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Bacterial microbiota of Kazakhstan cheese revealed by single molecule real time (SMRT) sequencing and its comparison with Belgian, Kalmykian and Italian artisanal cheeses

Overview of attention for article published in BMC Microbiology, January 2017
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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 (88th percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

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Title
Bacterial microbiota of Kazakhstan cheese revealed by single molecule real time (SMRT) sequencing and its comparison with Belgian, Kalmykian and Italian artisanal cheeses
Published in
BMC Microbiology, January 2017
DOI 10.1186/s12866-016-0911-4
Pubmed ID
Authors

Jing Li, Yi Zheng, Haiyan Xu, Xiaoxia Xi, Qiangchuan Hou, Shuzhen Feng, Laga Wuri, Yanfei Bian, Zhongjie Yu, Lai-Yu Kwok, Zhihong Sun, Tiansong Sun

Abstract

In Kazakhstan, traditional artisanal cheeses have a long history and are widely consumed. The unique characteristics of local artisanal cheeses are almost completely preserved. However, their microbial communities have rarely been reported. The current study firstly generated the Single Molecule, Real-Time (SMRT) sequencing bacterial diversity profiles of 6 traditional artisanal cheese samples of Kazakhstan origin, followed by comparatively analyzed the microbiota composition between the current dataset and those from cheeses originated from Belgium, Russian Republic of Kalmykia (Kalmykia) and Italy. Across the Kazakhstan cheese samples, a total of 238 bacterial species belonging to 14 phyla and 140 genera were identified. Lactococcus lactis (28.93%), Lactobacillus helveticus (26.43%), Streptococcus thermophilus (12.18%) and Lactobacillus delbrueckii (12.15%) were the dominant bacterial species for these samples. To further evaluate the cheese bacterial diversity of Kazakhstan cheeses in comparison with those from other geographic origins, 16S rRNA datasets of 36 artisanal cheeses from Belgium, Russian Republic of Kalmykia (Kalmykia) and Italy were retrieved from public databases. The cheese bacterial microbiota communities were largely different across sample origins. By principal coordinate analysis (PCoA) and multivariate analysis of variance (MANOVA), the structure of the Kazakhstan artisanal cheese samples was found to be different from those of the other geographic origins. Furthermore, the redundancy analysis (RDA) identified 16 bacterial OTUs as the key variables responsible for such microbiota structural difference. Our results together suggest that the diversity of bacterial communities in different groups is stratified by geographic region. This study does not only provide novel information on the bacterial microbiota of traditional artisanal cheese of Kazakhstan at species level, but also interesting insights into the bacterial diversity of artisanal cheeses of various geographical origins.

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X Demographics

The data shown below were collected from the profiles of 11 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 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 58 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 19%
Researcher 9 16%
Student > Bachelor 7 12%
Student > Master 6 10%
Professor 2 3%
Other 4 7%
Unknown 19 33%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 11 19%
Agricultural and Biological Sciences 10 17%
Immunology and Microbiology 6 10%
Engineering 2 3%
Veterinary Science and Veterinary Medicine 1 2%
Other 1 2%
Unknown 27 47%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 14. 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 17 January 2017.
All research outputs
#2,374,648
of 24,162,141 outputs
Outputs from BMC Microbiology
#162
of 3,323 outputs
Outputs of similar age
#48,970
of 428,940 outputs
Outputs of similar age from BMC Microbiology
#4
of 41 outputs
Altmetric has tracked 24,162,141 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 3,323 research outputs from this source. They receive a mean Attention Score of 4.2. This one has done particularly well, scoring higher than 95% 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 428,940 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 88% of its contemporaries.
We're also able to compare this research output to 41 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 92% of its contemporaries.