PT  - JOURNAL ARTICLE
AU  - Yuiko Takebayashi
AU  - Wan Ahmad Kamil Wan Nur Ismah
AU  - Jacqueline Findlay
AU  - Kate J. Heesom
AU  - Jay Zhang
AU  - O. Martin Williams
AU  - Alasdair P. MacGowan
AU  - Matthew B. Avison
TI  - Prediction of cephalosporin and carbapenem susceptibility in multi-drug resistant Gram-negative bacteria using liquid chromatography-tandem mass spectrometry
AID  - 10.1101/138594
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 138594
4099  - http://biorxiv.org/content/early/2017/05/16/138594.short
4100  - http://biorxiv.org/content/early/2017/05/16/138594.full
AB  - In vitro antibacterial susceptibility testing informs clinical decision making concerning antibacterial therapeutics. Predicting, in a timely manner, which bacterial infection will respond to treatment by a given antibacterial drug reduces morbidity, mortality, and healthcare costs. It also allows prudent antibacterial use, because clinicians can focus on the least broad-spectrum agent suitable for each patient. Existing susceptibly testing methodologies rely on growth of bacteria in the presence of an antibacterial drug. There is significant interest in the possibility of predicting antibacterial drug susceptibility directly though the analysis of bacterial DNA or protein, because this may lead to more rapid susceptibility testing directly from clinical samples. Here we report a robust and tractable methodology that allows measurement of the abundance of key proteins responsible for antibacterial drug resistance within samples of 1 µg of total bacterial protein. The method allowed correct prediction of β-lactam susceptibility in clinical isolates from four key bacterial species and added considerable value over and above the information generated by whole genome sequencing, allowing for gene expression, not just gene presence to be considered, which is key when considering the complex interplays of multiple mechanisms of resistance.