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Nature. 2021 Nov;599(7883):120-124. doi: 10.1038/s41586-021-03986-2. Epub 2021 Oct 13.

Unravelling the collateral damage of antibiotics on gut bacteria.

Nature

Lisa Maier, Camille V Goemans, Jakob Wirbel, Michael Kuhn, Claudia Eberl, Mihaela Pruteanu, Patrick Müller, Sarela Garcia-Santamarina, Elisabetta Cacace, Boyao Zhang, Cordula Gekeler, Tisya Banerjee, Exene Erin Anderson, Alessio Milanese, Ulrike Löber, Sofia K Forslund, Kiran Raosaheb Patil, Michael Zimmermann, Bärbel Stecher, Georg Zeller, Peer Bork, Athanasios Typas

Affiliations

  1. Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany. [email protected].
  2. Interfaculty Institute of Microbiology and Infection Medicine, University of Tübingen, Tübingen, Germany. [email protected].
  3. Cluster of Excellence 'Controlling Microbes to Fight Infections', University of Tübingen, Tübingen, Germany. [email protected].
  4. Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
  5. Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
  6. Max-von-Pettenkofer Institute, LMU Munich, Munich, Germany.
  7. German Center for Infection Research (DZIF), partner site LMU Munich, Munich, Germany.
  8. Department of Biology, Humboldt University Berlin, Berlin, Germany.
  9. Interfaculty Institute of Microbiology and Infection Medicine, University of Tübingen, Tübingen, Germany.
  10. Cluster of Excellence 'Controlling Microbes to Fight Infections', University of Tübingen, Tübingen, Germany.
  11. Department of Chemistry, TU Munich, Munich, Germany.
  12. NYU School of Medicine, New York, NY, USA.
  13. Experimental and Clinical Research Center, a cooperation of Charité - Universitätsmedizin Berlin and Max-Delbrück-Center for Molecular Medicine, Berlin, Germany.
  14. Max-Delbrück-Center for Molecular Medicine, Berlin, Germany.
  15. The Medical Research Council Toxicology Unit, University of Cambridge, Cambridge, UK.
  16. Yonsei Frontier Lab (YFL), Yonsei University, Seoul, South Korea.
  17. Department of Bioinformatics, Biocenter, University of Würzburg, Würzburg, Germany.
  18. Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany. [email protected].
  19. Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany. [email protected].

PMID: 34646011 DOI: 10.1038/s41586-021-03986-2

Abstract

Antibiotics are used to fight pathogens but also target commensal bacteria, disturbing the composition of gut microbiota and causing dysbiosis and disease

© 2021. The Author(s), under exclusive licence to Springer Nature Limited.

