Abstract
Introduction
The fecal microbiota are relevant to the health and disease of many species. The importance of the fecal metabolome has more recently been appreciated, but our knowledge of the microbiota and metabolome at other sites along the gastrointestinal tract remains deficient.
Objective
To analyze the gastrointestinal microbiota and metabolome of healthy domestic dogs at four anatomical sites.
Methods
Samples of the duodenal, ileal, colonic, and rectal contents were collected from six adult dogs after humane euthanasia for an unrelated study. The microbiota were characterized using Illumina sequencing of 16S rRNA genes. The metabolome was characterized by mass spectrometry-based methods.
Results
Prevalent phyla throughout the samples were Proteobacteria, Firmicutes, Fusobacteria, and Bacteroidetes, consistent with previous findings in dogs and other species. A total of 530 unique metabolites were detected; 199 of these were identified as previously named compounds, but 141 of them had at least one significantly different site-pair comparison. Noteworthy examples include relative concentrations of amino acids, which decreased from the small to large intestine; pyruvate, which peaked in the ileum; and several phenol-containing carboxylic acid compounds that increased in the large intestine.
Conclusion
The microbiota and metabolome vary significantly at different sites along the canine gastrointestinal tract.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Annegers, J. H. (1969). Intestinal absorption of amino acids in the dog. American Journal of Physiology, 216(1), 1–4.
Broer, S. (2008). Amino acid transport across mammalian intestinal and renal epithelia. Physiological Reviews, 88(1), 249–286. doi:10.1152/physrev.00018.2006.
Caporaso, J. G., Bittinger, K., Bushman, F. D., DeSantis, T. Z., Andersen, G. L., & Knight, R. (2010). PyNAST: A flexible tool for aligning sequences to a template alignment. Bioinformatics (Oxford, England), 26(2), 266–267. doi:10.1093/bioinformatics/btp636.
Caporaso, J. G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F. D., Costello, E. K., et al. (2010). QIIME allows analysis of high-throughput community sequencing data. Nature methods, 7(5), 335–336. doi:10.1038/nmeth.f.303.
Cho, I., & Blaser, M. J. (2012). The human microbiome: At the interface of health and disease. Nature Reviews Genetics, 13(4), 260–270. doi:10.1038/nrg3182.
Cullender, T. C., Chassaing, B., Janzon, A., Kumar, K., Muller, C. E., Werner, J. J., et al. (2013). Innate and adaptive immunity interact to quench microbiome flagellar motility in the gut. Cell Host & Microbe, 14(5), 571–581. doi:10.1016/j.chom.2013.10.009.
DeSantis, T. Z., Hugenholtz, P., Larsen, N., Rojas, M., Brodie, E. L., Keller, K., et al. (2006). Greengenes, a chimera-checked 16 S rRNA gene database and workbench compatible with ARB. Applied and environmental microbiology, 72(7), 5069–5072. doi:10.1128/AEM.03006-05.
Di Cagno, R., De Angelis, M., De Pasquale, I., Ndagijimana, M., Vernocchi, P., Ricciuti, P., et al (2011). Duodenal and faecal microbiota of celiac children: molecular, phenotype and metabolome characterization. BMC Microbiology, 11, 219. doi:10.1186/1471-2180-11-219.
Edgar, R. C. (2010). Search and clustering orders of magnitude faster than BLAST. Bioinformatics (Oxford, England), 26(19), 2460–2461. doi:10.1093/bioinformatics/btq461.
Fiehn, O., Wohlgemuth, G., Scholz, M., Kind, T., Lee, D. Y., Lu, Y., et al. (2008). Quality control for plant metabolomics: Reporting MSI-compliant studies. The Plant journal: for cell and molecular biology, 53(4), 691–704. doi:10.1111/j.1365-313X.2007.03387.x.
Flint, H. J., Scott, K. P., Duncan, S. H., Louis, P., & Forano, E. (2012). Microbial degradation of complex carbohydrates in the gut. Gut Microbes, 3(4), 289–306. doi:10.4161/gmic.19897.
Garsin, D. A. (2012). Ethanolamine: A signal to commence a host-associated lifestyle?.MBio, 3(4), e00172–e00112. doi:10.1128/mBio.00172-12.
Haiko, J., & Westerlund-Wikstrom, B. (2013). The role of the bacterial flagellum in adhesion and virulence. Biology (Basel), 2(4), 1242–1267. doi:10.3390/biology2041242.
Hill, M. J. (1997). Intestinal flora and endogenous vitamin synthesis. Eur J Cancer Prev, 6(Suppl 1), S43–45.
Honneffer, J. B., Minamoto, Y., & Suchodolski, J. S. (2014). Microbiota alterations in acute and chronic gastrointestinal inflammation of cats and dogs. World journal of gastroenterology: WJG, 20(44), 16489–16497. doi:10.3748/wjg.v20.i44.16489.
