Affiliations 

  • 1 Biotechnology Centre, Faculty of Science, University of Yaoundé 1, Yaoundé, Cameroon
  • 2 Unit for Environmental Sciences and Management, North-West University, Potchefstroom, South Africa
  • 3 Laboratory of Bacteriology, Yaoundé University Teaching Hospital, Yaoundé, Cameroon
  • 4 Bacteriology Service, Centre Pasteur du Cameroun, Yaoundé, Cameroon
  • 5 Food Security and Safety Niche Area, Faculty of Natural and Agricultural Sciences, North-West University, Mmabatho, South Africa
PLoS One, 2020;15(9):e0238390.
PMID: 32886694 DOI: 10.1371/journal.pone.0238390

Abstract

Pseudomonas aeruginosa has been implicated in a wide range of post-operation wound and lung infections. A wide range of acquired resistance and virulence markers indicate surviving strategy of P. aeruginosa. Complete-genome analysis has been identified as efficient approach towards understanding the pathogenicity of this organism. This study was designed to sequence the entire genome of P. aeruginosa UY1PSABAL and UY1PSABAL2; determine drug-resistance profiles and virulence factors of the isolates; assess factors that contribute toward stability of the genomes; and thereafter determine evolutionary relationships between the strains and other isolates from similar sources. The genomes of the MDR P. aeruginosa UY1PSABAL and UY1PSABAL2 were sequenced on the Illumina Miseq platform. The raw sequenced reads were assessed for quality using FastQC v.0.11.5 and filtered for low quality reads and adapter regions using Trimmomatic v.0.36. The de novo genome assembly was made with SPAdes v.3.13 and annotated using Prokka v.2.1.1 annotation pipeline; Rapid Annotation using Subsytems Technology (RAST) server v.2.0; and PATRIC annotation tool v.3.6.2. Antimicrobial resistance genes and virulence determinants were searched through the functional annotation data generated from Prokka, RAST and PATRIC annotation pipelines; In addition to ResFinder and Comprehensive Antibiotic Resistance Database (CARD) which were employed to determine resistance genes. The PHAge Search Tool Enhanced Release (PHASTER) web server was used for the rapid identification and annotation of prophage sequences within bacterial genome. Predictive secondary metabolites were identified with AntiSMASH v.5.0. Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) and cas genes regions were also investigated with the CRISPRone and CRISPRFinder server. The genome sizes of 7.0 and 6.4 Mb were determined for UY1PSABAL and UY1PSABAL2 strains with G+C contents of 66.1% and 66.48% respectively. β-lactamines resistance genes blaPAO, aminoglycoside phosphorylating enzymes genes aph(3')-IIb, fosfomycine resistance gene fosA, vancomycin vanW and tetracycline tetA were among identified resistance genes harboured in both isolates. UY1PSABAL bore additional aph(6)-Id, aph(3'')-Ib, ciprofloxacin-modifying enzyme crpP and ribosomal methylation enzyme rmtB. Both isolates were found harbouring virulence markers such as flagella and type IV pili; and also present various type III secretion systems such as exoA, exoS, exoU, exoT. Secondary metabolites such as pyochelin and pyoverdine with iron uptake activity were found within the genomes as well as quorum-sensing systems, and various fragments for prophages and insertion sequences. Only the UY1PSABAL2 contains CRISPR-Cas system. The phylogeny revealed a very close evolutionary relationship between UY1PSABAL and the similar strain isolated from Malaysia; the same trend was observed between UY1PSABAL2 and the strain from Chinese origin. Complete analyses of the entire genomes provide a wide range of information towards understanding pathogenicity of the pathogens in question.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.