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，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研究时变得明显。双稳态（ON/OFF）基因表达表观遗传地导致细胞类型分化并产生倾向于利用/存活环境变化的亚群。在这里，我们探讨了独特的功能，在枯草芽孢杆菌的运动基因的双表达，产生单一的运动细胞和非运动链的混合人口通过表观遗传机制。我们将测量运动开启和运动关闭状态之间的切换动力学以及生长过程中每个状态的遗传。我们将确定的机制，其中的替代西格玛因子CD是由两个转录水平的逐渐下降，沿着一个27 kb的操纵子，和调节响应鞭毛组装，产生的基因表达。最后，我们将确定一个未知功能的发育调节因子SwrA使处于ON或OFF状态的人口比例发生偏差的机制。革兰氏阴性菌（如大肠杆菌）的运动性及其控制已被长期研究。大肠杆菌，我们打算提高进化上遥远的革兰氏阳性B。枯草杆菌的一个首演模型系统的运动基因调控的新范例的发现。双稳态是原核生物研究的一个重要新领域，它改变了我们对细菌种群的看法。我们收集的信息将直接关系到细菌的发展，抗生素治疗，毒力基因表达和细菌的发病机制。

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.