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Publication: Multicenter Prevalence Study Comparing Molecular and Toxin Assays for Clostridioides difficile Surveillance, Switzerland






Andreas F. Widmer, Reno Frei, Ed J. Kuijper, Mark H. Wilcox, Ruth Schindler, Violeta Spaniol, Daniel Goldenberger, Adrian Egli, Sarah Tschudin-Sutter , and Kuijper
Author affiliations: University Hospital Basel, Basel, Switzerland (A.F. Widmer, R. Frei, R. Schindler, V. Spaniol, D. Goldenberger, A. Egli, S. Tschudin-Sutter)Leiden University Medical Center, Leiden, the Netherlands (E.J. Kuijper)Leeds Institute of Biomedical and Clinical Sciences, University of Leeds, and Leeds Teaching Hospitals, Leeds, UK (M.H. Wilcox)


Public health authorities in the United States and Europe recommend surveillance for Clostridioides difficile infections among hospitalized patients, but differing diagnostic algorithms can hamper comparisons between institutions and countries. We compared surveillance based on the detection of C. difficile by PCR or enzyme immunoassay (EIA) in a nationwide C. difficile prevalence study in Switzerland. We included all routinely collected stool samples from hospitalized patients with diarrhea in 76 hospitals in Switzerland on 2 days, 1 in winter and 1 in summer, in 2015. EIA C. difficile detection rates were 6.4 cases/10,000 patient bed-days in winter and 5.7 cases/10,000 patient bed-days in summer. PCR detection rates were 11.4 cases/10,000 patient bed-days in winter and 7.1 cases/10,000 patient bed-days in summer. We found PCR used alone increased reported C. difficile prevalence rates by <80% compared with a 2-stage EIA-based algorithm.


Since its identification as a cause of antibiotic-associated pseudomembraneous colitis in 1978 (1), Clostridioides difficile has emerged as a major healthcare-associated pathogen worldwide. In the United States, C. difficile infection (CDI) rates doubled during 1996–2003 (2), and rates of CDI were reported to be 76.9 cases/10,000 discharges in 2005 (3). In a more recent national point-prevalence study including US healthcare facility in-patients, 13/1,000 patients were found to be either infected or colonized (4), a higher rate than had been previously estimated. In a national point-prevalence study of nosocomial infections in the United States, C. difficile was the most common causative pathogen overall (5). The increase largely has been attributed to the emergence of the hypervirulent strain, PCR ribotype 027 (RT027), which was identified as causative strain in 82% of cases during CDI outbreaks in Quebec, Canada, during 2001–2003 and accounted for 31% of all cases of healthcare-associated infections in the United States in 2011 (69). In Europe, CDI incidence varies across hospitals and countries with a weighted mean of 4.1 cases/10,000 patient-days per hospital in 2008 (10). The most recent study on CDI prevalence in Europe suggests an increase in the number of cases, reporting a mean of 7.0 cases/10,000 patient-bed days and ranging among countries from 0.7 to 28.7 cases/10,000 patient-bed days (11). The most common ribotype identified was RT027, which was detected in 4 countries: Germany, Hungary, Poland, and Romania (11).

To estimate and compare the burden of CDI across the United States, the US Centers for Disease Control and Prevention (CDC) began population-based CDI surveillance in 10 locations in 2011 (12). The European Centre for Disease Prevention and Control (ECDC) began coordinating CDI surveillance in acute care hospitals in Europe in 2016 (13). Both authorities provide case definitions based on different diagnostic approaches, including detection of C. difficile toxin A and B by enzyme immunoassay (EIA) or detection of toxin-producing C. difficile organisms by PCR. However, the use of different diagnostic algorithms to detect C. difficile might hamper comparisons between institutions and countries. Therefore, in a nationwide C. difficile multicenter prevalence study in Switzerland, we systematically compared surveillance measures based on detection of C. difficile in stool by either PCR as a stand-alone test or by a 2-stage algorithm consisting of an EIA to detect glutamate dehydrogenase (GDH) and toxins A and B.


Study Design

We performed a nationwide multicenter prevalence study of toxigenic C. difficile detected in stool samples routinely collected from hospitalized patients with diarrhea. Our study followed the design of a previous point-prevalence study for maximal comparability between our results and data from Europe (11). University Hospital Basel, a tertiary care center in Switzerland, coordinated the study. All hospitals participating in Swissnoso (https://www.swissnoso.chExternal Link), a national infection prevention network, were asked to participate. The Swissnoso network consists of 85 acute care hospitals that account for a total of 26,341 beds.

The Ethics Committee Northwest and Central Switzerland (Ethikkommission Nordwest-und Zentralschweiz) issued a declaration of no objection for this study. We adhered to STROBE guidelines for reporting on observational studies (14).

Sample Collection

All stool samples collected from inpatients >1 year of age with diarrhea that were submitted to the microbiology laboratory on 2 specified sampling days, 1 in winter and 1 in summer, in 2015 were eligble for inclusion. Only 1 sample per patient was included. In addition, stool samples that tested positive for toxigenic C. difficile <1 week prior to each study day also were collected from all institutions to obtain a more detailed estimate of ribotype distribution in Switzerland.

