Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Diarrhoeal events can trigger long-term Clostridium difficile colonization with recurrent blooms

Nature Microbiology volume 5, pages 642–650 (2020)Cite this article

Subjects

Abstract

Although Clostridium difficile is widely considered an antibiotic- and hospital-associated pathogen, recent evidence indicates that this is an insufficient depiction of the risks and reservoirs. A common thread that links all major risk factors of infection is their association with gastrointestinal disturbances, but this relationship to C. difficile colonization has never been tested directly. Here, we show that disturbances caused by diarrhoeal events trigger susceptibility to C. difficile colonization. Using survey data of the human gut microbiome, we detected C. difficile colonization and blooms in people recovering from food poisoning and Vibrio cholerae infections. Carriers remained colonized for year-long time scales and experienced highly variable patterns of C. difficile abundance, where increased shedding over short periods of 1–2 d interrupted week-long periods in which C. difficile was undetectable. Given that short shedding events were often linked to gastrointestinal disturbances, our results help explain why C. difficile is frequently detected as a co-infecting pathogen in patients with diarrhoea. To directly test the impact of diarrhoea on susceptibility to colonization, we developed a mouse model of variable disturbance intensity, which allowed us to monitor colonization in the absence of disease. As mice exposed to avirulent C. difficile spores ingested increasing quantities of laxatives, more individuals experienced C. difficile blooms. Our results indicate that the likelihood of colonization is highest in the days immediately following acute disturbances, suggesting that this could be an important window during which transmission could be interrupted and the incidence of infection lowered.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: C. difficile colonization and blooms are associated with recovery from diarrhoeal disturbances.
Fig. 2: C. difficile colonizes patients recovering from V. cholerae infections.
Fig. 3: Azithromycin treatment has no measurable impact on C. difficile colonization and carriage in infants relative to placebo controls.
Fig. 4: Increasing disturbance intensity increases the likelihood and magnitude C. difficile blooms in mice.

Similar content being viewed by others

Data availability

The publicly available data that we reanalysed here were generated by: David et al.30, European Nucleotide Archive under the accession number ERP006059; Hsaio et al.33, NCBI Short Read Archive (SRA) under the accession number PRJEB6358; Caporaso et al.36, MG-RAST under the accession number MG-RAST:4457768.3-4459735.3; Parker et al.34, SRA under accession number ERP022953; and The NIH Human Microbiome Project37 on NCBI under the accession number PRJNA43017. The amplicon sequencing data from the mouse model of varied disturbance intensity are available on the NCBI SRA under the accession number PRJNA507320. The genome of C. difficile BAA1801 is available on NCBI under the accession number PRJNA562328. All source data necessary to reproduce the figures presented in this manuscript are included in this article and its Supplementary information files. The microscope images used to calculate the cell and spore density are available online at Figshare (https://figshare.com/projects/Source_Data_for_Diarrheal_events_can_trigger_long-term_Clostridium_difficile_colonization_with_recurrent_blooms/72824).

Code availability

All custom computer code necessary to reproduce our results are available on GitHub (https://github.com/polzlab/VanInsberghe_2019_Cdiff_colonization).

References

  1. Loo, V. G. et al. Host and pathogen factors for Clostridium difficile infection and colonization. N. Engl. J. Med. 365, 1693–1703 (2011).

    Article  CAS  PubMed  Google Scholar 

  2. Dubberke, E. R. & Olsen, M. A. Burden of Clostridium difficile on the healthcare system. Clin. Infect. Dis. 55, S88–S92 (2012).

  3. Desai, K. et al. Epidemiological and economic burden of Clostridium difficile in the United States: estimates from a modeling approach. BMC Infect. Dis. 16, 303 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  4. Kelly, C. R. et al. Effect of fecal microbiota transplantation on recurrence in multiply recurrent Clostridium difficile infection a randomized trial. Ann. Intern. Med. 165, 609–616 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  5. Reveles, K. R., Lee, G. C., Boyd, N. K. & Frei, C. R. The rise in Clostridium difficile infection incidence among hospitalized adults in the United States: 2001-2010. Am. J. Infect. Control 42, 1028–1032 (2014).

    Article  PubMed  Google Scholar 

  6. Ray, A. J. et al. A multicenter randomized trial to determine the effect of an environmental disinfection intervention on the incidence of healthcare-associated Clostridium difficile infection. Infect. Control Hosp. Epidemiol. 38, 777–783 (2017).

