scholarly journals Technical note: Comparison of automated ribosomal intergenic spacer analysis and denaturing gradient gel electrophoresis to assess bacterial diversity in the rumen of sheep1

2014 ◽  
Vol 92 (3) ◽  
pp. 1083-1088 ◽  
Author(s):  
C. Saro ◽  
M. J. Ranilla ◽  
A. Cifuentes ◽  
R. Rosselló-Mora ◽  
M. D. Carro
Keyword(s):  
Bacterial Diversity ◽  
Gel Electrophoresis ◽  
Denaturing Gradient Gel Electrophoresis ◽  
Intergenic Spacer ◽  
Technical Note ◽  
Ribosomal Intergenic Spacer ◽  
Gradient Gel Electrophoresis

Source tracking ofEscherichia coliby 16S–23S intergenic spacer region denaturing gradient gel electrophoresis (DGGE) of therrnBribosomal operon

2007 ◽  
Vol 53 (10) ◽  
pp. 1174-1184 ◽  
Author(s):  
Thomas V. D’Elia ◽  
Chester R. Cooper ◽  
Carl G. Johnston
Keyword(s):  
Escherichia Coli ◽  
Gel Electrophoresis ◽  
Denaturing Gradient Gel Electrophoresis ◽  
Intergenic Spacer ◽  
Source Tracking ◽  
Combined Sewer Overflow ◽  
Intergenic Spacer Region ◽  
E Coli ◽  
Combined Sewer ◽  
Gradient Gel Electrophoresis

This research validates a novel approach for source tracking based on denaturing gradient gel electrophoresis (DGGE) analysis of DNA extracted from Escherichia coli isolates. Escherichia coli from different animal sources and from river samples upstream from, at, and downstream of a combined sewer overflow were subjected to DGGE to determine sequence variations within the 16S–23S intergenic spacer region (ISR) of the rrnB ribosomal operon. The ISR was analyzed to determine if E. coli isolates from various animal sources could be differentiated from each other. DNA isolated from the E. coli animal sources was PCR amplified to isolate the rrnB operon. To prevent amplification of all 7 E. coli ribosomal operons by PCR amplification using universal primers, sequence-specific primers were utilized for the rrnB operon. Another primer set was then used to prepare samples of the 16S–23S ISR for DGGE. Comparison of PCR–DGGE results between human and animal sources revealed differences in the distribution and frequency of the DGGE bands produced. Human and Canada Goose isolates had the most unique distribution patterns and the highest percent of unique isolates and were grouped separately from all other animal sources. Method validation suggests that there are enough host specificity and genetic differences for use in the field. Field results at and around a combined sewer overflow indicate that this method can be used for microbial source tracking.

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