We collected the following institutional data for all hospitals and their affiliated microbiology laboratories: contact information; detailed information regarding laboratory diagnostics in place; and detailed information on the total number of admissions, number of beds, and number of patients hospitalized on the 2 days of the study. We also collected information on the total number of diagnosed CDI cases at each institution during the study year. For each eligible stool sample, we collected the following data: date of sample collection, age and gender of patient, ward location and clinical specialty, institution, whether a C. difficile test was ordered by the treating physician, and result of the C. difficile test if testing was performed at the local laboratory.


We tested all stool samples at the Division of Clinical Microbiology of the University Hospital Basel by using a 2-stage algorithm consisting of EIA and PCR. We performed EIA to detect GDH and toxins A and B by using C. DIFF QUIK CHEK COMPLETE (Techlab, https://www.techlab.comExternal Link), following the manufacturer’s instructions. We then performed PCR to detect the toxin B gene by using the RealStar PCR Kit (Altona Diagnostics, https://www.altona-diagnostics.comExternal Link). For detected C. difficile, we performed strain typing by using high-resolution capillary gel-based PCR ribotyping according to the method previously described by Stubbs et al. (15).


We calculated reported and measured rates of detected toxigenic C. difficile per 10,000 patient bed-days across participating institutions. We compared differences in testing algorithms for detection of toxigenic C. difficile across institutions in Switzerland and performance characteristics of diagnostic algorithms. We considered the proportion of missed toxigenic C. difficile cases and ribotype distributions as additional outcomes. We further assessed the proportion of laboratories using optimized C. difficile diagnostic tests, which we defined as using an algorithm recommended by the European Society of Clinical Microbiology and Infectious Diseases (16).

Statistical Analyses

We separately calculated rates for each diagnostic algorithm performed in the coordinating center laboratory. In addition, we separately calculated rates for dedicated children’s hospitals. We defined missed C. difficile cases as those in which tests were negative at the participating hospital’s laboratory but positive at our institution. We used descriptive statistics to report ribotypes and differences in diagnostic algorithms across all participating institutions. All analyses were performed in Stata version 15.1 (StataCorp, https://www.stata.comExternal Link).


Figure 1. Distribution of centers participating in a prevalence study comparing molecular and toxin assays for nationwide surveillance of Clostridioides difficile, Switzerland. Red circles represent the location of participating centers.

Participating institutions included 76/85 (89.4%) institutions belonging to the Swissnoso network. Among participating institutions, 5 were academic teaching hospitals, 3 were dedicated children’s hospitals, and 36 were affiliated microbiology laboratories. Participating institutions were distributed across all geographic regions of Switzerland (Figure 1).

Participating institutions reported collecting a fecal sample for microbiological workup in »65% (SD +25%) of all patients with hospital-onset diarrhea. Among participating institutions, 15/76 (19.7%) did not begin CDI treatment before fecal sample collection. Among institutions that initiated treatment before collecting fecal samples, 23/76 (30.3%) began treatment in <2% of patients, 12/76 (15.8%) began treatment in 3%–5% of patients, 8/76 (10.5%) began treatment in 6%–10% of patients, and 1 (1.3%) began treatment in 11%–20% of patients. The other 17 (22%) institutions were not able to provide an estimate of these data.

Overall, 354 stool samples were submitted to the coordinating center, of which 338 were eligible for study inclusion; 16 samples were excluded because they were not liquid, their submitted data were incomplete, or they were duplicate samples from 1 patient. Among 338 samples included, 250 were collected as part of the point-prevalence study. We excluded 8 of these because the samples were collected from patients <1 year of age. In all, we included 242 samples in the point-prevalence study.

Diagnostic Algorithms

Figure 2. Testing algorithms at the 36 laboratories participating in a prevalence study comparing molecular and toxin assays for nationwide surveillance of Clostridioides difficile, Switzerland. EIA, enzyme immunoassay; GDH, glutamate dehydrogenase; NAAT, nucleic…

Among the 36 participating laboratories, 1 routinely tested all diarrheal stool samples for toxigenic C. difficile and 35 tested only if a specific test was requested. Optimized diagnostic tests for detection of toxigenic C. difficile were used by 58% (21/36) of laboratories in the winter sampling period and by 61% (22/36) in the summer sampling period. Among laboratories not following the recommendations of the European Society of Clinical Microbiology and Infectious Diseases (16), 9 in the winter sampling period and 10 in the summer sampling period used a nucleic acid amplification test (NAAT) alone, and 5 in the winter sampling period and 3 in the summer sampling period used EIAs for A and B toxins either as a standalone test or as an initial screening test. Only 1 laboratory reported having established PCR ribotyping methodologies (Figure 2).

Point-Prevalence Analyses

We collected demographic characteristics of patients whose stool samples tested positive by our testing algorithms (Table 1). C. difficile tests were required and performed for 68% (165/242) of stool samples; 6% (27/165) were reported as positive by the affiliated microbiology laboratory.

