Quantification of promoter activity using Lux read-outs and mathematical models

细菌对人类、动物和植物的健康和疾病都很重要。它们负责我们肠道的健康功能和健康的土壤;它们也负责许多食源性感染，如大肠杆菌。大肠杆菌和沙门氏菌，动物感染包括奶牛和绵羊的乳腺炎，以及医院感染如C.艰难梭菌和“超级细菌”MRSA。细菌可以在不同的环境条件下打开和关闭不同的基因。例如，在宿主细胞存在的情况下，它们可以打开建立感染的毒力基因，或者在抗生素存在的情况下，它们可以打开基因来对抗它们，例如将它们从细胞中泵出。由于基因活性的这种变化如此重要，大量旨在了解细菌并防止对人类和动物造成伤害的实验工作都涉及测量这些变化。这项工作的目的是开发更好的方法来测量基因活性的变化。有许多实验方法可以确定基因活性。我们打算改进的方法是基于一组特殊的基因，这些基因使一些细菌在黑暗中发光。我们可以将这些在黑暗中发光的基因连接到其他细菌中，这样我们就可以测量细胞中任何基因的反应：当被研究的基因被打开时，细菌就会发光。这项技术与其他技术相比有很多优势。首先，它非常敏感，使我们能够轻松测量非常小和快速的变化。这是一个优势，超过一个主要的替代技术，这是使用荧光蛋白的水母（其发明者获得了2008年诺贝尔奖），这是缓慢的，并遭受更大的背景噪音。其次，因为我们是在测量光，所以我们可以快速连续地进行很多次测量。这意味着我们可以轻松、廉价地捕获详细的时间序列响应;其他技术使用起来更昂贵、更复杂，使得这种详细的测量要么不切实际，要么不可能。第三，因为我们测量的是光，所以可以在活的动物身上进行重复测量，而不必屠宰它们。其他技术要求实验者在每次测量时杀死一只动物。动物实验对于开发和测试抗生素至关重要;如果应用得当，这项技术将使研究人员能够大大减少此类工作所需的动物数量。夜光技术并非没有缺点。为了工作，细菌制造一组特殊的蛋白质，这些蛋白质控制一组复杂的化学反应，从而产生光。因此，所测量的光只是基因活性的间接测量。我们希望能够从光测量中了解基因的活性。要做到这一点，我们需要知道细胞制造这些特殊蛋白质需要多长时间，产生光的化学反应的每一步发生的速度，以及每种关键化学物质在细胞中持续的时间。然后，这些数字需要输入一个详细的数学模型，描述所有这些事件，然后可以使用复杂的计算机算法来计算基因活动。在这项工作中，我们将专注于细菌金黄色葡萄球菌，这是重要的许多感染在动物和人类，包括皮肤感染，肺炎和乳腺炎，以及具有耐药性的形式，如MRSA。然而，我们开发的方法旨在通用并适用于其他细菌。这项工作的成果将是专门为S。金黄色;从光测量中计算出基因活性所需的所有测量;以及计算所需的数学模型和计算机软件。因此，这项工作将有助于研究人员了解和对抗这种细菌和其他细菌，包括开发针对MRSA的新抗生素。

Bacteria are important in human, animal and plant health and disease. They are responsible for healthy functioning of our gut and healthy soil; they are also responsible for many food-borne infections such as E. coli and Salmonella, animal infections including mastitis in cows and sheep, and hospital infections such as C. difficile and the 'superbug' MRSA. Bacteria can switch different genes on and off in different environmental conditions. For example, in the presence of host cells, they can switch on virulence genes that establish infection, or in the presence of antibiotics they can switch on genes to counter them, such as by pumping them out of their cells. Because such changes in gene activity are so important, a great deal of experimental work aimed at understanding bacteria and preventing harm to humans and animals involves measuring theses changes. The aim of this work is to develop better methods for measuring changes in gene activity. There are many experimental ways of determining gene activity. The method we intend to improve is based around a special set of genes that make some bacteria glow in the dark. We can take the glow-in-the-dark genes and hook them up in other bacteria in a way that can allow us to measure the response of any gene in the cells: when the gene under study would be switched on, the bacteria will glow. This technology has many advantages over other technologies. Firstly, it is very sensitive, allowing us to measure very small and fast changes easily. This is an advantage over one major alternative technology, which is using the fluorescent proteins made by jellyfish (whose inventors won the Nobel Prize in 2008), which is slower and suffers from greater background noise. Secondly, because we are measuring light, we can take very many measurements in quick succession. This means that we can capture detailed time series of responses easily and cheaply; other technologies are more expensive and complicated to use, making such detailed measurements either impractical or impossible. Thirdly, because we are measuring light, it is possible to take repeated measurements in live animals without having to slaughter them. Other technologies require experimenters to kill an animal for every measurement taken. Animal experiments are crucial for developing and testing antibiotics; this technology, if applied properly, will allow researchers to greatly reduce the number of animals needed in such work. Glow-in-the-dark technology is not without its draw-backs. In order to work, the bacteria make a special set of proteins, and these proteins control a complex set of chemical reactions that result in light. Thus the measured light is only an indirect measurement of gene activity. We want to be able to know what the gene activity is from the light measurement. To do this, we need to know how long it takes the cells to make these special proteins, how quickly each step of the chemical reactions that produce light take place, and how long each of the key chemicals persist in the cells. These numbers then need to be fed into a detailed mathematical model that describes all these events, and sophisticated computer algorithms can then be used to work out the gene activity. In this work, we will focus on the bacterium Staphylococcus aureus, which is important in many infections in animals and humans, including skin infections, pneumonia and mastitis, as well as having antibiotic-resistant forms such as MRSA. However, the approach we develop is intended to be general and applicable to other bacteria. The outcomes of this work will be glow-in-the-dark technology specially optimized for S. aureus; all the measurements necessary for working out gene activity from light measurements; and the mathematical models and computer software needed for the calculations. Thus this work will help researchers to understand and combat this and other bacteria, including the development of new antibiotics to target MRSA.