@文章{Sulaiman2003434，作者= {Sulaiman, Imran和Wu, Benjamin G.和Li, Yonghua和Tsay, Jun-Chieh和Sauthoff, Maya和Scott, Adrienne S.和Ji, Kun和Koralov, Sergei B.和Weiden, Michael和Clemente, Jose C.和Jones, Drew和Huang, Yvonne J.和Stringer, Kathleen A.和Zhang, Lingdi和Geber, Adam和Banakis, Stephanie和Tipton, Laura和Ghedin, Elodie和Segal, Leopoldo n}，标题={功能性下气道微生物组基因组图谱捕捉活性微生物代谢}，体积={58}，数量={1}，定位-id ={2003434}，年份= {2021}，doi ={10.1185 /13993003.03434-2020}，出版商={欧洲呼吸学会}，摘要={背景基于细菌16S rRNA基因测序的下气道微生物组研究评估了微生物群落结构，但只能推断功能特征。188bet官网地址下气道中的短链脂肪酸(SCFAs)等微生物产物对宿主的免疫张力有显著影响。因此，对微生物组进行功能分析是必要的。方法在这里，我们使用来自研究支气管镜吸烟者队列的上气道和下气道样本。此外，我们在实验小鼠模型上验证了我们的结果。我们使用全基因组霰弹枪(WGS)和RNA元转录组测序，将微生物区系特征扩展到16S rRNA基因测序之外。下气道样本中也测量了SCFAs，并与每个测序数据集相关。在小鼠模型中，对16S rRNA基因和RNA元转录组进行测序。结果使用推断的宏基因组、WGS和元转录组数据对下气道微生物群的功能评价不同。 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}, issn = {0903-1936}, URL = {//www.qdcxjkg.com/content/58/1/2003434}, eprint = {//www.qdcxjkg.com/content/58/1/2003434.full.pdf}, journal = {European Respiratory Journal} }