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Antibiotics in early life alter the murine colonic microbiome and adiposity

Abstract

Antibiotics administered in low doses have been widely used as growth promoters in the agricultural industry since the 1950s, yet the mechanisms for this effect are unclear. Because antimicrobial agents of different classes and varying activity are effective across several vertebrate species, we proposed that such subtherapeutic administration alters the population structure of the gut microbiome as well as its metabolic capabilities. We generated a model of adiposity by giving subtherapeutic antibiotic therapy to young mice and evaluated changes in the composition and capabilities of the gut microbiome. Administration of subtherapeutic antibiotic therapy increased adiposity in young mice and increased hormone levels related to metabolism. We observed substantial taxonomic changes in the microbiome, changes in copies of key genes involved in the metabolism of carbohydrates to short-chain fatty acids, increases in colonic short-chain fatty acid levels, and alterations in the regulation of hepatic metabolism of lipids and cholesterol. In this model, we demonstrate the alteration of early-life murine metabolic homeostasis through antibiotic manipulation.

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Figure 1: Weight and body composition of control and STAT mice.
Figure 2: Bone development and serum GIP measurements.
Figure 3: Changes in the faecal gut microbiome after 50 days of STAT.
Figure 4: Caecal SCFA production after STAT exposure.
Figure 5: Differentially regulated genes related to hepatic lipogenesis, identified through microarray and quantitative PCR analyses.

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References

  1. McCaig, L. F. & Hughes, J. M. Trends in antimicrobial drug prescribing among office-based physicians in the United States. J. Am. Med. Assoc. 273, 214–219 (1995)

    Article  CAS  Google Scholar 

  2. Kozyrskyj, A. L., Ernst, P. & Becker, A. B. Increased risk of childhood asthma from antibiotic use in early life. Chest 131, 1753–1759 (2007)

    Article  Google Scholar 

  3. Blaser, M. J. & Falkow, S. What are the consequences of the disappearing human microbiota? Nature Rev. Microbiol. 7, 887–894 (2009)

    Article  CAS  Google Scholar 

  4. Dethlefsen, L. & Relman, D. A. Microbes and Health Sackler Colloquium: Incomplete recovery and individualized responses of the human distal gut microbiota to repeated antibiotic perturbation. Proc. Natl Acad. Sci. USA 108, 4554–4561 (2010)

    Article  ADS  Google Scholar 

  5. Manichanh, C. et al. Reshaping the gut microbiome with bacterial transplantation and antibiotic intake. Genome Res. 20, 1411–1419 (2010)

    Article  CAS  Google Scholar 

  6. Butaye, P., Devriese, L. A. & Haesebrouck, F. Antimicrobial growth promoters used in animal feed: effects of less well known antibiotics on gram-positive bacteria. Clin. Microbiol. Rev. 16, 175–188 (2003)

    Article  CAS  Google Scholar 

  7. Ozawa, E. Studies on growth promotion by antibiotics. J. Antibiot. 8, 205–214 (1955)

    CAS  PubMed  Google Scholar 

  8. Abreu, M. T., Fukata, M. & Arditi, M. TLR signaling in the gut in health and disease. J. Immunol. 174, 4453–4460 (2005)

    Article  CAS  Google Scholar 

  9. Qin, J. et al. A human gut microbial gene catalogue established by metagenomic sequencing. Nature 464, 59–65 (2010)

    Article  CAS  Google Scholar 

  10. Hansotia, T. & Drucker, D. J. GIP and GLP-1 as incretin hormones: lessons from single and double incretin receptor knockout mice. Regul. Pept. 128, 125–134 (2005)

    Article  CAS  Google Scholar 

  11. Gesta, S., Tseng, Y. H. & Kahn, C. R. Developmental origin of fat: tracking obesity to its source. Cell 131, 242–256 (2007)

    Article  CAS  Google Scholar 

  12. Turnbaugh, P. J. et al. An obesity-associated gut microbiome with increased capacity for energy harvest. Nature 444, 1027–1031 (2006)

    Article  ADS  Google Scholar 

  13. Reikvam, D. H. et al. Depletion of murine intestinal microbiota: effects on gut mucosa and epithelial gene expression. PLoS ONE 6, e17996 (2011)

