Mind the gap! Typing Escherichia coli O157:H7 in the pre- and post-genomic revolution eras

Shiga toxin-producing Escherichia coli (STEC) serotype O157:H7 emerged in the 1980s as a cause of foodborne outbreaks of infectious intestinal disease. Over the last decade, whole-genome sequencing (WGS) has replaced phage typing (PT) as the typing method of choice to detect outbreaks and monitor trends of STEC O157:H7. The aim of this study was to correlate historical PT data with WGS outputs and to describe the continuous trends in STEC O157:H7 notifications in England over a 40-year period from 1985 to 2024.At the UK Health Security Agency (UKHSA), both PT and WGS typing schemes were in use for a 6-year period from 2016 to 2021, providing an opportunity to compare the two typing datasets. We focused on the three major phage types, PT2, PT21/28 and PT8, as the numbers of other phage types were comparatively low and did not make a notable impact on the trends. Lineage and sub-lineage typing data from 2016 to 2024 were superimposed on PT data from 1989 to 2021.Between 2016 and 2021, 3,229 isolates of STEC O157:H7 referred to UKHSA for typing were linked to PT, Shiga toxin (stx) subtype and WGS data. For PT21/28 stx2, there was a good correlation between sub-lineage Ic (n=495/499, 99.2%). PT8 stx2 isolates were associated with sub-lineage IIb (n=215/262, 82.1%), and PT8 stx1+2 isolates aligned with sub-lineage IIc (n=851/857, 99.3%). Notifications of PT2 stx2 were low, and the correlation with lineage I/II during the overlapping time frame was less robust (n=48/85, 56.5%), although analysis of historical data indicated that the association was stronger when PT2 notifications were at their peak in the 1980s and 1990s.We extrapolated the sub-lineage data for the four major STEC O157:H7 PT and stx profiles in the UK, to bridge the gap across the pre- and post-genomic revolution eras and to facilitate future trend analyses based on sub-lineage alone. We created a window to the past to review the WGS data in the context of the historical PT data. This enabled us to link common exposures, learn from previous outbreak investigations and predict, investigate and prepare for emerging threats to public health.