Literature DB >> 23891204

Recommendations following a multi-laboratory comparison of microbial source tracking methods.

Jill R Stewart1, Alexandria B Boehm, Eric A Dubinsky, Theng-Theng Fong, Kelly D Goodwin, John F Griffith, Rachel T Noble, Orin C Shanks, Kannappan Vijayavel, Stephen B Weisberg.   

Abstract

Microbial source tracking (MST) methods were evaluated in the Source Identification Protocol Project (SIPP), in which 27 laboratories compared methods to identify host sources of fecal pollution from blinded water samples containing either one or two different fecal types collected from California. This paper details lessons learned from the SIPP study and makes recommendations to further advance the field of MST. Overall, results from the SIPP study demonstrated that methods are available that can correctly identify whether particular host sources including humans, cows and birds have contributed to contamination in a body of water. However, differences between laboratory protocols and data processing affected results and complicated interpretation of MST method performance in some cases. This was an issue particularly for samples that tested positive (non-zero Ct values) but below the limits of quantification or detection of a PCR assay. Although false positives were observed, such samples in the SIPP study often contained the fecal pollution source that was being targeted, i.e., the samples were true positives. Given these results, and the fact that MST often requires detection of targets present in low concentrations, we propose that such samples be reported and identified in a unique category to facilitate data analysis and method comparisons. Important data can be lost when such samples are simply reported as positive or negative. Actionable thresholds were not derived in the SIPP study due to limitations that included geographic scope, age of samples, and difficulties interpreting low concentrations of target in environmental samples. Nevertheless, the results of the study support the use of MST for water management, especially to prioritize impaired waters in need of remediation. Future integration of MST data into quantitative microbial risk assessments and other models could allow managers to more efficiently protect public health based on site conditions.
Copyright © 2013 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Bacteroidales; Coliform; Enterococcus; Microbial source tracking; Water quality; qPCR

Mesh:

Year:  2013        PMID: 23891204     DOI: 10.1016/j.watres.2013.04.063

Source DB:  PubMed          Journal:  Water Res        ISSN: 0043-1354            Impact factor:   11.236


  13 in total

1.  Blautia and Prevotella sequences distinguish human and animal fecal pollution in Brazil surface waters.

Authors:  Amber M Koskey; Jenny C Fisher; A Murat Eren; Rafael Ponce-Terashima; Mitermayer G Reis; Ronald E Blanton; Sandra L McLellan
Journal:  Environ Microbiol Rep       Date:  2014-07-09       Impact factor: 3.541

2.  Data Acceptance Criteria for Standardized Human-Associated Fecal Source Identification Quantitative Real-Time PCR Methods.

Authors:  Orin C Shanks; Catherine A Kelty; Robin Oshiro; Richard A Haugland; Tania Madi; Lauren Brooks; Katharine G Field; Mano Sivaganesan
Journal:  Appl Environ Microbiol       Date:  2016-04-18       Impact factor: 4.792

3.  Portable platform for rapid in-field identification of human fecal pollution in water.

Authors:  Yu Sherry Jiang; Timothy E Riedel; Jessica A Popoola; Barrett R Morrow; Sheng Cai; Andrew D Ellington; Sanchita Bhadra
Journal:  Water Res       Date:  2017-12-13       Impact factor: 11.236

4.  Source tracking swine fecal waste in surface water proximal to swine concentrated animal feeding operations.

Authors:  Christopher D Heaney; Kevin Myers; Steve Wing; Devon Hall; Dothula Baron; Jill R Stewart
Journal:  Sci Total Environ       Date:  2015-01-17       Impact factor: 7.963

5.  A human fecal contamination score for ranking recreational sites using the HF183/BacR287 quantitative real-time PCR method.

Authors:  Yiping Cao; Mano Sivaganesan; Catherine A Kelty; Dan Wang; Alexandria B Boehm; John F Griffith; Stephen B Weisberg; Orin C Shanks
Journal:  Water Res       Date:  2017-10-31       Impact factor: 11.236

6.  Acute toxic effect of sewage effluent on the early life phase of an estuarine crab Scylla serrata.

Authors:  Manickavalli Gurunadhan Ragunathan
Journal:  Environ Sci Pollut Res Int       Date:  2017-06-02       Impact factor: 4.223

7.  Lessons learned from implementing a wet laboratory molecular training workshop for beach water quality monitoring.

Authors:  Marc Paul Verhougstraete; Sydney Brothers; Wayne Litaker; A Denene Blackwood; Rachel Noble
Journal:  PLoS One       Date:  2015-03-30       Impact factor: 3.240

8.  A controlled, before-and-after trial of an urban sanitation intervention to reduce enteric infections in children: research protocol for the Maputo Sanitation (MapSan) study, Mozambique.

Authors:  Joe Brown; Oliver Cumming; Jamie Bartram; Sandy Cairncross; Jeroen Ensink; David Holcomb; Jackie Knee; Peter Kolsky; Kaida Liang; Song Liang; Rassul Nala; Guy Norman; Richard Rheingans; Jill Stewart; Olimpio Zavale; Valentina Zuin; Wolf-Peter Schmidt
Journal:  BMJ Open       Date:  2015-06-18       Impact factor: 2.692

9.  Nanofluidic digital PCR for the quantification of Norovirus for water quality assessment.

Authors:  Silvia Monteiro; Ricardo Santos
Journal:  PLoS One       Date:  2017-07-27       Impact factor: 3.240

10.  The Use of Ribosomal RNA as a Microbial Source Tracking Target Highlights the Assay Host-Specificity Requirement in Water Quality Assessments.

Authors:  Annastiina Rytkönen; Ananda Tiwari; Anna-Maria Hokajärvi; Sari Uusheimo; Asko Vepsäläinen; Tiina Tulonen; Tarja Pitkänen
Journal:  Front Microbiol       Date:  2021-06-02       Impact factor: 5.640

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