The mechanism of bistable motility gene expression in Bacillus subtilis.

描述（由申请人提供）：细菌种群曾经被认为是均匀的，但实际上是不同细胞类型的异质混合物，当在单个细胞水平上进行研究时，这种混合物变得显而易见。双稳态（开/关）基因表达在表观遗传上导致细胞类型分化，并产生易于利用/生存环境变化的亚群。在这里，我们探讨了枯草芽孢杆菌中运动基因双稳态表达的独特特征，该基因通过表观遗传机制产生单个运动细胞和非运动链的混合群体。我们将测量运动开启和运动关闭状态之间切换的动力学以及生长过程中每种状态的遗传。我们将确定替代 sigma 因子 CD 的机制，通过 27 kb 操纵子转录水平的逐渐下降和响应鞭毛组装的调节来控制，以产生双稳态基因表达。最后，我们将确定未知功能的发育调节因子 SwrA 使处于开启或关闭状态的群体比例产生偏差的机制。人们对大肠杆菌等革兰氏阴性细菌的运动性及其控制进行了长期研究，我们打算将进化距离较远的革兰氏阳性枯草芽孢杆菌提升为首要模型系统，以发现运动性基因调控的新范例。双稳定性是原核研究的一个重要新领域，它改变了我们对细菌种群的看法。我们收集的信息将与细菌发育、抗生素治疗、毒力基因表达和细菌发病机制直接相关。

DESCRIPTION (provided by applicant): Bacterial populations, once thought to be uniform, are in fact heterogeneous mixtures of distinct cell types that become apparent when studied at the level of individual cells. Bistable (ON/OFF) gene expression epigenetically results in cell type differentiation and creates subpopulations predisposed to exploit/survive environmental change. Here we explore the unique features of the bistable expression of motility genes in Bacillus subtilis that generates mixed populations of single motile cells and non-motile chains through an epigenetic mechanism. We will measure the kinetics of switching between motility-ON and motility-OFF states and the inheritance of each state during growth. We will determine the mechanism by which the alternative sigma factor CD is controlled by both a gradual decline in transcript levels along a 27 kb operon, and regulation in response to flagellar assembly, to produce bistable gene expression. Finally, we will determine the mechanism by which a developmental regulator of unknown function, SwrA, biases the proportion of the population that is in an ON or OFF state. Motility and its control has been long-studied in Gram negative bacteria like E. coli and we intend to elevate the evolutionarily distant Gram positive B. subtilis to a premiere model system for the discovery of new paradigms of motility gene regulation. Bistability is an important new area of prokaryotic research that changes the way we think about bacterial populations. The information we gather will be directly relevant to bacterial development, antibiotic therapy, virulence gene expression, and bacterial pathogenesis.