Skip to main content
SpringerLink
Log in

The Dynamics of Interacting Bacterial and Fungal Communities of the Mouse Colon Following Antibiotics

  • Fungal Microbiology
  • Published:
Microbial Ecology Aims and scope Submit manuscript

Abstract

We tested two hypotheses concerning the dynamics of intestinal microbial communities of young mice following antibiotic-induced disturbance. The first is that disturbance of the bacterial community causes disturbance of the fungal community. Our results were consistent with that hypothesis. Antibiotics significantly altered bacterial community structure. Antibiotics also altered fungal community structure, significantly increasing the relative abundance of Candida lusitaniae, a known pathogen, while simultaneously significantly decreasing the relative abundances of several other common fungal species. The result was a temporary decrease in fungal diversity. Moreover, bacterial load was negatively correlated with the relative abundances of Candida lusitaniae and Candida parapsilosis, while it was positively correlated with the relative abundances of many other fungal species. Our second hypothesis is that control mice serve as a source of probiotics capable of invading intestines of mice with disturbed microbial communities and restoring pre-antibiotic bacterial and fungal communities. However, we found that control mice did not restore disturbed microbial communities. Instead, mice with disturbed microbial communities induced disturbance in control mice, consistent with the hypothesis that antibiotic-induced disturbance represents an alternate stable state that is easier to achieve than to correct. Our results indicate the occurrence of significant interactions among intestinal bacteria and fungi and suggest that the stimulation of certain bacterial groups may potentially be useful in countering the dominance of fungal pathogens such as Candida spp. However, the stability of disturbed microbial communities could complicate recovery.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

Data Availability

Illumina sequence data are deposited in the NCBI Sequence Read Archive (Bioproject Accession PRJNA633842).

References

  1. Jones RM, Luo L, Ardita CS et al (2013) Symbiotic lactobacilli stimulate gut epithelial proliferation via Nox-mediated generation of reactive oxygen species. EMBO J 32:3017–3028. https://doi.org/10.1038/emboj.2013.224

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Liou A, Paziuk M, Luevano J-MJ et al (2013) Conserved shifts in the gut microbiota due to gastric bypass reduce host weight and adiposity. Sci Med 5:1–23. https://doi.org/10.1037/a0032811.Child

    Article  Google Scholar 

  3. Rogers GB (2015) Germs and joints: the contribution of the human microbiome to rheumatoid arthritis. Nat Med 21:839–841. https://doi.org/10.1038/nm.3916

    Article  CAS  PubMed  Google Scholar 

  4. Zhang X, Zhang D, Jia H et al (2015) The oral and gut microbiomes are perturbed in rheumatoid arthritis and partly normalized after treatment. Nat Med 21:895–905. https://doi.org/10.1038/nm.3914

    Article  CAS  PubMed  Google Scholar 

  5. Alkanani AK, Hara N, Gottlieb PA et al (2015) Alterations in intestinal microbiota correlate with susceptibility to type 1 diabetes. Diabetes 64:3510–3520. https://doi.org/10.2337/db14-1847

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Burrows MP, Volchkov P, Kobayashi KS et al (2015) Microbiota regulates type 1 diabetes through Toll-like receptors. Proc Natl Acad Sci U S A 112:9973–9977. https://doi.org/10.1073/pnas.1508740112

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Becker C, Neurath MF, Wirtz S (2015) The intestinal microbiota in inflammatory bowel disease. ILAR J 56:192–204. https://doi.org/10.1093/ilar/ilv030

    Article  CAS  PubMed  Google Scholar 

  8. Schaubeck M, Haller D (2015) Reciprocal interaction of diet and microbiome in inflammatory bowel diseases. Curr Opin Gastroenterol 31:464–470

    Article  CAS  Google Scholar 

  9. Dzutsev A, Goldszmid RS, Viaud S et al (2015) The role of the microbiota in inflammation, carcinogenesis, and cancer therapy. Eur J Immunol 45:17–31. https://doi.org/10.1002/eji.201444972

