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.

许多较小，更简单的显微镜通常可以看到一台以上昂贵的大型机器。我们建议创新研究质量的全自动显微镜设计，该设计可以针对特定的实验量身定制，并易于复制以并行执行许多实验。借助计算机视觉来控制和分析这些实验，设备和员工时间的瓶颈被删除，并且有可能与新的基因技术保持同步 - 即使对于以前耗时的研究，例如通过疟原虫寄生虫测量侵入红细胞的侵袭。我们将开发显微镜和计算机视觉技术，展示它们在疟疾实验室和合作者的功效，并发布开源设计，使其他人可以复制我们的进度。有效筛选数百种不同突变菌株的能力将导致对许多疾病的更深入了解，最终创建新的药物发现靶标，并有可能导致疟疾等疾病的新疫苗。由于CRISPR-CAS9方案，基因编辑正处于革命之中，并且细胞表型需要保持步伐。特别是在疟疾中，我们的合作者现在使用CRISPR来扩大恶性疟原虫的淘汰赛，并预计今年将制作200条淘汰赛线，而未来五年则可淘汰1000。虽然菌株产生的缩放是如此明显，但表型不是，即我们无法确定这些基因的功能 - 我们需要涉及活细胞成像，特别是宿主/病原体入侵的稳健和便宜的可扩展表型测定法。通过当前的方法和技术进行这些测定是无法想象的。必须开发和部署新的，更具自动化和负担得起的成像方法。然后，这将使我们能够系统地筛选GM线的几种表型，包括梅罗阵数，细胞因子，出口和侵袭。我们在这里解决了疟疾的情况，但指出在许多其他传染病中可以确定非常相似的挑战和目标。

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

Flat-field and colour correction for the Raspberry Pi camera module

• DOI: 10.5334/joh.20
• 发表时间: 2019-01-01
• 期刊: J. Open Hardware
• 作者: Bowman, R.;Vodenicharski, B.;Stirling, J.
• 通讯作者: Stirling, 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