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Perilipin-2 Modulates Lipid Absorption and Microbiome Responses in the Mouse Intestine.

Frank DN, Bales ES, Monks J, Jackman MJ, MacLean PS, Ir D, Robertson CE, Orlicky DJ, McManaman JL - PLoS ONE (2015)

Bottom Line: Here we test the hypotheses that Plin2 function impacts the earliest steps of HF diet-mediated pathogenesis as well as the dynamics of diet-associated changes in gut microbiome diversity and function.Plin2- mice had significantly lower respiratory exchange ratios, diminished frequencies of enterocyte CLDs, and increased fecal triglyceride levels compared with WT mice.Microbiome analyses, employing both 16S rRNA profiling and metagenomic deep sequencing, indicated that dietary fat content and Plin2 genotype were significantly and independently associated with gut microbiome composition, diversity, and functional differences.

View Article: PubMed Central - PubMed

Affiliation: Division of Infectious Disease, University of Colorado School of Medicine, Aurora, Colorado, United States of America; Microbiome Research Consortium, University of Colorado School of Medicine, Aurora, Colorado, United States of America.

ABSTRACT
Obesity and its co-morbidities, such as fatty liver disease, are increasingly prevalent worldwide health problems. Intestinal microorganisms have emerged as critical factors linking diet to host physiology and metabolic function, particularly in the context of lipid homeostasis. We previously demonstrated that deletion of the cytoplasmic lipid drop (CLD) protein Perilipin-2 (Plin2) in mice largely abrogates long-term deleterious effects of a high fat (HF) diet. Here we test the hypotheses that Plin2 function impacts the earliest steps of HF diet-mediated pathogenesis as well as the dynamics of diet-associated changes in gut microbiome diversity and function. WT and perilipin-2 mice raised on a standard chow diet were randomized to either low fat (LF) or HF diets. After four days, animals were assessed for changes in physiological (body weight, energy balance, and fecal triglyceride levels), histochemical (enterocyte CLD content), and fecal microbiome parameters. Plin2- mice had significantly lower respiratory exchange ratios, diminished frequencies of enterocyte CLDs, and increased fecal triglyceride levels compared with WT mice. Microbiome analyses, employing both 16S rRNA profiling and metagenomic deep sequencing, indicated that dietary fat content and Plin2 genotype were significantly and independently associated with gut microbiome composition, diversity, and functional differences. These data demonstrate that Plin2 modulates rapid effects of diet on fecal lipid levels, enterocyte CLD contents, and fuel utilization properties of mice that correlate with structural and functional differences in their gut microbial communities. Collectively, the data provide evidence of Plin2 regulated intestinal lipid uptake, which contributes to rapid changes in the gut microbial communities implicated in diet-induced obesity.

No MeSH data available.


Related in: MedlinePlus

Principal components analysis of fecal microbiomes.PCA was carried out on genus-level microbiome datasets, as described in the text. PC1, PC2, and PC3 accounted for 35.3%, 26.8%, and 15.7% of the total variance in the dataset (77.8% cumulative proportion). Microbiomes from individual fecal samples, color-coded by genotype and diet, are plotted along the first three PC axes in Panels A, C, and D. Panel B displays the same plot as Panel A, but with arrows connecting pairs of samples from the same animals on different diets. Panel E displays a heat-map color-coding Spearman correlation coefficients between PC scores and the abundances of prevalent OTUs (abundances >1%) in fecal samples. OTU names are prefixed by letters indicating phyla classifications of the OTUs: A: Actinobacteria, B: Bacteroidetes, F: Firmicutes, P: Proteobacteria; T: TM7. Asterisks depict p-values for correlations: *: p<0.1; **: p<0.05; ***p<0.001. Blue shading indicates positive correlations, while red shading indicates negative correlations. OTUs that could not be classified to the genus level are labeled by adding “other” to the higher-order taxonomic assignment.
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pone.0131944.g005: Principal components analysis of fecal microbiomes.PCA was carried out on genus-level microbiome datasets, as described in the text. PC1, PC2, and PC3 accounted for 35.3%, 26.8%, and 15.7% of the total variance in the dataset (77.8% cumulative proportion). Microbiomes from individual fecal samples, color-coded by genotype and diet, are plotted along the first three PC axes in Panels A, C, and D. Panel B displays the same plot as Panel A, but with arrows connecting pairs of samples from the same animals on different diets. Panel E displays a heat-map color-coding Spearman correlation coefficients between PC scores and the abundances of prevalent OTUs (abundances >1%) in fecal samples. OTU names are prefixed by letters indicating phyla classifications of the OTUs: A: Actinobacteria, B: Bacteroidetes, F: Firmicutes, P: Proteobacteria; T: TM7. Asterisks depict p-values for correlations: *: p<0.1; **: p<0.05; ***p<0.001. Blue shading indicates positive correlations, while red shading indicates negative correlations. OTUs that could not be classified to the genus level are labeled by adding “other” to the higher-order taxonomic assignment.

