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Related Experiment Video

Updated: Dec 26, 2025

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

FORENSIC: an Online Platform for Fecal Source Identification.

Adélaïde Roguet¹, Özcan C Esen², A Murat Eren²

¹School of Freshwater Sciences, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, USA.

|March 19, 2020

Summary

This summary is machine-generated.

Identify fecal pollution sources in water using the FORENSIC online platform. This library-independent tool analyzes microbial signatures to pinpoint contamination from humans, pets, and livestock, aiding water quality assessment.

Keywords:

16S rRNA gene Bacteroidales Clostridiales high-throughput sequencing microbial source tracking random forest classification toolkit

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Published on: April 25, 2025

Area of Science:

Environmental microbiology
Bioinformatics
Water quality assessment

Background:

Fecal pollution from sewage, agriculture, and stormwater impacts surface water quality.
Microbial community analysis offers a promising approach for water quality assessment.
Current methods require extensive reference libraries and bioinformatics expertise, limiting accessibility.

Purpose of the Study:

To introduce FORENSIC (FORest Enteric Source IdentifiCation), an online, library-independent platform for fecal source tracking.
To enable identification of common fecal contamination sources (human, domestic pets, agricultural animals) in environmental samples.
To provide a fast, intuitive, and accessible tool for public health and water resource management.

Main Methods:

Utilizes random forest classification on 16S rRNA gene amplicon sequences.
Leverages a broad reference signature database of *Bacteroidales* and *Clostridiales* bacteria.
Tested for global applicability using samples from diverse geographic locations.

Main Results:

FORENSIC successfully identifies fecal sources without the need for custom reference library construction.
The platform demonstrates cohesive and reliable microbial assemblage patterns within host species.
Tested V4V5 reads trimmed to V4 positions for generating reference signatures, showing scalability and extensibility.

Conclusions:

FORENSIC provides a scalable, extensible, and globally applicable solution for fecal source identification.
The platform makes advanced sequence-based water quality assessment accessible to a wider community.
This approach is particularly valuable for identifying sewage signals in polluted waters, addressing human health risks.