This article is part of the supplement: Eleventh International Conference on Bioinformatics (InCoB2012): Computational Biology
An approach to identifying drug resistance associated mutations in bacterial strains
1 Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Poland
2 School of Computing, National University of Singapore, Singapore
BMC Genomics 2012, 13(Suppl 7):S23 doi:10.1186/1471-2164-13-S7-S23Published: 13 December 2012
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.
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.
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.