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. 2016 May 16:6:26035.
doi: 10.1038/srep26035.

Marked variation between winter and spring gut microbiota in free-ranging Tibetan Macaques (Macaca thibetana)

Binghua Sun  1 , Xi Wang  1 , Sofi Bernstein  2 , Michael A Huffman  2 , Dong-Po Xia  3 , Zhiyuan Gu  1 , Rui Chen  1 , Lori K Sheeran  4 , R S Wagner  5 , Jinhua Li  1   6
Affiliations

Marked variation between winter and spring gut microbiota in free-ranging Tibetan Macaques (Macaca thibetana)

Binghua Sun et al. Sci Rep. .

Abstract

Variation in the availability and distribution of food resources is a strong selective pressure on wild primates. We explored variation in Tibetan macaque gut microbiota composition during winter and spring seasons. Our results showed that gut microbial composition and diversity varied by season. In winter, the genus Succinivibrio, which promotes the digestion of cellulose and hemicellulose, was significantly increased. In spring, the abundance of the genus Prevotella, which is associated with digestion of carbohydrates and simple sugars, was significantly increased. PICRUSt analysis revealed that the predicted metagenomes related to the glycan biosynthesis and metabolic pathway was significantly increased in winter samples, which would aid in the digestion of glycan extracted from cellulose and hemicellulose. The predicted metagenomes related to carbohydrate and energy metabolic pathways were significantly increased in spring samples, which could facilitate a monkey's recovery from acute energy loss experienced during winter. We propose that shifts in the composition and function of the gut microbiota provide a buffer against seasonal fluctuations in energy and nutrient intake, thus enabling these primates to adapt to variations in food supply and quality.

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Conflict of interest statement

The authors declare no competing financial interests.

Figures

Figure 1
Figure 1. Relative abundance of gut bacterial taxa at the phylum-level.
Stacked bar graphs illustrate the abundances of phyla.
Figure 2
Figure 2. Gut microbiota structure differentiation and inter-individual similarity.
PCoA was used to show patterns of separation by season, Yellow: spring sample; green, winter sample; (a) based on unweighted UniFrac distance (Permanova, P < 0.05), (b) based on weighted UniFrac distance (Permanova, P < 0.01). Permutation test was used to test inter-individual similarity; Yellow box (winter vs winter, WW); green box (spring vs spring, SS); (c) based on unweighted UniFrac distance (WW vs SS, permutations = 999, P < 0.001); (d) based on weighted UniFrac distance (WW vs SS, permutations = 999, P < 0.0001).
Figure 3
Figure 3. Phylum and genus differentially represented between winter and spring samples identified by linear discriminant analysis coupled with effect size (LEfSe) (LDA > 2, P < 0.05).
Red box: enriched in spring samples, green box: enriched in winter samples. (a) based on the relative abundance of phylum; (b) based on the relative abundance of genus.
Figure 4
Figure 4. Relative abundance of the predicted gene of metagenome related to KEGG pathways at level 1 and 2; orange box: winter samples, green box: spring samples.
The terms given on the left are KEGG pathways annotation at level 1 and level 2 (from left to right). **Enriched in winter samples (LDA > 2, P < 0.05); *enriched in spring samples (LDA > 2, P < 0.05).
Figure 5
Figure 5. Predicted genes from metagenome related to KEGG pathways differentially represented between the winter and spring samples identified by linear discriminant analysis coupled with effect size (LEfSe) (LDA > 2, P < 0.05).
Red box: enriched in spring samples, green box: enriched in winter samples.
See this image and copyright information in PMC

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