Evaluation of respiratory samples in etiology diagnosis and microbiome characterization by metagenomic sequencingOriginal paper
Karen Pendergrass is a microbiome researcher specializing in microbiome-targeted interventions (MBTIs). She systematically analyzes scientific literature to identify microbial patterns, develop hypotheses, and validate interventions. As the founder of the Microbiome Signatures Database, she bridges microbiome research with clinical practice. In 2012, based on her own investigative research, she became the first documented case of FMT for Celiac Disease, four years before the first published case study.
Read MoreWhat was studied?
This study evaluated how specimen choice shapes metagenomic next-generation sequencing (mNGS) diagnosis of respiratory infections. Researchers compared four specimen types: sputum, bronchoalveolar lavage fluid (BALF), lung tissue, and pleural fluid. They retrospectively analyzed mNGS data against discharge diagnoses, calculating positive and negative predictive values for bacteria, mycobacteria, and fungi. They also characterized the respiratory microbiome across infection types and immune states, and built a threshold-based bioinformatic pipeline to automate pathogen calling.
Who was studied?
The data came from 1261 respiratory specimens from 943 patients at Zhongshan Hospital, Shanghai, China, collected between March 2017 and October 2019. Patients were grouped by infection status and immune state: 740 immunocompetent with infection, 288 immunocompromised with infection, 154 immunocompromised without infection, and 79 immunocompetent controls. The validation for predictive values used 405 microbiologically confirmed infections and 233 non-infection cases. This was a human clinical dataset, not an animal or in-vitro study.
What were the most important findings?
BALF gave the strongest diagnostic performance. Overall positive predictive value was 73.7% and negative predictive value 92.1%. For fungi, BALF reached 35.5% versus only 10.2% in sputum. Sputum and lung tissue were better for Mycobacterium tuberculosis, matching the known route of upper-airway colonization. mNGS detected tuberculosis better than culture but was weaker for nontuberculous mycobacteria. The BALF microbiome covered nearly all species seen in other specimens. Tumor patients showed unique bacterial and viral profiles, and Epstein-Barr virus reads were positively associated with tumor status (p 0.023, odds ratio 1.399).
What are the greatest implications of this study?
The findings support using BALF as the preferred specimen for mNGS diagnosis of suspected common bacterial, nontuberculous mycobacterial, and fungal respiratory infections. Sputum and lung tissue remain useful for suspected tuberculosis. Because the airway is not sterile, distinguishing true pathogens from commensals and contaminants is the core challenge. Specimen-specific thresholds help, but the automated pipeline was less sensitive than expert interpretation. Results are single-center and retrospective, so external validation is needed before broad clinical adoption.