1887

Abstract

is the leading cause of healthcare-associated infectious diarrhoea. However, it is increasingly appreciated that healthcare-associated infections derive from both community and healthcare environments, and that the primary sites of transmission may be strain-dependent. We conducted a multisite genomic epidemiology study to assess differential genomic evidence of healthcare vs community spread for two of the most common strains in the USA: sequence type (ST) 1 (associated with ribotype 027) and ST2 (associated with ribotype 014/020). We performed whole-genome sequencing and phylogenetic analyses on 382 ST1 and ST2 isolates recovered from stool specimens collected during standard clinical care at 3 geographically distinct US medical centres between 2010 and 2017. ST1 and ST2 isolates both displayed some evidence of phylogenetic clustering by study site, but clustering was stronger and more apparent in ST1, consistent with our healthcare-based study more comprehensively sampling local transmission of ST1 compared to ST2 strains. Analyses of pairwise single-nucleotide variant (SNV) distance distributions were also consistent with more evidence of healthcare transmission of ST1 compared to ST2, with 44 % of ST1 isolates being within two SNVs of another isolate from the same geographical collection site compared to 5.5 % of ST2 isolates (-value=<0.001). Conversely, ST2 isolates were more likely to have close genetic neighbours across disparate geographical sites compared to ST1 isolates, further supporting non-healthcare routes of spread for ST2 and highlighting the potential for misattributing genomic similarity among ST2 isolates to recent healthcare transmission. Finally, we estimated a lower evolutionary rate for the ST2 lineage compared to the ST1 lineage using Bayesian timed phylogenomic analyses, and hypothesize that this may contribute to observed differences in geographical concordance among closely related isolates. Together, these findings suggest that ST1 and ST2, while both common causes of infection in hospitals, show differential reliance on community and hospital spread. This conclusion supports the need for strain-specific criteria for interpreting genomic linkages and emphasizes the importance of considering differences in the epidemiology of circulating strains when devising interventions to reduce the burden of infections.

Funding
This study was supported by the:
  • National Institute of Allergy and Infectious Diseases (Award U01AI124275)
    • Principle Award Recipient: EricG. Pamer
  • National Institute of Allergy and Infectious Diseases (Award U01AI124290)
    • Principle Award Recipient: TorC. Savidge
  • National Cancer Institute (Award P30CA008748)
    • Principle Award Recipient: NotApplicable
  • National Institute of Allergy and Infectious Diseases (Award T32AI007528)
    • Principle Award Recipient: NotApplicable
  • National Institute of Allergy and Infectious Diseases (Award U01AI12455)
    • Principle Award Recipient: VincentB. Young
  • This is an open-access article distributed under the terms of the Creative Commons Attribution License.
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2021-06-28
2024-04-27
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References

  1. Magill SS, O’Leary E, Janelle SJ, Thompson DL, Dumyati G et al. Changes in prevalence of health care–associated infections in U.S Hospitals. N Engl J Med 2018; 379:1732–1744
    [Google Scholar]
  2. Lessa FC, Mu Y, Bamberg WM, Beldavs ZG, Dumyati GK et al. Burden of Clostridium difficile infection in the United States. N Engl J Med 2015; 372:825–834 [View Article] [PubMed]
    [Google Scholar]
  3. Martin JSH, Monaghan TM, Wilcox MH. Clostridium difficile infection: Epidemiology, diagnosis and understanding transmission. Nat Rev Gastroenterol Hepatol 2016; 13:206–216 [View Article] [PubMed]
    [Google Scholar]
  4. Eyre DW, Cule ML, Wilson DJ, Griffiths D, Vaughan A et al. Diverse sources of C. difficile infection identified on whole-genome sequencing. N Engl J Med 2013; 369:1195–1205
