An accessible framework to achieve multi-dimensional live-cell super-resolution high-content screening

Lead Research Organisation: University College London
Department Name: Lab for Molecular Cell Bio MRC-UCL

Abstract

Imagine we could see how the molecular machineries inside cells behave, form networks and develop into complex tissues! What has been a dream for humanity for centuries has become ever closer to possibility through multiple technical advances. This development started with the optical microscope in the 17th century that enabled the visualisation of cells and bacteria, confocal and electron microscopy in the 1950's to visualise smaller structures, and culminated in the advent of super-resolution microscope in the 2000's that now enable us to see specific protein complexes at high resolution.

Microscopy has been a ground-breaking technology that most academic labs and pharma companies make use of to assay drugs and visualise disease models. One limitation of such techniques has been the time required for imaging, which made it impractical to acquire a large number of images - a pre-requisite for screening thousands of drugs. Therefore, high-content imaging platforms have been developed that enable the acquisition of thousands of images in a relatively short time frame. Yet, images generated by high-content screening microscopes often lack the resolution, for instance for visualising small sub-cellular structures. Here, in this proposal we aim to combine two methods in order to generate the first super-resolution high-content screening platform (SR-HCS). This platform will truly transform research in cell biology and enable discoveries at an unprecedented speed and resolution.

Technical Summary

High content biology has revolutionised our understanding of biological systems. The particular application of image-based high-content screening (HCS) essays into cell biology has provided us critical new insights into the role of gene networks, stochasticity in cell population behaviour, and the discovery of how tailored compounds modulate normal cell behaviour or in the presence of disease, among others. Chiefly, HCS brings a big data perspective into cell biology, allowing the image analysis of the behaviour of large cell populations under different states and conditions. However, to date, HCS still relies on underlying conventional imaging approaches such as confocal or widefield microscopy, resolution limited to ~500nm. This limit implies that HCS cannot accurately resolve the small details of molecular events critically regulating cell dynamics, such as molecular interactions and the formation of supra-molecular complexes existing at scales of few nanometres.

There is an urgent need to develop higher resolution instruments in high-content cell biology. For example, several cellular structures become only visible when examining with super-resolution microscopy. Typical image analysis workflows struggle to separate objects when looking at small intracellular organelles. Two technical advances in the last years have made it possible to overcome this limitation and can provide high resolution images on a HCS platform: 1) the development of a spinning disk confocal HCS platform (e.g. the PerkinElmer Opera Phenix), and 2) the development of image analysis software that enables the post-acquisition resolution of images to achieve sub-diffraction limit values (e.g. SRRF). Here, we aim to combine these two techniques and to develop the first super-resolution high-content screening platform (SR-HCS), in collaboration with PerkinElmer. We anticipate that this unique system will enable breakthrough discoveries in fundamental cell biology and biomedical research.

Planned Impact

Academic: We aim to deliver to researchers a novel large-scale imaging framework to study cell behaviour at the nanoscale. This super-resolution high-content screening platform will be the first such platform world-wide and enable academics, as well as interested pharmaceutical partners, to benefit from this technology. We expect that any lab engaged in biological or biomedical imaging to adopt this technology, in particular those that are interested in the study of sub-cellular organelles and protein complexes. It will allow findings from a novel imaging approach to be made available, enabling new avenues of interdisciplinary collaborative.

Commercial: It will be possible to rapidly translate the analytical and imaging developments from this project into applications of interest to biotechnology, microscopy and imaging companies. The data generated will be of high-value to the pharma industry as it has the potential to identify fundamental cell behaviour in the presence of disease, allowing for the tailored design of new drug targets. Most importantly, we are closely collaborating with PerkinElmer in this project to ensure that our software and hardware developments can be translated into a potential commercial solution.

