One versus Many: Polymicrobial Communities and the Cystic Fibrosis Airway.
One versus Many: Polymicrobial Communities and the Cystic Fibrosis Airway.
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DOI：
10.1128/mbio.00006-21
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发表时间：
2021-03-16
期刊：
影响因子：
6.4
通讯作者：
O'Toole GA
中科院分区：
文献类型：
--
作者：
Jean-Pierre F;Vyas A;Hampton TH;Henson MA;O'Toole GA
非培养研究表明，囊性纤维化（CSFCF）患者的慢性肺部感染很少局限于一种微生物。据报道，这些多微生物群落的细菌成员之间的相互作用在呼吸道CF调节临床相关的表型。非培养研究表明，囊性纤维化（CSFCF）患者的慢性肺部感染很少局限于一种微生物。据报道，这些多微生物群落的细菌成员之间的相互作用在呼吸道CF调节临床相关的表型。此外，很明显，CF气道感染背景下的单一多微生物群落不能解释临床结局的多样性。虽然基于16S rRNA基因的大型研究使我们能够深入了解CF肺中发现的微生物组成和预测社区的功能能力，但在这里，我们认为计算机模拟方法可以帮助建立多微生物群落的临床相关体外模型，这些模型反过来可以用于实验测试和验证计算生成的假设。此外，我们认为，结合计算和实验方法将提高我们对驱动微生物群落功能的机制的理解，并确定新的治疗方法来靶向多微生物感染。
Culture-independent studies have revealed that chronic lung infections in persons with cystic fibrosis (pwCF) are rarely limited to one microbial species. Interactions among bacterial members of these polymicrobial communities in the airways of pwCF have been reported to modulate clinically relevant phenotypes. Culture-independent studies have revealed that chronic lung infections in persons with cystic fibrosis (pwCF) are rarely limited to one microbial species. Interactions among bacterial members of these polymicrobial communities in the airways of pwCF have been reported to modulate clinically relevant phenotypes. Furthermore, it is clear that a single polymicrobial community in the context of CF airway infections cannot explain the diversity of clinical outcomes. While large 16S rRNA gene-based studies have allowed us to gain insight into the microbial composition and predicted functional capacities of communities found in the CF lung, here we argue that in silico approaches can help build clinically relevant in vitro models of polymicrobial communities that can in turn be used to experimentally test and validate computationally generated hypotheses. Furthermore, we posit that combining computational and experimental approaches will enhance our understanding of mechanisms that drive microbial community function and identify new therapeutics to target polymicrobial infections.