Background: Lower respiratory tract infections (LRTIs) are a leading cause of mortality in children. These infections disrupt the equilibrium of lower respiratory tract (LRT) microbiota, allowing respiratory pathogens to dominate. The conventional culture method has limitations in describing complex microbiomes and may fail in the detection of respiratory pathogens. In the present study, we sought to use the advanced technology of 16S metagenomics next-generation sequencing (16SmNGS) to characterize the LRT microbiome among children with LRTIs and to identify the underlying respiratory pathogens that commonly evade detection by traditional culture. Methods: Twenty LRT specimens from hospitalized children with LRTIs were analyzed using 16SmNGS, as well as standard microbiological culture. Results: The 16SmNGS taxonomical analysis revealed the highest relative abundances for Streptococcus (27.7%) and Escherichia (13.3%) genera, which belong to the phyla of Firmicutes (45.4%) and Proteobacteria (45.3%), respectively. Streptococcus pneumoniae (45%), Escherichia coli (45%), Pseudomonas aeruginosa (15%), Staphylococcus aureus (10%), Acinetobacter baumanii (5%), and Haemophilus influenzae (5%) were the primary respiratory pathogens. Conventional culture failed to detect growth in 100%, 77.7%, and 55.5% of 16SmNGS-positive specimens for H. influenza, S. pneumoniae, and E. coli, respectively.Conclusions: The 16SmNGS technique revealed a predominance of Streptococcus and Escherichia genera belonging to the phyla of Firmicutes and Proteobacteria in pediatric LRTIs. In this exploratory study, 16SmNGS was able to enhance the identification of significant respiratory pathogens, particularly those difficult to isolate in culture. However, to rule out contamination by flora, it is advisable not to interpret metagenomics results independently from culture, clinical, and radiological data. In addition, further clinical correlations are desired to reach appropriate clinical decision.
Huang et al. (Fri,) studied this question.