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. 2014 Mar 26;9(3):e92193.
doi: 10.1371/journal.pone.0092193. eCollection 2014.

Exercise prevents weight gain and alters the gut microbiota in a mouse model of high fat diet-induced obesity

Christian C Evans  1 , Kathy J LePard  2 , Jeff W Kwak  3 , Mary C Stancukas  3 , Samantha Laskowski  4 , Joseph Dougherty  5 , Laura Moulton  3 , Adam Glawe  3 , Yunwei Wang  6 , Vanessa Leone  6 , Dionysios A Antonopoulos  7 , Dan Smith  7 , Eugene B Chang  6 , Mae J Ciancio  3
Affiliations

Exercise prevents weight gain and alters the gut microbiota in a mouse model of high fat diet-induced obesity

Christian C Evans et al. PLoS One. .

Abstract

Background: Diet-induced obesity (DIO) is a significant health concern which has been linked to structural and functional changes in the gut microbiota. Exercise (Ex) is effective in preventing obesity, but whether Ex alters the gut microbiota during development with high fat (HF) feeding is unknown.

Objective: Determine the effects of voluntary Ex on the gastrointestinal microbiota in LF-fed mice and in HF-DIO.

Methods: Male C57BL/6 littermates (5 weeks) were distributed equally into 4 groups: low fat (LF) sedentary (Sed) LF/Sed, LF/Ex, HF/Sed and HF/Ex. Mice were individually housed and LF/Ex and HF/Ex cages were equipped with a wheel and odometer to record Ex. Fecal samples were collected at baseline, 6 weeks and 12 weeks and used for bacterial DNA isolation. DNA was subjected both to quantitative PCR using primers specific to the 16S rRNA encoding genes for Bacteroidetes and Firmicutes and to sequencing for lower taxonomic identification using the Illumina MiSeq platform. Data were analyzed using a one or two-way ANOVA or Pearson correlation.

Results: HF diet resulted in significantly greater body weight and adiposity as well as decreased glucose tolerance that were prevented by voluntary Ex (p<0.05). Visualization of Unifrac distance data with principal coordinates analysis indicated clustering by both diet and Ex at week 12. Sequencing demonstrated Ex-induced changes in the percentage of major bacterial phyla at 12 weeks. A correlation between total Ex distance and the ΔCt Bacteroidetes: ΔCt Firmicutes ratio from qPCR demonstrated a significant inverse correlation (r2 = 0.35, p = 0.043).