    Article  ADS  CAS  Google Scholar 

  14. Robinson, C. J. & Young, V. B. Antibiotic administration alters the community structure of the gastrointestinal micobiota. Gut Microbes 1, 279–284 (2010)

    Article  Google Scholar 

  15. Wlodarska, M. et al. Antibiotic treatment alters the colonic mucus layer and predisposes the host to exacerbated Citrobacter rodentium-induced colitis. Infect. Immun. 79, 1536–1545 (2011)

    Article  CAS  Google Scholar 

  16. McCracken, V. J., Simpson, J. M., Mackie, R. I. & Gaskins, H. R. Molecular ecological analysis of dietary and antibiotic-induced alterations of the mouse intestinal microbiota. J. Nutr. 131, 1862–1870 (2001)

    Article  CAS  Google Scholar 

  17. Pace, N. R. A molecular view of microbial diversity and the biosphere. Science 276, 734–740 (1997)

    Article  CAS  Google Scholar 

  18. Spor, A., Koren, O. & Ley, R. Unravelling the effects of the environment and host genotype on the gut microbiome. Nature Rev. Microbiol. 9, 279–290 (2011)

    Article  CAS  Google Scholar 

  19. Ley, R. E. et al. Obesity alters gut microbial ecology. Proc. Natl Acad. Sci. USA 102, 11070–11075 (2005)

    Article  ADS  CAS  Google Scholar 

  20. Buffa, R. et al. Identification of the intestinal cell storing gastric inhibitory peptide. Histochemistry 43, 249–255 (1975)

    Article  CAS  Google Scholar 

  21. Miyawaki, K. et al. Inhibition of gastric inhibitory polypeptide signaling prevents obesity. Nature Med. 8, 738–742 (2002)

    Article  CAS  Google Scholar 

  22. Tsukiyama, K. et al. Gastric inhibitory polypeptide is the major insulinotropic factor in KATP null mice. Eur. J. Endocrinol. 151, 407–412 (2004)

    Article  CAS  Google Scholar 

  23. Zhou, H. et al. Gastric inhibitory polypeptide modulates adiposity and fat oxidation under diminished insulin action. Biochem. Biophys. Res. Commun. 335, 937–942 (2005)

    Article  CAS  Google Scholar 

  24. Yip, R. G., Boylan, M. O., Kieffer, T. J. & Wolfe, M. M. Functional GIP receptors are present on adipocytes. Endocrinology 139, 4004–4007 (1998)

    Article  CAS  Google Scholar 

  25. Yamada, Y. & Seino, Y. Physiology of GIP—a lesson from GIP receptor knockout mice. Horm. Metab. Res. 36, 771–774 (2004)

    Article  CAS  Google Scholar 

  26. Ley, R. E. et al. Obesity alters gut microbial ecology. Proc. Natl Acad. Sci. USA 102, 11070–11075 (2005)

    Article  ADS  CAS  Google Scholar 

  27. Turnbaugh, P. J., Backhed, F., Fulton, L. & Gordon, J. I. Diet-induced obesity is linked to marked but reversible alterations in the mouse distal gut microbiome. Cell Host Microbe 3, 213–223 (2008)

    Article  CAS  Google Scholar 

  28. Murphy, E. F. et al. Composition and energy harvesting capacity of the gut microbiota: relationship to diet, obesity and time in mouse models. Gut 59, 1635–1642 (2010)

    Article  CAS  Google Scholar 

  29. Fleissner, C. K. et al. Absence of intestinal microbiota does not protect mice from diet-induced obesity. Br. J. Nutr. 104, 919–929 (2010)

    Article  CAS  Google Scholar 

  30. Wong, J. M., de Souza, R., Kendall, C. W., Emam, A. & Jenkins, D. J. Colonic health: fermentation and short chain fatty acids. J. Clin. Gastroenterol. 40, 235–243 (2006)

    Article  CAS  Google Scholar 

  31. Hong, Y. H. et al. Acetate and propionate short chain fatty acids stimulate adipogenesis via GPCR43. Endocrinology 146, 5092–5099 (2005)

