Integrated multiplex PCR and metatranscriptomics reveal upper-lower airway microbial landscapes in pediatric respiratory infections
Year: 2026
Type: article
Study design: Observational Study
Abstract: Despite widespread use of multiple PCR, a substantial proportion of pediatric acute respiratory tract infections (ARTIs) lack identifiable pathogens and are classified as unknown etiology. The microbial characteristics and clinical relevance of these cases remain unclear. In this study, we compared the airway microbiomes of PCR-positive and PCR-negative ARTIs and examined their relationships with sampling site and disease severity. A total of 514 hospitalized children with ARTIs were enrolled. Nasopharyngeal swabs (NS) and bronchoalveolar lavage fluid (BALF) samples were tested using a 22-target multiplex PCR panel and subsequently stratified by pathogen status for pooled metatranscriptomic sequencing to profile active microbial communities, viral genotypes, and antibiotic resistance genes. PCR identified common respiratory pathogens in 77.0% of NS and 54.1% of BALF samples. Metatranscriptomic analysis showed that PCR-negative pools displayed markedly lower viral activity and comparatively higher bacterial transcript abundance, with notable enrichment of Pseudomonas. Microbial signatures differed between upper and lower airway samples and across clinical severity, with severe cases demonstrating increased bacterial burden and Pseudomonas enrichment, whereas mild infections exhibited relatively stronger viral signals. Under current thresholds, antibiotic resistance genes were detected in patient pools but not in healthy controls. Overall, PCR-negative pediatric ARTIs exhibited distinct, bacteria-enriched microbial profiles. Integrating metatranscriptomics with PCR enhances pathogen characterization and reveals site- and severity-related microbial patterns that may support diagnostic evaluation and clinical management.
Source: Virologica Sinica
Authors: Peilan Wei, Lu Zhang, Qingtao Hu, Airu Zhu, Zhen Zhuang, Zhaoyong Zhang, Shengnan Zhang, Jiantao Chen, Xinyi Xiong, Bin Qu, Yuanyuan Zhang, Lei Chen, Zhiwei Xu, Zhao Chen, Qier Zhong, Xindan Xing, Xinxin Li, Jingjing Gao, Yifang He, Guifei Xie, Juan Shang, Xiaoke Guo, Jiaxin Jiang, Yongxia Shi, Jingxian Zhao, Yanqun Wang, Jincun Zhao, Yingkang Jin
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $1,500
OpenAlex ID: W7127982954
