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  • Poster Presentation
  • P-HAMI-013

Functional bacterial diversity of the digestive tract of chicken

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Poster

Functional bacterial diversity of the digestive tract of chicken

Topic

  • Host-associated microbiomes and microbe-host interactions

Authors

Bibiana Rios-Galicia (Stuttgart / DE), Johan S. Saenz (Stuttgart / DE), Amelia Camarinha-Silva (Stuttgart / DE), Jana Seifert (Stuttgart / DE)

Abstract

The study of intestinal microbial communities complements the knowledge gained through metagenomic studies with cultivation approaches. Although cultivation methods carry a selection bias to microorganisms that adapt better to the culture conditions, sequenced genomes obtained from cultivation play an important role in providing reference material to deeply characterise metagenomic observations. The objective of this work is to estimate the functional diversity along the gastrointestinal tract of chicken considering the prevalence, abundance and functional annotation of the cultured fraction reported so far. To address this, genome assemblies generated from cultivation studies obtained from crop, jejunum, ileum, caeca, and faeces were collected, quality filtered and compared against metagenomic sequences derived from studies on the chicken gastrointestinal tract (GIT). Genes obtained from genome annotation were mapped to estimate abundance of functions along the different GIT regions. Members of Lactobacillaceae dominated the upper regions and this was reflected on the redundancy of isolation. Limosilactobacillus species were found to be more abundant in the crop, while Ligilactobacillus species dominated the small intestine. Species from upper regions encode a high number of glycosidases specialised in complex polysaccharides compared to species found in lower regions (caeca and faeces). Along all regions, genes that encode collagenases and hyaluronidases are equally found, indicating a common adaptation to along the gastrointestinal tract. These results enlighten the microbial ecology of the GIT of chicken through the observation of species and functions distribution.

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