Han Xinjie, Ma Peng, Liu Chang, Yao Chen, Yi Yaxing, Du Zhenshan, Liu Pengfei, Zhang Minlong, Xu Jianqiao, Meng Xiaoyun, Liu Zidan, Wang Weijia, Ren Ruotong, Xie Lixin, Han Xu, Xiao Kun
College of Pulmonary & Critical Care Medicine, 8th Medical Center of Chinese PLA General Hospital, Beijing, China.
Chinese PLA Medical School, Beijing, China.
Adv Biotechnol (Singap). 2025 Apr 25;3(2):13. doi: 10.1007/s44307-025-00064-w.
The homeostatic balance of the lung microbiota is important for the maintenance of normal physiological function of the lung, but its role in pathological processes such as severe pneumonia is poorly understood.
We screened 34 patients with community-acquired pneumonia (CAP) and 12 patients with hospital-acquired pneumonia (HAP), all of whom were admitted to the respiratory intensive care unit. Clinical samples, including bronchoalveolar lavage fluid (BALF), sputum, peripheral blood, and tissue specimens, were collected along with traditional microbiological test results, routine clinical test data, and clinical treatment information. The pathogenic spectrum of lower respiratory tract pathogens in critically ill respiratory patients was characterized through metagenomic next-generation sequencing (mNGS). Additionally, we analyzed the composition of the commensal microbiota and its correlation with clinical characteristics.
The sensitivity of the mNGS test for pathogens was 92.2% and the specificity 71.4% compared with the clinical diagnosis of the patients. Using mNGS, we detected more fungi and viruses in the lower respiratory tract of CAP-onset severe pneumonia patients, whereas bacterial species were predominant in HAP-onset patients. On the other hand, using mNGS data, commensal microorganisms such as Fusobacterium yohimbe were observed in the lower respiratory tract of patients with HAP rather than those with CAP, and most of these commensal microorganisms were associated with hospitalization or the staying time in ICU, and were significantly and positively correlated with the total length of stay.
mNGS can be used to effectively identify pathogenic pathogens or lower respiratory microbiome associated with pulmonary infectious diseases, playing a crucial role in the early and accurate diagnosis of these conditions. Based on the findings of this study, it is possible that a novel set of biomarkers and predictive models could be developed in the future to efficiently identify the cause and prognosis of patients with severe pneumonia.
肺部微生物群的稳态平衡对于维持肺部正常生理功能很重要，但其在严重肺炎等病理过程中的作用尚不清楚。
我们筛选了34例社区获得性肺炎（CAP）患者和12例医院获得性肺炎（HAP）患者，所有患者均入住呼吸重症监护病房。收集临床样本，包括支气管肺泡灌洗液（BALF）、痰液、外周血和组织标本，以及传统微生物检测结果、常规临床检测数据和临床治疗信息。通过宏基因组下一代测序（mNGS）对危重症呼吸患者下呼吸道病原体的致病谱进行了表征。此外，我们分析了共生微生物群的组成及其与临床特征的相关性。
与患者的临床诊断相比，mNGS检测病原体的敏感性为92.2%，特异性为71.4%。使用mNGS，我们在CAP起病的重症肺炎患者的下呼吸道中检测到更多的真菌和病毒，而在HAP起病的患者中细菌种类占主导。另一方面，利用mNGS数据，在HAP患者而非CAP患者的下呼吸道中观察到了诸如约氏梭杆菌等共生微生物，这些共生微生物大多与住院或在ICU的停留时间有关，并且与总住院时间呈显著正相关。
mNGS可用于有效识别与肺部感染性疾病相关的致病病原体或下呼吸道微生物群，在这些疾病的早期准确诊断中发挥关键作用。基于本研究的结果，未来有可能开发出一套新的生物标志物和预测模型，以有效识别重症肺炎患者的病因和预后。
