%A Yue,Min %A Schifferli,Dieter %D 2014 %J Frontiers in Microbiology %C %F %G English %K Salmonella,colonization,adhesin,invasion,T3SS,snps %Q %R 10.3389/fmicb.2013.00419 %W %L %M %P %7 %8 2014-January-07 %9 Review %+ Dr Dieter Schifferli,University of Pennsylvania,Pathobiology,School of Veterinary Medicine,3800 Spruce Street,Philadelphia,19104-6049,PA,United States,dmschiff@vet.upenn.edu %# %! Allelic variation in Salmonella %* %< %T Allelic variation in Salmonella: an underappreciated driver of adaptation and virulence %U https://www.frontiersin.org/articles/10.3389/fmicb.2013.00419 %V 4 %0 JOURNAL ARTICLE %@ 1664-302X %X Salmonella enterica causes substantial morbidity and mortality in humans and animals. Infection and intestinal colonization by S. enterica require virulence factors that mediate bacterial binding and invasion of enterocytes and innate immune cells. Some S. enterica colonization factors and their alleles are host restricted, suggesting a potential role in regulation of host specificity. Recent data also suggest that colonization factors promote horizontal gene transfer of antimicrobial resistance genes by increasing the local density of Salmonella in colonized intestines. Although a profusion of genes are involved in Salmonella pathogenesis, the relative importance of their allelic variation has only been studied intensely in the type 1 fimbrial adhesin FimH. Although other Salmonella virulence factors demonstrate allelic variation, their association with specific metadata (e.g., host species, disease or carrier state, time and geographic place of isolation, antibiotic resistance profile, etc.) remains to be interrogated. To date, genome-wide association studies (GWAS) in bacteriology have been limited by the paucity of relevant metadata. In addition, due to the many variables amid metadata categories, a very large number of strains must be assessed to attain statistically significant results. However, targeted approaches in which genes of interest (e.g., virulence factors) are specifically sequenced alleviates the time-consuming and costly statistical GWAS analysis and increases statistical power, as larger numbers of strains can be screened for non-synonymous single nucleotide polymorphisms (SNPs) that are associated with available metadata. Congruence of specific allelic variants with specific metadata from strains that have a relevant clinical and epidemiological history will help to prioritize functional wet-lab and animal studies aimed at determining cause-effect relationships. Such an approach should be applicable to other pathogens that are being collected in well-curated repositories.