Utilization of targeted sequencing for etiological diagnosis of pulmonary infections in different samples

TL;DR

This study shows that targeted sequencing is more effective than traditional methods for diagnosing lung infections by detecting a wider range of pathogens and antibiotic resistance genes.

Contribution

The study demonstrates that targeted next-generation sequencing outperforms traditional methods in diagnosing pulmonary infections and detecting antibiotic resistance genes.

Findings

tNGS had a significantly higher positive detection rate (81.33%) compared to traditional methods (32.53%).

tNGS identified 65 pathogens, including 18 viruses, while traditional methods found only 14 pathogens.

tNGS detected 16 antibiotic resistance genes and showed better performance in mixed infections.

Abstract

This study aims to assess the diagnostic value of targeted next-generation sequencing (tNGS) for pathogen identification from multiple sample types in patients with pulmonary infection, and to provide an alternative diagnostic method for clinical practice.

Clinical data were collected from patients with suspected of pulmonary infection at the Thoracic Surgery Center of the Xinjiang Uygur Autonomous Region Sixth People’s Hospital. Samples, including bronchial lavage fluid (BALF), fresh tissue, pleural effusion, and sputum, were collected by attending physicians based on the patients’ clinical conditions. A total of 166 patients were enrolled, and their samples were subjected to pathogen detection using both tNGS and traditional pathogen detection methods (TPDs). The pathogen detection performance of tNGS was then compared with that of TPDs.

The positive detection rate of tNGS was significantly higher than that of TPDs (81.33% vs. 32.53%, p < 0.001). Among the 166 samples, tNGS identified a total of 65 pathogens, whereas TPDs identified only 14 (11 bacterial species, 2 fungal species, and Mycoplasma pneumoniae). TPDs primarily identified bacteria (including Mycobacterium tuberculosis) and fungi, and were unable to detect viruses. In contrast, tNGS revealed a broader spectrum of pathogens, including 35 bacterial species, 10 fungal species, 18 viral species, as well as Mycoplasma pneumoniae and Chlamydia pneumoniae. Notably, tNGS demonstrated greater efficiency in detecting mixed infections and further identified 16 antibiotic resistance genes (ARGs).

tNGS exhibits higher sensitivity, a broader pathogen detection spectrum, and enhanced capability to identify mixed infections, along with the ability to detect ARGs. These advantages establish tNGS as a promising and reliable diagnostic modality for patients with pulmonary infections.

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