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Bacteria and Archaea diversity within the hot springs of Lake Magadi and Little Magadi in Kenya

Overview of attention for article published in BMC Microbiology, July 2016
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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 (85th percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

Mentioned by

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1 blog
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5 X users
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1 Q&A thread

Citations

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86 Dimensions

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157 Mendeley
Title
Bacteria and Archaea diversity within the hot springs of Lake Magadi and Little Magadi in Kenya
Published in
BMC Microbiology, July 2016
DOI 10.1186/s12866-016-0748-x
Pubmed ID
Authors

Anne Kelly Kambura, Romano Kachiuru Mwirichia, Remmy Wekesa Kasili, Edward Nderitu Karanja, Huxley Mae Makonde, Hamadi Iddi Boga

Abstract

Lake Magadi and little Magadi are hypersaline, alkaline lakes situated in the southern part of Kenyan Rift Valley. Solutes are supplied mainly by a series of alkaline hot springs with temperatures as high as 86 °C. Previous culture-dependent and culture-independent studies have revealed diverse groups of microorganisms thriving under these conditions. Previous culture independent studies were based on the analysis of 16S rDNA but were done on less saline lakes. For the first time, this study combined illumina sequencing and analysis of amplicons of both total community rDNA and 16S rRNA cDNA to determine the diversity and community structure of bacteria and archaea within 3 hot springs of L. Magadi and little Magadi. Water, wet sediments and microbial mats were collected from springs in the main lake at a temperature of 45.1 °C and from Little Magadi "Nasikie eng'ida" (temperature of 81 °C and 83.6 °C). Total community DNA and RNA were extracted from samples using phenol-chloroform and Trizol RNA extraction protocols respectively. The 16S rRNA gene variable region (V4 - V7) of the extracted DNA and RNA were amplified and library construction performed following Illumina sequencing protocol. Sequences were analyzed done using QIIME while calculation of Bray-Curtis dissimilarities between datasets, hierarchical clustering, Non Metric Dimensional Scaling (NMDS) redundancy analysis (RDA) and diversity indices were carried out using the R programming language and the Vegan package. Three thousand four hundred twenty-six and one thousand nine hundred thirteen OTUs were recovered from 16S rDNA and 16S rRNA cDNA respectively. Uncultured diversity accounted for 89.35 % 16S rDNA and 87.61 % 16S rRNA cDNA reads. The most abundant phyla in both the 16S rDNA and 16S rRNA cDNA datasets included: Proteobacteria (8.33-50 %), Firmicutes 3.52-28.92 %, Bacteroidetes (3.45-26.44 %), Actinobacteria (0.98-28.57 %) and Euryarchaeota (3.55-34.48 %) in all samples. NMDS analyses of taxonomic composition clustered the taxa into three groups according to sample types (i.e. wet sediments, mats and water samples) with evident overlap of clusters between wet sediments and microbial mats from the three sample types in both DNA and cDNA datasets. The hot spring (45.1 °C) contained less diverse populations compared to those in Little Magadi (81-83 °C). There were significant differences in microbial community structure at 95 % level of confidence for both total diversity (P value, 0.009) based on 16S rDNA analysis and active microbial diversity (P value, 0.01) based on 16S rRNA cDNA analysis, within the three hot springs. Differences in microbial composition and structure were observed as a function of sample type and temperature, with wet sediments harboring the highest diversity.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 157 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 <1%
Netherlands 1 <1%
Germany 1 <1%
Unknown 154 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 33 21%
Student > Master 20 13%
Student > Bachelor 18 11%
Researcher 17 11%
Student > Postgraduate 12 8%
Other 22 14%
Unknown 35 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 45 29%
Biochemistry, Genetics and Molecular Biology 29 18%
Immunology and Microbiology 13 8%
Environmental Science 12 8%
Nursing and Health Professions 2 1%
Other 15 10%
Unknown 41 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 07 June 2017.
All research outputs
#2,983,968
of 24,885,505 outputs
Outputs from BMC Microbiology
#221
of 3,434 outputs
Outputs of similar age
#51,571
of 363,396 outputs
Outputs of similar age from BMC Microbiology
#8
of 92 outputs
Altmetric has tracked 24,885,505 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,434 research outputs from this source. They receive a mean Attention Score of 4.2. This one has done particularly well, scoring higher than 93% 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 363,396 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 85% of its contemporaries.
We're also able to compare this research output to 92 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.