The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800, Kgs. Lyngby, Denmark.
Department of Clinical Microbiology, Rigshospitalet, 2100, Copenhagen Ø, Denmark.
Nat Commun. 2019 Feb 7;10(1):629. doi: 10.1038/s41467-019-08504-7.
Persistent infections require bacteria to evolve from their naïve colonization state by optimizing fitness in the host via simultaneous adaptation of multiple traits, which can obscure evolutionary trends and complicate infection management. Accordingly, here we screen 8 infection-relevant phenotypes of 443 longitudinal Pseudomonas aeruginosa isolates from 39 young cystic fibrosis patients over 10 years. Using statistical modeling, we map evolutionary trajectories and identify trait correlations accounting for patient-specific influences. By integrating previous genetic analyses of 474 isolates, we provide a window into early adaptation to the host, finding: (1) a 2-3 year timeline of rapid adaptation after colonization, (2) variant "naïve" and "adapted" states reflecting discordance between phenotypic and genetic adaptation, (3) adaptive trajectories leading to persistent infection via three distinct evolutionary modes, and (4) new associations between phenotypes and pathoadaptive mutations. Ultimately, we effectively deconvolute complex trait adaptation, offering a framework for evolutionary studies and precision medicine in clinical microbiology.
持续感染要求细菌通过在宿主中同时适应多种特征来优化适应性，从而从其初始定植状态进化，这可能会掩盖进化趋势并使感染管理复杂化。因此，在这里，我们对 39 名年轻囊性纤维化患者的 443 株纵向铜绿假单胞菌分离株的 8 种与感染相关的表型进行了筛选，时间跨度为 10 年。通过使用统计建模，我们可以描绘进化轨迹并确定解释患者特定影响的特征相关性。通过整合对 474 株分离株的先前遗传分析，我们深入了解了早期对宿主的适应情况，发现：（1）定植后快速适应的 2-3 年时间线，（2）反映表型和遗传适应性之间不匹配的“原始”和“适应”状态变体，（3）通过三种不同的进化模式导致持续感染的适应性轨迹，以及（4）表型与病理适应突变之间的新关联。最终，我们有效地解析了复杂的特征适应性，为临床微生物学中的进化研究和精准医学提供了框架。