Mentions: Data exploration through principal components analysis (PCA) indicated that both diet and genotype affected microbiome structure among the mouse groups (Fig 5; each symbol represents an individual mouse, color-coded by diet and genotype). Qualitatively, the HF diet appeared to have the strongest effects on sample clustering within the PCA plots, compared with the effects of either genotype or LF/chow diets, because all HF samples (regardless of genotype) segregated away from the remainder of the samples along PC1, PC2, and PC3 (lower right quadrants of Fig 5A, 5B and 5C). Indeed, PC1 scores were significantly associated with diet (p = 6.4e-11) and genotype (p = 0.0001), whereas PC2 and PC3 scores were weakly associated with genotype and diet (Fig 5F). Higher PC1 scores, which were associated with a HF diet (Fig 5F), were negatively correlated with the Bacteroidetes family S24-7 and positively correlated with several groups of Firmicutes, Actinobacteria, and Proteobacteria (Fig 5E). Similarly, higher PC3 scores were observed for WT mice, compared with Plin2- mice, and were positively correlated with the genus Bacteroides. Thus, differential shifts in Firmicutes and sub-groups of Bacteroidetes (e.g. S24-7 vs. Bacteroides) resulting from genotype and/or dietary factors help to explain the observed PCA clustering.


Perilipin-2 Modulates Lipid Absorption and Microbiome Responses in the Mouse Intestine.

Frank DN, Bales ES, Monks J, Jackman MJ, MacLean PS, Ir D, Robertson CE, Orlicky DJ, McManaman JL - PLoS ONE (2015)

Principal components analysis of fecal microbiomes.PCA was carried out on genus-level microbiome datasets, as described in the text. PC1, PC2, and PC3 accounted for 35.3%, 26.8%, and 15.7% of the total variance in the dataset (77.8% cumulative proportion). Microbiomes from individual fecal samples, color-coded by genotype and diet, are plotted along the first three PC axes in Panels A, C, and D. Panel B displays the same plot as Panel A, but with arrows connecting pairs of samples from the same animals on different diets. Panel E displays a heat-map color-coding Spearman correlation coefficients between PC scores and the abundances of prevalent OTUs (abundances >1%) in fecal samples. OTU names are prefixed by letters indicating phyla classifications of the OTUs: A: Actinobacteria, B: Bacteroidetes, F: Firmicutes, P: Proteobacteria; T: TM7. Asterisks depict p-values for correlations: *: p<0.1; **: p<0.05; ***p<0.001. Blue shading indicates positive correlations, while red shading indicates negative correlations. OTUs that could not be classified to the genus level are labeled by adding “other” to the higher-order taxonomic assignment.
© Copyright Policy
Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC4493139&req=5

