Clinical Value of Metagenomics Next-Generation Sequencing in Antibiotic Resistance of a Patient with Severe Refractory Mycoplasma pneumoniae Pneumonia: A Case Report

Infect Drug Resist. 2023 Jul 13:16:4593-4597. doi: 10.2147/IDR.S419873. eCollection 2023.

Abstract

Background: Mycoplasma pneumoniae is an important infectious pathogen of lower respiratory tract infection in children and adolescents. Macrolide resistant M. pneumoniae (MRMP) has become increasingly prevalent, and identifying pathogen resistance genes is crucial for treatment.

Case presentation: We report a patient with severe refractory M. pneumoniae pneumonia (MPP). The failure of initial clinical treatment prompted the re-analysis of metagenomic next-generation sequencing (mNGS) data for macrolide-resistant gene. Macrolide-resistance 23S ribosomal RNA gene was confirmed with read depth of 64 X for the A2063G mutation, which can decrease the affinity of macrolide with M. pneumoniae ribosome resulting in macrolide resistance. Furthermore, antimicrobial susceptibility testing demonstrated that M. pneumoniae was resistant to macrolide. PCR confirmatory test about M. pneumoniae resistance A2063G mutation, clinical treatment course and prognosis with altered treatment strategy, and M. pneumoniae antimicrobial susceptibility confirmed that the severe refractory MPP was due to macrolide resistant M. pneumoniae.

Conclusion: As a new molecular level detection, mNGS is an effective method for detecting M. pneumoniae resistance genes. Early recognition of macrolide resistance and suitable antibiotics strategy is of vital importance for the prognosis of severe refractory MPP.

Keywords: A2063G mutation; Mycoplasma pneumoniae; macrolide-resistant gene; metagenomic next-generation sequencing; pneumonia.

Publication types

  • Case Reports

Grants and funding

This work was supported by National Key R&D Program of China (Grant number: 2020YFC2005401, 2020YFC2005406), Xicheng financial, scientific and technological project (Grant number: XCSTS-SD2021-02), Project funded by Baidu Fund of Peking University (Grant number: 2020BD045), Capital Health Development Scientific Research Project (Grant number: 2021-1G-4301), and National Natural Science Foundation of China (Grant number: 8211101008).