Digital insights into Pseudomonas aeruginosa PBH03: in-silico analysis for genomic toolbox and unraveling cues for heavy metal bioremediation

Genes Genomics. 2024 Dec 23. doi: 10.1007/s13258-024-01609-4. Online ahead of print.

Abstract

Background: The genomes of publicly available electroactive Pseudomonas aeruginosa strains are currently limited to in-silico analyses. This study analyzed the electroactive Pseudomonas aeruginosa PBH03 genome using comparative in-silico studies for biotechnological applications.

Objective: Comparative in-silico and experimental analyses were conducted to identify the novel traits of P. aeruginosa PBH03 by genome sequencing.

Methods: The publicly available genomes of Pseudomonas aeruginosa strains (PA01, PA14, and KRP1) were used for a comparative in-silico study with PBH03. Genome assembly, annotation, phylogenetic analysis, metabolic reconstruction, and comparative functional genes analysis were conducted using bioinformatics tools. The experimental analyses were conducted to validate the heavy metal resistance (Hg and Cu), salinity tolerance levels of PBH03, and acetate assimilation under microaerobic conditions.

Results: Computational analysis showed that the PBH03 genome had a size of 6.8 Mb base pairs with a GC content of 65.7%. Whole genome annotation identified the unique genes absent in the previously sequenced Pseudomonas aeruginosa genomes. These genes were associated with resistance to heavy metals, such as Cu, Hg, As, and a Co-Zn-Cd efflux system. In addition, clustered, regularly interspaced short palindromic repeats, transposable elements, and conjugative transfer proteins were observed in the clustering-based systems. The strain exhibited resistance to Hg (150 mg/L) and Cu (500 mg/L) and showed growth at salinity levels of 40 g/L (typical sea/ocean levels). PBH03 could consume acetate up to 110 mM.

Conclusion: Integrating in-silico and experimental data highlights the intriguing adaptive genomic qualities of PBH03, making it a promising candidate for various biotechnological applications.

Keywords: Bioinformatics; Comparative genomics; Genome sequencing; Heavy metal resistance.