Sumner Jack T, Pickens Chiagozie I, Huttelmaier Stefanie, Moghadam Anahid A, Abdala-Valencia Hiam, Hauser Alan R, Seed Patrick C, Wunderink Richard G, Hartmann Erica M
Department of Civil and Environmental Engineering, Northwestern University, Evanston, IL, USA.
Department of Medicine, Division of Pulmonary and Critical Care, Northwestern University, Chicago, IL, USA.
medRxiv. 2024 Sep 25:2024.08.02.24311426. doi: 10.1101/2024.08.02.24311426.
The precise microbial determinants driving clinical outcomes in severe pneumonia are unknown. Competing ecological forces produce dynamic microbiota states in health; infection and treatment effects on microbiota state must be defined to improve pneumonia therapy. Here, we leverage our unique clinical setting, which includes systematic and serial bronchoscopic sampling in patients with suspected pneumonia, to determine lung microbial ecosystem dynamics throughout pneumonia therapy. We combine 16S rRNA gene amplicon, metagenomic, and transcriptomic sequencing with bacterial load quantification to reveal clinically-relevant pneumonia progression drivers. Microbiota states are predictive of pneumonia category and exhibit differential stability and pneumonia therapy response. Disruptive forces, like aspiration, associate 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.
导致严重肺炎临床结局的精确微生物决定因素尚不清楚。相互竞争的生态力量在健康状态下产生动态的微生物群状态;必须明确感染和治疗对微生物群状态的影响,以改善肺炎治疗。在此,我们利用我们独特的临床环境,包括对疑似肺炎患者进行系统的系列支气管镜采样,来确定整个肺炎治疗过程中的肺部微生物生态系统动态。我们将16S rRNA基因扩增子、宏基因组和转录组测序与细菌载量定量相结合,以揭示与临床相关的肺炎进展驱动因素。微生物群状态可预测肺炎类别,并表现出不同的稳定性和肺炎治疗反应。诸如误吸等破坏力量与基因表达和微生物群落结构的凝聚性变化相关。总之,我们表明宿主和微生物群格局与临床表型同步变化,并且微生物群状态动态反映肺炎进展。我们认为肺部微生物群落演替的不同途径介导了肺炎进展。