    Article  CAS  PubMed  Google Scholar 

  10. Paul B, Barnes S, Demark-Wahnefried W et al (2015) Influences of diet and the gut microbiome on epigenetic modulation in cancer and other diseases. Clin Epigenetics 7:1–11. https://doi.org/10.1186/s13148-015-0144-7

    Article  CAS  Google Scholar 

  11. Ghaisas S, Maher J, Kanthasamy A (2016) Gut microbiome in health and disease: linking the microbiome-gut-brain axis and environmental factors in the pathogenesis of systemic and neurodegenerative diseases. Pharmacol Ther 158:52–62. https://doi.org/10.1016/j.pharmthera.2015.11.012

    Article  CAS  PubMed  Google Scholar 

  12. Haq RA, Schlachetzki JCM, Glass CK, Mazmanian SK (2018) Microbiome–microglia connections via the gut–brain axis. J Exp Med 216:41–59

  13. Rojo D, Méndez-García C, Raczkowska BA et al (2017) Exploring the human microbiome from multiple perspectives: factors altering its composition and function. FEMS Microbiol Rev 41:453–478. https://doi.org/10.1093/femsre/fuw046

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Hoffmann C, Dollive S, Grunberg S et al (2013) Archaea and fungi of the human gut microbiome: correlations with diet and bacterial residents. PLoS One 8:e66019. https://doi.org/10.1371/journal.pone.0066019

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Ott SJ, Kuhbacher T, Musfeldt M et al (2008) Fungi and inflammatory bowel diseases: alterations of composition and diversity. Scand J Gastroenterol 43:831–841. https://doi.org/10.1080/00365520801935434

    Article  CAS  PubMed  Google Scholar 

  16. Petersen C, Round JL (2014) Defining dysbiosis and its influence on host immunity and disease. Cell Microbiol 16:1024–1033. https://doi.org/10.1111/cmi.12308

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Schulfer A, Blaser MJ (2015) Risks of antibiotic exposures early in life on the developing microbiome. PLoS Pathog 11:1–6. https://doi.org/10.1371/journal.ppat.1004903

    Article  CAS  Google Scholar 

  18. Jakobsson HE, Jernberg C, Andersson AF, et al (2010) Short-term antibiotic treatment has differing long-term impacts on the human throat and gut microbiome. PLoS One 5: . doi: https://doi.org/10.1371/journal.pone.0009836

  19. Dollive S, Chen Y-Y, Grunberg S et al (2013) Fungi of the murine gut: episodic variation and proliferation during antibiotic treatment. PLoS One 8:e71806. https://doi.org/10.1371/journal.pone.0071806

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Huseyin CE, O’Toole PW, Cotter PD, Scanlan PD (2017) Forgotten fungi-the gut mycobiome in human health and disease. FEMS Microbiol Rev 41:479–511. https://doi.org/10.1093/femsre/fuw047

    Article  CAS  PubMed  Google Scholar 

  22. Hoarau G, Mukherjee PK, Gower-Rousseau C et al (2016) Bacteriome and mycobiome interactions underscore microbial dysbiosis in familial Crohn’s disease. MBio 7:1–11. https://doi.org/10.1128/mBio.01250-16

    Article  Google Scholar 

  23. Grandview Research (2019) Antibiotics market size, share & trends analysis report by action mechanism (protein, DNA, RNA, cell wall synthesis inhibitors), by drug class (penicillin, cephalosporins, fluoroquinolones), and segment forecasts, 2019-2026. Grandview Research, Inc., San Francisco, California, USA.

  24. Mukherjee PK, Chandra J, Retuerto M et al (2014) Oral mycobiome analysis of HIV-infected patients: identification of Pichia as an antagonist of opportunistic fungi. PLoS Pathog:10. https://doi.org/10.1371/journal.ppat.1003996

  25. ten Oever J, Netea MG (2014) The bacteriome-mycobiome interaction and antifungal host defense. Eur J Immunol 44:3182–3191. https://doi.org/10.1002/eji.201344405

    Article  CAS  PubMed  Google Scholar 

  26. Suhr MJ, Hallen-Adams HE (2015) The human gut mycobiome: pitfalls and potentials - a mycologist’s perspective. Mycologia 107:1057–1073. https://doi.org/10.3852/15-147

