Taylor Steven L, Leong Lex E X, Ivey Kerry L, Wesselingh Steve, Grimwood Keith, Wainwright Claire E, Rogers Geraint B
SAHMRI Microbiome Research Laboratory, Flinders University College of Medicine and Public Health, Adelaide, SA, Australia; Microbiome and Host Health, South Australia Health and Medical Research Institute, North Terrace, Adelaide, SA, Australia.
Microbiology and Infectious Diseases, SA Pathology, South Australia, Australia.
J Cyst Fibros. 2020 Nov;19(6):923-930. doi: 10.1016/j.jcf.2020.03.008. Epub 2020 Mar 19.
Cystic fibrosis (CF) is characterised by reduced airway clearance, microbial accumulation, inflammation, and lung function decline. Certain bacterial species may contribute disproportionately to worsening lung disease. However, the relative importance of these microorganisms compared to the absolute abundance of all bacteria is uncertain. We aimed to identify the characteristics of lower airway microbiology that best reflect CF airway inflammation and disease in children.
Analysis was performed on bronchoalveolar lavage (BAL) fluid from 78 participants of the Australasian CF Bronchoalveolar Lavage (ACFBAL) clinical trial, aged 4.5-5.5 years. Universal bacterial quantitative PCR (qPCR), species-specific qPCR, and 16S rRNA gene sequencing were performed on DNA extracts to determine total bacterial load, species-specific load and taxa relative abundance. Quantification of pre-specified pathogens was performed by culture-based methods. Bacteriological data were related to neutrophil counts, interleukin-8, lung function, and two computed-tomography based measures, CF-CT (as the primary measure) and PRAGMA.
Of all bacteriological measures assessed, total bacterial load determined by qPCR correlated most strongly with structural disease (CF-CT total score, r=0.30, P=0.0095). Specifically, total bacterial load correlated with bronchiectasis, airway wall thickening, mucus plugging and parenchymal disease sub-scores. In contrast, culture-based quantification, microbiota-derived measures, and pathogen-specific qPCR-based quantification were weakly associated with total CF-CT. Regression analyses supported correlation findings, with total bacterial load explaining the greatest variance in total CF-CT (R=0.097, P=0.0061). Correlations with PRAGMA score were comparable to CF-CT total score.
Within the ACFBAL trial, culture-independent quantification of total bacteria provided the most clinically-informative bacteriological measure in 5-year-old CF patients.
囊性纤维化（CF）的特征是气道清除功能降低、微生物积聚、炎症以及肺功能下降。某些细菌种类可能对肺部疾病的恶化起不成比例的作用。然而，与所有细菌的绝对丰度相比，这些微生物的相对重要性尚不确定。我们旨在确定最能反映儿童CF气道炎症和疾病的下呼吸道微生物学特征。
对澳大利亚CF支气管肺泡灌洗（ACFBAL）临床试验中78名年龄在4.5至5.5岁的参与者的支气管肺泡灌洗（BAL）液进行分析。对DNA提取物进行通用细菌定量PCR（qPCR）、种属特异性qPCR和16S rRNA基因测序，以确定总细菌载量、种属特异性载量和分类群相对丰度。通过基于培养的方法对预先指定的病原体进行定量。细菌学数据与中性粒细胞计数、白细胞介素-8、肺功能以及两种基于计算机断层扫描的测量指标CF-CT（作为主要测量指标）和PRAGMA相关。
在所有评估的细菌学指标中，通过qPCR测定的总细菌载量与结构性疾病（CF-CT总分，r = 0.30，P = 0.0095）的相关性最强。具体而言，总细菌载量与支气管扩张、气道壁增厚、黏液阻塞和实质疾病亚评分相关。相比之下，基于培养的定量、微生物群衍生指标以及基于病原体特异性qPCR的定量与总CF-CT的相关性较弱。回归分析支持相关性结果，总细菌载量解释了总CF-CT中最大的方差（R = 0.097，P = 0.0061）。与PRAGMA评分的相关性与CF-CT总分相当。
在ACFBAL试验中，对5岁CF患者进行的不依赖培养的总细菌定量提供了最具临床信息的细菌学测量指标。
