Department of Molecular Biology and Biotechnology, The University of Sheffield, Western Bank, Sheffield S10 2TN, UK.
School of Informatics, University of Edinburgh, Informatics Forum, 10 Crichton Street, Edinburgh EH8 9AB, UK.
Microbiology (Reading). 2012 Jan;158(Pt 1):284-292. doi: 10.1099/mic.0.053843-0. Epub 2011 Oct 20.
We describe a hybrid transcriptomic and modelling analysis of the dynamics of a bacterial response to stress, namely the addition of 200 µM Zn to Escherichia coli growing in severely Zn-depleted medium and of cells growing at different Zn concentrations at steady state. Genes that changed significantly in response to the transition were those reported previously to be associated with zinc deficiency (zinT, znuA, ykgM) or excess (basR, cpxP, cusF). Cellular Zn levels were confirmed by ICP-AES to be 14- to 28-fold greater after Zn addition but there was also 6- to 8-fold more cellular Fe 30 min after Zn addition. Statistical modelling of the transcriptomic data generated from the Zn shift focused on the role of ten key regulators; ArsR, BaeR, CpxR, CusR, Fur, OxyR, SoxS, ZntR, ZraR and Zur. The data and modelling reveal a transient change in the activity of the iron regulator Fur and of the oxidative stress regulator SoxS, neither of which is evident from the steady-state transcriptomic analyses. We hypothesize a competitive binding mechanism that combines these observations and existing data on the physiology of Zn and Fe uptake. Formalizing the mechanism in a differential equation model shows that it can reproduce qualitatively the behaviour seen in the data. This gives new insights into the interplay of these two fundamental metal ions in gene regulation and bacterial physiology, as well as highlighting the importance of dynamic studies to reverse-engineer systems behaviour.
我们描述了一种混合转录组学和建模分析细菌对压力反应的动态，即添加 200µM Zn 到在严重缺锌培养基中生长的大肠杆菌，以及在稳态下生长在不同 Zn 浓度下的细胞。对过渡有显著变化的基因是先前报道与缺锌（zinT、znuA、ykgM）或过量（basR、cpxP、cusF）相关的基因。通过 ICP-AES 确认细胞中的 Zn 水平在添加 Zn 后增加了 14 到 28 倍，但在添加 Zn 30 分钟后，细胞中的 Fe 水平也增加了 6 到 8 倍。对从 Zn 转变生成的转录组数据进行的统计建模集中在十个关键调节剂的作用上：ArsR、BaeR、CpxR、CusR、Fur、OxyR、SoxS、ZntR、ZraR 和 Zur。数据和建模揭示了铁调节剂 Fur 和氧化应激调节剂 SoxS 的活性发生短暂变化，而这两种调节剂在稳态转录组分析中都不明显。我们假设了一种竞争结合机制，该机制结合了这些观察结果和现有的关于 Zn 和 Fe 摄取生理学的数据。在微分方程模型中形式化该机制表明，它可以定性地再现数据中观察到的行为。这为这两种基本金属离子在基因调控和细菌生理学中的相互作用提供了新的见解，同时也强调了动态研究对逆向工程系统行为的重要性。
