Biosensor-Based Platforms for the Detection and Screening of Mycobacterium leprae Infection

Area of Science:

• Biomedical Engineering
• Infectious Disease Diagnostics
• Nanotechnology

Background:

• Leprosy affects ~200,000 annually, with diagnosis hindered by traditional methods' limitations.
• Current diagnostic tools (PCR, serology) lack sensitivity and accessibility in resource-limited settings.
• Timely and accurate diagnosis is crucial for effective leprosy control and treatment.

Purpose of the Study:

• To review recent (past decade) biosensor-based diagnostic strategies for leprosy.
• To assess the potential of biosensors for point-of-care leprosy detection.
• To identify challenges and future directions for clinical translation of biosensor technology.

Main Methods:

• Review of studies on biosensor platforms (electrochemical, piezoelectric, optical) for leprosy diagnosis.
• Analysis of bioreceptors used (peptides, DNA probes, polymers) and innovative approaches (immunosensors, biomimetic).
• Evaluation of diagnostic accuracy and ability to differentiate disease types (paucibacillary vs. multibacillary).

Main Results:

• Biosensor platforms demonstrate high diagnostic accuracies, some exceeding 90%.
• Emerging biosensors utilize diverse bioreceptors and novel approaches like DNA-based and biomimetic strategies.
• Some biosensors can differentiate between paucibacillary and multibacillary leprosy cases.

Conclusions:

• Biosensors show significant potential for accurate, accessible point-of-care leprosy diagnostics.
• Clinical translation requires addressing affordability, field robustness, and large-scale validation.
• Multidisciplinary efforts and user-centered design are essential for implementing biosensors in leprosy control.