    [Google Scholar]
  5. Walker AS, Eyre DW, Wyllie DH, Dingle KE, Harding RM et al. Characterisation of Clostridium difficile hospital ward-based transmission using extensive epidemiological data and molecular typing. PLoS Med 2012; 9:
    [Google Scholar]
  6. Martin JSH, Eyre DW, Fawley WN, Griffiths D, Davies K. Patient and strain characteristics associated with Clostridium difficile transmission and adverse outcomes. Clin Infect Dis 2018; 1:9
    [Google Scholar]
  7. Poirier D, Gervais P, Fuchs M, Roussy JF, Paquet-Bolduc B et al. Predictors of Clostridioides difficile infection among asymptomatic, colonized patients: a retrospective cohort study. Clin Infect Dis 2019ciz626
    [Google Scholar]
  8. Eyre DW, Davies KA, Davis G, Fawley WN, Dingle KE et al. Two distinct patterns of Clostridium difficile diversity across Europe indicating contrasting routes of spread. Clin Infect Dis 2018; 67:1035–1044 [View Article] [PubMed]
    [Google Scholar]
  9. Loo VG, Oughton M, Bourgault AM, Kelly M, Dewar K et al. A predominantly clonal multi-institutional outbreak of Clostridium difficile–associated diarrhea with high morbidity and mortality. N Engl J Med 2005; 353:2442–2449 [View Article] [PubMed]
    [Google Scholar]
  10. McDonald LC, Owens RC, Johnson S. An epidemic, toxin gene–variant strain of Clostridium difficile . N Engl J Med 2005; 353:2433–2441 [View Article] [PubMed]
    [Google Scholar]
  11. Warny M, Pepin J, Fang A, Killgore G, Thompson A et al. Toxin production by an emerging strain of Clostridium difficile associated with outbreaks of severe disease in North America and Europe. Lancet 2005; 366:1079–1084
    [Google Scholar]
  12. Kuijper EJ, Barbut F, Brazier JS, Kleinkauf N, Eckmanns T et al. Update of Clostridium difficile infection due to PCR ribotype 027 in Europe, 2008. Eurosurveillance 2008; 13: [View Article]
    [Google Scholar]
  13. Guh AY, Mu Y, Winston LG, Johnston H, Olson D et al. Trends in U.S. Burden of Clostridioides difficile infection and outcomes. N Engl J Med 2020; 382:1320–1330 [View Article]
    [Google Scholar]
  14. Rao K, Micic D, Natarajan M, Winters S, Kiel MJ et al. Clostridium difficile ribotype 027: relationship to age, detectability of toxins A or B in stool with rapid testing, severe infection, and mortality. Clin Infect Dis 2015; 61:233–241 [View Article] [PubMed]
    [Google Scholar]
  15. Gonzales-Luna AJ, Carlson TJ, Dotson KM, Poblete K, Costa G et al. PCR ribotypes of Clostridioides difficile across Texas from 2011 to 2018 including emergence of ribotype 255. Emerg Microbes Infect 2020; 9:341–347 [View Article] [PubMed]
    [Google Scholar]
  16. Kamboj M, McMillen T, Syed M, Chow HY, Jani K et al. Evaluation of a combined multilocus sequence typing and whole-genome sequencing two-step algorithm for routine typing of Clostridioides difficile . J Clin Microbiol 2020; 59:e01955-20 [View Article]
    [Google Scholar]
  17. Endres BT, Begum K, Sun H, Walk ST, Memariani A et al. Epidemic Clostridioides difficile ribotype 027 lineages: comparisons of Texas versus worldwide strains. Open Forum Infect Dis 2019; 6:ofz013 [View Article] [PubMed]
    [Google Scholar]
  18. Martinson JNV, Broadaway S, Lohman E, Johnson C, Alam MJ et al. Evaluation of portability and cost of a fluorescent PCR ribotyping protocol for Clostridium difficile epidemiology. J Clin Microbiol 2015; 53:1192–1197 [View Article] [PubMed]
    [Google Scholar]
  19. Griffiths D, Fawley W, Kachrimanidou M, Bowden R, Crook DW et al. Multilocus sequence typing of Clostridium difficile . J Clin Microbiol 2010; 48:770–778 [View Article] [PubMed]
    [Google Scholar]
  20. Jolley KA, Bray JE, Maiden MCJ. Open-access bacterial population genomics: BIGSdb software, the PubMLST.org website and their applications. Wellcome Open Res 2018; 3:124 [View Article] [PubMed]
    [Google Scholar]
  21. Hunt M, Mather AE, Sánchez-Busó L, Page AJ, Parkhill J et al. ARIBA: rapid antimicrobial resistance genotyping directly from sequencing reads. Microb Genomics 2017; 3:e000131 [View Article]
