Detection of Pulmonary Infectious Pathogens From Lung Biopsy Tissues by Metagenomic Next-Generation Sequencing

Abstract

Metagenomic next-generation sequencing (mNGS) is a comprehensive approach for sequence-based identification of pathogenic microbes. However, reports on the use of mNGS in pulmonary infection applied to lung biopsy tissues remain scarce. In this study, we applied mNGS to detect the presence of pathogenic microbes in lung biopsy tissues from 20 patients with pulmonary disorders indicating possible infection. We applied a new data management for identifying pathogen species based on mNGS data. We determined the thresholds for the unique reads and relative abundance required to identify the infectious pathogens. Potential pathogens of pulmonary infections in 15 patients were identified by mNGS. The comparison between mNGS and culture method resulted that the sensitivity and specificity were 100.0% (95% CI: 31.0-100.0%) and 76.5% (95% CI: 49.8-92.2%) for bacteria, 57.1% (95% CI: 20.2-88.2%) and 61.5% (95% CI: 32.2-84.9%) for fungi. The positive predictive value (PPV) (42.9% for bacteria, 44.4% for fungi) was much lower than negative predictive value (NPV) (100% for bacteria, 72.7% for fungi) in mNGS vs. culture method. The mNGS showed the highest specificity (100.0 and 94.1%) and PPV (100.0 and 75.0%) in the evaluation of fungi and MTBC respectively, when compared with histopathology method. The study indicated that mNGS of lung biopsy tissues can be used to detect the presence (or absence) of pulmonary pathogens in patients, with potential benefits in speed and sensitivity. However, accurate data management and interpretation of mNGS are required, and should be combined with observations of clinical manifestations and conventional laboratory-based diagnostic methods.

Keywords: clinical diagnosis; data management; lung biopsy tissues; metagenomic next-generation sequencing (mNGS); pulmonary infection.

Figure 1

Heat maps reporting the relative abundance at the genus level of the 10 most abundant bacterial species (A) and fungal species (B) identified by metagenomic next-generation sequencing (mNGS) in 20 lung biopsy tissues. The infectious bacteria or fungi were marked with black horizontal lines if >30% relative abundance at the genus level, or marked with black scatter spots if included at least 50 unique reads from culture and/or histopathological examination positive bacteria or fungi.

Figure 2

Optimal thresholds for infectious fungi identification by metagenomic next-generation sequencing (mNGS). The fungal species which contained the highest relative abundance and maximum number of unique reads in each sample were selected, and the relative abundance and unique reads were shown in (A). The red dots indicated fungi identified by mNGS in samples which were consistent with culture results at the genus or species level. Blue dots indicated species identified by mNGS in samples which showed fungal hypha by histopathological examination. Black dots indicated species identified by mNGS in samples which had negative results of fungi by conventional culture and/or histopathology methods. Sensitivity and specificity with 95% confidence intervals were calculated under different threshold (B).

Figure 3

Testing of lung biopsy tissues from 20 patients with pulmonary disorders by conventional laboratory-based diagnostic methods and metagenomic next-generation sequencing (mNGS). MTBC, Mycobacterium tuberculosis complex; PCR, polymerase chain reaction; TAT, turn-around time.