WGS accurately predicts antimicrobial resistance in Escherichia coli.OBJECTIVES
 The objective of this study was to determine the effectiveness of WGS in identifying resistance genotypes of MDR Escherichia coli and whether these correlate with observed phenotypes.


 Isolates with resistance to at least four antimicrobials in three classes were selected for WGS using an Illumina MiSeq.  WGS also revealed information about rare resistance mechanisms, such as structural mutations in chromosomal copies of ampC conferring third-generation cephalosporin resistance.


 WGS can provide comprehensive resistance genotypes and is capable of accurately predicting resistance phenotypes, making it a valuable tool for surveillance.  Moreover, the data presented here showing the ability to accurately predict resistance suggest that WGS may be used as a screening tool in selecting anti-infective therapy, especially as costs drop and methods improve.
WGS
Genotypic analysis was conducted with in-house Perl scripts using BLAST analysis to identify known genes and mutations associated with clinical resistance.



Perl scripts
Isolates with resistance to at least four antimicrobials in three classes were selected for WGS using an Illumina MiSeq. 
Illumina MiSeq