AUTHOR=Guo Mingquan , Wang Yan , Sun Juntao , Qian Chengcheng , Lowrie Douglas B. , Niu Liangfei , Wu Juan , Hu Zhidong , Fan Xiao-Yong , Ma Ruiqing 

TITLE=Rapid detection of drug resistance in Mycobacterium tuberculosis clinical isolates for first-line antitubercular drugs by using a novel reporter mycobacteriophage

JOURNAL=Frontiers in Cellular and Infection Microbiology

VOLUME=Volume 15 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/cellular-and-infection-microbiology/articles/10.3389/fcimb.2025.1589236

DOI=10.3389/fcimb.2025.1589236

ISSN=2235-2988

ABSTRACT=The emergence of drug resistance presents a major challenge for the treatment of tuberculosis (TB). Reporter phage can provide an effective method for drug susceptibility testing (DST) of Mycobacterium tuberculosis (Mtb), but limited for parts of antitubercular drugs and the process of operation is usually time-consuming. Herein, we developed a new, sensitive, reporter phage with optimized method to detect drug susceptibility of Mtb clinical isolates for all first-line antitubercular drugs. The PfurAma promoter and nanoluciferase (Nluc) reporter sequences were integrated into the genome of the TM4 mycobacteriophage to generate a reporter phage, designated φFN. By optimizing concentration of Mtb, Tween 80 and drugs, we have established an efficient workflow for φFN-based DST of Mtb that provides results for four first-line antitubercular drugs within 72 hours. A total of 71 clinical isolates were tested and yielded significant relative luminescent units (RLUs), and their resistance to rifampin (RIF), isoniazid (INH), streptomycin (STR), and EMB were compared to the conventional DST by MGIT 960. The comparative sensitivities of φFN DST detection were 100%, 93.9%, 97.2%, and 81.3%, respectively; and the relative specificities were 98.1%, 97.4%, 97.1%, and 96.4%, respectively. The remaining luminescence rate (RLR) in the φFN DST assay showed correlation with minimum inhibitory concentration (MIC). The φFN DST assay provides an efficient phage-based workflow to detect drug-resistant Mtb for four first-line antitubercular drugs within 3 days.