At the coordinating center, we detected C. difficile in 9% (21/242) of samples by EIA for GDH and A and B toxins and in 12% (30/242) of samples by PCR alone. Among all 27 samples reported as positive by the participating centers, we confirmed 18 (67%) by EIA and 24 (89%) by PCR. Among 138 samples reported as negative by the participating centers, 1 (1%) sample tested positive by EIA and 3 (2%) tested positive by PCR at the coordinating center. Among 77 samples not tested for C. difficile at the participating centers, we detected C. difficile in 2 (3%) by EIA and in 3 (4%) by PCR. Among 21 stool samples that tested positive by EIA at the coordinating center, a C. difficile test was not requested in 2 (10%) cases. Among 30 samples that tested positive by PCR at the coordinating center, a C. difficile test was not requested in 3 cases (10%; Table 2).

Measured detection and testing rates of toxigenic C. difficile were higher than the reported rates across all participating institutions (Table 3). Depending on the diagnostic algorithm applied, the largest difference in prevalence across all institutions was measured during the winter sampling period, which had a prevalence of 6.4 cases/10,000 patient bed-days by EIA and 11.4 cases/10,000 patient bed-days by PCR alone. Thus, across all institutions, rates of toxigenic C. difficile detection by PCR alone were <80% higher than detection rates by EIA for GDH and A and B toxins. In addition, detection rates by PCR alone were <100% higher in dedicated children’s hospitals (Table 3).

Ribotype Distribution

Figure 3. Distribution of PCR ribotypes among 107 samples collected in a prevalence study comparing molecular and toxin assays for nationwide surveillance of Clostridioides difficile, Switzerland. *Unknown ribotype.

We cultured and ribotyped 107 toxigenic C. difficile strains, 29 from the 2 point-prevalence days and 78 collected <1 week before each prevalence day. We identified a large diversity of C. difficile ribotypes, 23 (22%) had not been referenced before. The ribotypes most commonly identified included RT014 (12/107; 11%), presumably hypervirulent RT078 (9/107; 8%), RT001 (7/107; 7%), and RT002 (7/107; 7%) (Figure 3).



In this nationwide multicenter study, we found that PCR as a stand-alone test increased reported C. difficile prevalence rates <80% compared with a 2-stage EIA-based algorithm. At first glance, this finding was not surprising given the higher sensitivity of EIA (16). However, the fact that our results and conclusions are based on a nationwide cohort representing all geographic regions of Switzerland adds to the study’s credibility. In addition, our results strengthen the advice of the European Society of Clinical Microbiology and Infectious Diseases study group for C. difficile against use of a single commercial test for diagnosing CDI because of the low positive predictive values when CDI prevalence is low, 46% at a CDI prevalence of 5% (16). However, CDC and ECDC protocols for CDI surveillance define a case of CDI as the combination of diarrheal stool and a positive PCR (12,13). In addition, the clinical practice guidelines for CDI in adults and children published by the Infectious Diseases Society of America and Society for Healthcare Epidemiology of America recommend testing by different approaches, such as multistep algorithms or NAAT, depending on the degree of clinical suspicion (17). Based on a systematic review and meta-analysis, the American Society of Microbiology also recommends different approaches, including NAAT-only testing, and algorithms that include GDH and NAAT or GDH, toxins, and NAAT (18). Although these recommendations stand to reason for detection of CDI in individual patients, our results challenge their utility for meaningful comparisons in surveillance studies and suggest that uniform definitions should be provided.

On both point-prevalence days, we noted a higher nationwide rate of toxigenic C. difficile than previously reported in incidence studies performed at different institutions in Switzerland (1921). Our findings suggest that CDI rates have increased during the last decade in Switzerland, a finding that is in line with reports from other countries in Europe (11). Using the same diagnostic algorithm, diagnostic test, and a similar study design to the multicenter point-prevalence study of CDI in hospitalized patients with diarrhea in Europe, the nationwide mean prevalence rates are comparable in Switzerland (mean 6.1 cases/10,000 patient bed-days) and Europe (7.0 cases/10,000 patient bed-days) (11). Because we only included liquid stools in our study, our mean prevalence rate of 9.3 cases/10,000 patient bed-days measured by PCR fulfills the ECDC case definition and further shows that CDI is increasing substantially nationwide.

We found a lower proportion of missed detection of toxigenic C. difficile in Switzerland (9.5%), driven by the absence of clinical suspicion, compared with Europe (23%), which equates to 1 missed case of C. difficile per day among the included institutions in Switzerland. False-negative testing accounted for 1 additional missed diagnosis during both point-prevalence days, which extrapolates to »550 missed cases of C. difficile per year among hospitals across the nation.

We detected a variety of different RTs during our study period, 21% of which had not been referenced before. Of note, we did not recover hypervirulent RT027, but RT078 was the third most common strain circulating in Switzerland during our study. In contrast, a point-prevalence study in Europe identified RT027 as the most commonly circulating strain during its study period but did not detect RT078. RT078 has been associated with similarly severe disease manifestations as RT027, but RT078 has been reported to affect younger patients and to be linked more commonly with community-associated disease in the Netherlands (22). RT078 has been isolated from piglets with diarrhea, possibly suggesting ongoing transmission by introduction to the food chain because isolates from humans and pigs were found to be highly genetically related (22). A component of RT078 infections also was reported in Northern Ireland, which has a large pig population and »1:1 ratio of cattle to humans (23). In Switzerland, RT078 has been isolated previously from 6 wastewater treatment plants, suggesting its dissemination in the community (24). Except for both hypervirulent RT027 and RT078, we identified other similarities in RT distribution between Switzerland and the rest of Europe; RT014, RT001, RT002, and RT020 were among the 10 most commonly identified ribotypes in both settings.