    Article  CAS  Google Scholar 

  32. Lovell, C. R. & Leaphart, A. B. Community-level analysis: key genes of CO2-reductive acetogenesis. Methods Enzymol. 397, 454–469 (2005)

    Article  CAS  Google Scholar 

  33. Henderson, G., Naylor, G. E., Leahy, S. C. & Janssen, P. H. Presence of novel, potentially homoacetogenic bacteria in the rumen as determined by analysis of formyltetrahydrofolate synthetase sequences from ruminants. Appl. Environ. Microbiol. 76, 2058–2066 (2010)

    Article  CAS  Google Scholar 

  34. Bergman, E. N. Energy contributions of volatile fatty acids from the gastrointestinal tract in various species. Physiol. Rev. 70, 567–590 (1990)

    Article  CAS  Google Scholar 

  35. Backhed, F. et al. The gut microbiota as an environmental factor that regulates fat storage. Proc. Natl Acad. Sci. USA 101, 15718–15723 (2004)

    Article  ADS  Google Scholar 

  36. Backhed, F., Ley, R. E., Sonnenburg, J. L., Peterson, D. A. & Gordon, J. I. Host-bacterial mutualism in the human intestine. Science 307, 1915–1920 (2005)

    Article  ADS  Google Scholar 

  37. Jukes, T. H. Antibiotics in animal feeds. N. Engl. J. Med. 282, 49–50 (1970)

    CAS  PubMed  Google Scholar 

  38. Paine, R. T., Tegner, M. J. & Johnson, E. A. Compounded perturbations yield ecological surprises. Ecosystems 1, 535–545 (1998)

    Article  Google Scholar 

  39. Pickett, S. T. & White, P. S. The Ecology of Natural Disturbance and Patch Dynamics (Academic, 1985)

    Google Scholar 

  40. Blaser, M. J. & Kirschner, D. The equilibria that allow bacterial persistence in human hosts. Nature 449, 843–849 (2007)

    Article  ADS  CAS  Google Scholar 

  41. Sole, R. V. & Montoya, J. M. Complexity and fragility in ecological networks. Proc. R. Soc. Lond. B 268, 2039–2045 (2001)

    Article  CAS  Google Scholar 

  42. Cho, I. & Blaser, M. J. The human microbiome: at the interface of health and disease. Nature Rev. Genet. 13, 260–270 (2012)

    Article  CAS  Google Scholar 

  43. Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA 102, 15545–15550 (2005)

    Article  ADS  CAS  Google Scholar 

  44. Harkness, J. E. & Wagner, J. E. The Biology and Medicine of Rabbits and Rodents 3rd edn (Lea and Febiger, 1989)

    Google Scholar 

  45. Reeder, S. B. et al. Iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL): application with fast spin-echo imaging. Magn. Reson. Med. 54, 636–644 (2005)

    Article  Google Scholar 

  46. Andrikopoulos, S., Blair, A. R., Deluca, N., Fam, B. C. & Proietto, J. Evaluating the glucose tolerance test in mice. Am. J. Physiol. Endocrinol. Metab. 295, E1323–E1332 (2008)

    Article  CAS  Google Scholar 

  47. Favier, C. F., Vaughan, E. E., De Vos, W. M. & Akkermans, A. D. L. Molecular monitoring of succession of bacterial communities in human neonates. Appl. Environ. Microbiol. 68, 219–226 (2002)

    Article  CAS  Google Scholar 

  48. Martínez-Murcia, A. J., Acinas, S. G. & Rodriguez-Valera, F. Evaluation of prokaryotic diversity by restrictase digestion of 16S rDNA directly amplified from hypersaline environments. FEMS Microbiol. Ecol. 17, 247–255 (1995)

    Article  Google Scholar 

  49. Li, K. et al. ANDES: Statistical tools for the ANalyses of DEep Sequencing. BMC Res. Notes 3, 199 (2010)

    Article  Google Scholar 

  50. Altschul, S. F., Gish, W., Miller, W., Myers, E. W. & Lipman, D. J. Basic local alignment search tool. J. Mol. Biol. 215, 403–410 (1990)

