儿童哮喘健康与疾病状态下宿主和微生物群的双重转录组分析
Dual Transcriptomic Profiling of Host and Microbiota during Health and Disease in Pediatric Asthma.
作者信息
Pérez-Losada Marcos, Castro-Nallar Eduardo, Bendall Matthew L, Freishtat Robert J, Crandall Keith A
机构信息
Computational Biology Institute, George Washington University, Ashburn, Virginia, United States of America; Division of Emergency Medicine, Children's National Medical Center, Washington, DC, United States of America; CIBIO-InBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, Universidade do Porto, Campus Agrário de Vairão, Vairão, Portugal.
Computational Biology Institute, George Washington University, Ashburn, Virginia, United States of America; Universidad Andrés Bello, Center for Bioinformatics and Integrative Biology, Facultad de Ciencias Biológicas, Santiago, Chile.
出版信息
PLoS One. 2015 Jun 30;10(6):e0131819. doi: 10.1371/journal.pone.0131819. eCollection 2015.
BACKGROUND
High-throughput sequencing (HTS) analysis of microbial communities from the respiratory airways has heavily relied on the 16S rRNA gene. Given the intrinsic limitations of this approach, airway microbiome research has focused on assessing bacterial composition during health and disease, and its variation in relation to clinical and environmental factors, or other microbiomes. Consequently, very little effort has been dedicated to describing the functional characteristics of the airway microbiota and even less to explore the microbe-host interactions. Here we present a simultaneous assessment of microbiome and host functional diversity and host-microbe interactions from the same RNA-seq experiment, while accounting for variation in clinical metadata.
METHODS
Transcriptomic (host) and metatranscriptomic (microbiota) sequences from the nasal epithelium of 8 asthmatics and 6 healthy controls were separated in silico and mapped to available human and NCBI-NR protein reference databases. Human genes differentially expressed in asthmatics and controls were then used to infer upstream regulators involved in immune and inflammatory responses. Concomitantly, microbial genes were mapped to metabolic databases (COG, SEED, and KEGG) to infer microbial functions differentially expressed in asthmatics and controls. Finally, multivariate analysis was applied to find associations between microbiome characteristics and host upstream regulators while accounting for clinical variation.
RESULTS AND DISCUSSION
Our study showed significant differences in the metabolism of microbiomes from asthmatic and non-asthmatic children for up to 25% of the functional properties tested. Enrichment analysis of 499 differentially expressed host genes for inflammatory and immune responses revealed 43 upstream regulators differentially activated in asthma. Microbial adhesion (virulence) and Proteobacteria abundance were significantly associated with variation in the expression of the upstream regulator IL1A; suggesting that microbiome characteristics modulate host inflammatory and immune systems during asthma.
背景
呼吸道微生物群落的高通量测序（HTS）分析严重依赖于16S rRNA基因。鉴于这种方法的内在局限性，气道微生物组研究主要集中于评估健康和疾病状态下的细菌组成，以及其与临床和环境因素或其他微生物组的关系变化。因此，致力于描述气道微生物群功能特征的工作非常少，而探索微生物与宿主相互作用的工作则更少。在此，我们展示了从同一RNA测序实验中同时评估微生物组和宿主功能多样性以及宿主-微生物相互作用，同时考虑临床元数据的变化。
方法
对8名哮喘患者和6名健康对照者鼻上皮的转录组（宿主）和宏转录组（微生物群）序列进行计算机分离，并映射到可用的人类和NCBI-NR蛋白质参考数据库。然后，将哮喘患者和对照者中差异表达的人类基因用于推断参与免疫和炎症反应的上游调节因子。同时，将微生物基因映射到代谢数据库（COG、SEED和KEGG），以推断哮喘患者和对照者中差异表达的微生物功能。最后，应用多变量分析来寻找微生物组特征与宿主上游调节因子之间的关联，同时考虑临床差异。
结果与讨论
我们的研究表明，哮喘儿童和非哮喘儿童的微生物组代谢在高达25%的测试功能特性上存在显著差异。对499个差异表达的宿主炎症和免疫反应基因进行的富集分析揭示了哮喘中43个差异激活的上游调节因子。微生物黏附（毒力）和变形菌丰度与上游调节因子IL1A表达的变化显著相关；这表明在哮喘期间，微生物组特征调节宿主炎症和免疫系统。
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