Interfakultäres Institut für Genetik und Funktionelle Genomforschung, Ernst-Moritz-Arndt-Universität Greifswald, Germany.
Institut für Mikrobiologie, Ernst-Moritz-Arndt-Universität Greifswald, Germany.
Microbiology (Reading). 2012 Mar;158(Pt 3):696-707. doi: 10.1099/mic.0.055434-0. Epub 2011 Dec 15.
The structure of the SigB-dependent general stress regulon of Bacillus subtilis has previously been characterized by proteomics approaches as well as DNA array-based expression studies. However, comparing the SigB targets published in three previous major transcriptional profiling studies it is obvious that although each of them identified well above 100 target genes, only 67 were identified in all three studies. These substantial differences can likely be attributed to the different strains, growth conditions, microarray platforms and experimental setups used in the studies. In order to gain a better understanding of the structure of this important regulon, a targeted DNA microarray analysis covering most of the known SigB-inducing conditions was performed, and the changes in expression kinetics of 252 potential members of the SigB regulon and appropriate control genes were recorded. Transcriptional data for the B. subtilis wild-type strain 168 and its isogenic sigB mutant BSM29 were analysed using random forest, a machine learning algorithm, by incorporating the knowledge from previous studies. This analysis revealed a strictly SigB-dependent expression pattern for 166 genes following ethanol, butanol, osmotic and oxidative stress, low-temperature growth and heat shock, as well as limitation of oxygen or glucose. Kinetic analysis of the data for the wild-type strain identified 30 additional members of the SigB regulon, which were also subject to control by additional transcriptional regulators, thus displaying atypical SigB-independent induction patterns in the mutant strain under some of the conditions tested. For 19 of these 30 SigB regulon members, published reports support control by secondary regulators along with SigB. Thus, this microarray-based study assigns a total of 196 genes to the SigB-dependent general stress regulon of B. subtilis.
先前，通过蛋白质组学方法和基于 DNA 芯片的表达研究，已经对枯草芽孢杆菌 SigB 依赖的一般应激调控子的结构进行了描述。然而，将之前 3 项主要转录谱研究中发表的 SigB 靶标进行比较，很明显，尽管每一项研究都鉴定出了 100 多个靶基因，但只有 67 个基因在这 3 项研究中都被鉴定出来。这些显著差异可能归因于研究中使用的不同菌株、生长条件、微阵列平台和实验设置。为了更好地理解这个重要调控子的结构，进行了一项靶向 DNA 微阵列分析，该分析涵盖了大多数已知的 SigB 诱导条件，并记录了 252 个潜在 SigB 调控子成员和适当对照基因的表达动力学变化。使用随机森林（一种机器学习算法）对枯草芽孢杆菌 168 野生型菌株和其同源 sigB 突变体 BSM29 的转录数据进行了分析，该算法整合了先前研究的知识。这项分析表明，在乙醇、丁醇、渗透压和氧化应激、低温生长和热休克以及氧气或葡萄糖限制等情况下，166 个基因严格依赖 SigB 表达。对野生型菌株数据的动力学分析确定了 SigB 调控子的另外 30 个成员，这些成员还受到其他转录调节剂的控制，因此在测试的一些条件下，在突变体菌株中表现出非典型的 SigB 非诱导模式。在这 30 个 SigB 调控子成员中，有 19 个的发表报告支持次级调节剂与 SigB 共同控制。因此，这项基于微阵列的研究将总共 196 个基因分配到枯草芽孢杆菌 SigB 依赖的一般应激调控子中。
