Antibiotic Resistance Analysis ofEnterococciin Chester Creek

2005 ◽  
Author(s):  
Graham R. Stahnke ◽  
William Schnabel ◽  
Khrys Duddleston ◽  
Tammie Wilson
Keyword(s):  
Antibiotic Resistance ◽  
Resistance Analysis ◽  
Antibiotic Resistance Analysis

Identification of sources of Escherichia coli in South Carolina estuaries using antibiotic resistance analysis

2004 ◽  
Vol 298 (2) ◽  
pp. 179-195 ◽  
Author(s):  
Laura F Webster ◽  
Brian C Thompson ◽  
Michael H Fulton ◽  
David E Chestnut ◽  
Robert F Van Dolah ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Antibiotic Resistance ◽  
South Carolina ◽  
Resistance Analysis ◽  
Antibiotic Resistance Analysis

scholarly journals Use of Antibiotic Resistance Analysis for Representativeness Testing of Multiwatershed Libraries

2003 ◽  
Vol 69 (6) ◽  
pp. 3399-3405 ◽  
Author(s):  
Bruce A. Wiggins ◽  
Philip W. Cash ◽  
Wes S. Creamer ◽  
Scott E. Dart ◽  
Preston P. Garcia ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Natural Waters ◽  
Cross Validation ◽  
Microbial Source Tracking ◽  
Wild Animal ◽  
Source Tracking ◽  
Correct Classification ◽  
Resistance Analysis ◽  
Resistance Patterns ◽  
Antibiotic Resistance Analysis

ABSTRACT The use of antibiotic resistance analysis (ARA) for microbial source tracking requires the generation of a library of isolates collected from known sources in the watershed. The size and composition of the library are critical in determining if it represents the diversity of patterns found in the watershed. This study was performed to determine the size that an ARA library needs to be to be representative of the watersheds for which it will be used and to determine if libraries from different watersheds can be merged to create multiwatershed libraries. Fecal samples from known human, domesticated, and wild animal sources were collected from six Virginia watersheds. From these samples, enterococci were isolated and tested by ARA. Based on cross-validation discriminant analysis, only the largest of the libraries (2,931 isolates) were found to be able to classify nonlibrary isolates as well as library isolates (i.e., were representative). Small libraries tended to have higher average rates of correct classification, but were much less able to correctly classify nonlibrary isolates. A merged multiwatershed library (6,587 isolates) was created and was found to be large enough to be representative of the isolates from the contributing watersheds. When isolates that were collected from the contributing watersheds approximately 1 year later were analyzed with the multiwatershed library, they were classified as well as the isolates in the library, suggesting that the resistance patterns are temporally stable for at least 1 year. The ability to obtain a representative, temporally stable library demonstrates that ARA can be used to identify sources of fecal pollution in natural waters.

Experience with the antibiotic resistance analysis and DNA fingerprinting in tracking faecal pollution at two lake beaches

2007 ◽  
Vol 56 (11) ◽  
pp. 51-58 ◽  
Author(s):  
T.A. Edge ◽  
S. Hill ◽  
G. Stinson ◽  
P. Seto ◽  
J. Marsalek
Keyword(s):  
Antibiotic Resistance ◽  
Dna Fingerprinting ◽  
Microbial Source Tracking ◽  
Source Tracking ◽  
Faecal Contamination ◽  
E Coli ◽  
Resistance Analysis ◽  
Antibiotic Resistance Analysis ◽  
Environmental Challenge ◽  
Made In

Posting or closing of swimming beaches because of faecal contamination is a widespread problem reported in many locations. In a risk-based approach to this problem, the risk to swimmers' health is assessed by field monitoring of indicator bacteria and the associated risks are managed by source controls and other remedial measures. In risk assessment, great advances have been made in recent years with the introduction of microbial source tracking (MST) techniques. Two such techniques, antibiotic resistance analysis and DNA fingerprinting, were applied in a study of causes of faecal contamination at two lake beaches in Toronto, Ontario. Both methods identified bird faeces as the dominant sources of E. coli. Coping with this type of pollution presents a major environmental challenge.

Microbiological Quality and Antibiotic Resistance Analysis of a Brazilian Water Supply Source

2010 ◽  
Vol 218 (1-4) ◽  
pp. 611-618 ◽  
Author(s):  
Trajano Felipe Barrabas Xavier da Silva ◽  
Débora Toledo Ramos ◽  
Maurício Dziedzic ◽  
Cíntia Mara Ribas de Oliveira ◽  
Eliane Carvalho de Vasconcelos
Keyword(s):  
Antibiotic Resistance ◽  
Water Supply ◽  
Microbiological Quality ◽  
Supply Source ◽  
Resistance Analysis ◽  
Antibiotic Resistance Analysis

scholarly journals Use of Antibiotic Resistance Analysis To Identify Nonpoint Sources of Fecal Pollution

1999 ◽  
Vol 65 (8) ◽  
pp. 3483-3486 ◽  
Author(s):  
B. A. Wiggins ◽  
R. W. Andrews ◽  
R. A. Conway ◽  
C. L. Corr ◽  
E. J. Dobratz ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Average Rate ◽  
Fecal Pollution ◽  
Resistance Analysis ◽  
Large Sets ◽  
Fecal Streptococci ◽  
Resistance Patterns ◽  
Antibiotic Resistance Patterns ◽  
Level Resistance ◽  
Antibiotic Resistance Analysis

ABSTRACT A study was conducted to determine the reliability and repeatability of antibiotic resistance analysis as a method of identifying the sources of fecal pollution in surface water and groundwater. Four large sets of isolates of fecal streptococci (from 2,635 to 5,990 isolates per set) were obtained from 236 samples of human sewage and septage, cattle and poultry feces, and pristine waters. The patterns of resistance of the isolates to each of four concentrations of up to nine antibiotics were analyzed by discriminant analysis. When isolates were classified individually, the average rate of correct classification (ARCC) into four possible types (human, cattle, poultry, and wild) ranged from 64 to 78%. When the resistance patterns of all isolates from each sample were averaged and the resulting sample-level resistance patterns were classified, the ARCCs were much higher (96 to 100%). These data confirm that there are measurable and consistent differences in the antibiotic resistance patterns of fecal streptococci isolated from various sources of fecal pollution and that antibiotic resistance analysis can be used to classify and identify these sources.

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