Data to accompany "Clinical and wildlife populations share Salmonella enterica core genomes but harbour distinct resistomes: a multi-year study of cohabiting populations in a high sanitation urban setting"

This Figshare contains 6 files: - README excel file describing the data included in the figshare, with detailed metadata and source/processing info for the four data frames - 4 .csv files (dataframes) called in statistical analysis - these are processed from bioinformatic outputs, as detailed in the readme file - One .r script that includes the code used to generate tables, figures (excluding Fig1 - Salmonella phylogeny, and Extended data Figure 5 (Antimicrobial Resistance Gene hits across Salmonella phylogeny)), and statistical analyses presented in the manuscript These files relate to 188 Salmonella enterica subsp. enterica genomes sourced from Silver gulls or clinical cases in the Illawarra region of NSW. Cloacal swabs from Silver gull chicks sampled during the breeding season in 2012 and 2017-2019 on Big Island, Five Islands Nature Reserve, NSW under approval from the Office of Environment and Heritage Animal Ethics Committee (permit 021028/02; 2012), the University of Wollongong Animal Ethics Committee (AE17/20; 2017-2019), the NSW National Parks and Wildlife Service (Scientific Licences 100668 and 100109), the ABBBS (project 2731-03) and Czech nature protection authorities (Permissions S-JMK78643/2018 OŽP/Ško and S-JMK 40970/2019 OŽP/Ško). Human clinical faecal samples were collected when patients presented with clinical symptoms consistent with suspected Salmonella infection to any of the 8 public hospitals of the Illawarra Shoalhaven Local Health District (ISLHD) or to a general practitioner (GP). Human clinical isolates were obtained under approval from the Joint University of Wollongong and Illawarra and Shoalhaven Local Health District Human Research Ethics Committee (HREA 2018/464). Isolates were sequenced using an Illumina NovaSeq producing paired-end reads of 150 bp and subsequently analysed through several bioinformatic pipelines, including read filtering, genomic assembly, species identification, quality control, phylogenetic analysis, cgMLST clustering and identification of antimicrobial resistance genes carried, as detailed in the methods section of the manuscript.