    [Google Scholar]
  22. Han JH, Lapp Z, Bushman F, Lautenbach E, Goldstein EJC et al. Whole-genome sequencing to identify drivers of carbapenem-resistant Klebsiella pneumoniae transmission within and between regional long-term acute-care hospitals. Antimicrob Agents Chemother 2019; 63:e01622-19 [View Article] [PubMed]
    [Google Scholar]
  23. Bolger AM, Lohse M, Usadel B. Trimmomatic: A flexible trimmer for Illumina sequence data. Bioinformatics 2014; 30:2114–2120 [View Article] [PubMed]
    [Google Scholar]
  24. He M, Sebaihia M, Lawley TD, Stabler RA, Dawson LF et al. Evolutionary dynamics of Clostridium difficile over short and long time scales. Proc Natl Acad Sci U S A 2010; 107:7527–7532 [View Article] [PubMed]
    [Google Scholar]
  25. Yin C, Chen DS, Zhuge J, McKenna D, Sagurton J et al. Complete genome sequences of four toxigenic Clostridium difficile clinical isolates from patients of the lower Hudson Valley, New York, USA. Genome Announc 2018; 6:e01537-17 [View Article] [PubMed]
    [Google Scholar]
  26. Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 2009; 25:1754–1760 [View Article] [PubMed]
    [Google Scholar]
  27. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 2009; 25:2078–2079 [View Article] [PubMed]
    [Google Scholar]
  28. Croucher NJ, Page AJ, Connor TR, Delaney AJ, Keane JA et al. Rapid phylogenetic analysis of large samples of recombinant bacterial whole genome sequences using Gubbins. Nucleic Acids Res 2015; 43:e15 [View Article] [PubMed]
    [Google Scholar]
  29. Nguyen LT, Schmidt HA, Von Haeseler A, Minh BQ. IQ-TREE: A fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol Biol Evol 2015; 32:268–274 [View Article] [PubMed]
    [Google Scholar]
  30. Sebaihia M, Wren BW, Mullany P, Fairweather NF, Minton N et al. The multidrug-resistant human pathogen Clostridium difficile has a highly mobile, mosaic genome. Nat Genet 2006; 38:779–786 [View Article] [PubMed]
    [Google Scholar]
  31. Spigaglia P, Barbanti F, Mastrantonio P, Brazier JS, Barbut F et al. Fluoroquinolone resistance in Clostridium difficile isolates from a prospective study of C. difficile infections in Europe. J Med Microbiol 2008; 57:784–789 [View Article] [PubMed]
    [Google Scholar]
  32. He M, Miyajima F, Roberts P, Ellison L, Pickard DJ et al. Emergence and global spread of epidemic healthcare-associated Clostridium difficile . Nat Genet 2013; 45:109–113 [View Article] [PubMed]
    [Google Scholar]
  33. Popovich KJ, Snitkin ES, Hota B, Green SJ, Pirani A et al. Genomic and epidemiological evidence for community origins of hospital-onset methicillin-resistant Staphylococcus aureus bloodstream infections. J Infect Dis 2017; 215:1640–1647 [View Article] [PubMed]
    [Google Scholar]
  34. Suchard MA, Lemey P, Baele G, Ayres DL, Drummond AJ et al. Bayesian phylogenetic and phylodynamic data integration using BEAST 1.10. Virus Evol 2018; 4:vey016 [View Article] [PubMed]
    [Google Scholar]
  35. Eyre DW, Didelot X, Buckley AM, Freeman J, Moura IB et al. Clostridium difficile trehalose metabolism variants are common and not associated with adverse patient outcomes when variably present in the same lineage. EBioMedicine 2019; 43:347–355 [View Article] [PubMed]
    [Google Scholar]
  36. Rambaut A, Lam TT, Max Carvalho L, Pybus OG. Exploring the temporal structure of heterochronous sequences using TempEst (formerly Path-O-Gen. Virus Evol 2016; 2:vew007 [View Article]
    [Google Scholar]
  37. Didelot X, Croucher NJ, Bentley SD, Harris SR, Wilson DJ. Bayesian inference of ancestral dates on bacterial phylogenetic trees. Nucleic Acids Res 2018; 46:e134 [View Article] [PubMed]
    [Google Scholar]
  38. Duchêne S, Duchêne D, Holmes EC, SYW H. The performance of the date-randomization test in phylogenetic analyses of time-structured virus data. Mol Biol Evol 2015; 32:1895–1906
    [Google Scholar]
  39. Didelot X, Eyre DW, Cule M, CL I, Ansari MA et al. Microevolutionary analysis of Clostridium difficile genomes to investigate transmission. Genome Biol 2012; 13:R118 [View Article]
