Computer Program Predicts Drug Resistance by Evaluating Whole Genome Sequencing Data

By LabMedica International staff writers
Posted on 03 Jan 2016

A software package is being evaluated in the United Kingdom that can identify a bacterium from the DNA sequence of its genome and predict which antibiotics will kill it.

The Mykrobe Predictor software for laptop and tablet computer use was developed by investigators at the University of Oxford (United Kingdom). It supports Illumina Inc. (San Diego, CA, USA) instrument sequencing data as standard input. Antibiotics supported include: Beta-lactams (methicillin, penicillin), quinolones (ciprofloxacin), macrolides/lincosamides (erythromycin, clindamycin), tetracycline, aminoglycosides (gentamicin), glycopeptides (vancomycin), rifampicin, mupirocin, fusidic acid, and trimethoprim.

Image: A screenshot from the Mykrobe Predictor software package shows results for an analysis of a methicillin-resistant Staphylococcus aureus (MRSA) bacterium (Photo courtesy of Mykrobe [University of Oxford]).

The program takes raw sequence data as input and generates a clinician-friendly report within three minutes on a laptop or tablet computer.

Mykrobe Predictor is currently being evaluated in three medical centers in the United Kingdom. A preliminary study comprising more than 4,500 retrospective patient samples was published in the December 21, 2015, online edition of the journal Nature Communications. Results highlighted the ability of the Mykrobe Predictor program to accurately detect antibiotic resistance in two life-threatening bacterial infections: Staphylococcus aureus (including MRSA) and Mycobacterium tuberculosis (TB).

For S. aureus, the error rates of the method were comparable to gold-standard phenotypic methods, with sensitivity/specificity of 99.1%/99.6% across 12 antibiotics. For M. tuberculosis, the method predicted resistance with sensitivity/specificity of 82.6%/98.5%. Sensitivity was lower for M. tuberculosis, probably because of limited understanding of the underlying genetic mechanisms.

The program also identified infections caused by a mixture of drug-resistant and drug-susceptible bacteria. This ability to distinguish between bacterial sub-populations gave the Mykrobe Predictor program an advantage over conventional testing in detecting resistance to second-line TB drugs.

Senior author Dr. Zamin Iqbal, a researcher in human genetics at the University of Oxford, said, "One of the barriers to making whole genome sequencing a routine part of NHS care is the need for powerful computers and expertise to interpret the masses of complex data. Our software manages data quickly and presents the results to doctors and nurses in ways that are easy to understand, so they can instinctively use them to make better treatment decisions."

Related Links:
University of Oxford
Mykrobe Predictor
Illumina Inc.