Hooda, S., Minamoto, Y., Suchodolski, J. S., & Swanson, K. S. (2012). Current state of knowledge: The canine gastrointestinal microbiome. Animal health research reviews/Conference of Research Workers in Animal Diseases, 13(1), 78–88. doi:10.1017/S1466252312000059.
Ismail, A. S., Valastyan, J. S., & Bassler, B. L. (2016). A host-produced autoinducer-2 mimic activates bacterial quorum sensing. Cell Host & Microbe, 19(4), 470–480. doi:10.1016/j.chom.2016.02.020.
Kanehisa, M., & Goto, S. (2000). KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Research, 28, 27–30.
Kanehisa, M., Sato, Y., Kawashima, M., Furumichi, M., & Tanabe, M. (2016). KEGG as a reference resource for gene and protein annotation. Nucleic acids research, 44(D1), D457–D462. doi:10.1093/nar/gkv1070.
Kil, D. Y., & Swanson, K. S. (2011). Companion animals symposium: Role of microbes in canine and feline health. Journal of Animal Science, 89(5), 1498–1505. doi:10.2527/jas.2010-3498.
Langille, M. G., Zaneveld, J., Caporaso, J. G., McDonald, D., Knights, D., Reyes, J. A., et al. (2013). Predictive functional profiling of microbial communities using 16 S rRNA marker gene sequences. Nature Biotechnology, 31(9), 814–821. doi:10.1038/nbt.2676.
LeBlanc, J. G., Milani, C., de Giori, G. S., Sesma, F., van Sinderen, D., & Ventura, M. (2013). Bacteria as vitamin suppliers to their host: A gut microbiota perspective. Current Opinion in Biotechnology, 24(2), 160–168. doi:10.1016/j.copbio.2012.08.005.
Li, G., Yang, M., Zhou, K., Zhang, L., Tian, L., Lv, S., et al. (2015). Diversity of duodenal and rectal microbiota in biopsy tissues and luminal contents in healthy volunteers. Journal of Microbiology and Biotechnology, 25(7), 1136–1145. doi:10.4014/jmb.1412.12047.
Lin, H., An, Y., Hao, F., Wang, Y., & Tang, H. (2016). Correlations of fecal metabonomic and microbiomic changes induced by high-fat diet in the pre-obesity state. Scientific Reports, 6, 21618. doi:10.1038/srep21618.
Lozupone, C., & Knight, R. (2005). UniFrac: A new phylogenetic method for comparing microbial communities. Applied and environmental microbiology, 71(12), 8228–8235. doi:10.1128/AEM.71.12.8228-8235.2005.
Macfarlane, G. T., & Macfarlane, S. (1997). Human colonic microbiota: Ecology, physiology and metabolic potential of intestinal bacteria. Scandinavian Journal of Gastroenterology, 32(Suppl 222), 3–9. doi:10.1080/00365521.1997.11720708.
Mao, S., Zhang, M., Liu, J., & Zhu, W. (2015). Characterising the bacterial microbiota across the gastrointestinal tracts of dairy cattle: Membership and potential function. Scientific Reports, 5, 16116. doi:10.1038/srep16116.
Marks, J., Debnam, E. S., & Unwin, R. J. (2013). The role of the gastrointestinal tract in phosphate homeostasis in health and chronic kidney disease. Current Opinion in Nephrology and Hypertension, 22(4), 481–487. doi:10.1097/MNH.0b013e3283621310.
McHardy, I. H., Goudarzi, M., Tong, M., Ruegger, P. M., Schwager, E., Weger, J. R., et al. (2013). Integrative analysis of the microbiome and metabolome of the human intestinal mucosal surface reveals exquisite inter-relationships. Microbiome, 1(1), 17. doi:10.1186/2049-2618-1-17.
Mead, G. C. (1971). The amino acid-fermenting clostridia. Journal of General Microbiology, 67(1), 47–56. doi:10.1099/00221287-67-1-47.
Papenfort, K., & Bassler, B. L. (2016). Quorum sensing signal-response systems in gram-negative bacteria. Nature reviews. Microbiology, 14(9), 576–588. doi:10.1038/nrmicro.2016.89.
Paradis, E., Claude, J., & Strimmer, K. (2004). APE: Analyses of phylogenetics and evolution in R language. Bioinformatics (Oxford, England), 20(2), 289–290. doi:10.1093/bioinformatics/btg412.
Pytkowski, B., & Michalowski, J. (1977). Motility- and blood flow-dependent absorption of amino acids in canine small intestine. European journal of clinical investigation, 7(2), 79–86.
Rios, L. Y., Gonthier, M. P., Remesy, C., Mila, I., Lapierre, C., Lazarus, S. A., et al. (2003). Chocolate intake increases urinary excretion of polyphenol-derived phenolic acids in healthy human subjects. The American journal of clinical nutrition, 77(4), 912–918.
Saric, J., Wang, Y., Li, J., Coen, M., Utzinger, J., Marchesi, J. R., et al. (2008). Species variation in the fecal metabolome gives insight into differential gastrointestinal function. Journal of Proteome Research, 7(1), 352–360. doi:10.1021/pr070340k.
