Transitions in lung microbiota landscape associate with distinct patterns of pneumonia progression

Abstract

The precise microbial determinants driving clinical outcomes in severe pneumonia are unknown. Competing ecological forces produce dynamic microbiota states in health and disease, and a more thorough understanding of these states has the potential to improve pneumonia therapy. Here, we leverage a large collection of bronchoscopic samples from patients with suspected pneumonia to determine lung microbial ecosystem dynamics throughout the course of pneumonia. We combine 16S rRNA gene, metagenomic, and metatranscriptomic sequencing with bacterial-load quantification to reveal clinically relevant drivers of pneumonia progression. Microbiota states are predictive of pneumonia subtypes and exhibit differential stability and pneumonia therapy response. Disruptive forces, such as aspiration, are associated with cohesive changes in gene expression and microbial community structure. In summary, we show that host and microbiota landscapes change in unison with clinical phenotypes and that microbiota state dynamics reflect pneumonia progression. We suggest that distinct pathways of lung microbial community succession mediate pneumonia progression.

Keywords: infection; metagenomics; metatranscriptomics; multiomics; pneumonia; respiratory tract microbiome.