    [Google Scholar]
  40. Minin VN, Bloomquist EW, Suchard MA. Smooth skyride through a rough skyline: Bayesian coalescent-based inference of population dynamics. Mol Biol Evol 2008; 25:1459–1471 [View Article] [PubMed]
    [Google Scholar]
  41. Rambaut A, Suchard M, Xie D, Drummond A. Tracer v1.6; 2014 http://beast.bio.ed.ac.uk/Tracer
  42. Loo VG, Oughton M, Bourgault AM, Kelly M, Dewar K. A predominantly clonal multi-institutional outbreak of Clostridium difficile–associated diarrhea with high morbidity and mortality. N Engl J Med 2005; 8: [View Article]
    [Google Scholar]
  43. Alam MJ, Walk ST, Endres BT, Basseres E, Khaleduzzaman M et al. Community environmental contamination of toxigenic Clostridium difficile . Open Forum Infect Dis 2017; 4:ofx018 [View Article] [PubMed]
    [Google Scholar]
  44. Dingle KE, Didelot X, Quan TP, Eyre DW, Stoesser N et al. Effects of control interventions on Clostridium difficile infection in England: an observational study. Lancet Infect Dis 2017; 17:411–421 [View Article] [PubMed]
    [Google Scholar]
  45. Davies KA, Ashwin H, Longshaw CM, Burns DA, Davis GL et al. Diversity of Clostridium difficile PCR ribotypes in Europe: results from the European, multicentre, prospective, biannual, point-prevalence study of Clostridium difficile infection in hospitalised patients with diarrhoea (EUCLID), 2012 and 2. Euro Surveill Bull Eur Sur Mal Transm Eur Commun Dis Bull 2016; 21:pii30294
    [Google Scholar]
  46. Tenover FC, Tickler IA, Persing DH. Antimicrobial-resistant strains of Clostridium difficile from North America. Antimicrob Agents Chemother 2012; 56:2929–2932 [View Article] [PubMed]
    [Google Scholar]
  47. Foster NF, Collins DA, Ditchburn SL, Duncan CN, van Schalkwyk JW et al. Epidemiology of Clostridium difficile infection in two tertiary-care hospitals in Perth, Western Australia: a cross-sectional study. New Microbes New Infect 2014; 2:64–71 [View Article] [PubMed]
    [Google Scholar]
  48. Aitken SL, Alam MJ, Khaleduzzaman M, Khaleduzzuman M, Walk ST et al. In the endemic setting, Clostridium difficile ribotype 027 is virulent but not hypervirulent. Infect Control Hosp Epidemiol 2015; 36:1318–1323 [View Article] [PubMed]
    [Google Scholar]
  49. Knight DR, Squire MM, Collins DA, Riley TV. Genome analysis of Clostridium difficile PCR ribotype 014 lineage in australian pigs and humans reveals a diverse genetic repertoire and signatures of long-range interspecies transmission. Front Microbiol 2016; 7:2138 [View Article] [PubMed]
    [Google Scholar]
  50. Janezic S, Zidaric V, Pardon B, Indra A, Kokotovic B et al. International Clostridium difficile animal strain collection and large diversity of animal associated strains. BMC Microbiol 2014; 14:173 [View Article] [PubMed]
    [Google Scholar]
  51. Romano V, Pasquale V, Krovacek K, Mauri F, Demarta A et al. Toxigenic Clostridium difficile PCR ribotypes from wastewater treatment plants in southern Switzerland. Appl Environ Microbiol 2012; 78:6643–6646 [View Article] [PubMed]
    [Google Scholar]
  52. Croucher NJ, Harris SR, Grad YH, Hanage WP. Bacterial genomes in epidemiology–present and future. Philos Trans R Soc Lond B Biol Sci 2013; 368:20120202 [View Article] [PubMed]
    [Google Scholar]
  53. Peacock SJ, Parkhill J, Brown NM. Changing the paradigm for hospital outbreak detection by leading with genomic surveillance of nosocomial pathogens. Microbiology (Reading) 2018; 164:1213–1219 [View Article] [PubMed]
    [Google Scholar]
  54. Weller C, Wu M. A generation-time effect on the rate of molecular evolution in bacteria. Evolution 2015; 69:643–652 [View Article] [PubMed]
    [Google Scholar]
  55. Carlson PE, Walk ST, Bourgis AET, Liu MW, Kopliku F et al. The relationship between phenotype, ribotype, and clinical disease in human Clostridium difficile isolates. Anaerobe 2013; 24:109–116 [View Article] [PubMed]
    [Google Scholar]
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