Differentiation of faecal Escherichia coli from humans and animals by multiple antibiotic resistance analysis

Abstract

Aims: Multiple antibiotic resistance (MAR) was performed on 128 Escherichia coli isolates, recovered from faecal samples of humans and animals (cattle, goat, sheep) to determine and compare their antibiotic resistance patterns and to evaluate them statistically in order to specify the source of the faecal material. Methods and Results: Disk diffusion method was applied with a selection of antibiotics. Statistical approach was performed with hierarchical cluster analysis (CA), discriminant analysis (DA) and principal component analysis. Comparing human and animal isolates there was significant difference in levels of resistance to all antibiotics tested (P < 0·05) with 46 and 24 distinct resistance patterns for human and animal isolates respectively. CA and DA separated human and animal isolates with a high average rate of correct classification (99·2%), when all animal isolates were pooled together. Conclusions: MAR analysis compared with appropriate statistical evaluation may provide a useful tool for differentiating the human or animal origin of E. coli isolates derived from environmental samples. Subsequently, determination of the source of faecal pollution becomes possible. Significance and Impact of the Study: Determining the source of faecal pollution enables the prediction of possible risk for public health and the application of appropriate management plans for prevention of further contamination.

Seasonal variation in bacterial contamination of water sources with antibiotic resistant faecal coliforms in relation to pollution

“…Kaspar et al (1990) noticed that indexing the antibiotic resistance among E. coli may be useful to identify the sources of faecal contamination in water. Recently, Vantarakis et al, (2006) have observed that MAR analysis is useful tool in differentiating the faecal E.coli from human being and animals.…”

Influence of hydrological conditions on the Escherichia coli population structure in the water of a creek on a rural watershed

“…The aquatic environment can thus be considered a secondary habitat, where some authors have even shown the possible growth of E. coli [17,18]. The diversity of E. coli populations in their secondary habitats has been studied by analyzing the sequences of the gene uidA [19,20], palindromic repetitive sequences [21,22], ribotypes [23], and profiles of antibiotic resistance [24,25]. Using these methods, the dynamics of E. coli populations have been investigated and, in some cases, it has been possible to discriminate between the human or animal origin of the contamination.…”

Assessment of the 16S‐23S rDNA Intergenic Spacer Region in Enterococcus spp. for Microbial Source Tracking

“…The overall inadequate performance of the methods involved resurrected previous concerns of temporal instability of strains within host organisms (Jenkins et al, 2003). Therefore in this study, once the library size was increased to 200 isolates, comparable to numbers frequently reported in several publications (Dombek et al, 2000; Guan et al, 2002; Seurinck et al, 2003; Lasalde et al, 2005; Duran et al, 2006; Vantarakis et al, 2006), a VS of isolates (collected simultaneously, but from different fecal samples) were fingerprinted to serve as an additional means of predicting the classification ability of the known‐source library. In library‐based MST methods, small libraries typically produce high ARCCs solely due to the random placement of isolates into defined categories (Whitlock et al, 2002).…”