Our study has some limitations, most of which are intrinsic to point-prevalence studies. First, our study only reflects frequency of toxigenic C. difficile detected on 2 days in 2015; therefore, we cannot draw solid conclusions regarding incidence. We expanded the timeframe for assessing the distribution of ribotypes circulating in Switzerland by an additional week for each prevalence day, but this still represents a limited collection of the true incidence. Second, we cannot rule out introduction of bias to testing policies at the participating hospitals, which might have increased testing on the 2 point-prevalence days. However, we did not provide any promotional information regarding our study, so alterations in daily clinical practice among treating physicians is unlikely on these 2 days. Third, we only included liquid stool samples for analyses, but we did not consider any other preanalytical factors, such as the use of laxatives, for testing eligibility. Finally, we applied surveillance definitions recommended by CDC and ECDC rather than defintions used for the clinical diagnosis of CDI in individual patients, such as detection of C. difficile in the context of symptoms related to CDI. Therefore, we cannot rule out detection of toxigenic C. difficile from colonization rather than infection in some cases.

In conclusion, this nationwide multicenter study reveals that PCR as a stand-alone test results in an increase of C. difficile prevalence rates of <80% compared with a 2-stage EIA-based algorithm. Our findings underscore the need for consistent testing algorithms for meaningful interinstitutional and nationwide comparisons. Our results also challenge the utility of the current CDC and ECDC case definitions and highlight the need for uniform recommendations on diagnostic approaches.


Dr. Widmer is head of the infection control program at University Hospital Basel, University of Basel, Switzerland. His research interests include all aspects of Clostridioides difficile and the epidemiology and prevention of hospital-acquired infections.



We acknowledge and thank the ESCMID (European Society of Clinical Microbiology and Infectious Diseases) Study group for C. difficile (ESGCD) for professional support. We also thank all participating centers and laboratories (Appendix).

Astellas Pharmaceuticals Europe provided financial support for this study. The funder did not influence the study design and did not contribute to data collection, data analysis, data interpretation, or writing of the report. Astellas Pharma Europe reviewed the report for factual accuracy before submission, in line with the terms of the funding agreement. The corresponding author had full access to all data in the study and had final responsibility for the decision to submit for publication. Alere provided C. DIFF QUIK CHEK COMPLETE test kits for conducting EIAs to detect GDH and toxins A and B.

The authors declare the following possible conflicts of interest: A.W. is a member of the Astellas and Merck Sharp & Dohme Corp. advisory boards for C. difficile and reports grants from the Swiss National Science Foundation. S.T.-S. is a member of the Astellas and Merck Sharp & Dohme Corp. advisory boards for C. difficile and reports grants from the Swiss National Science Foundation (grant nos. NRP72 and 407240_167060), the Gottfried und Julia Bangerter-Rhyner Stiftung, and the Fund for the Promotion of Teaching and Research of the Voluntary Academic Society, Base


