Literature DB >> 27912100

Source tracking using microbial community fingerprints: Method comparison with hydrodynamic modelling.

D T McCarthy1, D Jovanovic2, A Lintern3, I Teakle4, M Barnes4, A Deletic2, R Coleman5, G Rooney5, T Prosser5, S Coutts6, M R Hipsey7, L C Bruce7, R Henry2.   

Abstract

Urban estuaries around the world are experiencing contamination from diffuse and point sources, which increases risks to public health. To mitigate and manage risks posed by elevated levels of contamination in urban waterways, it is critical to identify the primary water sources of contamination within catchments. Source tracking using microbial community fingerprints is one tool that can be used to identify sources. However, results derived from this approach have not yet been evaluated using independent datasets. As such, the key objectives of this investigation were: (1) to identify the major sources of water responsible for bacterial loadings within an urban estuary using microbial source tracking (MST) using microbial communities; and (2) to evaluate this method using a 3-dimensional hydrodynamic model. The Yarra River estuary, which flows through the city of Melbourne in South-East Australia was the focus of this study. We found that the water sources contributing to the bacterial community in the Yarra River estuary varied temporally depending on the estuary's hydrodynamic conditions. The water source apportionment determined using microbial community MST correlated to those determined using a 3-dimensional hydrodynamic model of the transport and mixing of a tracer in the estuary. While there were some discrepancies between the two methods, this investigation demonstrated that MST using bacterial community fingerprints can identify the primary water sources of microorganisms in an estuarine environment. As such, with further optimization and improvements, microbial community MST has the potential to become a powerful tool that could be practically applied in the mitigation of contaminated aquatic systems.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Community profiling; Faecal source tracking; Microbial source tracking (MST); SourceTracker; Tuflow; Urban stormwater

Mesh:

Year:  2016        PMID: 27912100     DOI: 10.1016/j.watres.2016.11.043

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


  5 in total

1.  Quantifying the Relative Contributions of Environmental Sources to the Microbial Community in an Urban Stream under Dry and Wet Weather Conditions.

Authors:  Darshan Baral; Allison Speicher; Bruce Dvorak; David Admiraal; Xu Li
Journal:  Appl Environ Microbiol       Date:  2018-07-17       Impact factor: 4.792

2.  Periodontitis may induce gut microbiota dysbiosis via salivary microbiota.

Authors:  Jun Bao; Lili Li; Yangheng Zhang; Min Wang; Faming Chen; Shaohua Ge; Bin Chen; Fuhua Yan
Journal:  Int J Oral Sci       Date:  2022-06-23       Impact factor: 24.897

3.  Aquatic Bacterial Communities Associated With Land Use and Environmental Factors in Agricultural Landscapes Using a Metabarcoding Approach.

Authors:  Wen Chen; Graham Wilkes; Izhar U H Khan; Katarina D M Pintar; Janis L Thomas; C André Lévesque; Julie T Chapados; Edward Topp; David R Lapen
Journal:  Front Microbiol       Date:  2018-10-30       Impact factor: 5.640

4.  Next-Generation High-Throughput Sequencing to Evaluate Bacterial Communities in Freshwater Ecosystem in Hydroelectric Reservoirs.

Authors:  Martha Virginia R Rojas; Diego Peres Alonso; Milena Dropa; Maria Tereza P Razzolini; Dario Pires de Carvalho; Kaio Augusto Nabas Ribeiro; Paulo Eduardo M Ribolla; Maria Anice M Sallum
Journal:  Microorganisms       Date:  2022-07-11

5.  Fecal source identification using random forest.

Authors:  Adélaïde Roguet; A Murat Eren; Ryan J Newton; Sandra L McLellan
Journal:  Microbiome       Date:  2018-10-18       Impact factor: 14.650

  5 in total

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