Oral bacteria colonize and compete with gut microbiota in gnotobiotic mice View Full Text


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Article Info

DATE

2019-03

AUTHORS

Bolei Li, Yang Ge, Lei Cheng, Benhua Zeng, Jinzhao Yu, Xian Peng, Jianhua Zhao, Wenxia Li, Biao Ren, Mingyun Li, Hong Wei, Xuedong Zhou

ABSTRACT

The oral microbiota is associated with oral diseases and digestive systemic diseases. Nevertheless, the causal relationship between them has not been completely elucidated, and colonisation of the gut by oral bacteria is not clear due to the limitations of existing research models. The aim of this study was to develop a human oral microbiota-associated (HOMA) mouse model and to investigate the ecological invasion into the gut. By transplanting human saliva into germ-free (GF) mice, a HOMA mouse model was first constructed. 16S rRNA gene sequencing was used to reveal the biogeography of oral bacteria along the cephalocaudal axis of the digestive tract. In the HOMA mice, 84.78% of the detected genus-level taxa were specific to the donor. Principal component analysis (PCA) revealed that the donor oral microbiota clustered with those of the HOMA mice and were distinct from those of specific pathogen-free (SPF) mice. In HOMA mice, OTU counts decreased from the stomach and small intestine to the distal gut. The distal gut was dominated by Streptococcus, Veillonella, Haemophilus, Fusobacterium, Trichococcus and Actinomyces. HOMA mice and human microbiota-associated (HMA) mice along with the GF mice were then cohoused. Microbial communities of cohoused mice clustered together and were significantly separated from those of HOMA mice and HMA mice. The Source Tracker analysis and network analysis revealed more significant ecological invasion from oral bacteria in the small intestines, compared to the distal gut, of cohoused mice. In conclusion, a HOMA mouse model was successfully established. By overcoming the physical and microbial barrier, oral bacteria colonised the gut and profiled the gut microbiota, especially in the small intestine. More... »

PAGES

10

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/s41368-018-0043-9

    DOI

    http://dx.doi.org/10.1038/s41368-018-0043-9

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1112505658

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/30833566


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    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1038/s41368-018-0043-9'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/s41368-018-0043-9'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/s41368-018-0043-9'

    RDF/XML is a standard XML format for linked data.

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/s41368-018-0043-9'


     

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