Literature DB >> 15294775

Sample size, library composition, and genotypic diversity among natural populations of Escherichia coli from different animals influence accuracy of determining sources of fecal pollution.

LeeAnn K Johnson1, Mary B Brown, Ethan A Carruthers, John A Ferguson, Priscilla E Dombek, Michael J Sadowsky.   

Abstract

A horizontal, fluorophore-enhanced, repetitive extragenic palindromic-PCR (rep-PCR) DNA fingerprinting technique (HFERP) was developed and evaluated as a means to differentiate human from animal sources of Escherichia coli. Box A1R primers and PCR were used to generate 2,466 rep-PCR and 1,531 HFERP DNA fingerprints from E. coli strains isolated from fecal material from known human and 12 animal sources: dogs, cats, horses, deer, geese, ducks, chickens, turkeys, cows, pigs, goats, and sheep. HFERP DNA fingerprinting reduced within-gel grouping of DNA fingerprints and improved alignment of DNA fingerprints between gels, relative to that achieved using rep-PCR DNA fingerprinting. Jackknife analysis of the complete rep-PCR DNA fingerprint library, done using Pearson's product-moment correlation coefficient, indicated that animal and human isolates were assigned to the correct source groups with an 82.2% average rate of correct classification. However, when only unique isolates were examined, isolates from a single animal having a unique DNA fingerprint, Jackknife analysis showed that isolates were assigned to the correct source groups with a 60.5% average rate of correct classification. The percentages of correctly classified isolates were about 15 and 17% greater for rep-PCR and HFERP, respectively, when analyses were done using the curve-based Pearson's product-moment correlation coefficient, rather than the band-based Jaccard algorithm. Rarefaction analysis indicated that, despite the relatively large size of the known-source database, genetic diversity in E. coli was very great and is most likely accounting for our inability to correctly classify many environmental E. coli isolates. Our data indicate that removal of duplicate genotypes within DNA fingerprint libraries, increased database size, proper methods of statistical analysis, and correct alignment of band data within and between gels improve the accuracy of microbial source tracking methods.

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Year:  2004        PMID: 15294775      PMCID: PMC492448          DOI: 10.1128/AEM.70.8.4478-4485.2004

Source DB:  PubMed          Journal:  Appl Environ Microbiol        ISSN: 0099-2240            Impact factor:   4.792


  38 in total

1.  Classification of antibiotic resistance patterns of indicator bacteria by discriminant analysis: use in predicting the source of fecal contamination in subtropical waters.

Authors:  V J Harwood; J Whitlock; V Withington
Journal:  Appl Environ Microbiol       Date:  2000-09       Impact factor: 4.792

2.  Comparison of ribotyping and repetitive extragenic palindromic-PCR for identification of fecal Escherichia coli from humans and animals.

Authors:  C Andrew Carson; Brian L Shear; Mark R Ellersieck; Jennifer D Schnell
Journal:  Appl Environ Microbiol       Date:  2003-03       Impact factor: 4.792

3.  Genetic structure of natural populations of Escherichia coli in wild hosts on different continents.

Authors:  V Souza; M Rocha; A Valera; L E Eguiarte
Journal:  Appl Environ Microbiol       Date:  1999-08       Impact factor: 4.792

4.  A highly conserved repeated DNA element located in the chromosome of Streptococcus pneumoniae.

Authors:  B Martin; O Humbert; M Camara; E Guenzi; J Walker; T Mitchell; P Andrew; M Prudhomme; G Alloing; R Hakenbeck
Journal:  Nucleic Acids Res       Date:  1992-07-11       Impact factor: 16.971

5.  Potential of Enterococcus faecalis as a human fecal indicator for microbial source tracking.

Authors:  Andrea L Wheeler; Peter G Hartel; Dominique G Godfrey; Jennifer L Hill; William I Segars
Journal:  J Environ Qual       Date:  2002 Jul-Aug       Impact factor: 2.751

6.  Use of repetitive sequences and the polymerase chain reaction technique to classify genetically related Bradyrhizobium japonicum serocluster 123 strains.

