Journal article
Novel primer sets for next generation sequencing-based analyses of water quality
PLoS ONE, Vol.12(1), e0170008
2017
Abstract
Next generation sequencing (NGS) has rapidly become an invaluable tool for the detection, identification and relative quantification of environmental microorganisms. Here, we demonstrate two new 16S rDNA primer sets, which are compatible with NGS approaches and are primarily for use in water quality studies. Compared to 16S rRNA gene based universal primers, in silico and experimental analyses demonstrated that the new primers showed increased specificity for the Cyanobacteria and Proteobacteria phyla, allowing increased sensitivity for the detection, identification and relative quantification of toxic bloom-forming microalgae, microbial water quality bioindicators and common pathogens. Significantly, Cyanobacterial and Proteobacterial sequences accounted for ca. 95% of all sequences obtained within NGS runs (when compared to ca. 50% with standard universal NGS primers), providing higher sensitivity and greater phylogenetic resolution of key water quality microbial groups. The increased selectivity of the new primers allow the parallel sequencing of more samples through reduced sequence retrieval levels required to detect target groups, potentially reducing NGS costs by 50% but still guaranteeing optimal coverage and species discrimination.
Details
- Title
- Novel primer sets for next generation sequencing-based analyses of water quality
- Authors/Creators
- E. Lee (Author/Creator) - Murdoch UniversityM.S. Khurana (Author/Creator) - Murdoch UniversityA.S. Whiteley (Author/Creator) - The University of Western AustraliaP.T. Monis (Author/Creator) - South Australian Water CorporationA. Bath (Author/Creator) - Water Corporation of Western Australia (Australia)C. Gordon (Author/Creator) - Water Corporation of Western Australia (Australia)U.M. Ryan (Author/Creator) - Murdoch UniversityA. Paparini (Author/Creator) - Murdoch University
- Publication Details
- PLoS ONE, Vol.12(1), e0170008
- Publisher
- Public Library of Science
- Identifiers
- 991005540236907891
- Copyright
- © 2017 Lee et al.
- Murdoch Affiliation
- School of Veterinary and Life Sciences
- Language
- English
- Resource Type
- Journal article
UN Sustainable Development Goals (SDGs)
This output has contributed to the advancement of the following goals:
Metrics
126 File views/ downloads
104 Record Views
InCites Highlights
These are selected metrics from InCites Benchmarking & Analytics tool, related to this output
- Collaboration types
- Domestic collaboration
- Citation topics
- 3 Agriculture, Environment & Ecology
- 3.2 Marine Biology
- 3.2.216 Lake Ecosystems
- Web Of Science research areas
- Microbiology
- ESI research areas
- Biology & Biochemistry