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Amplicon-based profiling of bacteria in raw and secondary treated wastewater from treatment plants across Australia

Overview of attention for article published in Applied Microbiology & Biotechnology, November 2016
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Title
Amplicon-based profiling of bacteria in raw and secondary treated wastewater from treatment plants across Australia
Published in
Applied Microbiology & Biotechnology, November 2016
DOI 10.1007/s00253-016-7959-9
Pubmed ID
Authors

Warish Ahmed, Christopher Staley, Jatinder Sidhu, Michael Sadowsky, Simon Toze

Abstract

In this study, we investigated the use of Illumina high-throughput sequencing of 16S ribosomal RNA (rRNA) amplicons to explore microbial diversity and community structure in raw and secondary treated wastewater (WW) samples from four municipal wastewater treatment plants (WWTPs A-D) across Australia. Sequence reads were analyzed to determine the abundance and diversity of bacterial communities in raw and secondary treated WW samples across the four WWTPs. In addition, sequence reads were also characterized to phenotypic features and to estimate the abundance of potential pathogenic bacterial genera and antibiotic-resistant genes in total bacterial communities. The mean coverage, Shannon diversity index, observed richness (S obs), and abundance-based coverage estimate (ACE) of richness for raw and secondary treated WW samples did not differ significantly (P > 0.05) among the four WWTPs examined. Generally, raw and secondary treated WW samples were dominated by members of the genera Pseudomonas, Arcobacter, and Bacteroides. Evaluation of source contributions to secondary treated WW, done using SourceTracker, revealed that 8.80-61.4% of the bacterial communities in secondary treated WW samples were attributed to raw WW. Twenty-five bacterial genera were classified as containing potential bacterial pathogens. The abundance of potentially pathogenic genera in raw WW samples was higher than that found in secondary treated WW samples. Among the pathogenic genera identified, Pseudomonas and Arcobacter had the greatest percentage of the sequence reads. The abundances of antibiotic resistance genes were generally low (<0.5%), except for genes encoding ABC transporters, which accounted for approximately 3% of inferred genes. These findings provided a comprehensive profile of bacterial communities, including potential bacterial pathogens and antibiotic-resistant genes, in raw and secondary treated WW samples from four WWTPs across Australia and demonstrated that Illumina high-throughput sequencing can be an alternative approach for monitoring WW quality in order to protect environmental and human health.

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 48 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 23%
Unspecified 9 19%
Student > Master 9 19%
Student > Ph. D. Student 6 13%
Student > Doctoral Student 4 8%
Other 9 19%
Readers by discipline Count As %
Unspecified 14 29%
Agricultural and Biological Sciences 10 21%
Environmental Science 10 21%
Engineering 5 10%
Biochemistry, Genetics and Molecular Biology 5 10%
Other 4 8%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 19 November 2016.
All research outputs
#9,769,320
of 12,225,271 outputs
Outputs from Applied Microbiology & Biotechnology
#4,138
of 5,233 outputs
Outputs of similar age
#229,255
of 335,746 outputs
Outputs of similar age from Applied Microbiology & Biotechnology
#58
of 110 outputs
Altmetric has tracked 12,225,271 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,233 research outputs from this source. They receive a mean Attention Score of 3.6. This one is in the 14th percentile – i.e., 14% 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 335,746 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 110 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.