Parallelised live microscopy for high-throughput behavioural phenotyping in malaria research

用于疟疾研究中高通量行为表型分析的并行活体显微镜

• 批准号: EP/R011443/1
• 负责人: Pietro Cicuta
• 金额: $ 75.48万
• 依托单位: University of Cambridge
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FR011443%2F1
• 关键词: Parallelised; live; microscopy; throughput; behavioural

Many smaller, simpler microscopes can often see more than one large, expensive machine. We propose to innovate a research-quality, fully automated microscope design that can be tailored to a particular experiment and easily replicated to perform many experiments in parallel. With computer vision to control and analyse these experiments, the bottlenecks of equipment and staff time are removed, and it becomes possible to keep pace with new genetic technologies - even for previously time-consuming studies, for example measuring the invasion of red blood cells by plasmodium parasites. We will develop the microscopy and computer vision technologies, demonstrate their efficacy in our malaria lab and those of our collaborators, and release open-source designs that allow others to replicate our progress. The ability to screen hundreds of different mutant strains efficiently will lead to a deeper understanding of many diseases, ultimately creating new drug discovery targets and potentially leading to new vaccines for conditions like malaria. Gene editing is in the midst of a revolution thanks to CRISPR-Cas9 protocols, and cell phenotyping needs to keep pace. Specifically in malaria, our collaborators are now scaling up knockouts in P. falciparum using CRISPR, and expect to make 200 knockout lines this year, and 1000 in the next five years . While strain generation is scaling so dramatically , phenotyping is not, i.e. we cannot determine the function of these genes - we need robust and cheap scalable phenotyping assays, which involve live cell imaging, and specifically of host/pathogen invasions. It is not conceivable to perform these assays through current methods and technologies. New, much more automated and affordable approaches to imaging have to be developed and deployed. This would then allow us to systematically screen GM lines for several phenotypes, including merozoite number, cytokinesis, egress and invasion. We address here the case of malaria, but point out that very similar challenges and objectives can be identified in many other infectious diseases.

许多更小、更简单的显微镜通常可以看到比一台昂贵的大型机器更多的东西。我们建议创新一种研究质量的全自动显微镜设计，可以针对特定的实验进行定制，并且可以轻松地复制以并行执行许多实验。有了计算机视觉来控制和分析这些实验，设备和工作人员时间的瓶颈就被消除了，并且有可能跟上新的基因技术的步伐——即使是以前耗时的研究，例如测量疟原虫对红细胞的入侵。我们将开发显微镜和计算机视觉技术，在我们的疟疾实验室和我们的合作者那里展示它们的功效，并发布开源设计，让其他人可以复制我们的进展。有效筛选数百种不同突变菌株的能力将使人们对许多疾病有更深入的了解，最终创造新的药物发现目标，并有可能为疟疾等疾病开发新的疫苗。由于CRISPR-Cas9协议的出现，基因编辑正处于一场革命之中，细胞表型也需要跟上步伐。特别是在疟疾方面，我们的合作者正在利用CRISPR技术扩大恶性疟原虫的基因敲除，预计今年将产生200个基因敲除系，未来5年将达到1000个。虽然菌株产生的规模如此之大，但表型却没有，即我们无法确定这些基因的功能-我们需要强大且廉价的可扩展表型分析，其中包括活细胞成像，特别是宿主/病原体入侵。通过目前的方法和技术进行这些检测是不可想象的。必须开发和部署新的、更加自动化和负担得起的成像方法。这将使我们能够系统地筛选转基因系的几种表型，包括分裂子数量、细胞分裂、输出和入侵。我们在此讨论疟疾的情况，但指出，在许多其他传染病中也可以发现非常类似的挑战和目标。

项目成果

Robotic microscopy for everyone: the OpenFlexure Microscope

适合所有人的机器人显微镜：OpenFlexure 显微镜

• DOI: 10.1101/861856
• 发表时间: 2019
• 作者: Collins J

Modern Microscopy with the Web of Things: The OpenFlexure Microscope Software Stack

物联网现代显微镜：OpenFlexure 显微镜软件堆栈

• DOI: 10.48550/arxiv.2101.00933
• 发表时间: 2021
• 作者: Collins J

Simplifying the OpenFlexure microscope software with the web of things.

利用物联网简化 OpenFlexure 显微镜软件。

• DOI: 10.17863/cam.79837
• 发表时间: 2021
• 作者: Collins J

HardOps: Utilising the software development toolchain for hardware design

HardOps：利用软件开发工具链进行硬件设计

• DOI: 10.36227/techrxiv.15052848
• 发表时间: 2021
• 作者: Bowman R