Biodetection Strategies for Selective Identification of Candidiasis

Abstract

Fungi are among the predominant pathogens seen in a greater proportion of infections acquired in healthcare settings. A common fungus that causes infections in medical settings is Candida species. Hospitalized patients who suffer from fungal diseases such as candidiasis and candidemia often have elevated rates of mortality and morbidity. It is evident that longer hospital stays have the possibility of bacterial and fungal recurrence and also have a negative economic impact. If left untreated, a Candida infection can spread to other organs and cause a systemic infection that can result in sepsis. Clinicians can treat patients quickly when fungal infections are timely detected, this enhances the results of clinical trials. Developing novel, sensitive, and quick methods for detecting Candida species is imperative. Conventional detection techniques are unsuitable for clinical settings and point-of-care systems as they require expensive equipment and take a longer detection time. This review examines a few of the most widely used biosensor systems for the detection of Candida species, their sensitivity, and the limit of detection. It focuses on various biorecognition elements used and follows utilization and advances in nanotechnology in the context of sensing. In addition to enabling general analysis and quick real-time analysis, crucial for detecting Candida species, biosensors provide an intriguing alternative to more conventional techniques.