Application of Metagenomic Next-Generation Sequencing in the Diagnosis of Pulmonary Infectious Pathogens From Bronchoalveolar Lavage Samples.

Yuqian Chen,Cui Zhai,Li Guo,Cong Li,Qianqian Zhang,Yuanlin Guan,Limin Chai,Qingting Wang,Kai Ye,Xin Yan,Jian Wang,Wei Feng,Pengtao Liu,Han Xia,Wenhua Shi,Manxiang Li

doi:10.3389/fcimb.2021.541092

Abstract

BackgroundMetagenomic next-generation sequencing (mNGS) is a powerful method for pathogen detection. In this study, we assessed the value of mNGS for bronchoalveolar lavage (BAL) samples in the diagnosis of pulmonary infections.MethodsFrom February 2018 to April 2019, BAL samples were collected from 235 patients with suspected pulmonary infections. mNGS and microbial culture were performed to evaluate the effectiveness of mNGS in pulmonary infection diagnosis.ResultsWe employed mNGS to evaluate the alpha diversity, results suggesting that patients with confirmed pathogens had a lower microbial diversity index compared to that of patients with uncertain pathogens. For the patients admitted to the respiratory intensive care unit (RICU) or on a ventilator, they experienced a lower diversity index than that of the patients in the general ward or not on a ventilator. In addition, mNGS of BAL had a diagnostic sensitivity of 88.89% and a specificity of 14.86% in pulmonary infection, with 21.16% positive predictive value (PPV) and 83.87% negative predictive value (NPV). When rare pathogens were excluded, the sensitivity of mNGS decreased to 73.33%, and the specificity increased to 41.71%. For patients in the simple pulmonary infection group and the immunocompromised group, the main infection types were bacterial infection (58.33%) and mixed-infection (43.18%). Furthermore, mNGS had an advantage over culture in describing polymicrobial ecosystem, demonstrating the microbial distribution and the dominant strains of the respiratory tract in patients with different underlying diseases.ConclusionsThe study indicated that mNGS of BAL samples could provide more accurate diagnostic information in pulmonary infections and demonstrate the changes of respiratory microbiome in different underlying diseases. This method might play an important role in the clinical use of antimicrobial agents in the future.

Highlights

Pulmonary infections, caused by bacteria, viruses, or fungi, displaying an increasing incidence and mortality rate worldwide, are the third leading cause of total years of life lost (YLLs) (Naghavi et al, 2017)
Specific diagnostic criteria of suspected pulmonary infection included new or deteriorated focal or diffuse infiltrating lesions on chest X-ray or computed tomography (CT), combined with at least one of the following four items: 1) fever >37°C, 2) cough, sputum production, hypoxia, or exacerbation of existing respiratory symptoms; 3) leukocytosis, 4) clinical signs of lung consolidation or moist rales. metagenomic next-generation sequencing (mNGS) tests for the bronchoalveolar lavage (BAL) samples were performed in patients who had suspected lung infection, paralleled with the conventional microbiological testing
Specimens from all patients were tested with the following traditional laboratory analysis: bacterial and fungal smear and culture, real-time polymerase chain reaction (PCR) for human betaherpesvirus 5, human gammaherpesvirus 4 (Epstein-Barr virus, EBV), and Mycobacterium tuberculosis, serum antibodies for indirect immunofluorescence assay (IFA) for respiratory syncytial virus (RSV), influenza A/B virus, parainfluenza virus, adenovirus, Legionella pneumophila, Mycoplasma pneumoniae, and Chlamydia pneumoniae

Summary

Introduction

Pulmonary infections, caused by bacteria, viruses, or fungi, displaying an increasing incidence and mortality rate worldwide, are the third leading cause of total years of life lost (YLLs) (Naghavi et al, 2017). Etiological diagnosis is critical for proper clinical treatment. The sequence reads generated can be linked to an accurate reference genome (or marker) database to identify pathogens (Forbes et al, 2017). It is unbiased and untargeted, so that it could enable wide-spectrum detection of known and unexpected pathogens or even unknown organisms. As a rapid microbiological diagnostic method for infectious diseases, mNGS had been recently introduced into clinical practice and provided vast quantities of etiological information, including species, strains, antibiotic resistance, and even virulence characteristics. We assessed the value of mNGS for bronchoalveolar lavage (BAL) samples in the diagnosis of pulmonary infections

Methods

Results

Conclusion