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16S rRNA gene-based association study identified microbial taxa associated with pork intramuscular fat content in feces and cecum lumen

Overview of attention for article published in BMC Microbiology, July 2017
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Title
16S rRNA gene-based association study identified microbial taxa associated with pork intramuscular fat content in feces and cecum lumen
Published in
BMC Microbiology, July 2017
DOI 10.1186/s12866-017-1055-x
Pubmed ID
Authors

Shaoming Fang, Xingwei Xiong, Ying Su, Lusheng Huang, Congying Chen

Abstract

Intramuscular fat (IMF) that deposits among muscle fibers or within muscle cells is an important meat quality trait in pigs. Previous studies observed the effects of dietary nutrients and additives on improving the pork IMF. Gut microbiome plays an important role in host metabolism and energy harvest. Whether gut microbiota exerts effect on IMF remains unknown. In this study, we investigated the microbial community structure of 500 samples from porcine cecum and feces using high-throughput 16S rRNA gene sequencing. We found that phylogenetic composition and potential function capacity of microbiome varied between two types of samples. Bacteria wide association study identified 119 OTUs significantly associated with IMF in the two types of samples (FDR < 0.1). Most of the IMF-associated OTUs belong to the bacteria related to polysaccharide degradation and amino acid metabolism (such as Prevotella, Treponema, Bacteroides and Clostridium). Potential function capacities related to metabolisms of carbohydrate, energy and amino acids, cell motility, and membrane transport were significantly associated with IMF content. FishTaco analysis suggested that the shifts of potential function capacities of microbiome associated with IMF might be caused by the IMF-associated microbial taxa. This study firstly evaluated the contribution of gut microbiome to porcine IMF content. The results presented a potential capacity for improving IMF through modulating gut microbiota.

Twitter Demographics

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

Mendeley readers

The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 43 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 23%
Researcher 6 14%
Student > Master 6 14%
Student > Postgraduate 3 7%
Student > Doctoral Student 2 5%
Other 4 9%
Unknown 12 28%
Readers by discipline Count As %
Agricultural and Biological Sciences 18 42%
Biochemistry, Genetics and Molecular Biology 6 14%
Veterinary Science and Veterinary Medicine 3 7%
Chemistry 2 5%
Medicine and Dentistry 2 5%
Other 2 5%
Unknown 10 23%

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 07 March 2018.
All research outputs
#10,088,674
of 12,612,351 outputs
Outputs from BMC Microbiology
#1,280
of 1,858 outputs
Outputs of similar age
#193,272
of 263,205 outputs
Outputs of similar age from BMC Microbiology
#1
of 1 outputs
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