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Microbial Community Structure of Activated Sludge in Treatment Plants with Different Wastewater Compositions

Overview of attention for article published in Frontiers in Microbiology, February 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

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1 blog
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Citations

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184 Dimensions

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363 Mendeley
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Title
Microbial Community Structure of Activated Sludge in Treatment Plants with Different Wastewater Compositions
Published in
Frontiers in Microbiology, February 2016
DOI 10.3389/fmicb.2016.00090
Pubmed ID
Authors

Nataliya M. Shchegolkova, George S. Krasnov, Anastasia A. Belova, Alexey A. Dmitriev, Sergey L. Kharitonov, Kseniya M. Klimina, Nataliya V. Melnikova, Anna V. Kudryavtseva

Abstract

Activated sludge (AS) plays a crucial role in the treatment of domestic and industrial wastewater. AS is a biocenosis of microorganisms capable of degrading various pollutants, including organic compounds, toxicants, and xenobiotics. We performed 16S rRNA gene sequencing of AS and incoming sewage in three wastewater treatment plants (WWTPs) responsible for processing sewage with different origins: municipal wastewater, slaughterhouse wastewater, and refinery sewage. In contrast to incoming wastewater, the taxonomic structure of AS biocenosis was found to become stable in time, and each WWTP demonstrated a unique taxonomic pattern. Most pathogenic microorganisms (Streptococcus, Trichococcus, etc.), which are abundantly represented in incoming sewage, were significantly decreased in AS of all WWTPs, except for the slaughterhouse wastewater. Additional load of bioreactors with influent rich in petroleum products and organic matter was associated with the increase of bacteria responsible for AS bulking and foaming. Here, we present a novel approach enabling the prediction of the metabolic potential of bacterial communities based on their taxonomic structures and MetaCyc database data. We developed a software application, XeDetect, to implement this approach. Using XeDetect, we found that the metabolic potential of the three bacterial communities clearly reflected the substrate composition. We revealed that the microorganisms responsible for AS bulking and foaming (most abundant in AS of slaughterhouse wastewater) played a leading role in the degradation of substrates such as fatty acids, amino acids, and other bioorganic compounds. Moreover, we discovered that the chemical, rather than the bacterial composition of the incoming wastewater was the main factor in AS structure formation. XeDetect (freely available: https://sourceforge.net/projects/xedetect) represents a novel powerful tool for the analysis of the metabolic capacity of bacterial communities. The tool will help to optimize bioreactor performance and avoid some most common technical problems.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 363 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
India 1 <1%
Philippines 1 <1%
Estonia 1 <1%
China 1 <1%
Unknown 359 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 76 21%
Researcher 44 12%
Student > Master 44 12%
Student > Bachelor 39 11%
Student > Doctoral Student 26 7%
Other 36 10%
Unknown 98 27%
Readers by discipline Count As %
Environmental Science 63 17%
Agricultural and Biological Sciences 47 13%
Engineering 38 10%
Biochemistry, Genetics and Molecular Biology 32 9%
Chemical Engineering 21 6%
Other 40 11%
Unknown 122 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 01 March 2016.
All research outputs
#4,090,151
of 23,577,761 outputs
Outputs from Frontiers in Microbiology
#3,889
of 26,068 outputs
Outputs of similar age
#61,263
of 299,573 outputs
Outputs of similar age from Frontiers in Microbiology
#110
of 535 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 26,068 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one has done well, scoring higher than 84% of its peers.
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 299,573 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 79% of its contemporaries.
We're also able to compare this research output to 535 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.