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      The Bamboo-Eating Giant Panda Harbors a Carnivore-Like Gut Microbiota, with Excessive Seasonal Variations

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          ABSTRACT

          The giant panda evolved from omnivorous bears. It lives on a bamboo-dominated diet at present, but it still retains a typical carnivorous digestive system and is genetically deficient in cellulose-digesting enzymes. To find out whether this endangered mammalian species, like other herbivores, has successfully developed a gut microbiota adapted to its fiber-rich diet, we conducted a 16S rRNA gene-based large-scale structural profiling of the giant panda fecal microbiota. Forty-five captive individuals were sampled in spring, summer, and late autumn within 1 year. Significant intraindividual variations in the diversity and structure of gut microbiota across seasons were observed in this population, which were even greater than the variations between individuals. Compared with published data sets involving 124 gut microbiota profiles from 54 mammalian species, these giant pandas, together with 9 captive and 7 wild individuals investigated previously, showed extremely low gut microbiota diversity and an overall structure that diverged from those of nonpanda herbivores but converged with those of carnivorous and omnivorous bears. The giant panda did not harbor putative cellulose-degrading phylotypes such as Ruminococcaceae and Bacteroides bacteria that are typically enriched in other herbivores, but instead, its microbiota was dominated by Escherichia/ Shigella and Streptococcus bacteria. Members of the class Clostridia were common and abundant in the giant panda gut microbiota, but most of the members present were absent in other herbivores and were not phylogenetically related with known cellulolytic lineages. Therefore, the giant panda appears not to have evolved a gut microbiota compatible with its newly adopted diet, which may adversely influence the coevolutionary fitness of this herbivore.

          IMPORTANCE

          The giant panda, an endangered mammalian species endemic to western China, is well known for its unique bamboo diet. Unlike other herbivores that have successfully evolved anatomically specialized digestive systems to efficiently deconstruct fibrous plant matter, the giant panda still retains a gastrointestinal tract typical of carnivores. We characterized the fecal bacterial communities from a giant panda population to determine whether this animal relies on its symbiotic gut microbiota to cope with the complex carbohydrates that dominate its diet, as is common in other herbivores. We found that the giant panda gut microbiota is low in diversity and highly variable across seasons. It also shows an overall composition typical of bears and entirely differentiated from other herbivores, with low levels of putative cellulose-digesting bacteria. The gut microbiota of this herbivore, therefore, may not have well adapted to its highly fibrous diet, suggesting a potential link with its poor digestive efficiency.

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          Most cited references23

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          Fast UniFrac: Facilitating high-throughput phylogenetic analyses of microbial communities including analysis of pyrosequencing and PhyloChip data

          Next-generation sequencing techniques, and PhyloChip, have made simultaneous phylogenetic analyses of hundreds of microbial communities possible. Insight into community structure has been limited by the inability to integrate and visualize such vast datasets. Fast UniFrac overcomes these issues, allowing integration of larger numbers of sequences and samples into a single analysis. Its new array-based implementation offers orders of magnitude improvements over the original version. New 3D visualization of principal coordinates analysis (PCoA) results, with the option to view multiple coordinate axes simultaneously, provides a powerful way to quickly identify patterns that relate vast numbers of microbial communities. We demonstrate the potential of Fast UniFrac using examples from three data types: Sanger-sequencing studies of diverse free-living and animal-associated bacterial assemblages and from the gut of obese humans as they diet, pyrosequencing data integrated from studies of the human hand and gut, and PhyloChip data from a study of citrus pathogens. We show that a Fast UniFrac analysis using a reference tree recaptures patterns that could not be detected without considering phylogenetic relationships and that Fast UniFrac, coupled with BLAST-based sequence assignment, can be used to quickly analyze pyrosequencing runs containing hundreds of thousands of sequences, revealing patterns relating human and gut samples. Finally, we show that the application of Fast UniFrac to PhyloChip data could identify well-defined subcategories associated with infection. Together, these case studies point the way towards a broad range of applications and demonstrate some of the new features of Fast UniFrac.
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            NAST: a multiple sequence alignment server for comparative analysis of 16S rRNA genes