  1. Bartlett  JGMoon  NChang  TWTaylor  NOnderdonk  ABRole of Clostridium difficile in antibiotic-associated pseudomembranous colitis. Gastroenterology1978;75:77882DOIExternal LinkPubMedExternal Link
  2. McDonald  LCOwings  MJernigan  DBClostridium difficile infection in patients discharged from US short-stay hospitals, 1996-2003. Emerg Infect Dis2006;12:40915DOIExternal LinkPubMedExternal Link
  3. Elixhauser  AJhung  MClostridium difficile-associated disease in U.S. hospitals, 1993–2005: statistical brief #50; Healthcare Cost and Utilization Project (HCUP). Rockville (MD, USA): Agency for Healthcare Research and Quality; 2008 [cited 2019 May 26]. https://www.hcup-us.ahrq.gov/reports/statbriefs/sb50.jspExternal Link
  4. Jarvis  WRSchlosser  JJarvis  AAChinn  RYNational point prevalence of Clostridium difficile in US health care facility inpatients, 2008. Am J Infect Control2009;37:26370DOIExternal LinkPubMedExternal Link
  5. Magill  SSEdwards  JRBamberg  WBeldavs  ZGDumyati  GKainer  MAet al.Emerging Infections Program Healthcare-Associated Infections and Antimicrobial Use Prevalence Survey TeamMultistate point-prevalence survey of health care–associated infections. N Engl J Med2014;370:1198208DOIExternal LinkPubMedExternal Link
  6. Pépin  JSaheb  NCoulombe  MAAlary  MECorriveau  MPAuthier  Set al. Emergence of fluoroquinolones as the predominant risk factor for Clostridium difficile-associated diarrhea: a cohort study during an epidemic in Quebec. Clin Infect Dis2005;41:125460DOIExternal LinkPubMedExternal Link
  7. Loo  VGPoirier  LMiller  MAOughton  MLibman  MDMichaud  Set al. A predominantly clonal multi-institutional outbreak of Clostridium difficile-associated diarrhea with high morbidity and mortality. N Engl J Med2005;353:24429DOIExternal LinkPubMedExternal Link
  8. O’Donoghue  CKyne  LUpdate on Clostridium difficile infection. Curr Opin Gastroenterol2011;27:3847DOIExternal LinkPubMedExternal Link
  9. Lessa  FCMu  YBamberg  WMBeldavs  ZGDumyati  GKDunn  JRet al. Burden of Clostridium difficile infection in the United States. N Engl J Med2015;372:82534DOIExternal LinkPubMedExternal Link
  10. Bauer  MPNotermans  DWvan Benthem  BHBrazier  JSWilcox  MHRupnik  Met al.ECDIS Study GroupClostridium difficile infection in Europe: a hospital-based survey. Lancet2011;377:6373DOIExternal LinkPubMedExternal Link
  11. Davies  KALongshaw  CMDavis  GLBouza  EBarbut  FBarna  Zet al. Underdiagnosis of Clostridium difficile across Europe: the European, multicentre, prospective, biannual, point-prevalence study of Clostridium difficile infection in hospitalised patients with diarrhoea (EUCLID). Lancet Infect Dis2014;14:120819DOIExternal LinkPubMedExternal Link
  12. US Centers for Disease Control and PreventionClostridioides difficile infection (CDI) tracking. [cited 2019 May 26]. https://www.cdc.gov/hai/eip/cdiff-tracking
  13. European Centre for Disease Prevention and Control. Surveillance and disease data for Clostridium difficile infections. [cited 2019 May 26]. https://ecdc.europa.eu/en/clostridium-difficile-infections/surveillance-and-disease-dataExternal Link
  14. von Elm  EAltman  DGEgger  MPocock  SJGøtzsche  PCVandenbroucke  JPSTROBE InitiativeThe Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Lancet2007;370:14537DOIExternal LinkPubMedExternal Link
  15. Stubbs  SLBrazier  JSO’Neill  GLDuerden  BIPCR targeted to the 16S-23S rRNA gene intergenic spacer region of Clostridium difficile and construction of a library consisting of 116 different PCR ribotypes. J Clin Microbiol1999;37:4613DOIExternal LinkPubMedExternal Link
  16. Crobach  MJPlanche  TEckert  CBarbut  FTerveer  EMDekkers  OMet al. European Society of Clinical Microbiology and Infectious Diseases: update of the diagnostic guidance document for Clostridium difficile infection. Clin Microbiol Infect2016;22(Suppl 4):S6381DOIExternal LinkPubMedExternal Link
  17. McDonald  LCGerding  DNJohnson  SBakken  JSCarroll  KCCoffin  SEet al. Clinical practice guidelines for Clostridium difficile infection in adults and children: 2017 update by the Infectious Diseases Society of America (IDSA) and Society for Healthcare Epidemiology of America (SHEA). Clin Infect Dis2018;66:98794DOIExternal LinkPubMedExternal Link
  18. Kraft  CSParrott  JSCornish  NERubinstein  MLWeissfeld  ASMcNult  Pet al. A laboratory medicine best practices systematic review and meta-analysis of nucleic acid amplification tests (NAATs) and algorithms including NAATs for the diagnosis of Clostridioides (Clostridiumdifficile in adults. Clin Microbiol Rev2019;32:e0003218.PubMedExternal Link
  19. Fenner  LFrei  RGregory  MDangel  MStranden  AWidmer  AFEpidemiology of Clostridium difficile-associated disease at University Hospital Basel including molecular characterisation of the isolates 2006-2007. Eur J Clin Microbiol Infect Dis2008;27:12017DOIExternal LinkPubMedExternal Link
  20. Vernaz  NSax  HPittet  DBonnabry  PSchrenzel  JHarbarth  STemporal effects of antibiotic use and hand rub consumption on the incidence of MRSA and Clostridium difficile. J Antimicrob Chemother2008;62:6017DOIExternal LinkPubMedExternal Link
  21. Kohler  PBregenzer-Witteck  ARafeiner  PSchlegel  MPresumably hospital-transmitted Clostridium difficile infections based on epidemiological linkage. Swiss Med Wkly2013;143:w13824. DOIExternal LinkPubMedExternal Link
  22. Goorhuis  ABakker  DCorver  JDebast  SBHarmanus  CNotermans  DWet al. Emergence of Clostridium difficile infection due to a new hypervirulent strain, polymerase chain reaction ribotype 078. Clin Infect Dis2008;47:116270DOIExternal LinkPubMedExternal Link
  23. Patterson  LWilcox  MHFawley  WNVerlander  NQGeoghegan  LPatel  BCet al. Morbidity and mortality associated with Clostridium difficile ribotype 078: a case–case study. J Hosp Infect2012;82:1258DOIExternal LinkPubMedExternal Link
  24. Romano  VPasquale  VKrovacek  KMauri  FDemarta  ADumontet  SToxigenic Clostridium difficile PCR ribotypes from wastewater treatment plants in southern Switzerland. Appl Environ Microbiol2012;78:66436DOIExternal LinkPubMedExternal Link

Cite This Article

DOI: 10.3201/eid2610.190804

Original Publication Date: September 09, 2020


Resource:  https://wwwnc.cdc.gov/eid/article/26/10/19-0804_article

Research Provides a Promising Starting Point for Scientists Developing Medications That Can Resolve C. diff. Infections

A newly published paper in PNAS details a research breakthrough that provides a promising starting point for scientists to create drugs that can cure C. diff — a virulent infection associated with health care facilities that cause severe diarrhea, nausea, internal bleeding, and potentially death. The bacteria affect roughly half a million Americans and cause nearly 15,000 deaths in the U.S. annually.

