基质辅助激光解吸电离飞行时间质谱法在结核分枝杆菌鉴定与耐药检测中的应用研究OA

Objective To evaluate the value of matrix-assisted laser desorption ionization time-of-flight mass spectrometry(MALDI-TOF MS)for rapid identification of Mycobacterium tuberculosis complex(MTBC)and prediction of rifampicin(RIF)and isoniazid(INH)resistance.Methods A total of 150 clinical specimens from suspected tuberculosis patients at Wenzhou Central Hospital,Affiliated to Wenzhou Medical University from January 2024 to January 2025 were collected.Culture and phenotypic drug susceptibility testing were used as the gold standard.After pretreatment,MALDI-TOF MS was performed directly and after short-term culture enrichment.Using machine learning to analyze protein fingerprint patterns,a random forest prediction model for RIF and INH resistance was constructed.Results The success rate of MALDI-TOF MS direct method in identifying MTBC was 70.00%(91/130),after short-term culture,the identification success rate of MALDI-TOF MS for MTBC reached 96.15%(125/130),with a significant difference(P<0.001).Twenty-six resistance-associated protein peaks were identified.The random forest model predicted RIF resistance with an area under the curve(AUC)of 0.93(sensitivity 91.70%,specificity 89.30%)and INH resistance with an AUC of 0.88.The model predictions were highly consistent with genotypic resistance.Conclusion MALDI-TOF MS combined with short-term culture enables efficient identification of MTBC,and the machine learning model based on protein fingerprints accurately predicts RIF and INH resistance,providing a novel strategy for rapid tuberculosis diagnosis and resistance screening.