Author
Listed:
- David J. Beale
(Land and Water, Commonwealth Scientific and Industrial Research Organization, P.O. Box 2583, Dutton Park, Queensland 4001, Australia)
- Avinash V. Karpe
(Land and Water, Commonwealth Scientific and Industrial Research Organization, P.O. Box 2583, Dutton Park, Queensland 4001, Australia
Department of Chemistry and Biotechnology, Faculty of Science, Engineering and Technology, Swinburne University of Technology, P.O. Box 218, Hawthorn, Victoria 3122, Australia)
- Warish Ahmed
(Land and Water, Commonwealth Scientific and Industrial Research Organization, P.O. Box 2583, Dutton Park, Queensland 4001, Australia)
- Stephen Cook
(Land and Water, Commonwealth Scientific and Industrial Research Organization, Private Bag 10 Clayton South, Victoria 3169, Australia)
- Paul D. Morrison
(Australian Centre for Research on Separation Science, School of Applied Sciences, RMIT University, P.O. Box 2547, Melbourne, Victoria 3000, Australia)
- Christopher Staley
(Biotechnology Institute, University of Minnesota, St. Paul, MI 55108, USA)
- Michael J. Sadowsky
(Biotechnology Institute, University of Minnesota, St. Paul, MI 55108, USA)
- Enzo A. Palombo
(Department of Chemistry and Biotechnology, Faculty of Science, Engineering and Technology, Swinburne University of Technology, P.O. Box 218, Hawthorn, Victoria 3122, Australia)
Abstract
A multi-omics approach was applied to an urban river system (the Brisbane River (BR), Queensland, Australia) in order to investigate surface water quality and characterize the bacterial population with respect to water contaminants. To do this, bacterial metagenomic amplicon-sequencing using Illumina next-generation sequencing (NGS) of the V5–V6 hypervariable regions of the 16S rRNA gene and untargeted community metabolomics using gas chromatography coupled with mass spectrometry (GC-MS) were utilized. The multi-omics data, in combination with fecal indicator bacteria (FIB) counts, trace metal concentrations (by inductively coupled plasma mass spectrometry (ICP-MS)) and in-situ water quality measurements collected from various locations along the BR were then used to assess the health of the river ecosystem. Sites sampled represented the transition from less affected (upstream) to polluted (downstream) environments along the BR. Chemometric analysis of the combined datasets indicated a clear separation between the sampled environments. Burkholderiales and Cyanobacteria were common key factors for differentiation of pristine waters. Increased sugar alcohol and short-chain fatty acid production was observed by Actinomycetales and Rhodospirillaceae that are known to form biofilms in urban polluted and brackish waters. Results from this study indicate that a multi-omics approach enables a deep understanding of the health of an aquatic ecosystem, providing insight into the bacterial diversity present and the metabolic output of the population when exposed to environmental contaminants.
Suggested Citation
David J. Beale & Avinash V. Karpe & Warish Ahmed & Stephen Cook & Paul D. Morrison & Christopher Staley & Michael J. Sadowsky & Enzo A. Palombo, 2017.
"A Community Multi-Omics Approach towards the Assessment of Surface Water Quality in an Urban River System,"
IJERPH, MDPI, vol. 14(3), pages 1-24, March.
Handle:
RePEc:gam:jijerp:v:14:y:2017:i:3:p:303-:d:93059
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