The Healthspan Machine: an automated method to screen for interventions that slow ageing

人们的寿命越来越长，但许多人的健康状况不佳，导致NHS、家庭和整个社会的负担越来越重。对衰老生物学的更深入了解将使研究人员能够设计出干预措施，使老年人保持活动能力和更长久的健康。一个人保持健康的时间被称为“健康跨度”，我们的目标是找到延长这段健康时间的干预措施。衰老领域一些最有成效的研究使用了小型实验动物，因为它们衰老得很快，我们可以弄清楚它们的基因和环境条件是如何影响衰老的。秀丽隐杆线虫（Caenorhabditis elegans）的寿命只有几周，对这种动物的研究已经在衰老生物学以及许多其他生物学领域产生了一些见解。将这种蠕虫用于生物学研究的优势之一是它可以用于基因筛选。基因筛选包括在大量的变异蠕虫中寻找那些不同的。研究这些特殊的突变体揭示了使它们不同的基因的功能。然而，找到一个长寿的突变体是非常困难的，因为即使在基因相同的动物之间，衰老也是非常不同的，这些蠕虫需要观察几个星期。这个建议解决了这些问题。首先，我们不是寻找寿命更长的蠕虫，而是寻找那些持续运动更长的蠕虫，即那些具有更长的“健康寿命”的蠕虫。其次，我们将使用自动化技术来测量蠕虫运动。我们的设计灵感来自哈佛医学院最近研发的“寿命机器”。他们的方法是使用特制的高规格平板扫描仪来测量大量蠕虫的寿命。虽然这项技术是可行的，并且已经被许多研究小组采用，但它对用户来说是具有挑战性和昂贵的，并且它消耗了大量的空间和能源。我们的建议通过使用几个小型零售相机来跟踪蠕虫运动来克服这些问题。“寿命机器”检测每个蠕虫的死亡。我们的方法是监测一群蠕虫是如何随着年龄增长而减速的。我们修改了运行相机的软件，以便在短时间内拍摄一群蠕虫的数百张照片。利用最初用于监测天文图像的技术，我们对蠕虫图像进行处理，并使用处理后的图像来测量蠕虫的运动。定期监测虫群将使我们能够测量它们随年龄增长而减少的活动。通过扩大这项技术的规模，我们可以测试上千种不同的基因和条件，这些基因和条件可能会延缓运动能力的衰退。我们制作了一个“健康机器”的原型用两台摄像机对准两个装有蠕虫的培养皿。在使用100多个摄像头扩展到一台功能机器的过程中存在许多障碍，但我们已经设计了一套解决方案来克服这些挑战，并制定了开发机器的逻辑顺序。例如，我们需要能够非常快速地存储和处理大量数据，我们计划通过使用与摄像机通信的计算机网络来实现这一目标。我们将从连接6到12台摄像机到计算机开始，然后将多台计算机连接在一起。每台计算机将处理来自附加相机的原始图像，生成更小的文件，以便于进一步的数据处理和存储。到项目结束时，我们的目标是拥有一台功能齐全的机器，可以用于许多不同的筛选实验，并被世界各地的其他研究人员使用。这些实验将帮助我们了解导致长寿的基因和环境条件。然后，我们还可以使用“健康跨度机器”来筛选新的营养和药物干预化合物，使我们更健康。

People are living longer but many suffer several years of ill health leading to an increasing burden to the NHS, families and society in general. A greater understanding of the biology of ageing would allow researchers to design interventions that would keep the elderly mobile and generally healthy for longer. The time that someone stays healthy is termed their "healthspan", and we aim to find interventions that extend this time of health. Some of the most productive research in the field of ageing has used small lab animals because they age quickly and we can work out how their genes and environmental conditions influence ageing. The nematode worm Caenorhabditis elegans has a lifespan of only a few weeks, and studies with this animal have produced several insights in the biology of ageing, as well as in many other areas of biology. One of the strengths of using this worm for biological research is that it can be used for genetic screens. A genetic screen involves searching through a large number of mutant worms to find those that are different. Studying these particular mutants reveals the function of genes that make them different. However, finding a long-lived mutant is very difficult because even between genetically identical animals, ageing is very variable and the worms need to be observed over several weeks. This proposal addresses these problems.Firstly, rather than looking for worms that live longer, we will find those that stay moving for longer, i.e. those with a longer "healthspan". Secondly, we will use automated techniques to measure worm movement. Our proposal is inspired by the "Lifespan Machine", which was recently developed at Harvard Medical School. Their method uses specially adapted high-specification flatbed scanners to measure the lifespan of large numbers of worms. While this technology works and has been taken up by a number of research groups, it can be challenging and expensive for users to implement and it consumes considerable space and energy. Our proposal overcomes these issues by using several small retail cameras to track worm movement. The "Lifespan Machine" detects the death of each worm. Our approach is to monitor how a group of worms slow down as they age. We have modified the software that runs the cameras so that hundreds of images of a group of worms are taken in a short space of time. Using techniques originally developed to monitor astronomical images, we process the worm images and use the processed images to measure the movement of the worms. Monitoring the groups of worms at regular time intervals will allow us to measure the decline in movement with age. By scaling up this technology we can test 1000s of different genes and conditions that might delay this decay of movement. We have generated a prototype of this "Healthspan Machine" with two cameras trained on two petri dishes containing worms. There are many obstacles to scaling up to a functioning machine using 100+ cameras but we have devised a set of solutions to overcome these challenges and a logical order of developing the machine. For example, we need to be able to store and process a large amount of data very quickly and we plan to do this by using a network of computers that communicate with the cameras. We will start with linking up 6 to 12 cameras to computers, and then link multiple computers together. Each computer will process the raw images from the attached cameras, producing smaller files so that further data processing and storage is easier. By the end of the project, we aim to have a functioning machine that can be used for many different screening experiments and used by other researchers across the world. These experiments will help us understand the genes and environmental conditions that lead to a long healthspan. We can then also use the "Healthspan Machine" to screen compounds for new nutritional and pharmaceutical interventions that keep us healthier for longer.