RT期刊文章SR电子T1功能性下气道基因组群的功能分析，以捕获活跃的微生物代谢JF欧洲呼吸杂志JO EUR RESSIR J FD欧洲呼吸学会SP 2003434 DO 10.1183/13993003.0343434-2020 vo 58 IS 1 A1 A1 Sulaiman，Imran A1 Wu，Imran A1 Wu，188bet官网地址Benjamin G. A1 Li, Yonghua A1 Tsay, Jun-Chieh A1 Sauthoff, Maya A1 Scott, Adrienne S. A1 Ji, Kun A1 Koralov, Sergei B. A1 Weiden, Michael A1 Clemente, Jose C. A1 Jones, Drew A1 Huang,Yvonne J. A1 Stringer，Kathleen A. A1 Zhang，Lingdi A1 Geber，Adam A1 Banakis，Stephanie A1 Tipton，Laura A1 Ghedin，Elodie A1 Segal，Leopoldo N.58/1/2003434.根据细菌16S rRNA基因测序评估微生物群落的结构，对下气道进行了AB背景微生物组研究，但只能推断功能特征。较低气道中的微生物产物，例如短链脂肪酸（SCFA），对宿主的免疫张力产生了重大影响。因此，需要进行微生物组分析的功能方法。在这里，我们使用了研究支气管镜吸烟者队列中的上和下气道样品。此外，我们在实验小鼠模型中验证了结果。我们通过使用全基因组shot弹枪（WGS）和RNA metatranscriptome测序来扩展了微生物群的表征超过16S rRNA基因测序。还在下部气道样品中测量了SCFA，并与每个测序数据集相关。在小鼠模型中，进行了16S rRNA基因和RNA元转录组测序。使用推断的元基因组，WGS和metatranscriptome数据对下气道微生物群进行了功能评估。 Comparison with measured levels of SCFAs shows that the inferred metagenome from the 16S rRNA gene sequencing data was poorly correlated, while better correlations were noted when SCFA levels were compared with WGS and metatranscriptome data. Modelling lower airway aspiration with oral commensals in a mouse model showed that the metatranscriptome most efficiently captures transient active microbial metabolism, which was overestimated by 16S rRNA gene sequencing.Conclusions Functional characterisation of the lower airway microbiota through metatranscriptome data identifies metabolically active organisms capable of producing metabolites with immunomodulatory capacity, such as SCFAs.This study shows that both whole-genome shotgun and RNA metatranscriptome sequencing can be done on lower airway samples and can provide valuable information on bacterial function https://bit.ly/3hNmZfi