Direct comparison of four bacterial source tracking methods and use of composite data sets

Area of Science:

• Environmental microbiology
• Water quality assessment
• Bacterial source tracking

Background:

• Accurate identification of fecal pollution sources is crucial for safeguarding water resources.
• Various bacterial source tracking (BST) methods exist, but their comparative performance and optimal application remain areas of investigation.

Purpose of the Study:

• To directly compare the efficacy of four distinct BST methods: ERIC-PCR, automated ribotyping, Kirby-Bauer antibiotic resistance analysis (KB-ARA), and PFGE.
• To evaluate the accuracy of individual BST methods and their composite data sets in identifying sources of Escherichia coli contamination in water.

Main Methods:

• Collected fecal samples from various sources (domestic sewage, livestock, wildlife) and water samples.
• Isolated and screened Escherichia coli (E. coli) using ERIC-PCR to create a diverse library.
• Analyzed selected E. coli isolates using automated ribotyping, KB-ARA, and PFGE.
• Compared the performance of individual methods and composite data sets based on rates of correct classification (RCCs) and identification of water isolates.

Main Results:

• A composite data set combining all four BST methods achieved the highest rates of correct classification and identified the most sources.
• Two-method composite data sets demonstrated comparable accuracy to the four-method composite, offering potential cost and time efficiencies.
• Individual BST methods showed varying levels of success, with composite approaches consistently outperforming them.

Conclusions:

• Composite bacterial source tracking data sets significantly enhance the accuracy and reliability of identifying fecal pollution origins compared to single methods.
• Utilizing two-method composite BST approaches presents a practical and effective strategy, balancing high accuracy with resource savings.