Design of an in-silico workflow to trace the spread of zoonotic bacteria using NGS data

Tracing the spread of foodborne illness to analyze and prevent future outbreaks has become a major subject of the food-producing industry and the national food agency these past decades, and one of the main worries of the veterinarian sector. Methods for comparing bacterial strains for this purpose have generally required substantial manual effort, and have provided insufficient information. With the rise of New Generation Sequencing technologies, and the phenomenal cost decrease for complete genome sequencing, new opportunities have arisen. The possibility to completely and simultaneously sequence dozens of bacterial samples at the same time for a reasonable cost is now available, and with it the need to create tools to exploit the data produced. In this work, we will discuss how bioinformatic tools, and in particular SNV calling and tree-building softwares, can be used to create a single-command, easy to use, fast-processing workflow using genomic sequencing data to analyze trace of bacteria from different locations and times; and how these results can be interpreted and exploited. For this purpose, We will explain the entire analyzing process, from sample isolation to genotyping, passing by library preparation and sequencing, using two batches of samples from two different serotypes of Salmonella enterica that were involved in outbreaks in Sweden these past years. One of these batch presenting a case of cross-contamination, its case will be used as a template for future analysis