Reliability of Matrix-Assisted Laser Desorption-Ionisation Time-of-Flight Mass Spectrometry as a Method for Drug-Resistant Tuberculosis Gene Identification.

Instances of drug-resistant tuberculosis (TB), particularly multidrug- and extensive drug-resistant TB, are escalating worldwide; therefore, there is an urgent need to explore suitable treatment strategies. This study assessed the precision of matrix-assisted laser desorption-ionisation time-of-flight mass spectrometry (MALDI-TOF MS) in detecting drug-resistant TB. We developed a multiplex MALDI-TOF MS detection assay that concurrently identifies 51 gene mutations for six commonly used medications: rifampicin (RFP), isoniazid (INH), levofloxacin (LVX), moxifloxacin (MOX), capreomycin (CPM) and amikacin (AMK). Subsequently, we evaluated the accuracy of the system by testing clinical sputum samples with known (n = 45) and unknown (n = 254) minimum inhibitory concentrations (MICs), using Sanger-sequenced genes as references. The detection system exhibited a minimum sensitivity of 88.00% and a specificity of 95.24% for the 45 known isolates. Similarly, for the 254 unknown samples, the detection system demonstrated sensitivity and specificity for mutations associated with each medication as follows: RFP-sensitivity: 98.97%, specificity: 99.36%; INH-sensitivity: 97.80%, specificity: 100.00%; LVX and MOX-sensitivity: 97.14%, specificity: 100.00%; AMK and CPM-sensitivity: 100.00%, specificity: 100.00%. The unknown samples also displayed favourable sensitivity and specificity values in the MIC validation as follows: RFP-sensitivity: 92.39%, specificity: 92.59%; INH-sensitivity: 75.21%, specificity: 99.27%; LVX-sensitivity: 75.28%, specificity: 99.39%; MOX-sensitivity: 73.24%, specificity: 91.26%; AMK-sensitivity: 94.87%, specificity: 96.74%; CPM-sensitivity: 89.47%, specificity: 95.83%. Meanwhile, our study allows for the identification of the Mycobacterium tuberculosis complex (MTBC). The MALDI-TOF MS exhibited remarkable accuracy in the detection of drug-resistant TB, making it a potential alternative approach for clinical TB diagnosis.