Tag Archives: Clostridioides difficile Infection Study

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


Abstract

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.

Authors:

  • 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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https://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1008224

  • Published: July 5, 2019

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

SUMMARY

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

INTRODUCTION

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).

First Time Clostridioides difficile Infection Study Reveals Correlation Between Antibiotic Use and CDI Utilizing Data From 2006-2012

ABSTRACT :   Association between Antibiotic Use and Hospital-Onset Clostridioides difficile Infection in U.S. Acute Care Hospitals, 2006-2012: an Ecologic Analysis

“> Sophia V Kazakova, M.D., M.P.H, Ph.D James Baggs, Ph.D L Clifford McDonald, M.D Sarah H Yi, Ph.D Kelly M Hatfield, M.S.P.H Alice Guh, M.D., M.P.H Sujan C Reddy, M.D., M.Sc John A Jernigan, M.D., M.S

Clinical Infectious Diseases, ciz169, https://doi.org/10.1093/cid/ciz169
Published:
01 March 2019
Article history

Abstract

Background

Unnecessary antibiotic use (AU) contributes to increased rates of Clostridioides difficile Infection (CDI). The impact of antibiotic restriction on hospital-onset CDI (HO-CDI) has not been assessed in a large group of U.S. acute care hospitals (ACHs).

Methods

We examined cross-sectional and temporal associations between rates of hospital-level AU and HO-CDI using data from 549 ACHs. HO-CDI, a discharge with a secondary ICD-9-CM for CDI (008.45) and treatment with metronidazole or oral vancomycin ≥ 3 days after admission. Analyses were performed using multivariable generalized estimating equation models adjusting for patient and hospital characteristics.

Results

During 2006-2012, the unadjusted annual rates of HO-CDI and total AU were 7.3 per 10,000 patient-days (PD) (95% CI: 7.1-7.5) and 811 days of therapy (DOT)/1,000 PD (95% CI: 803-820), respectively. In the cross-sectional analysis, for every 50 DOT/1,000 PD increase in total AU, there was a 4.4% increase in HO-CDI.

For every 10 DOT/1,000 PD increase in use of third- and fourth-generation cephalosporins or carbapenems there was a 2.1% and 2.9% increase in HO-CDI, respectively. In the time-series analysis, the 6 ACHs with a ≥ 30% decrease in total AU had a 33% decrease in HO-CDI (rate ratio, 0.67; 95% CI, 0.47-0.96); ACHs with a ≥ 20% decrease in fluoroquinolone or third- and fourth-generation cephalosporin use had a corresponding decrease in HO-CDI of 8% and 13%, respectively.

Conclusions

At an ecologic level, reductions in total AU, use of fluoroquinolones and third- and fourth-generation cephalosporins were each associated with decreased HO-CDI rates.

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https://academic.oup.com/cid/advance-article/doi/10.1093/cid/ciz169/5367464?fbclid=IwAR0S6XfRWoKTJNmBoZLQicy2BqzuOOyRF9dx2ctQGRn0K9K0m79cr7Or7pQ