Abstract
The composition of the gastrointestinal microorganisms in poultry is closely associated with the host and its environment. In this study, using 16S rRNA and metagenomic techniques, we comprehensively analyzed the structure and diversity of the cecal microbiota of broiler chickens (BC) and laying hens (LH). The 16S rRNA sequencing analysis showed Firmicutes, Bacteroidetes, and Proteobacteria were the main cecal bacterial phyla in BC and LH. However, at the genus level, LH had a greater abundance of Bacteroides (P < 0.05), Rikenellaceae_RC9_gut_group (P < 0.01), Phascolarctobacterium (P < 0.05), Desulfovibrio (P < 0.05), Prevotellaceae_UCG-001 (P < 0.05), and unclassified_o_Bacteroidales (P < 0.05), whereas BC had a greater abundance of Alistipes (P < 0.05), Rikenella (P < 0.05), Ruminococcaceae_UCG-005 (P < 0.05), Lachnoclostridium (P < 0.05), and unclassified_f_Ruminococcaceae (P < 0.05). It is particularly noteworthy that the genus Desulfovibrio was significantly more abundant in the LH cecum than in the BC cecum (P < 0.05). A metagenomic analysis showed that the annotations in the LH dataset were significantly more abundant than in the BC dataset, and included replication, recombination and repair, energy production and transformation, cell wall/membrane/envelope biogenesis, and amino acid transport and metabolism-related functions (P < 0.05). This study indicates that microbial genotypic differences in chickens of the same species can cause changes in the abundances of the gut microbiota, but do not alter the structural composition or major functional characteristics of the gut microbiota.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Altschul SF, Madden TL, Schaffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 25(17):3389–3402. https://doi.org/10.1093/nar/25.17.3389
Carlsson AH, Yakymenko O, Olivier I, Hakansson F, Postma E, Keita AV, Soderholm JD (2013) Faecalibacterium prausnitzii supernatant improves intestinal barrier function in mice DSS colitis. Scand J Gastroenterol 48(10):1136–1144
Chambers JR, Gong J (2011) The intestinal microbiota and its modulation for Salmonella control in chickens. Food Res Int 44(10):3149–3159
Chang Q, Luan Y, Sun F (2011) Variance adjusted weighted UniFrac: a powerful beta diversity measure for comparing communities based on phylogeny. Bmc Bioinform 12(118):1–14. https://doi.org/10.1186/1471-2105-12-118
Clavijo V, Vives Florez MJ (2018) Non-invited review the gastrointestinal microbiome and its association with the control of pathogens in broiler chicken production: a review. Poult Sci 97(3):1006–1021
Cui Y, Wang Q, Liu S, Sun R, Zhou Y, Li Y (2017) Age-related variations in intestinal microflora of free-range and caged hens. Front Microbiol 8(1310):1–10. https://doi.org/10.3389/fmicb.2017.01310
De Vadder F, Kovatcheva-Datchary P, Zitoun C, Duchampt A, Backhed F, Mithieux G (2016) Microbiota-produced succinate improves glucose homeostasis via intestinal gluconeogenesis. Cell Metab 24(1):151–157
DeSantis TZ, Hugenholtz P, Larsen N, Rojas M, Brodie EL, Keller K, Huber T, Dalevi D, Hu P, Andersen GL (2006) Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl Environ Microbiol 72(7):5069–5072. https://doi.org/10.1128/aem.03006-05
Edgar RC (2010) Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26(19):2460–2461. https://doi.org/10.1093/bioinformatics/btq461
Eren AM, Vineis JH, Morrison HG, Sogin ML (2013) A filtering method to generate high quality short reads using illumina paired-end technology. Plos One 8(6):e66643. https://doi.org/10.1371/journal.pone.0066643
Faith DP, Baker AM (2006) Phylogenetic diversity (PD) and biodiversity conservation: some bioinformatics challenges. Evolutionary Bioinform 2:121–128
Fu L, Niu B, Zhu Z, Wu S, Li W (2012) CD-HIT: accelerated for clustering the next-generation sequencing data. Bioinformatics 28(23):3150–3152. https://doi.org/10.1093/bioinformatics/bts565
Garcia-Mazcorro JF, Dowd SE, Poulsen J, Steiner JM, Suchodolski JS (2012) Abundance and short-term temporal variability of fecal microbiota in healthy dogs. Microbiologyopen 1(3):340–347
Hufeldt MR, Nielsen DS, Vogensen FK, Midtvedt T, Hansen AK (2010) Variation in the Gut microbiota of laboratory mice is related to both genetic and environmental factors. Comp Med 60(5):336–342
Jensen LJ, Julien P, Kuhn M, von Mering C, Muller J, Doerks T, Bork P (2008) eggNOG: automated construction and annotation of orthologous groups of genes. Nucleic Acids Res 36:D250–D254. https://doi.org/10.1093/nar/gkm796
Li J, Sung CYJ, Lee N, Ni Y, Pihlajamaki J, Panagiotou G, El-Nezami H (2016) Probiotics modulated gut microbiota suppresses hepatocellular carcinoma growth in mice. Proc Natl Acad Sci USA 113(9):E1306–E1315
Macfarlane S, Macfarlane GT (2003) Regulation of short-chain fatty acid production. Proc Nutr Soc 62(1):67–72
Mancabelli L, Ferrario C, Milani C, Mangifesta M, Turroni F, Duranti S, Lugli GA, Viappiani A, Ossiprandi MC, van Sinderen D, Ventura M (2016) Insights into the biodiversity of the gut microbiota of broiler chickens. Environ Microbiol 18(12):4727–4738. https://doi.org/10.1111/1462-2920.13363