    Article  CAS  PubMed  Google Scholar 

  27. Witherden EA, Shoaie S, Hall RA, Moyes DL (2017) The human mucosal mycobiome and fungal community interactions. J Fungi 3:56. https://doi.org/10.3390/jof3040056

    Article  CAS  Google Scholar 

  28. Li Q, Wang C, Tang C, et al (2014) Dysbiosis of gut fungal microbiota is associated with mucosal inflammation in crohn’s disease. J Clin Gastroenterol 48:513–523 . doi: https://doi.org/10.1097/MCG.0000000000000035

  29. Hill DA, Hoffmann C, Abt MC et al (2010) Metagenomic analyses reveal antibiotic-induced temporal and spatial changes in intestinal microbiota with associated alterations in immune cell homeostasis. Mucosal Immunol 3:148–158. https://doi.org/10.1038/mi.2009.132

    Article  CAS  PubMed  Google Scholar 

  30. Hu X, Wang T, Liang S et al (2015) Antibiotic-induced imbalances in gut microbiota aggravates cholesterol accumulation and liver injuries in rats fed a high-cholesterol diet. Appl Microbiol Biotechnol 99:9111–9122. https://doi.org/10.1007/s00253-015-6753-4

    Article  CAS  PubMed  Google Scholar 

  31. Ebino KY, Yoshinaga K, Saito TR (1988) A simple method for prevention of coprophagy in the mouse. Lab Anim 22:1–4. https://doi.org/10.1258/002367788780746548

    Article  CAS  PubMed  Google Scholar 

  32. Levine JM, D’Antonio CM (1999) Elton revisited: a review of evidence linking diversity and invasibility. Oikos 87:15–26

    Article  Google Scholar 

  33. Turnbaugh PJ, Ridaura VK, Faith JJ et al (2009) The effect of diet on the human gut microbiome: a metagenomic analysis in humanized gnotobiotic mice. Sci Transl Med 1:6ra14. https://doi.org/10.1126/scitranslmed.3000322

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. David LA, Maurice CF, Carmody RN et al (2014) Diet rapidly and reproducibly alters the human gut microbiome. Nature 505:559–563. https://doi.org/10.1038/nature12820

    Article  CAS  PubMed  Google Scholar 

  35. Singh RK, Chang HW, Yan D et al (2017) Influence of diet on the gut microbiome and implications for human health. J Transl Med 15:1–17. https://doi.org/10.1186/s12967-017-1175-y

    Article  CAS  Google Scholar 

  36. Sonnenburg E, Sonnenburg J (2014) Starving our microbial self: the deleterious consequences of a diet deficient in microbiota-accessible carbohydrates. Cell Metab 20:779–786. https://doi.org/10.1016/j.physbeh.2017.03.040

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Granfeldt YE, Drews AW, Björck IME (1993) Starch bioavailability in arepas made from ordinary or high amylose corn: concentration adn gastrointestinal fate of resistant starch in rats. J Nutr 123:1676–1684. https://doi.org/10.1093/jn/123.10.1676

    Article  CAS  PubMed  Google Scholar 

  38. Lloyd-Price J, Abu-Ali G, Huttenhower C (2016) The healthy human microbiome. Genome Med 8:1–11. https://doi.org/10.1186/s13073-016-0307-y

    Article  Google Scholar 

  39. Koide RT, Xu B, Sharda J et al (2005) Evidence of species interactions within an ectomycorrhizal fungal community. New Phytol 165:305–316. https://doi.org/10.1111/j.1469-8137.2004.01216.x

    Article  PubMed  Google Scholar 

  40. Szink I, Davis E, Ricks KD, Koide R (2016) New evidence for broad trophic status of leaf endophytic fungi of Quercus gambelii. Fungal Ecol 22:2–9. https://doi.org/10.1016/j.bmcl.2008.01.042

    Article  CAS  Google Scholar 

  41. Hiscox J, Savoury M, Müller CT et al (2015) Priority effects during fungal community establishment in beech wood. ISME J 9:2246–2260. https://doi.org/10.1038/ismej.2015.38