Overuse of antibiotics has increased the risk of patients in health care facilities acquiring C. diff and made some strains of the bacteria particularly hard to treat. But newly discovered information about a type of toxin released by the most dangerous strains of C. diff is providing researchers with a map to develop drugs that can block the toxin and prevent the bacteria from entering human cells.

NSF-funded researchers at CUNY, Merck and the University of Maryland used a combination of tools — cryogenic electron microscopy, X-ray crystallography, nuclear magnetic resonance spectroscopy, and small-angle X-ray scattering — to observe and identify the C. diff toxin’s structure and mode of action.

The scientists believe that it is a binary toxin (it needs two components to function) that might employ a method similar to that used by anthrax to enter cells. Using this information as their starting point, the researchers sought to characterize how the C. diff toxin is different from anthrax.

The researchers observed two similar but distinct forms of the C. diff toxin — one where they saw a pore-forming channel and one where the channel was invisible. That observation gave them clues about how to stop the channel from forming and bacteria from entering the cell.

According to Robin McCarley, a program director in NSF’s Division of Chemistry, “NSF funds this type of research because it allows a fundamental understanding of the behavior, at the molecular level, of a highly complex biological system with broad impacts on society.”





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CspC Plays a Critical Role in Regulating C. diff. Spore Germination in Response to Multiple Environmental Signals.


The gastrointestinal pathogen, Clostridioides difficile, initiates infection when its metabolically dormant spore form germinates in the mammalian gut. While most spore-forming bacteria use transmembrane germinant receptors to sense nutrient germinants, C. difficile is thought to use the soluble pseudoprotease, CspC, to detect bile acid germinants. To gain insight into CspC’s unique mechanism of action, we solved its crystal structure. Guided by this structure, we identified CspC mutations that confer either hypo- or hyper-sensitivity to bile acid germinant. Surprisingly, hyper-sensitive CspC variants exhibited bile acid-independent germination as well as increased sensitivity to amino acid and/or calcium co-germinants. Since mutations in specific residues altered CspC’s responsiveness to these different signals, CspC plays a critical role in regulating C. difficile spore germination in response to multiple environmental signals. Taken together, these studies implicate CspC as being intimately involved in the detection of distinct classes of co-germinants in addition to bile acids and thus raises the possibility that CspC functions as a signaling node rather than a ligand-binding receptor

Author summary

The major nosocomial pathogen Clostridioides difficile depends on spore germination to initiate infection. Interestingly, C. difficile’s germinant sensing mechanism differs markedly from other spore-forming bacteria, since it uses bile acids to induce germination and lacks the transmembrane germinant receptors conserved in almost all spore-forming organisms. Instead, C. difficile is thought to use CspC, a soluble pseudoprotease, to sense these unique bile acid germinants. To gain insight into how a pseudoprotease senses germinant and propagates this signal, we solved the crystal structure of C. difficile CspC. Guided by this structure, we identified mutations that alter the sensitivity of C. difficile spores to not only bile acid germinant but also to amino acid and calcium co-germinants. Taken together, our study implicates CspC in either directly or indirectly sensing these diverse small molecules and thus raises new questions regarding how C. difficile spores physically detect bile acid germinants and co-germinants.


  • Amy E. Rohlfing ,
  • Brian E. Eckenroth ,
  • Emily R. Forster,
  • Yuzo Kevorkian,
  • M. Lauren Donnelly,
  • Hector Benito de la Puebla,
  • Sylvie Doublié,
  • Aimee Shen

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  • Published: July 5, 2019

Researchers Find Sulfated glycosaminoglycans and Low-Density Lipoprotein Receptor Contribute To Clostridioides difficile Toxin A Cell Entry



Clostridium difficile toxin A (TcdA) is a major exotoxin contributing to disruption of the colonic epithelium during C. difficile infection. TcdA contains a carbohydrate-binding combined repetitive oligopeptides (CROPs) domain that mediates its attachment to cell surfaces, but recent data suggest the existence of CROPs-independent receptors. Here, we carried out genome-wide clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated protein 9 (Cas9)-mediated screens using a truncated TcdA lacking the CROPs, and identified sulfated glycosaminoglycans (sGAGs) and low-density lipoprotein receptor (LDLR) as host factors contributing to binding and entry of TcdA. TcdA recognizes the sulfation group in sGAGs. Blocking sulfation and glycosaminoglycan synthesis reduces TcdA binding and entry into cells. Binding of TcdA to the colonic epithelium can be reduced by surfen, a small molecule that masks sGAGs, by GM-1111, a sulfated heparan sulfate analogue, and by sulfated cyclodextrin, a sulfated small molecule. Cells lacking LDLR also show reduced sensitivity to TcdA, although binding between LDLR and TcdA are not detected, suggesting that LDLR may facilitate endocytosis of TcdA. Finally, GM-1111 reduces TcdA-induced fluid accumulation and tissue damage in the colon in a mouse model in which TcdA is injected into the caecum. These data demonstrate in vivo and pathological relevance of TcdA-sGAGs interactions, and reveal a potential therapeutic approach of protecting colonic tissues by blocking these interactions.

