Sequencing methods to study the microbiome with antibiotic resistance genes in patients with pulmonary infections

Abstract

Abstract Background Various antibiotic resistant bacteria are known to induce repeated pulmonary infections and increase morbidity and mortality. A thorough knowledge of the spectrum of bacteria with antibiotic resistance genes (ARGs) can improve the antibiotic treatment efficiency. In this study, we induced metagenomic next-generation sequencing (mNGS) alignment and assembly methods in the bioinformatics analysis pipeline to reveal the profile of bacteria with ARGs (ARB) in samples from patients with pulmonary infections. Methods A retrospective analysis of 151 clinical samples from 144 patients with pulmonary infections was undertaken by mNGS and conventional microbiological detection methods. Positive ARB were determined according to the analysis results detected both by the alignment and assembly methods. Co-occurrence analysis of ARG-ARB network was conducted to investigate the attributions between ARGs and microbial taxa. We also evaluated the potential application conditions to predict ARGs using those two approaches. Results Compared to that using conventional detection methods, the false-positive detection rate of ARB was significantly higher using mNGS alignment method. The assembly method could assist the determining of the detected pathogens by the alignment method as true ARB and improve the predictive capabilities (46% > 13%). ARG-ARB network revealed the main ARGs in predominant ARB. A total of 361 ARGs were detected, which mostly belonged to the multidrug class and β-lactam antibiotic classes. Specifically, 101 ARGs (existing in two approaches) and 34 ARGs (detected only by assembly method) achieved a clear ARG-bacteria attribution and potentially could optimize the reference antibiotic resistance database. The most prevalent ARB and its corresponding ARG and drug classes were as follows in this study: Acinetobacter baumannii (ADE, multidrug), Pseudomonas aeruginosa (MEX, multidrug), Klebsiella pneumoniae (MDT, aminocoumarin; EMR, fluoroquinolone), Stenotrophomonas maltophilia (SME, multidrug) and Corynebacterium striatum (carA, MLSB). Conclusion Collectively, our findings demonstrated the applicability of mNGS alignment and assembly as antibiotic resistant diagnostic methods and uncovered pulmonary infection-associated ARB and ARGs, potentially, as antibiotic treatment targets for the pulmonary infection.