Chao Lingshan, Li Jihong, Zhang Ya'nan, Pu Hao, Yan Xixin
Department of Respiratory and Critical Care Medicine, the Second Hospital of Hebei Medical University, Shijiazhuang, China.
Department of Laboratory Medicine, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Ann Transl Med. 2020 Dec;8(24):1644. doi: 10.21037/atm-20-7081.
Acute lower respiratory infections (ALRIs) have a high mortality rate. We aimed to apply a platform that rapidly detects 36 microorganisms and 49 antibiotic resistance markers in the clinical diagnosis of ALRI and drug resistance prediction.
Multicenter collection of clinical samples from patients with ALRIs was carried out from 2017 to 2018. Sputum culture (SC) was performed, which provided two outcomes: the detected pathogens and the resistance to different antibiotics. Additionally, each sputum sample was used to extract deoxyribonucleic acids (DNAs) followed by high-throughput sequencing.
Eleven commonly observed pathogens were surveyed, and for all samples with positive SC results (137 cases), the overall coverage was 95.62% according to the sequencing results. The receiver operating characteristic (ROC) curve was drawn, and cutoff reads of the most frequently detected pathogens were acquired. Overall, sequencing exhibited significantly higher sensitivity in the detection of pathogens compared with the traditional SC method, with a generally satisfactory specificity. Furthermore, we investigated the correlation between antibiotic resistance gene phenotypes and the actual outcomes of the drug sensitivity test, and some significant correlations were found, especially for the resistance to Amikacin in the presence of .
Sequencing-based sputum metagenomics can reveal a profile of the lung pathogen microbiome. The sequencing method offers both sufficient accuracy and significantly higher sensitivity in the detection of pathogens, and can be at least a complementary approach to traditional SC reporting. The sequencing technique also revealed some novel potential correlations between the presence of different pathogens, as well as new antimicrobial-resistant genes.
急性下呼吸道感染（ALRIs）死亡率很高。我们旨在应用一个平台，该平台能在ALRI的临床诊断和耐药性预测中快速检测36种微生物和49种抗生素耐药标志物。
2017年至2018年对ALRIs患者的临床样本进行多中心采集。进行痰培养（SC），其提供两种结果：检测到的病原体和对不同抗生素的耐药性。此外，每个痰样本用于提取脱氧核糖核酸（DNA），随后进行高通量测序。
对11种常见病原体进行了检测，对于所有痰培养结果呈阳性的样本（137例），根据测序结果总体覆盖率为95.62%。绘制了受试者工作特征（ROC）曲线，并获得了最常检测到的病原体的截断读数。总体而言，与传统的痰培养方法相比，测序在病原体检测中表现出显著更高的灵敏度，特异性总体令人满意。此外，我们研究了抗生素耐药基因表型与药敏试验实际结果之间的相关性，发现了一些显著相关性，特别是在存在某种情况时对阿米卡星的耐药性。
基于测序的痰宏基因组学可以揭示肺部病原体微生物群的概况。该测序方法在病原体检测中具有足够的准确性和显著更高的灵敏度，并且至少可以作为传统痰培养报告的一种补充方法。该测序技术还揭示了不同病原体存在之间的一些新的潜在相关性，以及新的抗菌耐药基因。