    Article  PubMed  Google Scholar 

  7. Patton, A. et al. Impact of antimicrobial stewardship interventions on Clostridium difficile infection and clinical outcomes: segmented regression analyses. J. Antimicrob. Chemother. 73, 517–526 (2017).

    Article  CAS  Google Scholar 

  8. Bruminhent, J. et al. Clostridium difficile colonization and disease in patients undergoing hematopoietic stem cell transplantation. Biol. Blood Marrow Transplant. 20, 1329–1334 (2014).

    Article  PubMed  Google Scholar 

  9. Leffler, D. A. & Lamont, J. T. Clostridium difficile infection. N. Engl. J. Med. 372, 1539–1548 (2015).

    Article  CAS  PubMed  Google Scholar 

  10. Durovic, A., Widmer, A. F. & Tschudin-Sutter, S. New insights into transmission of Clostridium difficile infection—narrative review. Clin. Microbiol. Infect. 24, 483–492 (2018).

    Article  CAS  PubMed  Google Scholar 

  11. Crobach, M. J. T. et al. Understanding Clostridium difficile Colonization. Clin. Microbiol. Rev. 31, e00021-17 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  12. Tschudin-Sutter, S. et al. Impact of toxigenic Clostridium difficile colonization on the risk of subsequent C. difficile infection in intensive care unit patients. Infect. Control Hosp. Epidemiol. 36, 1324–1329 (2015).

    Article  PubMed  Google Scholar 

  13. Eyre, D. W. et al. Diverse sources of C. difficile infection identified on whole-genome sequencing. N. Engl. J. Med. 369, 1195–1205 (2013).

    Article  CAS  PubMed  Google Scholar 

  14. Kociolek, L. K. et al. Clostridium difficile whole genome sequencing reveals limited transmission among symptomatic children: a single-center analysis. Clin. Infect. Dis. 67, 229–234 (2018).

  15. Guh, A. Y. et al. Risk factors for community-associated Clostridium difficile infection in adults: a case-control study. Open Forum Infect. Dis. 4, ofx171 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. McFarland, L. V., Surawicz, C. M. & Stamm, W. E. Risk factors for Clostridium difficile carriage and C. difficile-associated diarrhea in a cohort of hospitalized patients. J. Infect. Dis. 162, 678–684 (1990).

    Article  CAS  PubMed  Google Scholar 

  17. Dubberke, E. R. et al. Risk factors for acquisition and loss of Clostridium difficile colonization in hospitalized patients. Antimicrob. Agents Chemother. 59, 4533–4543 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Buffie, C. G. et al. Profound alterations of intestinal microbiota following a single dose of clindamycin results in sustained susceptibility to Clostridium difficile-induced colitis. Infect. Immun. 80, 62–73 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Brown, K. A., Khanafer, N., Daneman, N. & Fisman, D. N. Meta-analysis of antibiotics and the risk of community-associated Clostridium difficile infection. Antimicrob. Agents Chemother. 57, 2326–2332 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Tedesco, F., Barton, R. & Alpers, D. Clindamycin-associated colitis: a prospective study. Ann. Intern. Med. 81, 429–433 (1974).

    Article  CAS  PubMed  Google Scholar 

  21. Weingarden, A. R. et al. Microbiota transplantation restores normal fecal bile acid composition in recurrent Clostridium difficile infection. Am. J. Physiol. Gastrointest. Liver Physiol. 306, G310–G319 (2014).

    Article  CAS  PubMed  Google Scholar 

  22. Schubert, A. M., Sinani, H. & Schloss, P. D. Antibiotic-induced alterations of the murine gut microbiota and subsequent effects on colonization resistance against Clostridium difficile. mBio 6, e00974-15 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Davis, M. Y., Zhang, H., Brannan, L. E., Carman, R. J. & Boone, J. H. Rapid change of fecal microbiome and disappearance of Clostridium difficile in a colonized infant after transition from breast milk to cow milk. Microbiome 4, 53 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Zackular, J. P. et al. Dietary zinc alters the microbiota and decreases resistance to Clostridium difficile infection. Nat. Med. 22, 1330–1334 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Seekatz, A. M., Rao, K., Santhosh, K. & Young, V. B. Dynamics of the fecal microbiome in patients with recurrent and nonrecurrent Clostridium difficile infection. Genome Med. 8, 47 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Buffie, C. G. et al. Precision microbiome reconstitution restores bile acid mediated resistance to Clostridium difficile. Nature 517, 205–208 (2015).

