Dataset Information

Selective and sensitive method for PCR amplification of Escherichia coli 16S rRNA genes in soil.

ABSTRACT: A set of PCR primers targeting 16S rRNA gene sequences was designed, and PCR parameters were optimized to develop a robust and reliable protocol for selective amplification of Escherichia coli 16S rRNA genes. The method was capable of discriminating E. coli from other enteric bacteria, including its closest relative, Shigella. Selective amplification of E. coli occurred only when the annealing temperature in the PCR was elevated to 72 degrees C, which is 10 degrees C higher than the optimum for the primers. Sensitivity was retained by modifying the length of steps in the PCR, by increasing the number of cycles, and most importantly by optimizing the MgCl(2) concentration. The PCR protocol developed can be completed in less then 2 h and, by using Southern hybridization, has a detection limit of ca. 10 genomic equivalents per reaction. The method was demonstrated to be effective for detecting E. coli DNA in heterogeneous DNA samples, such as those extracted from soil.

SUBMITTER: Sabat G

PROVIDER: S-EPMC91908 | biostudies-literature | 2000 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Selective and sensitive method for PCR amplification of Escherichia coli 16S rRNA genes in soil.

Sabat G G Rose P P Hickey W J WJ Harkin J M JM

Applied and environmental microbiology 20000201 2

A set of PCR primers targeting 16S rRNA gene sequences was designed, and PCR parameters were optimized to develop a robust and reliable protocol for selective amplification of Escherichia coli 16S rRNA genes. The method was capable of discriminating E. coli from other enteric bacteria, including its closest relative, Shigella. Selective amplification of E. coli occurred only when the annealing temperature in the PCR was elevated to 72 degrees C, which is 10 degrees C higher than the optimum for ...[more]

PMID: 10653763

Similar Datasets

Project description:The advent of next generation sequencing has coincided with a growth in interest in using these approaches to better understand the role of the structure and function of the microbial communities in human, animal, and environmental health. Yet, use of next generation sequencing to perform 16S rRNA gene sequence surveys has resulted in considerable controversy surrounding the effects of sequencing errors on downstream analyses. We analyzed 2.7×10(6) reads distributed among 90 identical mock community samples, which were collections of genomic DNA from 21 different species with known 16S rRNA gene sequences; we observed an average error rate of 0.0060. To improve this error rate, we evaluated numerous methods of identifying bad sequence reads, identifying regions within reads of poor quality, and correcting base calls and were able to reduce the overall error rate to 0.0002. Implementation of the PyroNoise algorithm provided the best combination of error rate, sequence length, and number of sequences. Perhaps more problematic than sequencing errors was the presence of chimeras generated during PCR. Because we knew the true sequences within the mock community and the chimeras they could form, we identified 8% of the raw sequence reads as chimeric. After quality filtering the raw sequences and using the Uchime chimera detection program, the overall chimera rate decreased to 1%. The chimeras that could not be detected were largely responsible for the identification of spurious operational taxonomic units (OTUs) and genus-level phylotypes. The number of spurious OTUs and phylotypes increased with sequencing effort indicating that comparison of communities should be made using an equal number of sequences. Finally, we applied our improved quality-filtering pipeline to several benchmarking studies and observed that even with our stringent data curation pipeline, biases in the data generation pipeline and batch effects were observed that could potentially confound the interpretation of microbial community data.

Project description:BACKGROUND: The genus Vibrio is a diverse group of Gram-negative bacteria comprised of 74 species. Furthermore, the genus has and is expected to continue expanding with the addition of several new species annually. Consequently, it is of paramount importance to have a method which is able to reliably and efficiently differentiate the numerous Vibrio species. RESULTS: In this study, a novel and rapid polymerase chain reaction (PCR)-based intergenic spacer (IGS)-typing system for vibrios was developed that is based on the well-known IGS regions located between the 16S and 23S rRNA genes on the bacterial chromosome. The system was optimized to resolve heteroduplex formation as well as to take advantage of capillary gel electrophoresis technology such that reproducible analyses could be achieved in a rapid manner. System validation was achieved through testing of 69 archetypal Vibrio strains, representing 48 Vibrio species, from which an 'IGS-type' profile database was generated. These data, presented here in several cluster analyses, demonstrated successful differentiation of the 69 type strains showing that this PCR-based fingerprinting method easily discriminates bacterial strains at the species level among Vibrio. Furthermore, testing 36 strains each of V. parahaemolyticus and V. vulnificus, important food borne pathogens, isolated from a variety of geographical locations with the IGS-typing method demonstrated distinct IGS-typing patterns indicative of subspecies divergence in both populations making this technique equally useful for intraspecies differentiation, as well. CONCLUSION: This rapid, reliable and efficient IGS-typing system, especially in combination with 16S rRNA gene sequencing, has the capacity to not only discern and identify vibrios at the species level but, in some cases, at the sub-species level, as well. This procedure is particularly well-suited for preliminary species identification and, lends itself nicely to epidemiological investigations providing information more quickly than other time-honoured methods traditionally used in these types of analyses.

Dataset Information

Selective and sensitive method for PCR amplification of Escherichia coli 16S rRNA genes in soil.

Publications

Selective and sensitive method for PCR amplification of Escherichia coli 16S rRNA genes in soil.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets