Ultrafiltration and Microarray for Detection of Microbial Source Tracking Marker and Pathogen Genes in Riverine and...

Area of Science:

• Environmental microbiology
• Molecular biology
• Water quality assessment

Background:

• Fecal pollution in water poses risks to human health and ecosystems.
• Accurate pathogen identification and source tracking are crucial for water quality management.
• Existing methods can be time-consuming and lack comprehensive detection capabilities.

Purpose of the Study:

• To develop and validate a microarray-based method for simultaneous detection of multiple pathogens and microbial source tracking (MST) markers.
• To evaluate the efficacy of dead-end ultrafiltration (DEUF) and whole-genome amplification (WGA) in enhancing detection sensitivity.
• To assess the performance of the MST microarray in diverse water matrices, including sewage-contaminated samples.

Main Methods:

• Utilized dead-end ultrafiltration (DEUF) for concentrating microbial targets from water samples (>95% recovery for E. coli and human polyomavirus).
• Employed whole-genome amplification (WGA) to increase nucleic acid quantity and microarray sensitivity.
• Applied a custom MST microarray for simultaneous detection of bacterial pathogens, viruses, and antibiotic resistance genes.

Main Results:

• Detected various viruses (adenovirus, hepatitis A, polyomaviruses), pathogens (Legionella, Shigella, Campylobacter), and antibiotic resistance genes in sewage-contaminated samples.
• MST marker gene analysis successfully grouped sewage sources, differentiating them from other fecal origins.
• Microarray demonstrated 51-57% sensitivity and 79-81% specificity for sewage-associated gene targets, with semiquantitative results correlating with qPCR.
• Ultrafiltration coupled with WGA provided sufficient nucleic acids for broad microbial detection.

Conclusions:

• The combined DEUF and WGA approach with MST microarray offers a sensitive and comprehensive tool for water quality monitoring.
• This integrated method enables the detection of diverse microbial contaminants, including viruses, bacteria, and antibiotic resistance genes.
• The technology is applicable to various environmental settings, from beach monitoring to risk assessment, improving our understanding of fecal pollution impacts.