Confocal image acquisition system with capacity for robotic fluid additions: flexible tool for high-content screening

具有机器人液体添加能力的共焦图像采集系统：用于高内涵筛选的灵活工具

• 批准号: MR/X013383/1
• 负责人: Paola Vergani
• 金额: $ 48.37万
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FX013383%2F1
• 关键词: Confocal; image; acquisition; system; capacity

Experiments investigating cell physiology and drug responses often exploit light-emitting (fluorescent) proteins and probes. Fluorescent probes, engineered to report on different cellular parameters, can be used as "biosensors". In the past, these experiments were conducted examining a small visual field under a microscope, manually adding compounds to dishes carrying cells, and selecting a small number of cells on which to measure changes. New image-acquisition systems allow this process to be done in an automated way. Cells are grown on plates with tens or hundreds of separate wells. At specified time points in the experiment, robotic arms add different compounds to the different wells, while images are captured by a camera which detects light of different colours, emitted by different biosensors. Small, localised changes in response to perturbations are captured rapidly and continuously over a period of time. Automated computer-based analysis of the images greatly increases the efficiency of work.Such image-acquisition systems have made it possible to increase the number of cells studied by orders of magnitude. This has eliminated experimenter bias and allowed us to focus on subsets of cells. Optical resolution has improved, so we can even study sub-cellular structures, called organelles. In addition, the possibility of using multiple biosensors simultaneously has allowed measurement of multiple characteristics in the same cell/organelle. Assays with multiple readouts are described as having "high-content". Furthermore many different conditions can be rapidly compared on a single plate, (e.g. composition of the fluid added, genetic makeup of cells, etc.). This allows rapid "screening" of a large number of compounds, for instance, which can be useful when developing drugs.The image-acquisition system we propose to buy will be used by many research groups, and will be available across the UCL campus. It will allow us to develop and run different high-content assays.One proposed study will explore potential new therapies for cancer. All our cells have mitochondria, organelles that burn fuels and generate packages of energy, readily available for the cell's needs. Mitochondria have their own genetic material, mtDNA, distinct from that in the cell's nucleus. Scientists have discovered that tumour cells very often have changes, called mutations, in their mtDNA, not present in the surrounding healthy tissues. These mtDNA mutations can be used as targeting labels, directing specialized enzymes (called mitoTALENs) to make damaging cuts in mtDNA from tumour cells, without affecting the nearby tissues. Cells with damaged mtDNA grow more slowly, and are more susceptible to chemotherapy drugs. Using high-content screening techniques, tumour and healthy cells will be treated with mitoTALENs under a variety of different conditions. The information gained will validate the approach, and lay foundations for future therapy development.Another lab will work on improving treatment for people with cystic fibrosis (CF). In CF the CFTR protein is missing or defective. CFTR regulates flow of anions (negatively charged chloride and bicarbonate ions) into and out of cells that line ducts of our body (airways, intestine, pancreas, liver etc). The flow of bicarbonate is especially important for controlling mucous secretions produced by these duct cells. CFTR-targeted drugs can help CF patients, but we know that, at least in liver ducts, current drugs restore chloride but not bicarbonate flow. We will generate a model anion flux biosensor system. This will allow us to rapidly monitor chloride and bicarbonate flow and to determine how CFTR drugs affect it for 62 different variants of CFTR found in patients. What we will learn about processes at the root of CF disease will help clinicians choose the best drugs for individual patients, and guide future drug development.

研究细胞生理和药物反应的实验通常会利用发光（荧光）蛋白质和探针。荧光探针设计用于报告不同的细胞参数，可用作“生物传感器”。过去，对这些实验进行了检查，检查了显微镜下的一个小视野，手动在携带细胞的菜肴中添加化合物，并选择少量的细胞来测量变化。新的图像收购系统允许以自动化的方式完成此过程。细胞在板上生长，该板有数十个或数百个单独的井。在实验中的指定时间点，机器人臂在不同的井中添加了不同的化合物，而图像是由检测到不同颜色的光的相机捕获的，该光线由不同的生物传感器发出。在一段时间内，迅速且连续地捕获了响应扰动的局部变化。基于计算机的自动化图像分析大大提高了工作的效率。图像收购系统使得可以增加按数量级研究的细胞数量增加。这消除了实验者的偏见，并使我们能够专注于细胞子集。光学分辨率有所改善，因此我们甚至可以研究称为细胞器的亚细胞结构。另外，同时使用多个生物传感器的可能性已允许测量同一细胞/细胞器中的多个特性。带有多个读数的测定被描述为具有“高素质”。此外，可以在单个板上快速比较许多不同的条件（例如，添加的流体组成，细胞的遗传组成等）。例如，这允许快速“筛选”大量化合物，在开发药物时可能很有用。我们建议购买的图像收购系统将由许多研究组使用，并且将在UCL校园中提供。这将使我们能够开发和运行不同的高含量测定法。一项拟议的研究将探索潜在的癌症新疗法。我们所有的细胞都有线粒体，燃烧燃料并产生能量包装的细胞器，很容易适合细胞的需求。线粒体具有自己的遗传物质MtDNA，与细胞核中的遗传物质不同。科学家发现，肿瘤细胞经常在其mtDNA中发生变化，称为突变，不存在于周围的健康组织中。这些mtDNA突变可以用作靶向标签，指导专门的酶（称为MitotaLens）从肿瘤细胞中造成损坏的切割，而不会影响附近的组织。损坏的mtDNA的细胞生长较慢，并且更容易受到化学疗法药物的影响。使用高含量筛查技术，在各种不同的条件下，将用丝分裂物处理肿瘤和健康细胞。获得的信息将验证该方法，并为将来的治疗开发奠定基础。其他实验室将致力于改善囊性纤维化患者（CF）的治疗。在CF中，CFTR蛋白缺失或有缺陷。 CFTR调节阴离子（带负电荷的氯化物和碳酸氢盐离子）的流动进入我们人体管道（气道，肠，胰腺，肝脏等）的细胞。碳酸氢盐的流动对于控制这些管道细胞产生的粘液分泌物尤为重要。 CFTR靶向的药物可以帮助CF患者，但我们知道，至少在肝管道中，当前药物恢复氯化物，但不能恢复碳酸氢盐流量。我们将生成模型的阴离子通量生物传感器系统。这将使我们能够迅速监测氯化物和碳酸氢盐流量，并确定CFTR药物如何影响患者的62种不同变体CFTR。我们将了解有关CF疾病根源的过程的知识，将帮助临床医生为个别患者选择最佳药物，并指导未来的药物开发。