Species-Specific Detection of C. difficile Using Targeted Antibody Design

Clostridium difficile is a Gram-positive, spore-forming bacterium that continues to present a worldwide problem in healthcare settings. The bacterium causes disease, the symptoms of which include diarrhea, fever, nausea, abdominal pain and even death. Despite the prevalence of the disease, the diagnosis of C. difficile infection is still challenging, with a variety of methods available, each varying in their effectiveness. In this work we sought to identify a new biomarker for C. difficile, develop affinity reagents and design a diagnostic assay for C. difficile infection which could be used in a typical two-step testing algorithm. Initially a bioinformatics pipeline was developed that identified a surface associated biomarker "AKDGSTKEDQLVDALA" present in all C. difficile strains sequenced to-date and unique to the C. difficile species. Monoclonal antibodies were subsequently raised against peptides corresponding to the biomarker sequence. During characterization studies, monoclonal antibody 521 (mAb521) was shown to bind all known C. difficile surface layer types, but not closely related strains. Surface plasmon resonance measurements were used to calculate an apparent equilibrium dissociation constant of 36.5 nM between the purified protein target containing the biomarker (surface layer protein A) and mAb521. We demonstrate a limit of detection of 12.4 ng/mL against surface layer protein A and 1.7 × 10⁶ cells/mL in minimally processed C. difficile cultures. The utility of this computational approach to antibody design for diagnostic tests is the ability to produce antibodies that can act as universal species identifiers while mitigating the likelihood of false-positive detection by intelligently screening potential biomarkers against RefSeq data for other nontarget bacteria.