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Background Antibiotic resistance genes (ARGs) can spread among pathogens via horizontal gene transfer, resulting in imparities in their distribution even within the same species. Therefore, a pan-genome approach to analyzing resistomes is necessary for thoroughly characterizing patterns of ARGs distribution within particular pathogen populations. Software tools are readily available for either ARGs identification or pan-genome analysis, but few exist to combine the two functions. Results We developed Pan Resistome Analysis Pipeline (PRAP) for the rapid identification of antibiotic resistance genes from various formats of whole genome sequences based on the CARD or ResFinder databases. Detailed annotations were used to analyze pan-resistome features and characterize distributions of ARGs. The contribution of different alleles to antibiotic resistance was predicted by a random forest classifier. Results of analysis were presented in browsable files along with a variety of visualization options. We demonstrated the performance of PRAP by analyzing the genomes of 26 Salmonella enterica isolates from Shanghai, China. Conclusions PRAP was effective for identifying ARGs and visualizing pan-resistome features, therefore facilitating pan-genomic investigation of ARGs. This tool has the ability to further excavate potential relationships between antibiotic resistance genes and their phenotypic traits.

Background The disruption of the bacterial cell wall plays an important part in achieving quantitative extraction of DNA from Eubacteria essential for accurate analyses of genetic material recovered from environmental samples. Results In this work we have tested a dozen commercial bacterial genomic DNA extraction methodologies on an average of 7.70 × 106 (±9.05%), 4.77 × 108 (±31.0%), and 5.93 × 108 (±4.69%) colony forming units (CFU) associated with 3 cultures (n = 3) each of Brochothrix thermosphacta (Bt; Gram-positive), Shigella sonnei (Ss; Gram-negative), and Escherichia coli O79 (Ec; Gram-negative). We have utilized real-time PCR (qPCR) quantification with two specific sets of primers associated with the 16S rRNA “gene” to determine the number of copies CFU-1 by comparing the unknown target DNA qPCR results with standards for each primer set. Based upon statistical analyses of our results, we determined that the Agencourt Genfind v2, High Pure PCR Template Prep Kit, and Omnilyse methods consistently provided the best yield of genomic DNA ranging from 141 to 934, 8 to 21, and 16 to 27 16S rDNA copies CFU-1 for Bt, Ss, and Ec. If one assumes 6–7 copies of the 16S rRNA gene per genome, between 1 and 3 genomes per actively dividing cell and ≥ 100 cells CFU-1 for Bt (found to be a reasonable assumption using an optical method expounded upon herein) or between 1 and 2 cells CFU-1 for either Ss or Ec, then the Omnilyse procedure provided nearly quantitative extraction of genomic DNA from these isolates (934 ± 19.9 copies CFU-1 for Bt; 20.8 ± 2.68 copies CFU-1 for Ss; 26.9 ± 3.39 copies CFU-1 for Ec). The Agencourt, High Pure, and Omnilyse technologies were subsequently assessed using 5 additional Gram-positive and 10 Gram-negative foodborne isolates (n = 3) using a set of “universal” 16S rDNA primers. Conclusion Overall, the most notable DNA extraction method was found to be the Omnilyse procedure which is a “bead blender” technology involving high frequency agitation in the presence of zirconium silicate beads. Electronic supplementary material The online version of this article (doi:10.1186/s12866-014-0326-z) contains supplementary material, which is available to authorized users.