            Microbiologists conducting surveys of bacterial and archaeal diversity often require comparative alignments of thousands of 16S rRNA genes collected from a sample. The computational resources and bioinformatics expertise required to construct such an alignment has inhibited high-throughput analysis. It was hypothesized that an online tool could be developed to efficiently align thousands of 16S rRNA genes via the NAST (Nearest Alignment Space Termination) algorithm for creating multiple sequence alignments (MSA). The tool was implemented with a web-interface at . Each user-submitted sequence is compared with Greengenes' ‘Core Set’, comprising ∼10 000 aligned non-chimeric sequences representative of the currently recognized diversity among bacteria and archaea. User sequences are oriented and paired with their closest match in the Core Set to serve as a template for inserting gap characters. Non-16S data (sequence from vector or surrounding genomic regions) are conveniently removed in the returned alignment. From the resulting MSA, distance matrices can be calculated for diversity estimates and organisms can be classified by taxonomy. The ability to align and categorize large sequence sets using a simple interface has enabled researchers with various experience levels to obtain bacterial and archaeal community profiles.
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              Mitochondrial genomes reveal an explosive radiation of extinct and extant bears near the Miocene-Pliocene boundary

              Background Despite being one of the most studied families within the Carnivora, the phylogenetic relationships among the members of the bear family (Ursidae) have long remained unclear. Widely divergent topologies have been suggested based on various data sets and methods. Results We present a fully resolved phylogeny for ursids based on ten complete mitochondrial genome sequences from all eight living and two recently extinct bear species, the European cave bear (Ursus spelaeus) and the American giant short-faced bear (Arctodus simus). The mitogenomic data yield a well-resolved topology for ursids, with the sloth bear at the basal position within the genus Ursus. The sun bear is the sister taxon to both the American and Asian black bears, and this clade is the sister clade of cave bear, brown bear and polar bear confirming a recent study on bear mitochondrial genomes. Conclusion Sequences from extinct bears represent the third and fourth Pleistocene species for which complete mitochondrial genomes have been sequenced. Moreover, the cave bear specimen demonstrates that mitogenomic studies can be applied to Pleistocene fossils that have not been preserved in permafrost, and therefore have a broad application within ancient DNA research. Molecular dating of the mtDNA divergence times suggests a rapid radiation of bears in both the Old and New Worlds around 5 million years ago, at the Miocene-Pliocene boundary. This coincides with major global changes, such as the Messinian crisis and the first opening of the Bering Strait, and suggests a global influence of such events on species radiations.
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                Author and article information

                Journal
                mBio
                MBio
                mbio
                mbio
                mBio
                mBio
                American Society of Microbiology (1752 N St., N.W., Washington, DC )
                2150-7511
                19 May 2015
                May-Jun 2015
                : 6
                : 3
                : e00022-15
                Affiliations
                [ a ]State Key Laboratory of Microbial Metabolism, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, People’s Republic of China
                [ b ]Sichuan Key Laboratory of Conservation Biology on Endangered Wildlife, Chengdu Research Base of Giant Panda Breeding, Chengdu, People’s Republic of China
                [ c ]Yunnan Institute of Microbiology, Yunnan University, Kunming, People’s Republic of China
                [ d ]Ministry of Education Key Laboratory of Systems Biomedicine, Shanghai Centre for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, People’s Republic of China
                Author notes
                Address correspondence to Xiaoyan Pang, xypang@ 123456sjtu.edu.cn , or Zhihe Zhang, zzh@ 123456panda.org.cn .

                Z.X. and W.Z. contributed equally to this article.

                Editor Jizhong Zhou, University of Oklahoma

                This article is a direct contribution from a Fellow of the American Academy of Microbiology.

                Article
                mBio00022-15
                10.1128/mBio.00022-15
                4442137
                25991678
                bbbdf028-dc11-4af6-b933-6594323d5648
                Copyright © 2015 Xue et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-ShareAlike 3.0 Unported license, which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 8 January 2015
                : 31 March 2015
                Page count
                supplementary-material: 9, Figures: 5, Tables: 0, Equations: 0, References: 71, Pages: 12, Words: 11007
                Categories
                Research Article
                Custom metadata
                May/June 2015

                Life sciences
                Life sciences

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