References

  1. Blaser, M. J. Antibiotic use and its consequences for the normal microbiome. Science 352, 544–545 (2016). - PubMed
  2. Maier, L. et al. Extensive impact of non-antibiotic drugs on human gut bacteria. Nature 555, 623–628 (2018). - PubMed
  3. Cho, I. et al. Antibiotics in early life alter the murine colonic microbiome and adiposity. Nature 488, 621–626 (2012). - PubMed
  4. Cox, L. M. et al. Altering the intestinal microbiota during a critical developmental window has lasting metabolic consequences. Cell 158, 705–721 (2014). - PubMed
  5. Ruiz, V. E. et al. A single early-in-life macrolide course has lasting effects on murine microbial network topology and immunity. Nat. Commun. 8, 518 (2017). - PubMed
  6. Korpela, K. et al. Intestinal microbiome is related to lifetime antibiotic use in Finnish pre-school children. Nat. Commun. 7, 10410 (2016). - PubMed
  7. Parker, E. P. K. et al. Changes in the intestinal microbiota following the administration of azithromycin in a randomised placebo-controlled trial among infants in south India. Sci. Rep. 7, 9168 (2017). - PubMed
  8. Falony, G. et al. Population-level analysis of gut microbiome variation. Science 352, 560–564 (2016). - PubMed
  9. Rothschild, D. et al. Environment dominates over host genetics in shaping human gut microbiota. Nature 555, 210–215 (2018). - PubMed
  10. Zimmermann, M., Patil, K. R., Typas, A. & Maier, L. Towards a mechanistic understanding of reciprocal drug–microbiome interactions. Mol. Syst. Biol. 17, e10116 (2021). - PubMed
  11. Vich Vila, A. et al. Impact of commonly used drugs on the composition and metabolic function of the gut microbiota. Nat. Commun. 11, 362 (2020). - PubMed
  12. Kuhn, M., Letunic, I., Jensen, L. J. & Bork, P. The SIDER database of drugs and side effects. Nucleic Acids Res. 44, D1075–D1079 (2016). - PubMed
  13. Dethlefsen, L. & Relman, D. A. Incomplete recovery and individualized responses of the human distal gut microbiota to repeated antibiotic perturbation. Proc. Natl Acad. Sci. USA 108, 4554–4561 (2011). - PubMed
  14. Uzan-Yulzari, A. et al. Neonatal antibiotic exposure impairs child growth during the first six years of life by perturbing intestinal microbial colonization. Nat. Commun. 12, 443 (2021). - PubMed
  15. Nagy, E., Boyanova, L., Justesen, U. S. & ESCMID Study Group of Anaerobic Infections. How to isolate, identify and determine antimicrobial susceptibility of anaerobic bacteria in routine laboratories. Clin. Microbiol. Infect. 24, 1139–1148 (2018). - PubMed
  16. European Committee on Antimicrobial Susceptibility Testing. Breakpoint tables for interpretation of MICs and zone diameters. v.; http://www.eucast.org/clinical_breakpoints/ (2019). - PubMed
  17. Bullman, S. et al. Analysis of Fusobacterium persistence and antibiotic response in colorectal cancer. Science 358, 1443–1448 (2017). - PubMed
  18. Manfredo Vieira, S. et al. Translocation of a gut pathobiont drives autoimmunity in mice and humans. Science 359, 1156–1161 (2018). - PubMed
  19. Gaulton, A. et al. The ChEMBL database in 2017. Nucleic Acids Res. 45, D945–D954 (2017). - PubMed
  20. Slimings, C. & Riley, T. V. Antibiotics and hospital-acquired Clostridium difficile infection: update of systematic review and meta-analysis. J. Antimicrob. Chemother. 69, 881–891 (2014). - PubMed
  21. Baron, S., Diene, S. & Rolain, J.-M. Human microbiomes and antibiotic resistance. Hum. Microb. J. 10, 43–52 (2018). - PubMed
  22. Tramontano, M. et al. Nutritional preferences of human gut bacteria reveal their metabolic idiosyncrasies. Nat. Microbiol. 3, 514–522 (2018). - PubMed
  23. Habib, G. et al. 2015 ESC Guidelines for the management of infective endocarditis: the Task Force for the Management of Infective Endocarditis of the European Society of Cardiology (ESC). Endorsed by: European Association for Cardio-Thoracic Surgery (EACTS), the European Association of Nuclear Medicine (EANM). Eur. Heart J. 36, 3075–3128 (2015). - PubMed
  24. Kasper, D.L., F. A., Hauser S. L. & Longo D. L. Harrison’s Principles of Internal Medicine (McGraw-Hill, 2012). - PubMed
  25. Lobritz, M. A. et al. Antibiotic efficacy is linked to bacterial cellular respiration. Proc. Natl Acad. Sci. USA 112, 8173–8180 (2015). - PubMed
  26. French, G. L. Bactericidal agents in the treatment of MRSA infections—the potential role of daptomycin. J. Antimicrob. Chemother. 58, 1107–111 (2006). - PubMed
  27. Jelic, D. & Antolovic, R. From erythromycin to azithromycin and new potential ribosome-binding antimicrobials. Antibiotics (Basel) 5, 29 (2016). - PubMed
  28. Nemeth, J., Oesch, G. & Kuster, S. P. Bacteriostatic versus bactericidal antibiotics for patients with serious bacterial infections: systematic review and meta-analysis. J. Antimicrob. Chemother. 70, 382–395 (2015). - PubMed
  29. Wald-Dickler, N., Holtom, P. & Spellberg, B. Busting the myth of “static vs cidal” a systemic literature review. Clin. Infect. Dis. 66, 1470–1474 (2018). - PubMed
  30. Brochado, A. R. et al. Species-specific activity of antibacterial drug combinations. Nature 559, 259–263 (2018). - PubMed
