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Deciphering chicken gut microbial dynamics based on high-throughput 16S rRNA metagenomics analyses
BACKGROUND: Chicken gut microbiota has paramount roles in host performance, health and immunity. Understanding the topological difference in gut microbial community composition is crucial to provide knowledge on the functions of each members of microbiota to the physiological maintenance of the host...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4372169/ https://www.ncbi.nlm.nih.gov/pubmed/25806087 http://dx.doi.org/10.1186/s13099-015-0051-7 |
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author | Mohd Shaufi, Mohd Asrore Sieo, Chin Chin Chong, Chun Wie Gan, Han Ming Ho, Yin Wan |
author_facet | Mohd Shaufi, Mohd Asrore Sieo, Chin Chin Chong, Chun Wie Gan, Han Ming Ho, Yin Wan |
author_sort | Mohd Shaufi, Mohd Asrore |
collection | PubMed |
description | BACKGROUND: Chicken gut microbiota has paramount roles in host performance, health and immunity. Understanding the topological difference in gut microbial community composition is crucial to provide knowledge on the functions of each members of microbiota to the physiological maintenance of the host. The gut microbiota profiling of the chicken was commonly performed previously using culture-dependent and early culture-independent methods which had limited coverage and accuracy. Advances in technology based on next-generation sequencing (NGS), offers unparalleled coverage and depth in determining microbial gut dynamics. Thus, the aim of this study was to investigate the ileal and caecal microbiota development as chicken aged, which is important for future effective gut modulation. MATERIAL AND METHODS: Ileal and caecal contents of broiler chicken were extracted from 7, 14, 21 and 42-day old chicken. Genomic DNA was then extracted and amplified based on V3 hyper-variable region of 16S rRNA. Bioinformatics, ecological and statistical analyses such as Principal Coordinate Analysis (PCoA) was performed in mothur software and plotted using PRIMER 6. Additional analyses for predicted metagenomes were performed through PICRUSt and STAMP software package based on Greengenes databases. RESULTS: A distinctive difference in bacterial communities was observed between ilea and caeca as the chicken aged (P < 0.001). The microbial communities in the caeca were more diverse in comparison to the ilea communities. The potentially pathogenic bacteria such as Clostridium were elevated as the chicken aged and the population of beneficial microbe such as Lactobacillus was low at all intervals. On the other hand, based on predicted metagenomes analysed, clear distinction in functions and roles of gut microbiota such as gene pathways related to nutrient absorption (e.g. sugar and amino acid metabolism), and bacterial proliferation and colonization (e.g. bacterial motility proteins, two-component system and bacterial secretion system) were observed between ilea and caeca, respectively (P < 0.05). CONCLUSIONS: The caeca microbial communities were more diverse in comparison to ilea. The main functional differences between the two sites were found to be related to nutrient absorption and bacterial colonization. Based on the composition of the microbial community, future gut modulation with beneficial bacteria such as probiotics may benefit the host. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13099-015-0051-7) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4372169 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-43721692015-03-25 Deciphering chicken gut microbial dynamics based on high-throughput 16S rRNA metagenomics analyses Mohd Shaufi, Mohd Asrore Sieo, Chin Chin Chong, Chun Wie Gan, Han Ming Ho, Yin Wan Gut Pathog Research BACKGROUND: Chicken gut microbiota has paramount roles in host performance, health and immunity. Understanding the topological difference in gut microbial community composition is crucial to provide knowledge on the functions of each members of microbiota to the physiological maintenance of the host. The gut microbiota profiling of the chicken was commonly performed previously using culture-dependent and early culture-independent methods which had limited coverage and accuracy. Advances in technology based on next-generation sequencing (NGS), offers unparalleled coverage and depth in determining microbial gut dynamics. Thus, the aim of this study was to investigate the ileal and caecal microbiota development as chicken aged, which is important for future effective gut modulation. MATERIAL AND METHODS: Ileal and caecal contents of broiler chicken were extracted from 7, 14, 21 and 42-day old chicken. Genomic DNA was then extracted and amplified based on V3 hyper-variable region of 16S rRNA. Bioinformatics, ecological and statistical analyses such as Principal Coordinate Analysis (PCoA) was performed in mothur software and plotted using PRIMER 6. Additional analyses for predicted metagenomes were performed through PICRUSt and STAMP software package based on Greengenes databases. RESULTS: A distinctive difference in bacterial communities was observed between ilea and caeca as the chicken aged (P < 0.001). The microbial communities in the caeca were more diverse in comparison to the ilea communities. The potentially pathogenic bacteria such as Clostridium were elevated as the chicken aged and the population of beneficial microbe such as Lactobacillus was low at all intervals. On the other hand, based on predicted metagenomes analysed, clear distinction in functions and roles of gut microbiota such as gene pathways related to nutrient absorption (e.g. sugar and amino acid metabolism), and bacterial proliferation and colonization (e.g. bacterial motility proteins, two-component system and bacterial secretion system) were observed between ilea and caeca, respectively (P < 0.05). CONCLUSIONS: The caeca microbial communities were more diverse in comparison to ilea. The main functional differences between the two sites were found to be related to nutrient absorption and bacterial colonization. Based on the composition of the microbial community, future gut modulation with beneficial bacteria such as probiotics may benefit the host. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13099-015-0051-7) contains supplementary material, which is available to authorized users. BioMed Central 2015-02-26 /pmc/articles/PMC4372169/ /pubmed/25806087 http://dx.doi.org/10.1186/s13099-015-0051-7 Text en © Mohd Shaufi et al.; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Mohd Shaufi, Mohd Asrore Sieo, Chin Chin Chong, Chun Wie Gan, Han Ming Ho, Yin Wan Deciphering chicken gut microbial dynamics based on high-throughput 16S rRNA metagenomics analyses |
title | Deciphering chicken gut microbial dynamics based on high-throughput 16S rRNA metagenomics analyses |
title_full | Deciphering chicken gut microbial dynamics based on high-throughput 16S rRNA metagenomics analyses |
title_fullStr | Deciphering chicken gut microbial dynamics based on high-throughput 16S rRNA metagenomics analyses |
title_full_unstemmed | Deciphering chicken gut microbial dynamics based on high-throughput 16S rRNA metagenomics analyses |
title_short | Deciphering chicken gut microbial dynamics based on high-throughput 16S rRNA metagenomics analyses |
title_sort | deciphering chicken gut microbial dynamics based on high-throughput 16s rrna metagenomics analyses |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4372169/ https://www.ncbi.nlm.nih.gov/pubmed/25806087 http://dx.doi.org/10.1186/s13099-015-0051-7 |
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