Rapid detection of tuberculosis using droplet-based microfluidics

Liat Rosenfeld; Yunfeng Cheng; Jianghong Rao; Sindy K. Y. Tang

doi:10.1117/12.2038533

6 March 2014 Rapid detection of tuberculosis using droplet-based microfluidics

Liat Rosenfeld, Yunfeng Cheng, Jianghong Rao, Sindy K. Y. Tang

Proceedings Volume 8976, Microfluidics, BioMEMS, and Medical Microsystems XII; 897611 (2014) https://doi.org/10.1117/12.2038533
Event: SPIE MOEMS-MEMS, 2014, San Francisco, California, United States

Abstract

Tuberculosis is one of the most deadly diseases that kills over one million people each year and infects one-third of the world’s population. The disease is spread by infection with Mycobacterium tuberculosis (Mtb). Owing to its airborne transmission, early diagnosis is critical to the prevention and control of TB. Standard diagnostic methods, acid-fast smear from sputum, often do not become positive until after transmission occurs, which allows the spread of the disease. Culture-based techniques are more sensitive, but take weeks to obtain results because of the extremely slow growth rate of Mtb. In this study a new method to detect indicator enzyme based on the isolation of tubercle bacillus in a large number of picoliter droplets combined with a fluorescent probe has been developed. We use BlaC (an enzyme naturally expressed/secreted by tubercle bacilli) as a marker and a designed BlaC-specific fluorogenic substrates as probes for Mtb detection. We present here a new method to detect the indicator enzyme based on the isolation, digitization and concentration of bacteria samples in a large number of picoliter drops. We show that by controlling the size of the droplets we can control the rate of conversion. Hence rapid increase in signal has been observed as the size of the drops has been decreased. Our vision is that this tool will be able to detect tubercle bacilli in a sensitive, rapid, specific and quantitative manner in vitro at a low cost, particularly in resource limited settings where TB is the most prevalent.

Citation Download Citation

Liat Rosenfeld, Yunfeng Cheng, Jianghong Rao, and Sindy K. Y. Tang "Rapid detection of tuberculosis using droplet-based microfluidics", Proc. SPIE 8976, Microfluidics, BioMEMS, and Medical Microsystems XII, 897611 (6 March 2014); https://doi.org/10.1117/12.2038533

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