    Article  PubMed  PubMed Central  Google Scholar 

  42. Angebault C, Ghozlane A, Volant S et al (2018) Combined bacterial and fungal intestinal microbiota analyses: impact of storage conditions and DNA extraction protocols. PLoS One:13. https://doi.org/10.1371/journal.pone.0201174

  43. Videnska P, Smerkova K, Zwinsova B et al (2019) Stool sampling and DNA isolation kits affect DNA quality and bacterial composition following 16S rRNA gene sequencing using MiSeq Illumina platform. Sci Rep 9:1–14. https://doi.org/10.1038/s41598-019-49520-3

    Article  CAS  Google Scholar 

  44. Caporaso JG, Lauber CL, Walters WA et al (2011) Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc Natl Acad Sci U S A 108:4516–4522. https://doi.org/10.1073/pnas.1000080107

    Article  PubMed  Google Scholar 

  45. Magoč T, Salzberg SL (2011) FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics 27:2957–2963. https://doi.org/10.1093/bioinformatics/btr507

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Taylor D, Walters W, Lennon N et al (2016) Accurate estimation of fungal diversity and abundance through improved lineage-specific primers optimized for Illumina amplicon sequencing. Appl Environ Microbiol 82:7217–7226. https://doi.org/10.1128/AEM.02576-16.Editor

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Callahan BJ, McMurdie PJ, Rosen MJ et al (2016) DADA2: high-resolution sample inference from Illumina amplicon data. Nat Methods 13:581–583. https://doi.org/10.1038/nmeth.3869

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Edgar RC (2010) Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26:2460–2461. https://doi.org/10.1093/bioinformatics/btq461

    Article  CAS  PubMed  Google Scholar 

  49. Cai L, Ye L, Tong AHY et al (2013) Biased diversity metrics revealed by bacterial 16S pyrotags derived from different primer sets. PLoS One 8:1–11. https://doi.org/10.1371/journal.pone.0053649

    Article  CAS  Google Scholar 

  50. DeSantis TZ, Hugenholtz P, Larsen N et al (2006) Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl Environ Microbiol 72:5069–5072. https://doi.org/10.1128/AEM.03006-05

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Abarenkov K, Henrik Nilsson R, Larsson KH et al (2010) The UNITE database for molecular identification of fungi-recent updates and future perspectives. New Phytol 186:281–285. https://doi.org/10.1111/j.1469-8137.2009.03160.x

    Article  PubMed  Google Scholar 

  52. Anderson MJ (2001) A new method for non-parametric multivariate analysis of variance. Austral Ecol 26:32–46

    Google Scholar 

  53. R Core Team (2013) R: a language and environment for statistical computing

  54. Oksanen JF, Blanchet G, Friendly M, et al (2018) vegan: community ecology package. https://github.com/vegandevs/vegan

  55. Pielou EC (1966) The measurement of diversity in different types of biological collections. J Theor Biol 13:131–144. https://doi.org/10.1016/0022-5193(66)90013-0

    Article  Google Scholar 

  56. Jost L (2006) Entropy and diversity. Oikos 113:363–375. https://doi.org/10.1111/j.2006.0030-1299.14714.x

    Article  Google Scholar 

  57. Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15:1–21. https://doi.org/10.1186/s13059-014-0550-8

    Article  CAS  Google Scholar 

  58. Rivera-Pinto J, Egozcue JJ, Pawlowsky-Glahn V et al (2018) Balances: a new perspective for microbiome analysis. mSystems 3:1–12. https://doi.org/10.1128/msystems.00053-18

    Article  CAS  Google Scholar 

  59. Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc B 57:289–300. https://doi.org/10.2307/2346101

    Article  Google Scholar 

  60. Fiedorová K, Radvanský M, Němcová E et al (2019) The impact of DNA extraction methods on stool bacterial and fungal microbiota community recovery. Front Physiol 10:1–11. https://doi.org/10.3389/fmicb.2019.00821

    Article  Google Scholar 

  61. Barna C, Williams DH (1984) The structure and mode of action of glycopeptide antibiotics of the vancomycin group. Annu Rev Microbiol 38:339–357

