Image created by Dr. Michael J. Miller
A new retrospective study by researchers at the Department of Clinical Laboratory at the Second Affiliated Hospital of Nanchang University, China has shown that the high-throughput sequencing method called metagenomic next-generation sequencing (mNGS) can detect more than three times as many pathogens in pulmonary infections as conventional microbiological tests (CMTs). The new research, published in Frontiers in Cellular and Infection Microbiology, showed that mNGS detected pathogens in 86% of cases, significantly higher than the 67% detected by CMTs and identified 96 pathogens compared with only 28 pathogens identified through traditional testing.
“Metagenomic next-generation sequencing (mNGS) provides a broad-spectrum, rapid, and precise diagnostic approach for detecting pathogens in pulmonary infections. This enables personalized anti-infection therapy and enhances patient outcomes,” said corresponding author Wang Xiaozhong, PhD, director of the Department of Clinical Laboratory, The Second Affiliated Hospital of Nanchang University.
The study focused on identifying pathogens from pulmonary infection samples that included bronchoalveolar lavage fluid (BALF), blood, and sputum and comparing the performance of mNGS with those of conventional culture methods. The 96 pathogens detected included 59 bacteria, 18 fungi, 14 viruses, and four special pathogens.
The researchers note that an important advantage of mNGS is its capacity to detect atypical or rare pathogens that are frequently missed by CMTs. These include organisms such as Mycobacterium tuberculosis, Mycoplasma pneumoniae, Chlamydia psittaci, Pneumocystis jirovecii, and Talaromyces marneffei. The ability to identify these pathogens early enables clinicians to initiate targeted therapies that improve patient outcomes.
In terms of clinical utility, the study showed that 133 patients had their antibiotic treatment plans adjusted based on mNGS results. Of these, 54 patients, or 40.6%, benefited from more precise therapies. One instance of unnecessary antibiotic use was noted, but the overall outcome demonstrated the utility of mNGS in optimizing antimicrobial therapy. In total, treatment adjustments based on mNGS data led to improved prognoses in 16 patients with difficult-to-diagnose infections, the study demonstrated.
“Our results demonstrated that mNGS detects a broader spectrum of pathogens, especially fungi and viruses… indicating the feasibility of mNGS in assisting the clinical treatment of pulmonary infections,” the researchers wrote.
In addition to the higher detection rates, the study also compared diagnostic performance. The sensitivity and specificity of CMTs were found to be 68.75% and 50%, respectively. While previous studies often reported lower specificity for mNGS, in this study, mNGS showed a modestly higher specificity, possibly due to the use of BALF samples, which are less prone to contamination from upper respiratory flora.
Despite these findings of the potential diagnostic strengths of mNGS , it is not without limitations. The researchers acknowledged 18 false-negative results, likely due to low pathogen abundance or sample degradation. There were also four false-positive results, possibly caused by the misidentification of colonizing or contaminant organisms or prior infections without active disease.
Based on current capabilities, the study’s authors do not propose mNGS as a replacement for CMTs but rather as a complementary tool. They recommend integrating mNGS with clinical assessment, imaging, and conventional test results for a more comprehensive diagnostic approach.
“In the future, integrating mNGS with clinical manifestations, imaging findings, and traditional testing methods for multidimensional analysis will help establish an integrated diagnostic and treatment model featuring ‘rapid identification—precise intervention—dynamic monitoring,'” Wang said.
The findings suggest that mNGS has a strong potential to enhance clinical care by improving the speed and accuracy of pathogen detection in lung infections. But further prospective studies with larger cohorts will be necessary before mNGS can be more broadly adopted in routine diagnostics.
REFERENCE
Chen Song , Ouyang Tanglin , Wang Kaiyang , Hou Xuan , Zhang Rong , Li Meiyong , Zhang Haibin , He Qinghua , Li Xiuzhen , Liu Zezhang , Wang Xiaozhong , Huang Bo. Application of metagenomic next-generation sequencing in pathogen detection of lung infections. Frontiers in Cellular and Infection Microbiology. Volume 15 - 2025. DOI=10.3389/fcimb.2025.1513603.
ABSTRACT
Metagenomic next-generation sequencing (mNGS) has been widely reported to provide crucial information for the diagnosis and treatment of infectious diseases. In this study, we aimed to evaluate mNGS in pathogens diagnosis of lung infections.MethodsA total of 188 patients who were suspected of pulmonary infection and received medical treatment at the Second Affiliated Hospital of Nanchang University from August 2022 to December 2023 were enrolled in this study. Conventional microbiological tests (CMTs) and mNGS were employed for pathogens diagnosis.ResultsStatistical results indicated that mNGS were significantly better than CMTs in sensitivity, negative predictive value, and negative likelihood ratio. Remarkably, the positive detection rate of mNGS was significantly higher than that of CMTs (86.17% vs 67.55%, P < 0.01). Through mNGS, we identified 96 pathogens, comprising 59 bacteria, 18 fungi, 15 viruses, and 4 special pathogens. In contrast, CMTs detected 28 species, including 25 bacteria and 3 fungi. The effectiveness rate of antibiotic treatment decisions based on mNGS results was 40.60%. Out of 54 cases with positive treatment impacts, mNGS results contributed to the treatment and improved prognosis of 16 infections caused by atypical pathogens.ConclusionOur results proved the essential role of mNGS in lung infection diagnosis, enabling early detection and the prompt development of targeted anti-infection therapies. We recommended that the clinical application of mNGS can enhance treatment effectiveness and improve patient prognosis.