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Amplicon-based taxonomic characterization of bacteria in urban and peri-urban roof-harvested rainwater stored in tanks

Overview of attention for article published in Science of the Total Environment, January 2017
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Mentioned by

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3 tweeters

Citations

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9 Dimensions

Readers on

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28 Mendeley
Title
Amplicon-based taxonomic characterization of bacteria in urban and peri-urban roof-harvested rainwater stored in tanks
Published in
Science of the Total Environment, January 2017
DOI 10.1016/j.scitotenv.2016.10.090
Pubmed ID
Authors

W. Ahmed, C. Staley, K.A. Hamilton, D.J. Beale, M.J. Sadowsky, S. Toze, C.N. Haas

Abstract

Overall, 26% of Australian households use rainwater tanks as a source of potable and nonpotable water. Limited information is available on the total bacterial communities in tank water. Therefore, identification of dominant bacterial communities, diversity, and their distribution is important in understanding the microbial quality of tank water. In this study, the abundance and diversity of bacterial communities in 88 tank water samples collected from the urban areas of Brisbane (n=44) and the peri-urban center of Currumbin (n=44) in Southeast Queensland, Australia were determined using amplicon-based Illumina next-generation sequencing. In addition, the SourceTracker program was used to identify the sources of fecal contamination in tank water samples. Sequence reads were also analyzed to detect potential bacterial pathogenic genera in the tank water samples collected. Differences in sample coverage, alpha diversity, and richness did not differ significantly between the Brisbane and Currumbin tank water samples. Comamonadaceae and Planctomycetaceae were the most abundant families in all tank water samples. Curvibacter was the most abundant genus in all tank water samples. SourceTracker revealed that around 34% (Brisbane) and 43% (Currumbin) of tank water samples had a signature for bird fecal contamination. The potential opportunistic pathogenic genera including Burkholderia, Chromobacterium, Clostridium, Legionella, Mycobacterium, Nocardia, and Pseudomonas were most prevalent in tank water samples. Next-generation sequencing can be used as an initial screening tool to identify a wide array of potential pathogenic genera in tank water samples followed by quantifying specific pathogen(s) of interest using more sensitive molecular assays such as quantitative PCR (qPCR).

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 32%
Student > Master 7 25%
Unspecified 3 11%
Student > Bachelor 3 11%
Other 2 7%
Other 4 14%
Readers by discipline Count As %
Engineering 6 21%
Agricultural and Biological Sciences 6 21%
Environmental Science 6 21%
Unspecified 5 18%
Biochemistry, Genetics and Molecular Biology 2 7%
Other 3 11%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 October 2016.
All research outputs
#7,053,062
of 12,269,384 outputs
Outputs from Science of the Total Environment
#4,880
of 8,421 outputs
Outputs of similar age
#128,602
of 266,068 outputs
Outputs of similar age from Science of the Total Environment
#188
of 387 outputs
Altmetric has tracked 12,269,384 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,421 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.0. This one is in the 39th percentile – i.e., 39% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 266,068 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 387 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.