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The key factors that control the spread and mortality rate of tuberculosis (TB) are rapid detection and diagnosis. However, the current detection of Mycobacterium tuberculosis (M. tuberculosis) cannot meet the recommended requirements for clinical diagnosis in turnaround time. In this paper, the feature of phage D29 that infects M. tuberculosis and Mycobacterium smegmatis (M. smegmatis) was combined with the sensitivity of multichannel series piezoelectric quartz crystal sensor (MSPQC) to detect M. tuberculosis. The phage D29 played a role of inhibiting the growth of M. tuberculosis and M. smegmatis. M. tuberculosis is used to protect phage D29 from being killed by ferrous ammonium sulfate (FAS) and carries phage D29 into the detection medium containing M. smegmatis. The action of M. smegmatis indicated the existence state of phage D29 in the detection medium. The growth curve of M. smegmatis obtained by MSPQC indicated the state of the growth of M. tuberculosis. Therefore, M. tuberculosis in the sample could be rapidly detected by evaluating the extent of inhibiting the growth of M. smegmatis compared with the normal growth of M. smegmatis. The detection of M. tuberculosis was transformed into the detection of M. smegmatis, which is more rapid and sensitive than that of M. tuberculosis. For 10(2) cfu/mL of M. tuberculosis in clinical sample, the turnaround time was less than 30 h. Although statistical analysis showed that no significant difference existed between the results of the proposed method here and the BACTEC960 MGIT method in clinical M. tuberculosis detection, the phage amplified MSPQC (PA MSPQC) method presented here was faster and more economical.

A dual-stimuli responsive i-motif/nanoflare for molecule detection in lysosomes was designed. By combining the structure-switchable i-motif sequence and high recognition ability of an adenosine triphosphate (ATP) aptamer, subcellular sensing and visualization sensing of ATP in lysosomes at the subcellular level can be achieved. This general sensing technique can be applied for a broad range of cellular communication studies to improve our understanding of subcellular signaling and function.