Bamboo Specialists from Two Mammalian Orders (Primates, Carnivora) Share a High Number of Low-Abundance Gut Microbes

  • Erin A. McKenney
  • Michael Maslanka
  • Allen Rodrigo
  • Anne D. Yoder
Host Microbe Interactions

Abstract

Bamboo specialization is one of the most extreme examples of convergent herbivory, yet it is unclear how this specific high-fiber diet might selectively shape the composition of the gut microbiome compared to host phylogeny. To address these questions, we used deep sequencing to investigate the nature and comparative impact of phylogenetic and dietary selection for specific gut microbial membership in three bamboo specialists—the bamboo lemur (Hapalemur griseus, Primates: Lemuridae), giant panda (Ailuropoda melanoleuca, Carnivora: Ursidae), and red panda (Ailurus fulgens, Carnivora: Musteloideadae), as well as two phylogenetic controls—the ringtail lemur (Lemur catta) and the Asian black bear (Ursus thibetanus). We detected significantly higher Shannon diversity in the bamboo lemur (10.029) compared to both the giant panda (8.256; p = 0.0001936) and the red panda (6.484; p = 0.0000029). We also detected significantly enriched bacterial taxa that distinguished each species. Our results complement previous work in finding that phylogeny predominantly governs high-level microbiome community structure. However, we also find that 48 low-abundance OTUs are shared among bamboo specialists, compared to only 8 OTUs shared by the bamboo lemur and its sister species, the ringtail lemur (Lemur catta, a generalist). Our results suggest that deep sequencing is necessary to detect low-abundance bacterial OTUs, which may be specifically adapted to a high-fiber diet. These findings provide a more comprehensive framework for understanding the evolution and ecology of the microbiome as well as the host.

Keywords

Gut microbiome Convergent evolution Feeding strategy Bamboo specialist Host-microbiome relationship 

Notes

Acknowledgements

The authors would like to thank the staff at the Duke Lemur Center, the National Zoological Park, and Ion Torrent for their help and support. We are also especially grateful to Dr. Robert Fleischer and Dr. Scott Langdon for providing lab space and equipment for DNA extraction and sequencing.

Authors’ Contributions

Conceived of and designed the experiments: EAM ADY

Collected samples: EAM MM

Analyzed and interpreted the data: EAM AR

Contributed reagents/materials/analysis tools: EAM AR ADY

Wrote the manuscript: EAM MM AR ADY

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no conflict of interest.

Research Involving Animals

All applicable international, national, and/or institutional guidelines for the care and use of animals were followed. All procedures were reviewed and approved by Duke University IACUC under protocol number A203-11-08.

Supplementary material

248_2017_1114_Fig7_ESM.gif (116 kb)
Figure S1

Rarefaction curves (GIF 116 kb)

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High resolution image (EPS 83 kb)
248_2017_1114_MOESM2_ESM.pdf (25 kb)
Figure S2 Discrepancies in sequencing sample size drive patterns in Principal Coordinate Analysis of jackknifed unweighted UniFrac distance. UniFrac distance integrates the phylogenetic differences between different OTUs based on presence/absence in each gut community. Ion Torrent data was compared with two published data sets. McKenney et al. [5] used the Illumina MiSeq platform to sequence the v4 region in feces collected from three ringtail lemurs (Lemur catta, diverged from the bamboo lemur 11.8 mya [4]). Li et al. [3] compared V1-V3 regions amplified from 6 captive red pandas, 5 giant pandas, and 6 Asian black bears and sequenced using the 454 GS FLX Titanium platform. Each library was subsampled at a depth of 1280 to match the number of sequences in the smallest library (see Table S2). Ellipsoids were calculated using the InterQuartile Range (IQR) method and plotted to visualize the confidence interval for each sample. (PDF 24 kb)
248_2017_1114_MOESM3_ESM.pdf (30 kb)
Figure S3 Boxplot comparison of unweighted UniFrac distance reveals discrepancies between sequencing platforms, as well as phylogenetic effect. UniFrac distance integrates the phylogenetic differences between different OTUs based on presence/absence in each gut community. (PDF 30 kb)
248_2017_1114_Fig8_ESM.gif (39 kb)
Figure S4

Deep sequencing coverage detects rare membership in complex communities and affects UPGMA clustering. Samples sequenced on the Roche 454 platform (denoted by asterisks) cluster separately from samples sequenced on the Ion Torrent and Illumina MiSeq platforms. This discrepancy is likely driven by different data sizes (see Table S2), as limited sampling fails to detect the presence of rare OTUs. However, within this larger clustering effect, the microbiome tree topology appears to recapitulate host phylogenetic relationships as previously demonstrated [25]. Both OTUs and samples have been ordered by UPGMA hierarchical clustering. (GIF 38 kb)

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High resolution image (EPS 137 kb)
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ESM 1

(GIF 128 kb)

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High resolution image (EPS 73 kb)
248_2017_1114_MOESM6_ESM.docx (78 kb)
Table S1 (DOCX 78 kb)
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Table S2 (DOCX 111 kb)
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Table S3 (DOCX 167 kb)
248_2017_1114_MOESM9_ESM.docx (70 kb)
Table S4 (DOCX 69 kb)
248_2017_1114_MOESM10_ESM.txt (3 kb)
Additional File 1 (TXT 2 kb)

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2017

Authors and Affiliations

  • Erin A. McKenney
    • 1
    • 2
  • Michael Maslanka
    • 3
  • Allen Rodrigo
    • 1
    • 4
  • Anne D. Yoder
    • 1
    • 5
  1. 1.Department of BiologyDuke UniversityDurhamUSA
  2. 2.Department of Applied EcologyNorth Carolina State UniversityRaleighUSA
  3. 3.Smithsonian National Zoological Park and Conservation Biology InstituteWashingtonUSA
  4. 4.Australia National UniversityCanberraAustralia
  5. 5.Duke Lemur CenterDuke UniversityDurhamUSA

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