    Article  CAS  Google Scholar 

  62. Hancock REW, Bell A (1989) Antibiotic uptake into gram-negative bacteria. Curr Top Infect Dis Clin Microbiol 2:21–28. https://doi.org/10.1007/BF01975036

    Article  Google Scholar 

  63. Drawz SM, Bonomo RA (2010) Three decades of β-lactamase inhibitors. Clin Microbiol Rev 23:160–201. https://doi.org/10.1128/CMR.00037-09

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Jutila HM, Grace JB (2002) Effects of disturbance on germination and seedling establishment in a coastal prairie grassland: a test of the competitive release hypothesis. J Ecol 90:291–302. https://doi.org/10.1046/j.1365-2745.2001.00665.x

    Article  Google Scholar 

  65. Mason KL, Downward JRE, Falkowski NR et al (2012) Interplay between the gastric bacterial microbiota and Candida albicans during postantibiotic recolonization and gastritis. Infect Immun 80:150–158. https://doi.org/10.1128/IAI.05162-11

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Hogan DA, Vik Å, Kolter R (2004) A Pseudomonas aeruginosa quorum-sensing molecule influences Candida albicans morphology. Mol Microbiol 54:1212–1223. https://doi.org/10.1111/j.1365-2958.2004.04349.x

    Article  CAS  PubMed  Google Scholar 

  67. Noverr MC, Falkowski NR, Mcdonald RA et al (2005) Development of allergic airway disease in mice following antibiotic therapy and fungal microbiota increase: role of host development of allergic airway disease in mice following antibiotic therapy and fungal microbiota increase: role of host genetics. Infect Immun 73:30–38. https://doi.org/10.1128/IAI.73.1.30

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Lorek J, Pöggeler S, Weide MR et al (2008) Influence of farnesol on the morphogenesis of Aspergillus niger. J Basic Microbiol 48:99–103. https://doi.org/10.1002/jobm.200700292

    Article  PubMed  Google Scholar 

  69. Lee HB, Kim Y, Kim JC et al (2005) Activity of some aminoglycoside antibiotics against true fungi, Phytophthora and Pythium species. J Appl Microbiol 99:836–843. https://doi.org/10.1111/j.1365-2672.2005.02684.x

    Article  CAS  PubMed  Google Scholar 

  70. Pareek S, Kurakawa T, Das B et al (2019) Comparison of Japanese and Indian intestinal microbiota shows diet-dependent interaction between bacteria and fungi. npj Biofilms Microbiomes:5. https://doi.org/10.1038/s41522-019-0110-9

  71. Merz WG (1984) Candida lusitaniae: frequency of recovery, colonization, infection, and amphotericin B resistance. J Clin Microbiol 20:1194–1195

    Article  CAS  Google Scholar 

  72. Diaz PI, Strausbaugh LD, Dongari-Bagtzoglou A (2014) Fungal-bacterial interactions and their relevance to oral health: linking the clinic and the bench. Front Cell Infect Microbiol 4. https://doi.org/10.3389/fcimb.2014.00101

  73. Rauch M, Lynch SV (2012) The potential for probiotic manipulation of the gastrointestinal microbiome. Curr Opin Biotechnol 23:192–201. https://doi.org/10.1016/j.copbio.2011.11.004

    Article  CAS  PubMed  Google Scholar 

  74. Tung J, Barreiro LB, Burns MB et al (2015) Social networks predict gut microbiome composition in wild baboons. Elife 2015:1–18. https://doi.org/10.7554/eLife.05224

    Article  Google Scholar 

  75. Moeller A, Foerster S, Wilson M, et al (2016) Social behavior shapes the chimpanzee pan-microbiome. Sci Adv

  76. Liu C-X, Wang J-R, Lu Y-L (1990) Pharmacokinetics of sulbactam and ampicillin in mice and in dogs. Acta Pharm Sin 25:406–411

    CAS  Google Scholar 

  77. Jin Y, Jang JW, Lee MH, Han CH (2006) Development of ELISA and immunochromatographic assay for the detection of neomycin. Clin Chim Acta 364:260–266. https://doi.org/10.1016/j.cca.2005.07.024