Shreiner, A. B., Kao, J. Y., & Young, V. B. (2015). The gut microbiome in health and in disease. Current Opinion in Gastroenterology, 31(1), 69–75. doi:10.1097/MOG.0000000000000139.
Sridharan, G. V., Choi, K., Klemashevich, C., Wu, C., Prabakaran, D., Pan, L. B., et al. (2014). Prediction and quantification of bioactive microbiota metabolites in the mouse gut. Nature Communications, 5, 5492. doi:10.1038/ncomms6492.
Suchodolski, J. S. (2011). Companion animals symposium: microbes and gastrointestinal health of dogs and cats. Journal of Animal Science, 89(5), 1520–1530. doi:10.2527/jas.2010-3377.
Suchodolski, J. S., Camacho, J., & Steiner, J. M. (2008). Analysis of bacterial diversity in the canine duodenum, jejunum, ileum, and colon by comparative 16 S rRNA gene analysis. FEMS Microbiology Ecology, 66(3), 567–578. doi:10.1111/j.1574-6941.2008.00521.x.
Van Buskirk, J. J., Kirsch, W. M., Kleyer, D. L., Barkley, R. M., & Koch, T. H. (1984). Aminomalonic acid: identification in Escherichia coli and atherosclerotic plaque. Proceedings of the National Academy of Sciences of the United States of America, 81(3), 722–725.
Vazquez-Baeza, Y., Hyde, E. R., Suchodolski, J. S., & Knight, R. (2016). Dog and human inflammatory bowel disease rely on overlapping yet distinct dysbiosis networks. Nat Microbiol, 1, 16177. doi:10.1038/nmicrobiol.2016.177.
Vazquez-Baeza, Y., Pirrung, M., Gonzalez, A., & Knight, R. (2013). EMPeror: A tool for visualizing high-throughput microbial community data. Gigascience, 2(1), 16. doi:10.1186/2047-217X-2-16.
Wang, J., Fan, H., Han, Y., Zhao, J., & Zhou, Z. (2016). Characterization of the microbial communities along the gastrointestinal tract of sheep by 454 pyroseqencing analysis. Asian-Australasian Journal of Animal Sciences. doi:10.5713/ajas.16.0166.
Wang, M., Ahrne, S., Jeppsson, B., & Molin, G. (2005). Comparison of bacterial diversity along the human intestinal tract by direct cloning and sequencing of 16S rRNA genes. FEMS Microbiology Ecology, 54(2), 219–231. doi:10.1016/j.femsec.2005.03.012.
Wang, Q., Garrity, G. M., Tiedje, J. M., & Cole, J. R. (2007). Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Applied and environmental microbiology, 73(16), 5261–5267. doi:10.1128/AEM.00062-07.
Ward, N. C., Croft, K. D., Puddey, I. B., & Hodgson, J. M. (2004). Supplementation with grape seed polyphenols results in increased urinary excretion of 3-hydroxyphenylpropionic Acid, an important metabolite of proanthocyanidins in humans. Journal of Agricultural and Food Chemistry, 52(17), 5545–5549. doi:10.1021/jf049404r.
Weber, F. L., Maddrey, W. C., & Walser, M. (1977). Amino acid metabolism of dog jejunum before and during absorption of keto analogues. American Journal of Physiology, 232(3), E263–E269.
Winter, J., & Bokkenheuser, V. D. (1987). Bacterial metabolism of natural and synthetic sex hormones undergoing enterohepatic circulation. Journal of Steroid Biochemistry, 27(4–6), 1145–1149. doi:10.1016/0022-4731(87)90201-9.
Xia, J., Sinelnikov, I. V., Han, B., & Wishart, D. S. (2015). MetaboAnalyst 3.0—making metabolomics more meaningful. Nucleic Acids Research, 43(W1), W251–257. doi:10.1093/nar/gkv380.
Xia, J., & Wishart, D. S. (2011). Web-based inference of biological patterns, functions and pathways from metabolomic data using MetaboAnalyst. Nature Protocols, 6(6), 743–760. doi:10.1038/nprot.2011.319.
Yang, H., Huang, X., Fang, S., Xin, W., Huang, L., & Chen, C. (2016). Uncovering the composition of microbial community structure and metagenomics among three gut locations in pigs with distinct fatness. Scientific Reports, 6, 27427. doi:10.1038/srep27427.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare no conflict of interest.
Ethical approval
All applicable international, national, and institutional guidelines for the care and use of animals were followed. All procedures performed in studies involving animals were in accordance with the ethical standards of the institution at which the studies were conducted.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Honneffer, J.B., Steiner, J.M., Lidbury, J.A. et al. Variation of the microbiota and metabolome along the canine gastrointestinal tract. Metabolomics 13, 26 (2017). https://doi.org/10.1007/s11306-017-1165-3
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s11306-017-1165-3