%0 Journal Article %A Colles, F. M. %A Maiden, M. C. J. %T Campylobacter sequence typing databases: applications and future prospects %D 2012 %J Microbiology, %V 158 %N 11 %P 2695-2709 %@ 1465-2080 %R https://doi.org/10.1099/mic.0.062000-0 %I Microbiology Society, %X Human campylobacteriosis, caused by the zoonotic bacteria Campylobacter jejuni and Campylobacter coli, remains a major cause of gastroenteritis worldwide. For many countries the implementation of effective interventions to reduce the burden of this disease is a high priority. Nucleotide sequence-based typing, including multilocus sequence typing (MLST) and antigen gene sequence typing (AGST), has provided unified, comprehensive, and portable Campylobacter isolate characterization, with curated databases of genotypes available (pubMLST.org/campylobacter). Analyses of large collections of isolates from various sources with these approaches have provided many insights into the epidemiology of these ubiquitous and diverse organisms. C. jejuni and C. coli populations are structured into clonal complexes, which reflect genealogy and are associated with specific phenotypes, e.g. the predisposition to infect particular animals, a property that has permitted the development of genetic means of attributing isolates from human disease to potential sources. This has identified retail meat, and especially chicken, as the likely cause of most human disease in many countries, although some human isolates have other likely origins. Such data have led directly to effective intervention studies and will be important in ongoing targeting of intervention strategies and the monitoring of their effectiveness. MLST and AGST data have also been employed in epidemiological investigations and studies of Campylobacter evolution and population biology. The sequence databases that have been established are compatible with the whole-genome sequencing (WGS) approaches likely to be implemented soon; indeed, the hierarchical approach adopted by MLST and AGST will be essential for the exploitation of WGS data. %U https://www.microbiologyresearch.org/content/journal/micro/10.1099/mic.0.062000-0