    Article  CAS  PubMed  Google Scholar 

  78. Vesga O, Agudelo M, Salazar BE et al (2010) Generic vancomycin products fail in vivo despite being pharmaceutical equivalents of the innovator. Antimicrob Agents Chemother 54:3271–3279. https://doi.org/10.1128/AAC.01044-09

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. Stevens CE, Hume ID (1998) Contributions of microbes in vertebrate gastrointestinal tract to production and conservation of nutrients. Physiol Rev 78:393–427. https://doi.org/10.1152/physrev.1998.78.2.393

    Article  CAS  PubMed  Google Scholar 

  80. Martin R, Nauta AJ, Ben Amor K et al (2010) Early life: gut microbiota and immune development in infancy. Benefic Microbes 1:367–382. https://doi.org/10.3920/BM2010.0027

    Article  CAS  Google Scholar 

  81. Vangay P, Ward T, Gerber JS, Knights D (2015) Antibiotics, pediatric dysbiosis, and disease. Cell Host Microbe 17:553–564. https://doi.org/10.1016/j.chom.2015.04.006

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Arrieta MC, Stiemsma LT, Dimitriu PA et al (2015) Early infancy microbial and metabolic alterations affect risk of childhood asthma. Sci Transl Med 7. https://doi.org/10.1126/scitranslmed.aab2271

  83. Benson AK, Kelly SA, Legge R et al (2010) Individuality in gut microbiota composition is a complex polygenic trait shaped by multiple environmental and host genetic factors. Proc Natl Acad Sci U S A 107:18933–18938. https://doi.org/10.1073/pnas.1007028107

    Article  PubMed  PubMed Central  Google Scholar 

  84. Nützmann HW, Reyes-Dominguez Y, Scherlach K et al (2011) Bacteria-induced natural product formation in the fungus Aspergillus nidulans requires Saga/Ada-mediated histone acetylation. Proc Natl Acad Sci U S A 108:14282–14287. https://doi.org/10.1073/pnas.1103523108

    Article  PubMed  PubMed Central  Google Scholar 

  85. Kusari S, Hertweck C, Spiteller M (2012) Chemical ecology of endophytic fungi: origins of secondary metabolites. Chem Biol 19:792–798. https://doi.org/10.1016/j.chembiol.2012.06.004

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgments

We are grateful for the helpful suggestions of two anonymous reviewers.

Funding

Financial support was given to RTK provided by the Brigham Young University and by the Sustainable Bioenergy Research Program of the US Department of Agriculture, National Institute of Food and Agriculture (no. 2011-67009-20072).

Author information

Authors and Affiliations

  1. Department of Biology, Brigham Young University, Provo, UT, 84602, USA

    Rachel Nettles, Kevin D. Ricks & Roger T. Koide

  2. Currently: Kintai Therapeutics, 26 Landsdowne Street, Boston, MA, 02139, USA

    Rachel Nettles

  3. Currently: Program in Ecology, Evolution and Conservation Biology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA

    Kevin D. Ricks

Authors
  1. Rachel Nettles
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kevin D. Ricks
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Roger T. Koide
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conceptualization: Rachel Nettles and Roger T. Koide; methodology: Rachel Nettles, Kevin D. Ricks, and Roger T. Koide; formal analysis and investigation: Rachel Nettles, Kevin D. Ricks, and Roger T. Koide; writing—original draft preparation: Roger T. Koide; writing—review and editing: Rachel Nettles, Kevin D. Ricks, and Roger T. Koide; funding acquisition: Roger T. Koide; resources: Roger T. Koide; supervision: Roger T. Koide

Corresponding author

Correspondence to Roger T. Koide.

Ethics declarations

Disclaimer

Any opinions, findings, or conclusions expressed in this material are those of the authors and do not necessarily reflect the views of the United States Department of Agriculture or Brigham Young University.

Electronic supplementary material

ESM 1

(PDF 173 kb)

ESM 2

(PDF 857 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Nettles, R., Ricks, K.D. & Koide, R.T. The Dynamics of Interacting Bacterial and Fungal Communities of the Mouse Colon Following Antibiotics. Microb Ecol 80, 573–592 (2020). https://doi.org/10.1007/s00248-020-01525-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00248-020-01525-6

Keywords

Search

Navigation