    Article  CAS  PubMed  Google Scholar 

  27. Daquigan, N., Seekatz, A. M., Greathouse, K. L., Young, V. B. & White, J. R. High-resolution profiling of the gut microbiome reveals the extent of Clostridium difficile burden. NPJ Biofilms Microbiomes 3, 35 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  28. Vincent, C. et al. Reductions in intestinal Clostridiales precede the development of nosocomial Clostridium difficile infection. Microbiome 1, 18 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  29. Wunderlin, T., Junier, T., Roussel-Delif, L., Jeanneret, N. & Junier, P. Endospore-enriched sequencing approach reveals unprecedented diversity of Firmicutes in sediments. Environ. Microbiol. Rep. 6, 631–639 (2014).

    Article  CAS  PubMed  Google Scholar 

  30. David, L. A. et al. Host lifestyle affects human microbiota on daily timescales. Genome Biol. 15, R89 (2015).

  31. Sender, R., Fuchs, S. & Milo, R. Revised estimates for the number of human and bacteria cells in the body. PLoS Biol. 14, e1002533 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Vandeputte, D. et al. Quantitative microbiome profiling links gut community variation to microbial load. Nature 551, 507–511 (2017).

    Article  CAS  PubMed  Google Scholar 

  33. Hsiao, A. et al. Members of the human gut microbiota involved in recovery from Vibrio cholerae infection. Nature 515, 423–426 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. 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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Jangi, S. & Lamont, J. T. Asymptomatic colonization by Clostridium difficile in infants: implications for disease in later life. J. Pediatr. Gastroenterol. Nutr. 51, 2–7 (2010).

    Article  PubMed  Google Scholar 

  36. Caporaso, J. G. et al. Moving pictures of the human microbiome. Genome Biol. 12, R50 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  37. NIH HMP Working Group et al. The NIH Human Microbiome Project. Genome Res. 19, 2317–2323 (2009).

    Article  CAS  Google Scholar 

  38. Aagaard, K. et al. The Human Microbiome Project strategy for comprehensive sampling of the human microbiome and why it matters. FASEB J. 27, 1012–1022 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Pashankar, D. S. & Bishop, W. P. Efficacy and optimal dose of daily polyethylene glycol 3350 for treatment of constipation and encopresis in children. J. Pediatr. 139, 428–432 (2001).

    Article  CAS  PubMed  Google Scholar 

  40. Kashyap, P. C. et al. Complex interactions among diet, gastrointestinal transit, and gut microbiota in humanized mice. Gastroenterology 144, 967–977 (2013).

    Article  PubMed  Google Scholar 

  41. Miao, J. et al. 16SPIP: a comprehensive analysis pipeline for rapid pathogen detection in clinical samples based on 16S metagenomic sequencing. BMC Bioinform. 18, 568 (2017).

    Article  CAS  Google Scholar 

  42. van Prehn, J. et al. Diagnostic yield of repeat sampling with immunoassay, real-time PCR, and toxigenic culture for the detection of toxigenic Clostridium difficile in an epidemic and a non-epidemic setting. Eur. J. Clin. Microbiol. Infect. Dis. 34, 2325–2330 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Lawley, T. D. et al. Antibiotic treatment of Clostridium difficile carrier mice triggers a supershedder state, spore-mediated transmission, and severe disease in immunocompromised hosts. Infect. Immun. 77, 3661–3669 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Murphy, C. N., Fowler, R. C., Iwen, P. C. & Fey, P. D. Evaluation of the BioFire FilmArray® GastrointestinalPanel in a Midwestern academic hospital. Eur. J. Clin. Microbiol. Infect. Dis. 36, 747–754 (2017).

    Article  CAS  PubMed  Google Scholar 

  45. Halligan, E. et al. Multiplex molecular testing for management of infectious gastroenteritis in a hospital setting: a comparative diagnostic and clinical utility study. Clin. Microbiol. Infect. 20, O460–O467 (2014).

    Article  CAS  PubMed  Google Scholar 

  46. Bartlett, J. G. Antibiotic-associated diarrhea. Clin. Infect. Dis. 15, 573–581 (1992).

    Article  CAS  PubMed  Google Scholar 

  47. Allegretti, J. R. et al. Recurrent Clostridium difficile infection associates with distinct bile acid and microbiome profiles. Aliment. Pharmacol. Ther. 43, 1142–1153 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Shim, J. K., Johnson, S., Samore, M. H., Bliss, D. Z. & Gerding, D. N. Primary symptomless colonisation by Clostridium difficile and decreased risk of subsequent diarrhoea. Lancet 351, 633–636 (1998).

