MICROBIOLOGICAL SOURCE TRACKING BAKTERI Escherichia coli DENGAN METODE ANTIBIOTIC RESISTANCE ANALYSIS DI SUNGAI CIKAPUNDUNG

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.

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

Water Science & Technology ◽

10.2166/wst.2007.757 ◽

2007 ◽

Vol 56 (11) ◽

pp. 51-58 ◽

Cited By ~ 10

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.

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Fecal source tracking by antibiotic resistance analysis on a watershed exhibiting low resistance

Environmental Monitoring and Assessment ◽

10.1007/s10661-007-9805-0 ◽

2007 ◽

Vol 139 (1-3) ◽

pp. 15-25 ◽

Cited By ~ 9

Author(s):

Yolanda Olivas ◽

Barton R. Faulkner

Keyword(s):

Antibiotic Resistance ◽

Source Tracking ◽

Low Resistance ◽

Resistance Analysis ◽

Antibiotic Resistance Analysis

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Differentiation of faecal Escherichia coli from humans and animals by multiple antibiotic resistance analysis

Letters in Applied Microbiology ◽

10.1111/j.1472-765x.2005.01803.x ◽

2006 ◽

Vol 42 (1) ◽

pp. 71-77 ◽

Cited By ~ 9

Author(s):

A. Vantarakis ◽

D. Venieri ◽

G. Komninou ◽

M. Papapetropoulou

Keyword(s):

Escherichia Coli ◽

Antibiotic Resistance ◽

Multiple Antibiotic Resistance ◽

Resistance Analysis ◽

Antibiotic Resistance Analysis

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Identification of the sources of Escherichia coli in a watershed using carbon-utilization patterns and composite data sets

Journal of Water and Health ◽

10.2166/wh.2008.021 ◽

2008 ◽

Vol 6 (2) ◽

pp. 197-207 ◽

Cited By ~ 10

Author(s):

Samir H. Moussa ◽

Rene D. Massengale

Keyword(s):

Antibiotic Resistance ◽

Predictive Value ◽

Predictive Accuracy ◽

Source Tracking ◽

Carbon Utilization ◽

E Coli ◽

Bacterial Source Tracking ◽

Resistance Analysis ◽

Utilization Patterns ◽

Antibiotic Resistance Analysis

The field of bacterial source tracking (BST) has been rapidly evolving to meet the demands of water pollution analysis, specifically the contamination of waterways and drinking water reservoirs by point source and nonpoint source pollution. The goal of the current study was to create a BST library based on carbon-utilization patterns (CUP) for predicting sources of E. coli in a watershed, to compare this library to an antibiotic-resistance analysis (ARA) library previously published for the same isolates, and to determine the efficacy of using a composite dataset which combines data from both datasets into a single library for predicting the source of unknown isolates. This was accomplished by generating a CUP dataset and a composite ARA-CUP dataset for the E. coli isolates from known fecal sources within a watershed. These libraries were then used to predict the sources of E. coli isolates collected from 13 water sites in the same watershed and compared in regard to predictive accuracy. The dominant sources of E. coli in the South Bosque watershed were cattle as identified by all three methods. The 6-source composite library had higher average rates of correct classification (96.7%), specificity (99.2%), positive-predictive value (99.1%), and negative-predictive value (96.8%) than either the ARA or CUP 6 source libraries (ARCC 80.1% and 86.7% respectively). The current study is the first field study to compare two phenotypic methods, Antibiotic Resistance Analysis (ARA) and Carbon Utilization Profiling (CUP). This study is also the first to combine both of these methods to create a composite “toolbox” type approach.

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