Conclusion: Ex induces a unique shift in the gut microbiota that is different from dietary effects. Microbiota changes may play a role in Ex prevention of HF-DIO.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Exercise, Body Weight and Glucose Tolerance.
A. Weekly exercise was recorded for low fat/exercise (LF/Ex) and high fat/exercise (HF/Ex) mice. B. Weekly body weight starting at week 0 of the diet and activity protocol (age  = 5 weeks) through week 12 (age  = 17 weeks) was recorded. C. Oral glucose tolerance was tested at week 12 of the diet and activity protocol. D. The area under the curve (AUC) was calculated for oral glucose tolerance. Data are presented as mean ± SEM. Groups are abbreviated as follows: low-fat/sedentary (LF/Sed), low-fat/exercise (LF/Ex), high-fat/sedentary (HF/Sed) and high-fat/exercise (HF/Ex). Data were analyzed by 2-way ANOVA with a Sidak post hoc test. Significant differences indicated as follows: “*” p<0.05 for diet effect, “†” p<0.05 activity effect and “‡” p<0.05 diet and activity interaction. n = 6 mice/group.
Figure 2
Figure 2. Clustering of Samples Based on Litter, Diet and Activity.
Principal coordinate analysis (PCA) was performed based on the weighted UniFrac distance matrix generated from sequencing fecal 16S rRNA gene in samples from mice at week 0 and 12 of the diet and activity protocol. A. Clustering demonstrated by litter at week 0. B. No clustering demonstrated by litter at week 12. C. No clustering demonstrated by diet and activity at week 0. D. Clustering demonstrated by diet and activity at week 12. The top panels show the PCA keyed by litter (6 liters, 1–6, of 4 mice each) and the bottom panels show the PCA keyed by diet and activity group. The X-axis represents the primary coordinate, the Y-axis represents the secondary coordinate. Axis numbering represents the relative distance between samples based on the weighted UniFrac distance matrix.
Figure 3
Figure 3. Beta Diversity is Elevated by HF Diet and Exercise.
Significant differences indicated as follows: “*” p<0.05 for diet effect, “†” p<0.05 activity effect and “‡” p<0.05 diet and activity interaction. n = 6 mice/group.
Figure 4
Figure 4. Phylum Level Changes with Diet and Activity.
At week 12, diet and activity changed the levels of two major and two minor phyla of bacteria. Data were analyzed by 2-way ANOVA with a Sidak post hoc test. Significant differences indicated as follows: “*” p<0.05 for diet effect, “†” p<0.05 activity effect and “‡” p<0.05 diet and activity interaction. n = 6 mice/group.
Figure 5
Figure 5. Diet and Activity Altered the Relative Level of Bacteroidetes and Firmicutes.
A. The fold change in Bacteroidetes and Firmicutes was determined from the 2−ΔΔCt values calculated from the ΔCt values generated by quantitative polymerase chain reaction (qPCR) using primers specific to each phyla (one-way ANOVA). B. Criterion validity of qPCR was examined by correlating the ΔCt-Bacteroidetes: ΔCt-Firmicutes ratio with the %-Bacteroidetes: %- Firmicutes ratios from sequencing. Data was analyzed by Pearson product-moment correlation coefficient and alpha level of p<0.05.
Figure 6
Figure 6. ΔCt Bacteroidetes: ΔCt Firmicutes Ratio Correlates with Exercise Distance.
There was a significant, but modest inverse relationship between the ΔCt Bacteroidetes: ΔCt Firmicutes ratio and the distance recorded for the combined LF/Ex and HF/Ex mice. Data analyzed by Pearson product-moment correlation coefficient with an alpha level of p<0.05. n = 6 all groups.
Figure 7
Figure 7. Diet and Activity Altered Firmicutes at the Family Level.
Family level changes within the Firmicutes phyla were identified from sequencing the 16S rRNA gene from samples at week 12 of the diet and activity protocol. A. Three members of the Clostridia class were altered by the diet and activity protocol: Clostridiaceae, Lachnospiraceae, and Ruminococcaceae. B. Two members of the Bacilli class were altered by the diet and activity protocol: Lactobacillaceae and Turicibacteraceae. C. One family was altered within the Erysipelotrichi class by diet and activity: Erysipelotrichaceae. Data were analyzed by 2-way ANOVA with a Sidak post hoc test. Significant differences indicated as follows: “*” p<0.05 for diet effect, “†” p<0.05 activity effect and “‡” p<0.05 diet and activity interaction. n = 6 mice/group.
Figure 8
Figure 8. Diet and Activity Altered Families within the Bacteroidetes, Actinobacteria and Proteobacteria Phyla.
Family level taxonomic groups were identified from sequencing 16S rDNA at week 12 of the diet and activity protocol. A. Within the phylum Bacteroidetes, the class Bacteroidia had one family that was altered by diet and activity: S24-7. B. Within the Actinobacteria phylum and class, one family was altered by diet and activity: Bifidobacteriaceae. C. Within the Proteobacteria phylum, the class Deltaproteobacteria had one family that demonstrated a trend toward an effect of diet and activity: Desulfovibrionaceae. Data were analyzed by 2-way ANOVA with a Sidak post hoc test. Significant differences indicated as follows: “*” p<0.05 for diet effect, “†” p<0.05 activity effect and “‡” p<0.05 diet and activity interaction. n = 6 mice/group.
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References

    1. Flegal KM, Carroll MD, Kit BK, Ogden CL (2012) Prevalence of obesity and trends in the distribution of body mass index among US adults, 1999–2010. JAMA 307: 491–497. - PubMed
    1. Ogden CL, Carroll MD, Kit BK, Flegal KM (2012) Prevalence of obesity and trends in body mass index among US children and adolescents, 1999–2010. JAMA 307: 483–490. - PMC - PubMed
    1. Eeg-Olofsson K, Cederholm J, Nilsson P, Zethelius B, Nunez L, et al. (2009) Risk of cardiovascular disease and mortality in overweight and obese patients with type 2 diabetes: an observational study in 13,087 patients. Diabetologia 52: 65–73. - PubMed
    1. Finkelstein EA, Trogdon JG, Cohen JW, Dietz W (2009) Annual medical spending attributable to obesity: payer-and service-specific estimates. Health Aff (Milwood) 28: w822–w831. - PubMed
    1. Wright JD, Borrud LG, McDowell MA, Wang C-Y, Radimer K, et al. (2007) Nutrition assessment in the national health and nutrition examination survey 1999–2002. J Am Diet Assoc 107: 822–829. - PubMed

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