  31. Brugiroux, S. et al. Genome-guided design of a defined mouse microbiota that confers colonization resistance against Salmonella enterica serovar Typhimurium. Nat. Microbiol. 2, 16215 (2016). - PubMed
  32. Palleja, A. et al. Recovery of gut microbiota of healthy adults following antibiotic exposure. Nat. Microbiol. 3, 1255–1265 (2018). - PubMed
  33. Schmidt, T. S. B., Raes, J. & Bork, P. The human gut microbiome: from association to modulation. Cell 172, 1198–1215 (2018). - PubMed
  34. Milanese, A. et al. Microbial abundance, activity and population genomic profiling with mOTUs2. Nat. Commun. 10, 1014 (2019). - PubMed
  35. Feng, Q. et al. Gut microbiome development along the colorectal adenoma-carcinoma sequence. Nat. Commun. 6, 6528 (2015). - PubMed
  36. Vogtmann, E. et al. Colorectal cancer and the human gut microbiome: reproducibility with whole-genome shotgun sequencing. PLoS ONE 11 (2016). - PubMed
  37. Wirbel, J. et al. Meta-analysis of fecal metagenomes reveals global microbial signatures that are specific for colorectal cancer. Nat. Med. 25, 679–689 (2019). - PubMed
  38. Yu, J. et al. Metagenomic analysis of faecal microbiome as a tool towards targeted non-invasive biomarkers for colorectal cancer. Gut 66, 70–78 (2017). - PubMed
  39. Zeller, G. et al. Potential of fecal microbiota for early-stage detection of colorectal cancer. Mol. Syst. Biol. 10, 766 (2014). - PubMed
  40. Kultima, J. R. et al. MOCAT2: a metagenomic assembly, annotation and profiling framework. Bioinformatics 32, 2520–2523 (2016). - PubMed
  41. Schneider, C. A., Rasband, W. S. & Eliceiri, K. W. NIH Image to ImageJ: 25 years of image analysis. Nat. Methods 9, 671–675 (2012). - PubMed
  42. Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods 9, 676–682 (2012). - PubMed
  43. Frostegård, A. et al. Quantification of bias related to the extraction of DNA directly from soils. Appl. Environ. Microbiol. 65, 5409–5420 (1999). - PubMed
  44. Caporaso, J. G. et al. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc. Natl Acad. Sci. USA 108, 4516–4522 (2011). - PubMed
  45. Callahan, B. J. et al. DADA2: high-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581–583 (2016). - PubMed
  46. 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). - PubMed
  47. Matias Rodrigues, J. F., Schmidt, T. S. B., Tackmann, J. & von Mering, C. MAPseq: highly efficient k-mer search with confidence estimates, for rRNA sequence analysis. Bioinformatics 33, 3808–3810 (2017). - PubMed
  48. Nawrocki, E. P. & Eddy, S. R. Infernal 1.1: 100-fold faster RNA homology searches. Bioinformatics 29, 2933–2935 (2013). - PubMed
  49. Matias Rodrigues, J. F. & von Mering, C. HPC-CLUST: distributed hierarchical clustering for large sets of nucleotide sequences. Bioinformatics 30, 287–288 (2014). - PubMed
  50. Schmidt, T. S. B., Matias Rodrigues, J. F. & von Mering, C. Limits to robustness and reproducibility in the demarcation of operational taxonomic units. Environ. Microbiol. 17, 1689–1706 (2015). - PubMed
  51. Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014). - PubMed
  52. McMurdie, P. J. & Holmes, S. Waste not, want not: why rarefying microbiome data is inadmissible. PLoS Comput. Biol. 10, e1003531 (2014). - PubMed
  53. Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. B 57, 289–300 (1995). - PubMed
  54. Chen, M. et al. Inhibition of renal NQO1 activity by dicoumarol suppresses nitroreduction of aristolochic acid I and attenuates its nephrotoxicity. Toxicol. Sci. 122, 288–296 (2011). - PubMed
  55. Cai, H. Y. et al. Benzbromarone, an old uricosuric drug, inhibits human fatty acid binding protein 4 in vitro and lowers the blood glucose level in db/db mice. Acta Pharmacol. Sin. 34, 1397–1402 (2013). - PubMed
  56. Herp, S. et al. Mucispirillum schaedleri antagonizes Salmonella virulence to protect mice against colitis. Cell Host Microbe 25, 681–694 (2019). - PubMed
  57. Zimmermann, M., Zimmermann-Kogadeeva, M., Wegmann, R. & Goodman, A. L. Mapping human microbiome drug metabolism by gut bacteria and their genes. Nature 570, 462–467 (2019). - PubMed
  58. Sunagawa, S. et al. Metagenomic species profiling using universal phylogenetic marker genes. Nat. Methods 10, 1196–1199 (2013). - PubMed
  59. Huerta-Cepas, J., Serra, F. & Bork, P. ETE 3: reconstruction, analysis, and visualization of phylogenomic data. Mol. Biol. Evol. 33, 1635–1638 (2016). - PubMed
  60. Sievers, F. et al. Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega. Mol. Syst. Biol. 7, 539 (2011). - PubMed
  61. Nguyen, L. T., Schmidt, H. A., von Haeseler, A. & Minh, B. Q. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol. Biol. Evol. 32, 268–274 (2015). - PubMed
  62. Cani, P. D. & de Vos, W. M. Next-generation beneficial microbes: the case of Akkermansia muciniphila. Front. Microbiol. 8, 1765 (2017). - PubMed
  63. Routy, B. et al. Gut microbiome influences efficacy of PD-1-based immunotherapy against epithelial tumors. Science 359, 91–97 (2018). - PubMed

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