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Comparison of the microbiomes of two drinking water distribution systems—with and without residual chloramine disinfection

Overview of attention for article published in Microbiome, June 2019
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (84th percentile)

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1 blog
11 tweeters


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Comparison of the microbiomes of two drinking water distribution systems—with and without residual chloramine disinfection
Published in
Microbiome, June 2019
DOI 10.1186/s40168-019-0707-5
Pubmed ID

Michael B. Waak, Raymond M. Hozalski, Cynthia Hallé, Timothy M. LaPara


Residual disinfection is often used to suppress biological growth in drinking water distribution systems (DWDSs), but not without undesirable side effects. In this study, water-main biofilms, drinking water, and bacteria under corrosion tubercles were analyzed from a chloraminated DWDS (USA) and a no-residual DWDS (Norway). Using quantitative real-time PCR, we quantified bacterial 16S rRNA genes and ammonia monooxygenase genes (amoA) of Nitrosomonas oligotropha and ammonia-oxidizing archaea-organisms that may contribute to chloramine loss. PCR-amplified 16S rRNA genes were sequenced to assess community taxa and diversity. The chloraminated DWDS had lower biofilm biomass (P=1×10-6) but higher N. oligotropha-like amoA genes (P=2×10-7) than the no-residual DWDS (medians =4.7×104 and 1.1×103amoA copies cm-2, chloraminated and no residual, respectively); archaeal amoA genes were only detected in the no-residual DWDS (median =2.8×104 copies cm-2). Unlike the no-residual DWDS, biofilms in the chloraminated DWDS had lower within-sample diversity than the corresponding drinking water (P<1×10-4). Chloramine was also associated with biofilms dominated by the genera, Mycobacterium and Nitrosomonas (≤91.7% and ≤39.6% of sequences, respectively). Under-tubercle communities from both systems contained corrosion-associated taxa, especially Desulfovibrio spp. (≤98.4% of sequences). Although residual chloramine appeared to decrease biofilm biomass and alpha diversity as intended, it selected for environmental mycobacteria and Nitrosomonas oligotropha-taxa that may pose water quality challenges. Drinking water contained common freshwater plankton and did not resemble corresponding biofilm communities in either DWDS; monitoring of tap water alone may therefore miss significant constituents of the DWDS microbiome. Corrosion-associated Desulfovibrio spp. were observed under tubercles in both systems but were particularly dominant in the chloraminated DWDS, possibly due to the addition of sulfate from the coagulant alum.

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 76 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 76 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 28%
Student > Master 12 16%
Researcher 9 12%
Student > Doctoral Student 6 8%
Other 4 5%
Other 10 13%
Unknown 14 18%
Readers by discipline Count As %
Engineering 24 32%
Environmental Science 14 18%
Biochemistry, Genetics and Molecular Biology 6 8%
Agricultural and Biological Sciences 5 7%
Computer Science 3 4%
Other 5 7%
Unknown 19 25%

Attention Score in Context

This research output has an Altmetric Attention Score of 13. 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 12 June 2019.
All research outputs
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Outputs from Microbiome
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Outputs of similar age
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Outputs of similar age from Microbiome
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Altmetric has tracked 15,909,509 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 917 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 37.8. This one is in the 34th percentile – i.e., 34% 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 269,923 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 84% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them