Composition of pathogenic microorganism in chronic osteomyelitis based on metagenomic sequencing and its application value in etiological diagnosis

Abstract Background Traditionally, conventional microbiological culture methods have been used to detect pathogenic microorganisms in chronic osteomyelitis. However, these methods have been found to have a low detection rate, complicating the precise guidance of infection treatment. This study employed metagenomic next-generation sequencing (mNGS) to detect these microorganisms in chronic osteomyelitis with three main objectives: 1). Gain a deeper understanding of the composition of pathogenic microorganisms in chronic osteomyelitis. 2). Compare the microbial detection rates between mNGS and the standard culture methods used in laboratories to enhance the effectiveness of the traditional culture methods. 3). Explore the potential of mNGS in etiological diagnosis. Methods Fifty clinically confirmed intraoperative bone tissue samples of chronic osteomyelitis from January 2021 to December 2021 were collected and subjected to mNGS and microbiological testing, respectively. The orthopaedic surgeon combined clinical manifestations and related examinations to determine the causative pathogens. Results The culture method obtained 29 aerobic and parthenogenic anaerobic bacteria, 3 specific anaerobic bacteria, and 1 yeast-like fungus. Thirty-six aerobic and parthenogenic anaerobic bacteria, 11 specific anaerobic bacteria, and 1 yeast-like fungus were obtained by mNGS, and 2 Mycobacterium tuberculosis(MTB) strains were detected. However, there was no significant difference in the overall positive detection rate between mNGS and the culture method (P = 0.07), and the two were not statistically significant in detecting aerobic and partly anaerobic bacteria (P = 0.625). But, mNGS was significantly superior to culture in detecting anaerobic bacteria and Mycobacterium tuberculosis (P