Potential applications of next generation DNA sequencing of 16S rRNA gene amplicons in microbial water quality monitoring

Author:

Vierheilig J.123,Savio D.12,Ley R. E.4,Mach R. L.5,Farnleitner A. H.16,Reischer G. H.16

Affiliation:

1. Research Group Environmental Microbiology and Molecular Ecology, Institute for Chemical Engineering, Vienna University of Technology, Gumpendorfer Straße 1a, A-1060 Vienna, Austria

2. Centre for Water Resource Systems (CWRS), Vienna University of Technology, Karlsplatz 13/222, A-1040 Vienna, Austria

3. Present address: Division of Microbial Ecology, Department of Microbiology and Ecosystem Science, University of Vienna, Althanstraße 14, A-1090 Vienna, Austria

4. Department of Microbiology, Cornell University, Ithaca, NY 14853, USA

5. Gene Technology Group, Institute for Chemical Engineering, Vienna University of Technology, Gumpendorfer Straße 1a, A-1060 Vienna, Austria

6. Interuniversity Cooperation Centre Water & Health, Institute for Chemical Engineering, Vienna University of Technology, Gumpendorfer Straße 1a, A-1060 Vienna, Austria

Abstract

The applicability of next generation DNA sequencing (NGS) methods for water quality assessment has so far not been broadly investigated. This study set out to evaluate the potential of an NGS-based approach in a complex catchment with importance for drinking water abstraction. In this multi-compartment investigation, total bacterial communities in water, faeces, soil, and sediment samples were investigated by 454 pyrosequencing of bacterial 16S rRNA gene amplicons to assess the capabilities of this NGS method for (i) the development and evaluation of environmental molecular diagnostics, (ii) direct screening of the bulk bacterial communities, and (iii) the detection of faecal pollution in water. Results indicate that NGS methods can highlight potential target populations for diagnostics and will prove useful for the evaluation of existing and the development of novel DNA-based detection methods in the field of water microbiology. The used approach allowed unveiling of dominant bacterial populations but failed to detect populations with low abundances such as faecal indicators in surface waters. In combination with metadata, NGS data will also allow the identification of drivers of bacterial community composition during water treatment and distribution, highlighting the power of this approach for monitoring of bacterial regrowth and contamination in technical systems.

Publisher

IWA Publishing

Subject

Water Science and Technology,Environmental Engineering

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