Logo image
Development and clinical validation of an automated cell cytotoxicity neutralization assay for detecting Clostridioides difficile toxins in clinically relevant stools samples
Journal article   Peer reviewed

Development and clinical validation of an automated cell cytotoxicity neutralization assay for detecting Clostridioides difficile toxins in clinically relevant stools samples

Arik Elfassy, Warren V. Kalina, Roger French, Ha Nguyen, Charles Tan, Shite Sebastian, Mark H. Wilcox, Kerrie Davies, Michele A. Kutzler, Kathrin U. Jansen, …
Anaerobe, v 71, 102415
Oct 2021
PMID: 34298152

Abstract

Clostridioides difficile Cytotoxicity Diagnostic Neutralization Validation
To improve the diagnostic accuracy of Clostridioides difficile infection, current U.S. and E.U. guidelines recommend multistep testing that detects the presence of C. difficile and toxin in clinically relevant stool samples to confirm active disease. An accepted gold standard to detect C. difficile toxins is the cell cytotoxicity neutralization assay (CCNA). Although highly sensitive, the traditional CCNA has limitations. One such limitation is the subjective interpretation of an analyst to recognize cytopathic effects in cultured cells exposed to a fecal sample containing toxin. To overcome this limitation, an automated CCNA was developed that replaces most human pipetting steps with robotics and incorporates CellTiterGlo® for a semi-quantitative, non-subjective measure of cell viability instead of microscopy. To determine sample positivity and control for non-specific cytopathic effects, two thresholds were defined and validated by evaluating the sample with/without antitoxin antisera (sample-antitoxin/sample + antitoxin): 1) a >70% cell viability threshold was validated with samples containing anti-toxin, and 2) a >1.2-fold difference cut-off where sample results above the cut-off are considered positive. Assay validation demonstrated excellent accuracy, precision, and sample linearity with an LOD of 126.9 pg/mL toxin-B in stool. The positivity cut-offs were clinically validated by comparing 322 diarrheal stool sample results with those run in a predicate, microscopic readout-based CCNA. The automated CCNA demonstrated 96% sensitivity and 100% specificity compared with the predicate CCNA. Conclusions: Overall, the automated CCNA provides a specific, sensitive, and reproducible tool to support determination of CDI epidemiology or the efficacy of interventions such as vaccines. •The CCNA is the most sensitive method for detecting C. difficile free toxins in stool.•Conventional CCNA methods are manual-based and the readout is subjective.•Automation and luminescence readout improve assay performance.•Coupled with a screening assay, the automated CCNA has utility in large vaccine trials.

Metrics

8 Record Views
9 citations in Scopus

Details

UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#3 Good Health and Well-Being

InCites Highlights

Data related to this publication, from InCites Benchmarking & Analytics tool:

Collaboration types
Industry collaboration
Domestic collaboration
International collaboration
Web of Science research areas
Microbiology
Logo image