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Perilipin-2 modulates dietary fat-induced microbial global gene expression profiles in the mouse intestine

Overview of attention for article published in Microbiome, September 2017
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  • Above-average Attention Score compared to outputs of the same age (59th percentile)

Mentioned by

7 tweeters
1 Facebook page


9 Dimensions

Readers on

37 Mendeley
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Perilipin-2 modulates dietary fat-induced microbial global gene expression profiles in the mouse intestine
Published in
Microbiome, September 2017
DOI 10.1186/s40168-017-0327-x
Pubmed ID

Xuejian Xiong, Elise S. Bales, Diana Ir, Charles E. Robertson, James L. McManaman, Daniel N. Frank, John Parkinson


Intestinal microbiota are critical determinants of obesity and metabolic disease risk. In previous work, we showed that deletion of the cytoplasmic lipid droplet (CLD) protein perilipin-2 (Plin2) modulates gut microbial community structure and abrogates long-term deleterious effects of a high-fat (HF) diet in mice. However, the impact of Plin2 on microbiome function is unknown. Here, we used metatranscriptomics to identify differences in microbiome transcript expression in WT and Plin2-null mice following acute exposure to high-fat/low-carbohydrate (HF) or low-fat/high-carbohydrate (LF) diets. Consistent with previous studies, dietary changes resulted in significant taxonomic shifts. Unexpectedly, when fed a HF diet, the microbiota of Plin2-null and WT mice exhibited dramatic shifts in transcript expression despite no discernible shift in community structure. For Plin2-null mice, these changes included the coordinated upregulation of metabolic enzymes directing flux towards the production of growth metabolites such as fatty acids, nucleotides, and amino acids. In contrast, the LF diet did not appear to induce the same dramatic changes in transcript or pathway expression between the two genotypes. Our data shows that a host genotype can modulate microbiome function without impacting community structure and identify Plin2 as a specific host determinant of diet effects on microbial function. Along with uncovering potential mechanisms for integrating how diet modulates host and microbial metabolism, our findings demonstrate the limits of 16S rRNA surveys to inform on community functional activities and the need to prioritize metatranscriptomic studies to gain more meaningful insights into microbiome function.

Twitter Demographics

The data shown below were collected from the profiles of 7 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 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 37 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 16%
Researcher 6 16%
Student > Doctoral Student 3 8%
Student > Bachelor 3 8%
Student > Master 3 8%
Other 10 27%
Unknown 6 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 8 22%
Biochemistry, Genetics and Molecular Biology 6 16%
Medicine and Dentistry 6 16%
Nursing and Health Professions 2 5%
Immunology and Microbiology 2 5%
Other 4 11%
Unknown 9 24%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 03 May 2018.
All research outputs
of 12,886,920 outputs
Outputs from Microbiome
of 691 outputs
Outputs of similar age
of 265,345 outputs
Outputs of similar age from Microbiome
of 46 outputs
Altmetric has tracked 12,886,920 research outputs across all sources so far. This one is in the 47th percentile – i.e., 47% of other outputs scored the same or lower than it.
So far Altmetric has tracked 691 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 40.1. This one is in the 7th percentile – i.e., 7% 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 265,345 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 59% of its contemporaries.
We're also able to compare this research output to 46 others from the same source and published within six weeks on either side of this one. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.