P087

1:National Institute for Public Health and the Environment

The detection of emerging SNPs within clustered isolates (genetic drift) could help determine transmission dynamics and support epidemiological investigations. Tools for the routine detection of non-fixed SNPs in resistance genes and as well for emerging SNPs are being developed. To interpret emerging SNPs throughout the genome calls need to be checked for quality and false calls removed otherwise any real signal is masked. We present a validated strategy to detect epidemiologically informative (emerging) variation in clustered isolates and present examples of how this can be used to support epidemiological investigations. Clusters are first identified using a SNP threshold then all potentially informative SNPs not present in all members of the cluster are determined. The positions where these potentially informative SNPs occur are then interrogated with respect to their distribution in a large collection of isolates and the average quality of sequencing data at these sites (to detect platform specific sequencing noise). In this way noisy or non-informative SNPs can be identified and exclude. The remaining informative SNPs are examined in all members of the cluster for to identify non-fixed / emerging SNPs. In eight clusters of epidemiologically linked cases investigated in detail so far emerging SNPs were identified in seven clusters which were fixed in other members of the cluster, suggesting a direct link and transmission direction between cases. Emerging SNPs are often associated with high bacterial load and transmission as other groups have observed.