Development of a Python Pipeline for the Analysis of Campylobacter

Abstract: Statens veterinärmedicinska anstalt, SVA, is a government agency that works for better animal and human health with a primary focus on infectious animal diseases. One of their projects involves tracking the spread of Campylobacter infection in broilers and the occurrence of antimicrobial resistance in these bacteria. A pipeline was developed to contribute to making the analysis of Whole Genome Sequencing (WGS) data from Campylobacter more effective. This was done by changing the currently used pipeline’s programming language from Perl to Python and adding the possibility to run multiple analyses in parallel. With parallelization, the time for running multiple analyses was reduced compared to running them sequentially, even if it was not as fast in practice as in theory. It also did not work as well when running parallel analyses of different strains compared to identical strains. Furthermore, different attributes of the pipeline were changed or added to improve the pipeline and a database comparison was performed in order to suggest the best ones for future use. VFDB, CARD, and MEGARes were suggested as appropriate databases to use in future WGS analysis of Campylobacter. Due to a lack of resources and technical difficulties, some of the requested attributes for the pipeline could not be implemented, such as the tool Pilon and the inclusion of MLST and cgMLST analysis. Nonetheless, the pipeline is well structured, has most of the requested tools, and is easy to run. With some minor improvements, the pipeline will be a useful tool for SVA and their project.