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A Systematic Review Evaluates the Diagnostic Accuracy of Laboratory Testing Algorithms that Include Nucleic Acid Amplification Tests (NAATs) to Detect the Presence of C. difficile


The evidence base for the optimal laboratory diagnosis of Clostridioides (Clostridium) difficile in adults is currently unresolved due to the uncertain performance characteristics and various combinations of tests.

This systematic review evaluates the diagnostic accuracy of laboratory testing algorithms that include nucleic acid amplification tests (NAATs) to detect the presence of C. difficile. The systematic review and meta-analysis included eligible studies (those that had PICO [population, intervention, comparison, outcome] elements) that assessed the diagnostic accuracy of NAAT alone or following glutamate dehydrogenase (GDH) enzyme immunoassays (EIAs) or GDH EIAs plus C. difficile toxin EIAs (toxin). The diagnostic yield of NAAT for repeat testing after an initial negative result was also assessed.

Two hundred thirty-eight studies met inclusion criteria. Seventy-two of these studies had sufficient data for meta-analysis. The strength of evidence ranged from high to insufficient. The uses of NAAT only, GDH-positive EIA followed by NAAT, and GDH-positive/toxin-negative EIA followed by NAAT are all recommended as American Society for Microbiology (ASM) best practices for the detection of the C. difficile toxin gene or organism. Meta-analysis of published evidence supports the use of testing algorithms that use NAAT alone or in combination with GDH or GDH plus toxin EIA to detect the presence of C. difficile in adults. There is insufficient evidence to recommend against repeat testing of the sample using NAAT after an initial negative result due to a lack of evidence of harm (i.e., financial, length of stay, or delay of treatment) as specified by the Laboratory Medicine Best Practices (LMBP) systematic review method in making such an assessment. Findings from this systematic review provide clarity to diagnostic testing strategies and highlight gaps, such as low numbers of GDH/toxin/PCR studies, in existing evidence on diagnostic performance, which can be used to guide future clinical research studies.

SOURCE:  To Learn More:  https://cmr.asm.org/content/32/3/e00032-18.long?utm_source=dlvr.it&utm_medium=twitter


Clostridioides (Clostridium) difficile infection (CDI) is the leading cause of health care-associated infections in the United States (1, 2). It accounts for 15% to 25% of health care-associated diarrhea cases in all health care settings, with 453,000 documented cases of CDI and 29,000 deaths in the United States in 2015 (3). Acquisition of C. difficile as a health care-associated infection (HAI) is associated with increased morbidity and mortality. This adds a significant burden to the health care system by increasing the length of hospital stay and readmission rates, with significant financial implications. The cost of hospital-associated CDI ranges from $10,000 to $20,000 per case (47) and $500 million to $1.5 billion per year nationally (1, 4, 5, 810).

Accurate diagnosis of CDI is critical for effective patient management and implementation of infection control measures to prevent transmission (11). The diagnosis of CDI requires the combination of appropriate test ordering and accurate laboratory testing to differentiate CDI from non-CDI diarrheal cases, including non-CDI diarrhea in a C. difficile-colonized patient (8). Accurate diagnosis of CDI is critical for appropriate patient management and reduction of harms that may arise from diagnostic error (12) and is critical for implementation of infection control measures to prevent transmission (11). Consequently, among patients presenting with diarrhea, there is significant potential for underdiagnosis or overdiagnosis as can arise from incorrect diagnostic workups (13).

Quality Gap: Factors Associated with the Laboratory Diagnosis of C. difficile

Best practices for laboratory diagnosis of CDI remain controversial (14). Current laboratory practice is not standardized, with wide variation in test methods and diagnostic algorithms. Several laboratory assays are available to support CDI diagnosis in combination with clinical presentation. These include toxigenic culture (TC); the cell cytotoxicity neutralization assay (CCNA); enzyme immunoassays (EIAs) and immunochromatographic assays for the detection of glutamate dehydrogenase (GDH), toxin A or B, or both toxins; and, within the last 10 years, nucleic acid amplification tests (NAATs). Currently, two tests, TC and the CCNA, serve as reference methods for the diagnosis of C. difficile infection (15). The principle of the TC test is to detect strains of C. difficile that produce a toxin(s) following culture on an appropriate medium. CCNA detects fecal protein toxins contained within the stool and is often referred to as fecal toxin detection (16). Unfortunately, both tests are slow and labor-intensive.

Commercially available NAATs for C. difficile detection include those based on PCR or loop-mediated or helicase-dependent isothermal amplification (1720). The performance of NAATs and non-NAAT tests is commonly assessed using diagnostic accuracy measures for the presence of the organism (e.g., diagnostic sensitivity, diagnostic specificity, positive predictive value [PPV], and negative predictive value [NPV]). However, these measures may not directly link to the clinical definition of CDI or clinical outcomes, and some measures (e.g., PPV and NPV) are dependent on disease prevalence in the patient population being tested (8, 17, 19, 20). Finally, in addition to diagnostic sensitivity and specificity, other factors influence the choice of testing strategy, such as cost and turnaround time.