Authors:  A K Judd; M Schneider; M J Sadowsky; F J de Bruijn
Journal:  Appl Environ Microbiol       Date:  1993-06       Impact factor: 4.792

7.  Deer diet affects ribotype diversity of Escherichia coli for bacterial source tracking.

Authors:  Peter G Hartel; Jacob D Summer; William I Segars
Journal:  Water Res       Date:  2003-07       Impact factor: 11.236

8.  Distribution of repetitive DNA sequences in eubacteria and application to fingerprinting of bacterial genomes.

Authors:  J Versalovic; T Koeuth; J R Lupski
Journal:  Nucleic Acids Res       Date:  1991-12-25       Impact factor: 16.971

9.  Identification of Escherichia coli strains from cows with clinical mastitis by serotyping and DNA polymorphism patterns with REP and ERIC primers.

Authors:  L J Lipman; A de Nijs; T J Lam; W Gaastra
Journal:  Vet Microbiol       Date:  1995-01       Impact factor: 3.293

10.  Antibiotic resistance analysis of fecal coliforms to determine fecal pollution sources in a mixed-use watershed.

Authors:  Brian S Burnes
Journal:  Environ Monit Assess       Date:  2003-06       Impact factor: 2.513

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  48 in total

1.  Differentiation of fecal Escherichia coli from human, livestock, and poultry sources by rep-PCR DNA fingerprinting on the shellfish culture area of East China Sea.

Authors:  Hong-Jia Ma; Ling-Lin Fu; Jian-Rong Li
Journal:  Curr Microbiol       Date:  2011-01-30       Impact factor: 2.188

2.  Genotypic diversity of Escherichia coli in the water and soil of tropical watersheds in Hawaii.

Authors:  Dustin K Goto; Tao Yan
Journal:  Appl Environ Microbiol       Date:  2011-04-22       Impact factor: 4.792

3.  Large scale analysis of virulence genes in Escherichia coli strains isolated from Avalon Bay, CA.

Authors:  Matthew J Hamilton; Asbah Z Hadi; John F Griffith; Satoshi Ishii; Michael J Sadowsky
Journal:  Water Res       Date:  2010-06-30       Impact factor: 11.236

4.  Test of direct and indirect effects of agrochemicals on the survival of fecal indicator bacteria.

Authors:  Zachery R Staley; Jason R Rohr; Valerie J Harwood
Journal:  Appl Environ Microbiol       Date:  2011-10-14       Impact factor: 4.792

5.  Development of goose- and duck-specific DNA markers to determine sources of Escherichia coli in waterways.

Authors:  Matthew J Hamilton; Tao Yan; Michael J Sadowsky
Journal:  Appl Environ Microbiol       Date:  2006-06       Impact factor: 4.792

6.  Presence and growth of naturalized Escherichia coli in temperate soils from Lake Superior watersheds.

Authors:  Satoshi Ishii; Winfried B Ksoll; Randall E Hicks; Michael J Sadowsky
Journal:  Appl Environ Microbiol       Date:  2006-01       Impact factor: 4.792

7.  Spatial variation in Streptomyces genetic composition and diversity in a prairie soil.

Authors:  A L Davelos; K Xiao; D A Samac; A P Martin; L L Kinkel
Journal:  Microb Ecol       Date:  2004-10-28       Impact factor: 4.552

8.  Specificity of a Bacteroides thetaiotaomicron marker for human feces.

Authors:  C Andrew Carson; Jessica M Christiansen; Helen Yampara-Iquise; Verel W Benson; Claire Baffaut; Jerri V Davis; Robert R Broz; William B Kurtz; Wendi M Rogers; William H Fales
Journal:  Appl Environ Microbiol       Date:  2005-08       Impact factor: 4.792

Review 9.  Performance, design, and analysis in microbial source tracking studies.

Authors:  Donald M Stoeckel; Valerie J Harwood
Journal:  Appl Environ Microbiol       Date:  2007-02-16       Impact factor: 4.792

10.  Occurrence, genetic diversity, and persistence of enterococci in a Lake Superior watershed.

Authors:  Qinghong Ran; Brian D Badgley; Nicholas Dillon; Gary M Dunny; Michael J Sadowsky
Journal:  Appl Environ Microbiol       Date:  2013-03-01       Impact factor: 4.792

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