Respiratory Department, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
School of Clinical Medicine, Chongqing Medical and Pharmaceutical College, Chongqing, China.
Front Cell Infect Microbiol. 2023 Feb 15;13:1013809. doi: 10.3389/fcimb.2023.1013809. eCollection 2023.
Differences in bronchial microbiota composition have been found to be associated with asthma; however, it is still unclear whether these findings can be applied to recurrent wheezing in infants especially with aeroallergen sensitization.
To determine the pathogenesis of atopic wheezing in infants and to identify diagnostic biomarkers, we analyzed the bronchial bacterial microbiota of infants with recurrent wheezing and with or without atopic diseases using a systems biology approach.
Bacterial communities in bronchoalveolar lavage samples from 15 atopic wheezing infants, 15 non-atopic wheezing infants, and 18 foreign body aspiration control infants were characterized using 16S rRNA gene sequencing. The bacterial composition and community-level functions inferred from between-group differences from sequence profiles were analyzed.
Both α- and β-diversity differed significantly between the groups. Compared to non-atopic wheezing infants, atopic wheezing infants showed a significantly higher abundance in two phyla ( and unidentified bacteria) and one genus () and a significantly lower abundance in one phylum (). The random forest predictive model of 10 genera based on OTU-based features suggested that airway microbiota has diagnostic value for distinguishing atopic wheezing infants from non-atopic wheezing infants. PICRUSt2 based on KEGG hierarchy (level 3) revealed that atopic wheezing-associated differences in predicted bacterial functions included cytoskeleton proteins, glutamatergic synapses, and porphyrin and chlorophyll metabolism pathways.
The differential candidate biomarkers identified by microbiome analysis in our work may have reference value for the diagnosis of wheezing in infants with atopy. To confirm that, airway microbiome combined with metabolomics analysis should be further investigated in the future.
支气管微生物群落组成的差异与哮喘有关；然而，目前尚不清楚这些发现是否适用于婴儿反复喘息，尤其是伴有过敏原致敏的情况。
通过系统生物学方法分析反复喘息且伴有或不伴有特应性疾病的婴儿的支气管细菌微生物群，以确定特应性喘息婴儿的发病机制并确定诊断生物标志物。
采用 16S rRNA 基因测序技术分析 15 例特应性喘息婴儿、15 例非特应性喘息婴儿和 18 例异物吸入对照组婴儿支气管肺泡灌洗液样本中的细菌群落。分析从序列图谱中组间差异推断出的细菌组成和群落水平功能。
组间 α-多样性和β-多样性均有显著差异。与非特应性喘息婴儿相比，特应性喘息婴儿的两个门（和未鉴定细菌）和一个属（）的丰度显著较高，一个门（）的丰度显著较低。基于 OTU 特征的 10 个属的随机森林预测模型表明，气道微生物群对区分特应性喘息婴儿和非特应性喘息婴儿具有诊断价值。基于 KEGG 层次结构（第 3 级）的 PICRUSt2 预测细菌功能的差异包括细胞骨架蛋白、谷氨酸能突触和卟啉和叶绿素代谢途径。
本研究通过微生物组分析确定的差异候选生物标志物可能对特应性喘息婴儿喘息的诊断具有参考价值。为了证实这一点，未来应进一步进行气道微生物组与代谢组学分析。
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