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Updated: Jun 4, 2026

A Duplex Digital PCR Assay for Simultaneous Quantification of the Enterococcus spp. and the Human Fecal-associated HF183 Marker in Waters

A Duplex Digital PCR Assay for Simultaneous Quantification of the Enterococcus spp. and the Human Fecal-associated HF183 Marker in Waters

Published on: March 9, 2016

Faecal source apportionment using molecular methods: A proof of concept using the FEAST algorithm.

Laura T Kelly¹, Jack Sissons¹, Lucy Thompson¹

¹Cawthron Institute, Nelson, New Zealand.

|September 5, 2024

Summary

This summary is machine-generated.

The Fast Expectation Maximization (FEAST) algorithm can identify the main sources of fecal contamination in coastal waters. However, it may underestimate the exact proportion of contamination from the dominant source, requiring further validation.

Keywords:

Environmental DNA Freshwater Microbial source tracking Seafood

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Last Updated: Jun 4, 2026

A Duplex Digital PCR Assay for Simultaneous Quantification of the Enterococcus spp. and the Human Fecal-associated HF183 Marker in Waters

A Duplex Digital PCR Assay for Simultaneous Quantification of the Enterococcus spp. and the Human Fecal-associated HF183 Marker in Waters

Published on: March 9, 2016

Guided Protocol for Fecal Microbial Characterization by 16S rRNA-Amplicon Sequencing

Guided Protocol for Fecal Microbial Characterization by 16S rRNA-Amplicon Sequencing

Published on: March 19, 2018

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

Published on: October 15, 2019

Area of Science:

Environmental microbiology
Molecular ecology
Public health

Background:

Faecal contamination poses risks to public health, recreation, and food safety.
Effective tools for identifying multiple contamination sources are still developing.

Purpose of the Study:

To evaluate the Fast Expectation Maximization (FEAST) microbial source tracking (MST) algorithm.
To determine its efficacy in apportioning faecal contamination sources in New Zealand coastal waters.

Main Methods:

16S ribosomal DNA metabarcoding of faecal samples from cows, fur seals, sheep, and human wastewater.
Multivariate analysis to differentiate microbial communities.
Testing the FEAST algorithm with mixed DNA and faecal samples.

Main Results:

Significant differences in microbial communities were found among mammalian sources.
Specific bacterial classes indicated distinct contamination sources.
The FEAST algorithm correctly identified the dominant faecal source in all tested samples.

Conclusions:

The FEAST algorithm shows promise as an advance in microbial source tracking tools.
Further refinement and validation are needed for accurate source apportionment, especially in complex environmental samples.
FEAST may become a valuable tool for environmental management of water quality.