    Article  CAS  PubMed  Google Scholar 

  49. Nagaro, K. J. et al. Nontoxigenic Clostridium difficile protects hamsters against challenge with historic and epidemic strains of toxigenic BI/NAP1/027 C. difficile. Antimicrob. Agents Chemother. 57, 5266–5270 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Eyre, D. W. et al. Asymptomatic Clostridium difficile colonisation and onward transmission. PLoS ONE 8, e78445 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Alasmari, F., Seiler, S. M., Hink, T., Burnham, C. A. D. & Dubberke, E. R. Prevalence and risk factors for asymptomatic Clostridium difficile carriage. Clin. Infect. Dis. 59, 216–222 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  52. Scallan, E. et al. Foodborne illness acquired in the United States—major pathogens. Emerg. Infect. Dis. 17, 7–15 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  53. Hartmann, M., Howes, C. G., Abarenkov, K., Mohn, W. W. & Nilsson, R. H. V-Xtractor: an open-source, high-throughput software tool to identify and extract hypervariable regions of small subunit (16S/18S) ribosomal RNA gene sequences. J. Microbiol. Methods 83, 250–253 (2010).

    Article  CAS  PubMed  Google Scholar 

  54. Schloss, P. D. et al. Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl. Environ. Microbiol. 75, 7537–7541 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Pruesse, E. et al. SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB. Nucleic Acids Res. 35, 7188–7196 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Lawley, T. D. et al. Proteomic and genomic characterization of highly infectious Clostridium difficile 630 spores. J. Bacteriol. 191, 5377–5386 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Babiuk, L. A. & Paul, E. A. The use of fluorescein isothiocyanate in the determination of the bacterial biomass of grassland soil. Can. J. Microbiol. 16, 57–62 (1970).

    Article  CAS  PubMed  Google Scholar 

  59. Pau, G., Fuchs, F., Sklyar, O., Boutros, M. & Huber, W. EBImage—an R package for image processing with applications to cellular phenotypes. Bioinformatics 26, 979–981 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Preheim, S. P., Perrotta, A. R., Martin-Platero, A. M., Gupta, A. & Alm, E. J. Distribution-based clustering: using ecology to refine the operational taxonomic unit. Appl. Environ. Microbiol. 79, 6593–6603 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Callahan, B. J. et al. DADA2: high-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581–583 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Edgar, R. C. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 32, 1792–1797 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Untergasser, A. et al. Primer3—new capabilities and interfaces. Nucleic Acids Res. 40, e115 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Angiuoli, S. V. & Salzberg, S. L. Mugsy: fast multiple alignment of closely related whole genomes. Bioinformatics 27, 334–342 (2011).

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

This work was supported by a grant from the Center for Microbiome Informatics and Therapeutics to M.F.P. D.V. was partially supported by a fellowship through the Natural Sciences and Engineering Research Council of Canada Postgraduate Scholarship-Doctoral. We thank I. Nachamkin (University of Pennsylvania) and N. Pollock (Harvard Medical School) for their comments, which helped improve this study.

Author information

Authors and Affiliations

  1. The Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA

    David VanInsberghe, Joseph A. Elsherbini & Martin F. Polz

  2. The Division of Comparative Medicine, Massachusetts Institute of Technology, Cambridge, MA, USA

    Bernard Varian, Theofilos Poutahidis & Susan Erdman

  3. Department of Pathology, College of Veterinary Medicine, Aristotle University, Thessaloniki, Greece

    Theofilos Poutahidis

  4. Division of Microbial Ecology, Center for Microbiology and Environmental Systems Science, University of Vienna, Vienna, Austria

    Martin F. Polz

Authors
  1. David VanInsberghe
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Joseph A. Elsherbini
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Bernard Varian
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Theofilos Poutahidis
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Susan Erdman
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Martin F. Polz
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

The concept was developed by D.V. and M.F.P. D.V. performed the 16S rRNA amplicon sequence data and C. difficile genomic analyses. D.V., M.F.P. and S.E. designed the mouse model of variable disturbance intensity and D.V. performed the experiment that utilizes this model with the help of B.V. J.A.E. designed the pipeline for analysing the 16S rRNA amplicon sequences from the mouse faecal samples. T.P. and S.E. performed the histological analyses. D.V. and M.F.P. prepared the manuscript.

Corresponding author

Correspondence to Martin F. Polz.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Representative histology of caecum, ileocecal junction, ileum and ascending colon from mice fed varying amounts of polyethylene glycol 3350 (PEG335) while being exposed to avirulent C. difficile spores.

