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Sorbitol non-fermenting shiga toxin-producing Escherichia coli in cattle on smallholdings

Published online by Cambridge University Press:  27 February 2014

M. Z. ISLAM
Affiliation:
Department of Microbiology, Chittagong Veterinary and Animal Sciences University, Bangladesh
J. P. CHRISTENSEN
Affiliation:
Department of Veterinary Disease Biology, Copenhagen University, Denmark
P. K. BISWAS*
Affiliation:
Department of Microbiology, Chittagong Veterinary and Animal Sciences University, Bangladesh
*
* Author for correspondence: Dr P. K. Biswas, Department of Microbiology, Chittagong Veterinary and Animal Sciences University, Bangladesh. (Email: biswaspk2000@yahoo.com)
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Summary

We investigated faecal samples collected from the rectum of 518 cattle on 371 randomly selected smallholdings in Bangladesh for the presence of sorbitol non-fermenting (SN-F) shiga toxin-producing Escherichia coli (STEC). The SN-F isolates were tested for the presence of rfb O157, stx1, stx2, eae and hlyA genes by polymerase chain reaction (PCR). Seven SN-F isolates lacking these genes were profiled by pulsed-field gel electrophoresis (PFGE) to verify their clonality. SN-F E. coli was identified in 44 [8·5%, 95% confidence interval (CI) 6·4–11·2] samples; of these, 28 (5·4%, 95% CI 3·8–7·7) had shiga toxin-producing strains, although only two carried the rfb O157 gene. Thirteen isolates carried the hlyA gene while 18 harboured the eae gene. Based on PFGE, six pulsotypes were observed among the seven isolates that had no virulence genes. To the best of our knowledge this is the first report on shiga toxin-producing E. coli from direct rectal faecal samples of cattle on smallholdings.

Information

Type
Original Papers
Copyright
Copyright © Cambridge University Press 2014 
Figure 0

Fig. 1 [colour online]. Secondary homogeneous growth of sorbitol non-fermenting (SN-F) bacterial colonies on cefixime-potassium tellurite sorbitol MacConkey (CT-SMAC) agar, plated from the culture in tryptic soy broth obtained from multiple (⩾5) SN-F colonies inoculated into it from the primary SN-F bacterial colonies developed along with sorbitol-fermenting colonies and others on CT-SMAC agar from a rectal swab collected from a bovine animal on a smallholding in Bangladesh

Figure 1

Table 1. Sequences of the primer sets used to detect five genes: rfb, stx1, stx2, eae and hlyA in sorbitol non-fermenting Escherichia coli from cattle on smallholdings in Bangladesh

Figure 2

Table 2. Sampling levels – hierarchically from district to village, numbers of cattle sampled on the selected smallholdings and the corresponding number of sampled animals positive for shiga-toxin producing sorbitol non-fermenting Escherichia coli (SN-F STEC) in the study

Figure 3

Fig. 2. Results of polymerase chain reaction assays displaying amplicons of the shiga toxin 1-producing gene (stx1) in five (a), shiga toxin 2-producing gene (stx2) in seven (b), enterohaemolysin-producing gene (hlyA) in eight (c), intimin-producing gene (eae) in eight (d) and a somatic antigen-producing gene indicating presence of any member belonging to O157 serogroup (rfb) in two (e) of the sorbitol non-fermenting Escherichia coli strains (indicated by an asterisk in Table 3) from cattle on smallholdings in Bangladesh. Lane M, 1 kb plus DNA marker; lane P, positive control isolates having the specific gene of the concerned panel; lane N, negative control.

Figure 4

Table 3. Distribution of shiga toxin producing genes, stx1 and stx2, and two other virulent genes, eae and hlyA, in the 44 sorbitol non-fermenting strains of Escherichia coli resulting from a survey encompassing 518 cattle on smallholdings in Bangladesh using cefixime potassium tellurite sorbitol MacConkey agar as the initial screening medium

Figure 5

Fig. 3. Dendrogram showing the cluster analysis on the basis of XbaI pulsed-field gel electrophoresis (PFGE) of the seven sorbitol non-fermenting Escherichia coli isolates from cattle on smallholdings in Bangladesh lacking the shiga toxin genes, stx1 and stx2 and two other virulence genes eae and hlyA. Dice coefficient was used to perform similarity analysis, and clustering was performed by using The unweighted pair-group method with arithmetic means with 1% band position tolerance and 0·5% optimization parameter.