The diagnostic accuracies of current commercially available assays (GDH EIAs, toxin A/B EIAs, and NAATs) are based on comparison with one or both of the currently accepted reference methods (TC and CCNA) for the detection of toxigenic C. difficile, and these comparisons are generally made to inform potential replacement of these reference methods. Although a definitive reference “gold standard” is lacking, both TC and CCNA are regarded as acceptable reference methods (15). However, some view the gold standard to be TC of a stool specimen combined with colonic histopathology of pseudomembranous colitis in patients with symptoms, but it is known that there is a spectrum of disease wherein not all patients with C. difficile infection have pseudomembranes (21). Finally, less frequently, colonoscopic or histopathologic findings demonstrating pseudomembranous colitis can be used in diagnostic workups to increase the diagnostic specificity for CDI diagnosis (14).

In contrasting the two reference methods (TC and CCNA), TC, while infrequently performed in clinical laboratories, is regarded as being more analytically sensitive than CCNA for detecting C. difficile in fecal specimens but may have lower diagnostic specificity (and, therefore, a greater likelihood of false-positive [FP] test results). CCNA has been shown to have high diagnostic sensitivity, ranging from 80 to 100%. In addition, CCNA has high diagnostic specificity and positive predictive values as well as having greater clinical utility based upon clinical outcomes (2226). Furthermore, each reference method differs by the target detected: TC detects the presence of C. difficile strains that produce toxins A and/or B in vitro to confirm a toxigenic strain, whereas CCNA detects the presence of free toxin A or B in clinical specimens. Given these contrasting characteristics, there is potential for diagnostic discrepancy between the reference standards. Therefore, observed diagnostic performance may vary according to which reference standard is used.

Given the variety of test methods and diagnostic algorithms, there is disagreement in the laboratory community on whether best practices for the diagnosis of CDI consist of NAAT only or algorithmic testing that includes NAAT (GDH EIA followed by NAAT [GDH/NAAT] or GDH and toxin EIAs followed by NAAT [GDH/toxin/NAAT]) (20). At the initiation of these guidelines, this was the clinical quandary facing individuals who decide on a C. difficile testing strategy for their health care system, particularly as there is limited high-quality evidence to support which diagnostic testing strategy best supports the laboratory diagnosis of CDI (8, 22). Additionally, it remains to be determined if the potential differences in the accuracy of NAAT only or an algorithmic strategy would impact patient management or patient outcomes (27). There are few studies that encompass the nuances of laboratory CDI diagnosis as it occurs in the clinical context, for example, that evaluate the effect of preanalytic testing considerations on outcomes, to include clinical outcomes. This limitation is evident from the recent Infectious Diseases Society of America (IDSA)/Society for Healthcare Epidemiology of America (SHEA) systematic review, which included only studies that encompassed C. difficile testing within its clinical context, including preanalytic and postanalytic aspects (11).

Given these practice issues, and related diagnostic quality and patient safety concerns, the goal of this systematic review was to determine which laboratory testing strategies, with the inclusion of NAAT, had the best diagnostic accuracy for CDI. While it is clear that laboratory testing alone without taking into consideration the entire clinical picture is not appropriate for the diagnosis of CDI, the available literature has limited evidence linking laboratory diagnosis with clinical outcomes. Therefore, the questions for this systematic review were refined to be based only on the intermediate outcome of diagnostic accuracy for detecting the presence of the C. difficile organism or toxin. Although the reference standard in these studies defines what is meant by the target condition, this systematic review compares the diagnostic accuracies of these tests, including GDH detection by EIA, toxin detection by EIA, and NAAT, to those of CCNA and TC. It has been clear that preanalytical factors are crucial for NAAT specifically, and many of the studies did not include a preanalytical component, which limits whether this review can answer the question, Does this patient have C. difficile infection?

The questions that guided this systematic review were the following: (i) What is the diagnostic accuracy of NAAT only versus either TC or CCNA for detection of the C. difficile toxin gene?, (ii) What is the diagnostic accuracy of a GDH-positive EIA followed by NAAT versus either TC or CCNA for detection of the C. difficile organism/toxin gene?, (iii) What is the diagnostic accuracy of a GDH-positive/toxin-negative EIA followed by NAAT versus either TC or CCNA for detection of the C. difficile organism/toxin/toxin gene?, and (iv) What is the increased diagnostic yield of repeat testing using NAAT after an initial negative result for C. difficile detection of the toxin gene?

The goals of analysis based on these questions were specifically to evaluate the effectiveness of the following: (i) the diagnostic accuracies of NAAT-only and algorithmic (“two-step” or “three-step”) testing strategies, including detection of toxin or GDH in addition to NAAT, and (ii) the diagnostic yield of repeat testing after an initial negative NAAT result. The evidence supporting these two important issues was evaluated by applying the Centers for Disease Control and Prevention (CDC) Laboratory Medicine Best Practices (LMBP) Initiative’s systematic review method for translating results into evidence-based recommendations (28). The method has recently been used to evaluate practices for improving blood culture contamination (29), blood sample hemolysis (30), urine culture sample quality (31), timeliness of providing targeted therapy for bloodstream infections (32), and laboratory test utilization (33), in addition to others, and can be found at the CDC LMBP website (https://www.cdc.gov/labbestpractices/our-findings.html).