Saudi Pharmaceutical Journal (Jun 2023)

Draft genome sequence of potato crop bacterial isolates and nanoparticles-intervention for the induction of secondary metabolites biosynthesis

  • Nada Al-Theyab,
  • Omar Alrasheed,
  • Hatem A. Abuelizz,
  • Mingtao Liang

Journal volume & issue
Vol. 31, no. 6
pp. 783 – 794

Abstract

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Introduction: Insights about the effects of gold nanoparticles (AuNPs) on the biosynthetic manipulation of unknown microbe secondary metabolites could be a promising technique for prospective research on nano-biotechnology. Aim: In this research, we aimed to isolate a fresh, non-domesticated unknown bacterium strain from a common scab of potato crop located in Saudi Arabia and study the metabolic profile. Methodology: This was achieved through genomic DNA (gDNA) sequencing using Oxford Nanopore Technology. The genomic data were subjected to several bioinformatics tools, including canu-1.9 software, Prokka, DFAST, Geneious Prime, and AntiSMASH. We exposed the culture of the bacterial isolate with different concentrations of AuNPs and investigated the effects of AuNPs on secondary metabolites biosynthesis using several analytical techniques. Furthermore, Tandem-mass spectrometric (MS/MS) technique was optimized for the characterization of several significant sub-classes. Results: The genomic draft sequence assembly, alignment, and annotation have verified the bacterial isolate as Priestia megaterium. This bacterium has secondary metabolites related to different biosynthetic gene clusters. AuNPs intervention showed an increase in the production of compounds with the molecular weights of 254 and 270 Da in a direct-dependent manner with the increase of the AuNPs concentrations. Conclusion: The increase in the yields of compound 1 and 2 concomitantly with the increase in the concentration of the added AuNPs provide evidences about the effects of nanoparticles on the biosynthesis of the secondary metabolites. It contributes to the discovery of genes involved in different biosynthetic gene clusters (BGCs) and prediction of the structures of the natural products.

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