pone.0131944.g005: Principal components analysis of fecal microbiomes.PCA was carried out on genus-level microbiome datasets, as described in the text. PC1, PC2, and PC3 accounted for 35.3%, 26.8%, and 15.7% of the total variance in the dataset (77.8% cumulative proportion). Microbiomes from individual fecal samples, color-coded by genotype and diet, are plotted along the first three PC axes in Panels A, C, and D. Panel B displays the same plot as Panel A, but with arrows connecting pairs of samples from the same animals on different diets. Panel E displays a heat-map color-coding Spearman correlation coefficients between PC scores and the abundances of prevalent OTUs (abundances >1%) in fecal samples. OTU names are prefixed by letters indicating phyla classifications of the OTUs: A: Actinobacteria, B: Bacteroidetes, F: Firmicutes, P: Proteobacteria; T: TM7. Asterisks depict p-values for correlations: *: p<0.1; **: p<0.05; ***p<0.001. Blue shading indicates positive correlations, while red shading indicates negative correlations. OTUs that could not be classified to the genus level are labeled by adding “other” to the higher-order taxonomic assignment.
Mentions: Data exploration through principal components analysis (PCA) indicated that both diet and genotype affected microbiome structure among the mouse groups (Fig 5; each symbol represents an individual mouse, color-coded by diet and genotype). Qualitatively, the HF diet appeared to have the strongest effects on sample clustering within the PCA plots, compared with the effects of either genotype or LF/chow diets, because all HF samples (regardless of genotype) segregated away from the remainder of the samples along PC1, PC2, and PC3 (lower right quadrants of Fig 5A, 5B and 5C). Indeed, PC1 scores were significantly associated with diet (p = 6.4e-11) and genotype (p = 0.0001), whereas PC2 and PC3 scores were weakly associated with genotype and diet (Fig 5F). Higher PC1 scores, which were associated with a HF diet (Fig 5F), were negatively correlated with the Bacteroidetes family S24-7 and positively correlated with several groups of Firmicutes, Actinobacteria, and Proteobacteria (Fig 5E). Similarly, higher PC3 scores were observed for WT mice, compared with Plin2- mice, and were positively correlated with the genus Bacteroides. Thus, differential shifts in Firmicutes and sub-groups of Bacteroidetes (e.g. S24-7 vs. Bacteroides) resulting from genotype and/or dietary factors help to explain the observed PCA clustering.

Bottom Line: Here we test the hypotheses that Plin2 function impacts the earliest steps of HF diet-mediated pathogenesis as well as the dynamics of diet-associated changes in gut microbiome diversity and function.Plin2- mice had significantly lower respiratory exchange ratios, diminished frequencies of enterocyte CLDs, and increased fecal triglyceride levels compared with WT mice.Microbiome analyses, employing both 16S rRNA profiling and metagenomic deep sequencing, indicated that dietary fat content and Plin2 genotype were significantly and independently associated with gut microbiome composition, diversity, and functional differences.

View Article: PubMed Central - PubMed

Affiliation: Division of Infectious Disease, University of Colorado School of Medicine, Aurora, Colorado, United States of America; Microbiome Research Consortium, University of Colorado School of Medicine, Aurora, Colorado, United States of America.

ABSTRACT
Obesity and its co-morbidities, such as fatty liver disease, are increasingly prevalent worldwide health problems. Intestinal microorganisms have emerged as critical factors linking diet to host physiology and metabolic function, particularly in the context of lipid homeostasis. We previously demonstrated that deletion of the cytoplasmic lipid drop (CLD) protein Perilipin-2 (Plin2) in mice largely abrogates long-term deleterious effects of a high fat (HF) diet. Here we test the hypotheses that Plin2 function impacts the earliest steps of HF diet-mediated pathogenesis as well as the dynamics of diet-associated changes in gut microbiome diversity and function. WT and perilipin-2 mice raised on a standard chow diet were randomized to either low fat (LF) or HF diets. After four days, animals were assessed for changes in physiological (body weight, energy balance, and fecal triglyceride levels), histochemical (enterocyte CLD content), and fecal microbiome parameters. Plin2- mice had significantly lower respiratory exchange ratios, diminished frequencies of enterocyte CLDs, and increased fecal triglyceride levels compared with WT mice. Microbiome analyses, employing both 16S rRNA profiling and metagenomic deep sequencing, indicated that dietary fat content and Plin2 genotype were significantly and independently associated with gut microbiome composition, diversity, and functional differences. These data demonstrate that Plin2 modulates rapid effects of diet on fecal lipid levels, enterocyte CLD contents, and fuel utilization properties of mice that correlate with structural and functional differences in their gut microbial communities. Collectively, the data provide evidence of Plin2 regulated intestinal lipid uptake, which contributes to rapid changes in the gut microbial communities implicated in diet-induced obesity.

No MeSH data available.


Related in: MedlinePlus