US Geological Survey

 

Authors

Blythe A. Layton, Southern California Coastal Water Research Project
Yiping Cao, Southern California Coastal Water Research Project
Darcy L. Ebentier, UCLA Civil and Environmental Engineering
Kaitlyn Hanley, UCLA Civil and Environmental Engineering
Elisenda Balleste, University College Dublin
Joao Brandao, Instituto Nacional de Saude
Muruleedhara Byappanahalli, US Geological Survey
Reagan Converse, UNC Chapel Hill Institute of Marine Sciences
Andreas H. Farnleitner, Vienna University of Technology
Jennifer Gentry-Shields, University of North Carolina
Maribeth L. Gidley, University of Miami
Michele Gourmelon, Laboratoire de Microbiologie, MIC/LNR
Chang Soo Lee, The Ohio State University
Jiyoung Lee, The Ohio State University
Solen Lozach, Laboratoire de Microbiologie, MIC/LNR
Tania Madi, Source Molecular Corporation
Wim G. Meijer, University College Dublin
Rachel Noble, UNC Chapel Hill Institute of Marine Sciences
Lindsay Peed, US Environmental Protection Agency
Georg H. Reischer, Vienna University of Technology
Raquel Rodrigues, Instituto Nacional de Saude
Joan B. Rose, Michigan State UniversityFollow
Alexander Schriewer, University of California - Davis
Chris Sinigalliano, National Oceanic and Atmospheric Administration
Sangeetha Srinivasan, Michigan State University
Jill Stewart, University of North Carolina
Laurie C. Van De Werfhorst, University of California - Santa Barbara
Dan Wang, Stanford University
Richard Whitman, US Geological Survey
Stefan Wuertz, University of California - Davis
Jenny Jay, UCLA Civil and Environmental Engineering
Patricia A. Holden, University of California - Santa Barbara
Alexandria B. Boehm, Stanford University
Orin Shanks, US Environmental Protection Agency
John F. Griffith, Southern California Coastal Water Research ProjectFollow

Date of this Version

2013

Citation

Water Research 47 (2013) 6897-6908; http://dx.doi.org/10.1016/j.watres.2013.05.060

Abstract

A number of PCR-based methods for detecting human fecal material in environmental waters have been developed over the past decade, but these methods have rarely received independent comparative testing in large multi-laboratory studies. Here, we evaluated ten of these methods (BacH, BacHum-UCD, Bacteroides thetaiotaomicron (BtH), BsteriF1, gyrB, HF183 endpoint, HF183 SYBR, HF183 Taqman®, HumM2, and Methanobrevibacter smithii nifH (Mnif)) using 64 blind samples prepared in one laboratory. The blind samples contained either one or two fecal sources from human, wastewater or non-human sources. The assay results were assessed for presence/absence of the human markers and also quantitatively while varying the following: 1) classification of samples that were detected but not quantifiable (DNQ) as positive or negative; 2) reference fecal sample concentration unit of measure (such as culturable indicator bacteria, wet mass, total DNA, etc); and 3) human fecal source type (stool, sewage or septage). Assay performance using presence/absence metrics was found to depend on the classification of DNQ samples. The assays that performed best quantitatively varied based on the fecal concentration unit of measure and laboratory protocol. All methods were consistently more sensitive to human stools compared to sewage or septage in both the presence/absence and quantitative analysis. Overall, HF183 Taqman® was found to be the most effective marker of human fecal contamination in this California-based study.