title: An approach to identifying drug resistance associated mutations in bacterial strains.
abstract: BACKGROUND
  Drug resistance in bacterial pathogens is an increasing problem, which stimulates research. However, our understanding of drug resistance mechanisms remains incomplete. Fortunately, the fast-growing number of fully sequenced bacterial strains now enables us to develop new methods to identify mutations associated with drug resistance.
  
  
  RESULTS
  We present a new comparative approach to identify genes and mutations that are likely to be associated with drug resistance mechanisms. In order to test the approach, we collected genotype and phenotype data of 100 fully sequenced strains of S. aureus and 10 commonly used drugs. Then, applying the method, we re-discovered the most common genetic determinants of drug resistance and identified some novel putative associations.
  
  
  CONCLUSIONS
  Firstly, the collected data may help other researchers to develop and verify similar techniques. Secondly, the proposed method is successful in identifying drug resistance determinants. Thirdly, the in-silico identified genetic mutations, which are putatively involved in drug resistance mechanisms, may increase our understanding of the drug resistance mechanisms.
authors.affiliation: Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Poland. m.wozniak@mimuw.edu.pl
authors.forename: Michal
authors.initials: M
authors.lastname: Wozniak
authors.forename: Jerzy
authors.initials: J
authors.lastname: Tiuryn
authors.forename: Limsoon
authors.initials: L
authors.lastname: Wong
mesh_terms: D000465:Algorithms; D000900:Anti-Bacterial Agents / Q000494:pharmacology; D024881:Drug Resistance, Bacterial / Q000187:drug effects / Q000235:genetics*; D005838:Genotype; D009154:Mutation; D010641:Phenotype; D010802:Phylogeny; D013211:Staphylococcus aureus / Q000145:classification / Q000187:drug effects / Q000235:genetics*
chemical_list: D000900:Anti-Bacterial Agents