A bioinformatic approach to understanding antibiotic resistance in intracellular bacteria through whole genome analysis

Int J Antimicrob Agents. 2008 Sep;32(3):207-20. doi: 10.1016/j.ijantimicag.2008.03.017. Epub 2008 Jul 10.

Abstract

Intracellular bacteria survive within eukaryotic host cells and are difficult to kill with certain antibiotics. As a result, antibiotic resistance in intracellular bacteria is becoming commonplace in healthcare institutions. Owing to the lack of methods available for transforming these bacteria, we evaluated the mechanisms of resistance using molecular methods and in silico genome analysis. The objective of this review was to understand the molecular mechanisms of antibiotic resistance through in silico comparisons of the genomes of obligate and facultative intracellular bacteria. The available data on in vitro mutants reported for intracellular bacteria were also reviewed. These genomic data were analysed to find natural mutations in known target genes involved in antibiotic resistance and to look for the presence or absence of different resistance determinants. Our analysis revealed the presence of tetracycline resistance protein (Tet) in Bartonella quintana, Francisella tularensis and Brucella ovis; moreover, most of the Francisella strains possessed the blaA gene, AmpG protein and metallo-beta-lactamase family protein. The presence or absence of folP (dihydropteroate synthase) and folA (dihydrofolate reductase) genes in the genome could explain natural resistance to co-trimoxazole. Finally, multiple genes encoding different efflux pumps were studied. This in silico approach was an effective method for understanding the mechanisms of antibiotic resistance in intracellular bacteria. The whole genome sequence analysis will help to predict several important phenotypic characteristics, in particular resistance to different antibiotics. In the future, stable mutants should be obtained through transformation methods in order to demonstrate experimentally the determinants of resistance in intracellular bacteria.

Publication types

  • Review

MeSH terms

  • Animals
  • Anti-Bacterial Agents / pharmacology*
  • Bacteria / drug effects*
  • Bacteria / genetics
  • Base Sequence
  • Computational Biology / methods*
  • Cytoplasm / microbiology*
  • Drug Resistance, Bacterial* / genetics
  • Genome, Bacterial*
  • Humans
  • Microbial Sensitivity Tests
  • Molecular Sequence Data
  • Mutation
  • Phagosomes / microbiology*
  • RNA, Ribosomal, 23S / genetics
  • Sequence Analysis, DNA*

Substances

  • Anti-Bacterial Agents
  • RNA, Ribosomal, 23S