All 40 mice from all treatment groups have comparable intestinal histology and show no evidence of typhlitis, enteritis or colitis. Tissues were collected ten days after treatment. Hematoxylin and Eosin. Bars= 100 m.

Extended Data Fig. 2 Increasing disturbance intensity increases the likelihood and magnitude C. difficile blooms in mice.

Four groups of ten C57BL/6J Mice were single housed in cages with grated bottoms. Non-toxinogenic C. difficile spores were suspended in drinking water at 104 spores/ml for one day prior, during, and two days following PEG3350 laxative treatment. Daily faecal samples were characterized using 16S rRNA PCR amplicon sequencing. The top panels summarize the family-level phylogenetic structure of the faecal microbial community over time, where different shades of the same colour represent different families in the same phyla; Firmicutes and Bacteroidetes families are depicted in green and blue, respectively. Lower panels show the relative abundance of C. difficile over time.

Source data

Extended Data Fig. 3 C. difficile blooms occur the day after treatment when cell density and stool consistency have returned to pre-treatment levels.

(a) The cell density of faecal samples was measured by direct microscopic counts of diluted samples stained with the fluorescent dye fluorescein isothiocyanate (FITC), which covalently binds the amine groups of proteins. Cell density was calculated using 25 images of random fields of the fixed and stained stool samples; center values represent the average cell density and error bars express the 95% confidence intervals of the densities observed for each sample. (b) To confirm the abundance of C. difficile measured using V4 16S rRNA amplicon sequencing (solid line), the abundance was also measured using a qPCR assay that specifically amplifies the rplP gene of C. difficile. (c) Representative stool samples from mice before, during, and after treatment are shown to illustrate how loose the stools of mice fed 150 mg/ml PEG3350 were at the end of treatment, but returned to normal by the following day. All ten mice in the highest PEG3350 treatment group experienced the same pattern of changes in stool consistency over time shown here.

Source data

Extended Data Fig. 4 Isolation of C. difficile colonies and genotype-specific colony PCR confirms that the inoculating strain is responsible for the blooms observed in mice treated with laxatives.

Faecal samples from the two mice that experienced the highest magnitude increase in C. difficile measured via 16S rRNA amplicon sequencing were anaerobically homogenized and two dilutions were plated on cycloserine-cefoxitin fructose agar (CCFA) in duplicate. (A) Only one colony morphology was detected from all samples; ground class texture and diffuse edges are consistent with C. difficile. (B) Colony forming unit (CFU) counts roughly reflect the abundance of C. difficile measured via 16S rRNA sequencing. (C) PCR confirms that all isolates isolated on CCFA plates are the same genotype as the inoculating strain (ATCC BAA1801). The C. difficile specific PCR assay amplifies the rplP locus present in all C. difficile strains, while the assay specific to the BAA1801 genotypic cluster amplifies a gene that is present in BAA1801 and its 19 closest sequenced relatives (differentiated by only 270 SNPs, genome-wide) but no other C. difficile lineage. C. difficile strain ATCC-9689 is a toxinogenic control that can be successfully amplified using the rplP PCR assay but not the assay specific to the BAA1801 genotypic cluster. All 72 isolated colonies from all plated dilutions that grew on the CCFA plates were genotyped with both the rplP and BAA1801 genotypic cluster specific PCR assays once.

Source data

Supplementary information

Reporting Summary

Supplementary Table 1

Summary of 16S rRNA amplicon sequencing data necessary to reproduce the analysis of the mouse model of variable disturbance intensity.

Source data

Source Data Fig. 1

Statistical Source Data.

Source Data Fig. 2

Statistical Source Data.

Source Data Fig. 3

Statistical Source Data.

Source Data Fig. 4

Statistical Source Data.

Source Data Extended Data Fig. 2

Statistical Source Data.

Source Data Extended Data Fig. 3

Statistical Source Data.

Source Data Extended Data Fig. 4

Statistical Source Data.

Source Data Extended Data Fig. 4

Unprocessed DNA gel images.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

VanInsberghe, D., Elsherbini, J.A., Varian, B. et al. Diarrhoeal events can trigger long-term Clostridium difficile colonization with recurrent blooms. Nat Microbiol 5, 642–650 (2020). https://doi.org/10.1038/s41564-020-0668-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41564-020-0668-2

This article is cited by

Search

Advanced search

Quick links

Nature Briefing Microbiology

Sign up for the Nature Briefing: Microbiology newsletter — what matters in microbiology research, free to your inbox weekly.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing: Microbiology