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

Lead Research Organisation: University of Cambridge
Department Name: Physics

Abstract

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.

Planned Impact

Societal Impact
Half of the world's population is currently at risk of malaria with an estimated 214 million cases in 2015. There is considerable global effort to eliminate infectious diseases, with research targeted at meeting the sustainable development goal of ending epidemics related to malaria by 2030. To achieve these ambitious targets, and have significant impact on health and well-being on a global scale, the research at medical centres can be supported significantly by efforts in the physical sciences. This project aims to make use of the recent developments in low cost electronics, sensors and optics with advances in data analysis technique to produce a step change in how experiments can be performed to study host/pathogen interactions. Through automation of data collection and analysis results can be produced in days instead of months. The technique applied to the study of invasion phenotyping for malaria can aid the acceleration of vaccine development with the prospect of applying the know-how from the project to other infectious diseases.


Scientific dissemination
The results of the project will be disseminated through usual scientific channels with publication in high impact journals and presentations at international conferences. In addition there will be on-going collaboration with malaria groups in the UK, in particular Julian Rayner at the Wellcome Sanger Institute and Jake Baum in the Life Science Department at Imperial College who will have input on the scientific programme as well as being beta testers of the automated systems. The partners also have considerable experience with outreach projects with the microscope demonstrated at numerous events in Cambridge and further afield, with microscopes for education taken to countries including India, Gambia and Tanzania. The project partners will continue to support outreach activities with inclusion of results from the project.

Economic Impact
The ability to produce a system that can produce results at least an order of magnitude faster than current methods offers opportunities for a range of medical applications. The scaling up of the system within the project will be supported by the commercialisation partner, WaterScope, who will be involved with the project from the onset by offering free consultancy. WaterScope are a spin out from the University of Cambridge which is developing microscopy based products including rapid bacteria testing for drinking water and low-cost malaria testing systems. The project partners including WaterScope have experience working together and also with Cambridge Enterprise, the University's Technology Transfer Office and so are well placed to capture and exploit any IP generated by the project. In addition funding is requested for attendance for one of the post-doctoral researchers on the Impulse Entrepreneurship programme which will be an opportunity to evaluate commercial viability of outputs from the project under the mentorship of successful serial entrepreneurs from the Cambridge community.
 
Description We have published a paper describing the adhesion of malaria infected red blood cells onto blood vessel cells, in laboratory conditions. This could be useful to better understand the clinical outcomes of malaria infections, and also as a platform for drug screening.
We published a paper on the low-cost open-flexture microscope, with Dr R.Bowman in Bath. This is an important platform fo rus not just in terms of being an affordable microscope, but because of the software development in database and parallelisation of instrument control.
We published various papers on physics aspects of malaria infection in the bllod stage.
Exploitation Route Other resesarch groups, in both academic and commercial sectors, will be able to replicate our platform and protocols.
Sectors Digital/Communication/Information Technologies (including Software),Healthcare,Pharmaceuticals and Medical Biotechnology

 
Title Dataset for "Flat-field and colour correction for the Raspberry Pi camera module" 
Description This repository contains the hardware (OpenSCAD/STL files) and build instructions, software (Python scripts and Arduino firmware), data analysis (iPython notebook), and manuscript describing how to calibrate the colour response of a Raspberry Pi camera module. It also includes the calibration images acquired during the preparation of the work. 
Type Of Material Database/Collection of data 
Year Produced 2020 
Provided To Others? Yes  
URL https://researchdata.bath.ac.uk/id/eprint/764
 
Title Dataset for "Robotic microscopy for everyone: the OpenFlexure Microscope" 
Description This dataset contains microscopy images collected to demonstrate imaging capabilities of the OpenFlexure Microscope. Images for bright-field transmission and reflection, polarisation contrast, and fluorescence imaging are provided. A set of images obtained from a large tile scan are provided, along with the Microsoft Image Composite Editor file used for tiling. 
Type Of Material Database/Collection of data 
Year Produced 2020 
Provided To Others? Yes  
URL https://researchdata.bath.ac.uk/id/eprint/734
 
Description Malaria infection of erythrocytes 
Organisation University of Cambridge
Department Department of Physiology, Development and Neuroscience
Country United Kingdom 
Sector Academic/University 
PI Contribution The technology developed in the discipline hopping MRC grant, to investgate cell infection, is being translated to the different scenario of Malaria.
Collaborator Contribution An MPhil student was attracted to work on the project. The project is the subject of grant applications to EU and Wellcome trust.
Impact The MRC funding was for less than year, and the outcomes will be seen in the near future. The collaboration will hopefully be developed with grant funding.
Start Year 2010
 
Title Chief Ray Angle Compensation for the Raspberry Pi Camera Module 
Description This repository contains the hardware (OpenSCAD/STL files and build instructions, software (Python scripts and Arduino firmware), data analysis (iPython notebook), and manuscript describing how to calibrate the colour response of a Raspberry Pi camera module. analysis contains the data analysis code. data contains the images that we used for the graphs in the manuscript. neopixel_driver is the arduino firmware. image_acquisition includes the Python code that acquired the images and controlled the neopixel. calibration_jig contains the printable files, source OpenSCAD files, and assembly instructions for the calibration jig. colour_test_sheet contains source Inkscape SVG files and PDF renders of the test target used in the experiments. manuscript contains the source files for the manuscript. This is an open project, run by the Bath Open Instrumentation Group, part of the University of Bath. Unless otherwise specified, all code is licensed under the GPL v3 or later, hardware is under the CERN open hardware license, and documentation/manuscript is CC-BY 3.0 or later. The repository will be archived along with a published paper once it has been peer reviewed. If you are viewing a static archive of these files, you may want to consult the working repository, which may receive updates in the future. 
Type Of Technology Software 
Year Produced 2020 
URL https://zenodo.org/record/3699730
 
Title Chief Ray Angle Compensation for the Raspberry Pi Camera Module 
Description This repository contains the hardware (OpenSCAD/STL files and build instructions, software (Python scripts and Arduino firmware), data analysis (iPython notebook), and manuscript describing how to calibrate the colour response of a Raspberry Pi camera module. analysis contains the data analysis code. data contains the images that we used for the graphs in the manuscript. neopixel_driver is the arduino firmware. image_acquisition includes the Python code that acquired the images and controlled the neopixel. calibration_jig contains the printable files, source OpenSCAD files, and assembly instructions for the calibration jig. colour_test_sheet contains source Inkscape SVG files and PDF renders of the test target used in the experiments. manuscript contains the source files for the manuscript. This is an open project, run by the Bath Open Instrumentation Group, part of the University of Bath. Unless otherwise specified, all code is licensed under the GPL v3 or later, hardware is under the CERN open hardware license, and documentation/manuscript is CC-BY 3.0 or later. The repository will be archived along with a published paper once it has been peer reviewed. If you are viewing a static archive of these files, you may want to consult the working repository, which may receive updates in the future. 
Type Of Technology Software 
Year Produced 2020 
URL https://zenodo.org/record/3699731