↓ Skip to main content

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
Altmetric Badge

Mentioned by

twitter
2 X users

Citations

dimensions_citation
53 Dimensions

Readers on

mendeley
50 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
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.

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 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 50 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 22%
Researcher 8 16%
Student > Master 5 10%
Student > Doctoral Student 3 6%
Student > Bachelor 3 6%
Other 5 10%
Unknown 15 30%
Readers by discipline Count As %
Agricultural and Biological Sciences 21 42%
Biochemistry, Genetics and Molecular Biology 8 16%
Veterinary Science and Veterinary Medicine 3 6%
Chemistry 2 4%
Medicine and Dentistry 2 4%
Other 1 2%
Unknown 13 26%
Attention Score in Context

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
#18,562,247
of 22,990,068 outputs
Outputs from BMC Microbiology
#2,256
of 3,206 outputs
Outputs of similar age
#241,332
of 315,216 outputs
Outputs of similar age from BMC Microbiology
#31
of 55 outputs
Altmetric has tracked 22,990,068 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,206 research outputs from this source. They receive a mean Attention Score of 4.1. This one is in the 15th percentile – i.e., 15% 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 315,216 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 55 others from the same source and published within six weeks on either side of this one. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.