Abstract

This study investigated the methods for optimizing the workflow for improving the diagnostic efficiency for detection of Mycobacterium tuberculosis (MTB) in lung tissue specimens. A total of 278 specimens were used in this study. M. tuberculosis in fresh lung tissue samples was detected by BACTEC MGIT 960 culture system, culturing L-form MTB, rifampicin (RFP) and levofloxacin (LVFX) susceptibility test, and ribonucleic acid (RNA) simultaneous amplification and testing (SAT). Specimen samples were embedded in paraffin and serially sectioned. The sections were subjected to Ziehl-Neelsen staining and Intensified Kinyoun (IK) acid-fast staining. The suspected MTB or L-form MTB specimens were further investigated by deoxyribonucleic acid (DNA) sequencing and fluorescence polymerase chain reaction (PCR) melting curve method to detect the mutations in rpoB gene and gyrA gene. Thirteen specimens were suspected as MTB positive, and 37 specimens were suspected to be L-form MTB positive by Ziehl-Neelsen staining and IK acid-fast staining. Among the 50 specimens, the number of MTB positive specimens detected by SAT, DNA sequencing, and fluorescence PCR melting curve method was 43, 44, and 45, respectively. Only 11 MTB positive specimens were detected by BACTEC MGIT 960 culture system or by culturing L-form MTB. Mutations detected in rpoB gene and gyrA gene by fluorescence PCR melting curve method were similar to those detected by DNA sequencing. Some specimens, detected by melting curve method, exhibited varied drug resistance to RFP, suggesting heterogeneous resistance. Among the remaining 228 specimens, there was no MTB or L-form MTB detected by BACTEC MGIT 960 culture system. However, 5 specimens were detected to be MTB positive by the SAT method. The fluorescent PCR melting curve method, which has a high level of automation and high sensitivity and specificity, could effectively detect heterozygous drug resistance of MTB in lung tissue samples, which is important for clinicians to effectively formulate a therapeutic strategy.

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