Ultra-sensitive detection of mycobacterium cells on a smartphone through enhanced emission of autofluorescence signals.

Tuberculosis (TB) remains one of the deadliest infectious diseases of the 21st century, affecting millions of people worldwide each year. Traditional diagnostic methods primarily rely on light and fluorescence microscopy. However, the low sensitivity of light microscopy and the high cost and complexity associated with fluorescence microscopy limit their effectiveness in resource-limited settings. This study presents the design of an alternative sensing platform capable of detecting TB cells with enhanced sensitivity. The system leverages the natural autofluorescence (AF) signal emitted from Mycobacterium cells. The key innovation of the proposed platform is the integration of an onboard heating element, that significantly amplifies the AF signal, allowing detection at concentrations as low as 10 CFU/ml. The designed platform is standalone, low-cost, and compact and built around a smartphone. Housed within a 3D-printed enclosure, it ensures portability and ease of use-making it suitable for deployment in resourced limited environment. The proposed system holds promise to develop as an alternative platform for TB diagnosis in areas where access to advanced healthcare facilities is still very limited.