화학공학소재연구정보센터
International Journal of Molecular Sciences, Vol.15, No.6, 9735-9747, 2014
Genotypic Characterization of Escherichia coli O157:H7 Isolates from Different Sources in the North-West Province, South Africa, Using Enterobacterial Repetitive Intergenic Consensus PCR Analysis
In many developing countries, proper hygiene is not strictly implemented when animals are slaughtered and meat products become contaminated. Contaminated meat may contain Escherichia coli (E. coli) O157:H7 that could cause diseases in humans if these food products are consumed undercooked. In the present study, a total of 94 confirmed E. coli O157: H7 isolates were subjected to the enterobacterial repetitive intergenic consensus (ERIC) polymerase chain reaction (PCR) typing to generate genetic fingerprints. The ERIC fragments were resolved by electrophoresis on 2% (w/v) agarose gels. The presence, absence and intensity of band data were obtained, exported to Microsoft Excel (Microsoft Office 2003) and used to generate a data matrix. The unweighted pair group method with arithmetic mean (UPGMA) and complete linkage algorithms were used to analyze the percentage of similarity and matrix data. Relationships between the various profiles and/or lanes were expressed as dendrograms. Data from groups of related lanes were compiled and reported on cluster tables. ERIC fragments ranged from one to 15 per isolate, and their sizes varied from 0.25 to 0.771 kb. A large proportion of the isolates produced an ERIC banding pattern with three duplets ranging in sizes from 0.408 to 0.628 kb. Eight major clusters (I-VIII) were identified. Overall, the remarkable similarities (72% to 91%) between the ERIC profiles for the isolate from animal species and their corresponding food products indicated some form of contamination, which may not exclude those at the level of the abattoirs. These results reveal that ERIC PCR analysis can be reliable in comparing the genetic profiles of E. coli O157:H7 from different sources in the North-West Province of South Africa.