Homogeneous and digital proximity ligation assays for the detection of Clostridium difficile toxins A and B

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Abstract

Background The proximity ligation assay (PLA) detects proteins via their interaction with pairs of proximity probes, which are antibodies coupled to noncomplementary DNA oligonucleotides. The binding of both proximity probes to their epitopes on the target protein brings the oligonucleotides together, allowing them to be bridged by a third oligonucleotide with complementarity to the other two. This enables their ligation and the detection of the resulting amplicon by real-time quantitative PCR (qPCR), which acts as a surrogate marker for the protein of interest. Hence PLA has potential as a clinically relevant diagnostic tool for the detection of pathogens where nucleic acid based tests are inconclusive proof of infection. Methods We prepared monoclonal and polyclonal proximity probes targeting Clostridium difficile toxins A (TcdA) and B (TcdB) and used hydrolysis probe-based qPCR and digital PCR (dPCR) assays to detect antibody/antigen interactions. Results The performance of the PLA assays was antibody-dependent but both TcdA and TcdB assays were more sensitive than comparable ELISAs in either single- or dualplex formats. Both PLAs could be performed using single monoclonal antibodies coupled to different oligonucleotides. Finally, we used dPCR to demonstrate its potential for accurate and reliable quantification of TcdA. Conclusions PLA with either qPCR or dPCR readout have potential as new diagnostic applications for the detection of pathogens where nucleic acid based tests do not indicate viability or expression of toxins. Importantly, since it is not always necessary to use two different antibodies, the pool of potential antibodies useful for PLA diagnostic assays is usefully enhanced.

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Dhillon, H. S., Johnson, G., Shannon, M., Greenwood, C., Roberts, D., & Bustin, S. (2016). Homogeneous and digital proximity ligation assays for the detection of Clostridium difficile toxins A and B. Biomolecular Detection and Quantification, 10, 2–8. https://doi.org/10.1016/j.bdq.2016.06.003

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