McDonald D, Price MN, Goodrich J, Nawrocki EP, DeSantis TZ, Probst A, Andersen GL, Knight R, Hugenholtz P (2012) An improved Greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea. ISME J 6(3):610–618. https://doi.org/10.1038/ismej.2011.139
Neufeld JD, Mohn WW (2005) Unexpectedly high bacterial diversity in arctic tundra relative to boreal forest soils, revealed by serial analysis of ribosomal sequence tags. Appl Environ Microbiol 71(10):5710–5718. https://doi.org/10.1128/aem.71.10.5710-5718.2005
Noguchi H, Park J, Takagi T (2006) MetaGene: prokaryotic gene finding from environmental genome shotgun sequences. Nucleic Acids Res 34(19):5623–5630. https://doi.org/10.1093/nar/gkl723
Pan D, Yu Z (2014) Intestinal microbiome of poultry and its interaction with host and diet. Gut Microbes 5(1):108–119
Qin N, Li D, Yang R (2011) Next-generation sequencing technologies and the application in microbiology—a review. Wei Sheng Wu Xue Bao Acta Microbiol Sin 51(4):445–457
Shaufi MAM, Sieo CC, Chong CW, Gan HM, Ho YW (2015) Deciphering chicken gut microbial dynamics based on high-throughput 16S rRNA metagenomics analyses. Gut Pathogens 7(4):1–12. https://doi.org/10.1186/s13099-015-0051-7
Song H, Wang W, Shen B, Jia H, Hou Z, Chen P, Sun Y (2018) Pretreatment with probiotic Bifico ameliorates colitis-associated cancer in mice: transcriptome and gut flora profiling. Cancer Sci 109(3):666–677
Stanley D, Geier MS, Hughes RJ, Denman SE, Moore RJ (2013) Highly variable microbiota development in the chicken gastrointestinal tract. Plos One 8(12):e84290. https://doi.org/10.1371/journal.pone.0084290
van der Wielen P, Keuzenkamp DA, Lipman LJA, van Knapen F, Biesterveld S (2002) Spatial and temporal variation of the intestinal bacterial community in commercially raised broiler chickens during growth. Microb Ecol 44(3):286–293
Wen CL, Yan W, Sun CJ, Ji CL, Zhou QQ, Zhang DX, Zheng JX, Yang N (2019) The gut microbiota is largely independent of host genetics in regulating fat deposition in chickens. ISME J 13(6):1422–1436. https://doi.org/10.1038/s41396-019-0367-2
Wilkinson TJ, Cowan AA, Vallin HE, Onime LA, Oyama LB, Cameron SJ, Gonot C, Moorby JM, Waddams K, Theobald VJ, Leemans D, Bowra S, Nixey C, Huws SA (2017) Characterization of the microbiome along the gastrointestinal tract of growing turkeys. Front Microbiol 8:1–11. https://doi.org/10.3389/fmicb.2017.01089
Xie C, Mao X, Huang J, Ding Y, Wu J, Dong S, Kong L, Gao G, Li C-Y, Wei L (2011) KOBAS 2.0: a web server for annotation and identification of enriched pathways and diseases. Nucleic Acids Res 39:W316–W322. https://doi.org/10.1093/nar/gkr483
Yeoman CJ, Chia N, Jeraldo P, Sipos M, Goldenfeld ND, White BA (2012) The microbiome of the chicken gastrointestinal tract. Anim Health Res Rev 13(1):89–99
Zhao L, Wang G, Siegel P, He C, Wang H, Zhao W, Zhai Z, Tian F, Zhao J, Zhang H, Sun Z, Chen W, Zhang Y, Meng H (2013) Quantitative genetic background of the host influences gut microbiomes in chickens. Sci Rep 3:1163. https://doi.org/10.1038/srep01163
Zhou X, Jiang X, Yang C, Ma B, Lei C, Xu C, Zhang A, Yang X, Xiong Q, Zhang P, Men S, Xiang R, Wang H (2016) Cecal microbiota of tibetan chickens from five geographic regions were determined by 16S rRNA sequencing. Microbiologyopen 5(5):753–762. https://doi.org/10.1002/mbo3.367
Zhu XY, Zhong TY, Pandya Y, Joerger RD (2002) 16S rRNA-based analysis of microbiota from the cecum of broiler chickens. Appl Environ Microbiol 68(1):124–137
Acknowledgements
We thank the National Science Foundation of China (grant no. 31772707) for supporting the high-throughput sequencing. The collection of the experimental samples was supported by the Integration and Demonstration of Quality and Safety Control Technology for Green Ecological Livestock and Poultry Products Industry Chain (grant no. 1604a0702033) and the Animal Food Quality and Safety Control, Anhui Province 115 Industry Innovation Team. We thank International Science Editing (http://www.internationalscienceediting.com) for editing this manuscript.
Author information
Authors and Affiliations
Contributions
SL conceived and designed the experiments; ZQ and SS performed the experiments, and these authors contributed equally to this work; ZQ analyzed the data; SS and JT contributed reagents/materials/analysis tools, SS and ZQ wrote the paper. All authors critically read and contributed to the manuscript and approved the final version.
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflicts of interest.
Ethics approval and consent to participate
This study was performed in accordance with the Chinese Laboratory Animal Administration Act of 1988. Before the experiments, the research protocol was reviewed and approved by the Research Ethics Committee of Anhui Agricultural University. Permission was obtained from all managers of the chicken farms studied before the samples were collected.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Qi, Z., Shi, S., Tu, J. et al. Comparative metagenomic sequencing analysis of cecum microbiotal diversity and function in broilers and layers. 3 Biotech 9, 316 (2019). https://doi.org/10.1007/s13205-019-1834-1
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s13205-019-1834-1