    Article  CAS  Google Scholar 

  51. Caporaso, J. G. et al. QIIME allows analysis of high-throughput community sequencing data. Nature Methods 7, 335–336 (2010)

    Article  CAS  Google Scholar 

  52. Edgar, R. C. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26, 2460–2461 (2010)

    Article  CAS  Google Scholar 

  53. Wang, Q., Garrity, G. M., Tiedje, J. M. & Cole, J. R. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl. Environ. Microbiol. 73, 5261–5267 (2007)

    Article  CAS  Google Scholar 

  54. Caporaso, J. G. et al. PyNAST: a flexible tool for aligning sequences to a template alignment. Bioinformatics 26, 266–267 (2010)

    Article  CAS  Google Scholar 

  55. Price, M. N., Dehal, P. S. & Arkin, A. P. FastTree 2–approximately maximum-likelihood trees for large alignments. PLoS ONE 5, e9490 (2010)

    Article  ADS  Google Scholar 

  56. Lozupone, C., Lladser, M. E., Knights, D., Stombaugh, J. & Knight, R. UniFrac: an effective distance metric for microbial community comparison. ISME J. 5, 169–172 (2010)

    Article  Google Scholar 

  57. Lozupone, C. & Knight, R. UniFrac: a new phylogenetic method for comparing microbial communities. Appl. Environ. Microbiol. 71, 8228–8235 (2005)

    Article  CAS  Google Scholar 

  58. Gentleman, R. C. et al. Bioconductor: open software development for computational biology and bioinformatics. Genome Biol. 5, R80 (2004)

    Article  Google Scholar 

  59. Ihaka, R. & Gentleman, R. R: a language for data analysis and graphics. J. Comp. Graph. 5, 299–314 (1996)

    Google Scholar 

  60. Gentleman, R. C. et al. Bioconductor: open software development for computational biology and bioinformatics. Genome Biol. 5, R80 (2004)

    Article  Google Scholar 

  61. Pavoine, S. & Bailly, X. New analysis for consistency among markers in the study of genetic diversity: development and application to the description of bacterial diversity. BMC Evol. Biol. 7, 156 (2007)

    Article  Google Scholar 

  62. Pavoine, S., Dufour, A. B. & Chessel, D. From dissimilarities among species to dissimilarities among communities: a double principal coordinate analysis. J. Theor. Biol. 228, 523–537 (2004)

    Article  MathSciNet  Google Scholar 

  63. Hong, F. et al. Interleukin 6 alleviates hepatic steatosis and ischemia/reperfusion injury in mice with fatty liver disease. Hepatology 40, 933–941 (2004)

    Article  CAS  Google Scholar 

  64. Zhao, G., Nyman, M. & Jonsson, J. A. Rapid determination of short-chain fatty acids in colonic contents and faeces of humans and rats by acidified water-extraction and direct-injection gas chromatography. Biomed. Chromatogr. 20, 674–682 (2006)

    Article  CAS  Google Scholar 

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Acknowledgements

This work was supported in part with grants from the NIH (T-RO1-DK090989, 1UL1-RR029893, UL1-TR000038), the Diane Belfer Program in Human Microbial Ecology, the Philip and Janice Levin Foundation, the Michael Saperstein Fellowship, and institutional funds provided by the J. Craig Venter Institute, and the NYU Genome Technology Center. We thank N. Javitt for advice and J. Chung for technical assistance.

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I.C. and M.J.B. designed the study; I.C., L.C., S.Y., Z.G., D.M., I.T. and K.R. performed experiments; B.A.M. and K.L. performed sequencing and sequencing analysis; J.Z. performed microarray analyses; I.C. and H.L. performed statistical interpretation and analyses; A.V.A. performed bioinformatics analyses and interpretation; I.C. and M.J.B. took primary responsibility for writing the manuscript.

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Correspondence to Martin J. Blaser.

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The authors declare no competing financial interests.

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Cho, I., Yamanishi, S., Cox, L. et al. Antibiotics in early life alter the murine colonic microbiome and adiposity. Nature 488, 621–626 (2012). https://doi.org/10.1038/nature11400

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