Identification of Mycobacterium tuberculosis Resistance to Common Antibiotics: An Overview of Current Methods and Techniques

Abstract

Xue-Song Xiong,1,2,* Xue-Di Zhang,3,* Jia-Wei Yan,3 Ting-Ting Huang,1,2 Zhan-Zhong Liu,4 Zheng-Kang Li,5 Liang Wang,5 Fen Li1,2 1Department of Laboratory Medicine, The Affiliated Huai’an Hospital of Yangzhou University, Huai’an, Jiangsu Province, People’s Republic of China; 2Department of Laboratory Medicine, The Fifth People’s Hospital of Huai’an, Huai’an, Jiangsu Province, People’s Republic of China; 3Department of Laboratory Medicine, Xuzhou Infectious Diseases Hospital, Xuzhou, Jiangsu Province, People’s Republic of China; 4Department of Pharmacy, Xuzhou Infectious Diseases Hospital, Xuzhou, Jiangsu Province, People’s Republic of China; 5Department of Laboratory Medicine, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong Province, People’s Republic of China*These authors contributed equally to this workCorrespondence: Liang Wang; Fen Li, Email [email protected]; [email protected]: Multidrug-resistant tuberculosis (MDR-TB) is an essential cause of tuberculosis treatment failure and death of tuberculosis patients. The rapid and reliable profiling of Mycobacterium tuberculosis (MTB) drug resistance in the early stage is a critical research area for public health. Then, most traditional approaches for detecting MTB are time-consuming and costly, leading to the inappropriate therapeutic schedule resting on the ambiguous information of MTB drug resistance, increasing patient economic burden, morbidity, and mortality. Therefore, novel diagnosis methods are frequently required to meet the emerging challenges of MTB drug resistance distinguish. Considering the difficulty in treating MDR-TB, it is urgently required for the development of rapid and accurate methods in the identification of drug resistance profiles of MTB in clinical diagnosis. This review discussed recent advances in MTB drug resistance detection, focusing on developing emerging approaches and their applications in tangled clinical situations. In particular, a brief overview of antibiotic resistance to MTB was present, referred to as intrinsic bacterial resistance, consisting of cell wall barriers and efflux pumping action and acquired resistance caused by genetic mutations. Then, different drug susceptibility test (DST) methods were described, including phenotype DST, genotype DST and novel DST methods. The phenotype DST includes nitrate reductase assay, RocheTM solid ratio method, and liquid culture method and genotype DST includes fluorescent PCR, GeneXpert, PCR reverse dot hybridization, ddPCR, next-generation sequencing and gene chips. Then, novel DST methods were described, including metabolism testing, cell-free DNA probe, CRISPR assay, and spectral analysis technique. The limitations, challenges, and perspectives of different techniques for drug resistance are also discussed. These methods significantly improve the detection sensitivity and accuracy of multidrug-resistant tuberculosis (MRT) and can effectively curb the incidence of drug-resistant tuberculosis and accelerate the process of tuberculosis eradication. Keywords: MTB, antibiotic resistance, Raman spectroscopy, rapid detection

Keywords

• mtb
• antibiotic resistance
• raman spectroscopy
• rapid detection
• machine learning algorithm