the three phytopathogens tested, and A. alternate was the most sensible (MIC ≤ 4 µM). Moreover, the AgNPs 35 and AgNPs 58 did not induce phytotoxic effects on the germination and development of rice seedlings. In conclusion, these AgNPs are promising candidates to biocontrol of these phytopathogens without endangering rice plants.
Keyphrases
  • silver nanoparticles
  • escherichia coli
  • gene expression
  • photodynamic therapy
  • heavy metals
  • dna methylation
  • risk assessment
  • high throughput
  • genome wide
  • data analysis