The development of matrix-metalloproteinase responsive sensors for the machine-independent detection of oral inflammation

Abstract

Periodontitis is a chronic inflammatory disease that affects an estimated 20–50% of the world's population and can lead to high follow-up costs for the healthcare system. The disease is closely associated with a dysbiotic, pro-inflammatory change of the oral microbiota. As the disease progresses, the inflammation affects the periodontium with subsequent tooth mobility and tooth loss as clinical outcomes. Early diagnosis and early treatment are vital and can leverage overall clinical success, resulting in possible preservation. Therefore, periodontal inflammation should be detected as soon as possible. Unfortunately, early stages of periodontitis are mostly asymptomatic and unnoticed by affected patients or only noticed at advanced stages, making diagnosis impossible without medical consultation. Ideally, highly intuitive diagnostic tools would be available to anyone, anywhere and anytime for personal check-ups. Therefore, we developed peptide sensors, that are cleaved by upregulated matrix metalloproteinases (MMP) as present in oral inflammation. This leads to the release of a denatonium-based flavor substance, providing a rapid diagnostic indicator for further professional clarification. Two distinct techniques were employed to enhance sensor specificity. A peptide sensor was developed for disease-specific protease (MMP) digest using previously published information and proteome wide screening techniques, followed by optimization against nonspecific proteases present in the oral cavity. Finally, the selected sensor was tested in patient saliva, and the sensor cleavage correlated with MMP concentration and activity. Furthermore, the sensors significantly differentiated patient pools and pools of healthy volunteers, and cleavage was linked to pocket probing depths, a clinical sign of periodontal diseases.