Training: The PDRA to be recruited will receive continuous cross-disciplinary training and mentoring, which will aid his/her career progression. The skills learned over the course of this project, namely image analysis and high-content screening, are very rare to find in the UK and in high demand. We expect that training of researchers skilled in this area will contribute immensely to the UK competitiveness in these areas, both in academia and industry. In addition, the PDRA will benefit from generic skills gained on training courses at UCL, through co-authoring papers, grants and reviews and by presenting this work at international meetings. The project described here will be ideal for introducing students from different backgrounds to interdisciplinary research in life and physical sciences. Moreover, a large number of students will benefit from involvement in this interdisciplinary level research through rotation projects, MRes and tutorial activities associated with these programmes. Similarly, undergraduates will be exposed to this work through internships and short projects. Finally, by publicising this work, we expect to attract better and brighter students and researchers to the UK.

General Societal and Economical Impact: Microscopy approaches and instrumentation is one of the fastest growing areas in biomedical research, critical not only for cell biology, but for the direct discovery of new molecular targets mitigating human disease. Over the past decades, the UK has been a world leader in these developments. This project will enable and supply new approaches crucial for enhancing microscopy and cell biology studies, supplying UK research with novel state-of-the-art and experimental methods - a key attractor for industrial R&D collaborations - and empowering research in the UK with some of the most advanced imaging facilities in Europe. Locally, UCL (where this project will be housed) has made a commitment to make the interface between medicine, biophysics and imaging a key priority, contributing to the long-term sustainability of these studies and serving as a seeding source for collaborations with our partners such as the new Francis Crick Institute and NHS Hospitals (e.g. Royal Free Hospital).

Outreach: RH and RK have been involved in interactions with the wider community through media appearances, public discussions and school visits. Through this type of outreach we expect this work to reach a wide audience; giving the public a better understanding of how next-generation imaging technology may impact research, health and disease. Moreover, through our involvement in EMBO, EU and UK-South Africa networks, we expect this work to reach the global scientific community.

Publications

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Description This grant is helping establish the technology needed to achieve image-based high-content screening with near-molecular resolution. To do so, we have made considerable technological breakthroughs that are highlighted in our most recent papers.
Exploitation Route The entire nature of the grant is to provide open-source hardware and software to the community that can be easily accessed and replicated by researchers.
Sectors Healthcare,Pharmaceuticals and Medical Biotechnology

 
Description Andor Technology 
Organisation Andor Technology
Country United Kingdom 
Sector Private 
PI Contribution Developed the Super-Resolution Radial Fluctuations method which was used by Andor Technology to establish the worlds first Super-Resolution Cameras for fluorescence microscopy, which are now commercially available.
Collaborator Contribution Andor Technology has contributed with known-how and research financial support.
Impact This R&D collaboration has led to the development of a new generation of cameras for microscopy and spinning disk microscopes, these are now available commercially. This collaboration entails expertise in optical physics, cell biology and electrical engineering.
Start Year 2017
 
Description Andor Technology 
Organisation Andor Technology
Country United Kingdom 
Sector Private 
PI Contribution R&D partnership to implement analytical technologies developed into commercial turnkey systems.
Collaborator Contribution R&D partnership to implement analytical technologies developed into commercial turnkey systems.
Impact This collaboration has led to the translation of UCL developed technology into turn-key commercial hardware for biomedical research. As part of this collaboration Andor is bringing experimental kit and software to UCL that local researchers in biology and physics can use in their research.
Start Year 2017
 
Description Intelligent Imaging Innovations 
Organisation Intelligent Imaging Innovations Ltd
Country United Kingdom 
Sector Private 
PI Contribution R&D partnership to implement analytical technologies developed into commercial turnkey systems.
Collaborator Contribution R&D partnership to implement analytical technologies developed into commercial turnkey systems.
Impact This collaboration has led to the establishment of UCL as the R&D reference site for 3i in the UK. As part of this collaboration 3i is bringing experimental kit and software to UCL that local researchers in biology and physics can use in their research.
Start Year 2016
 
Title NanoJ 
Description In recent years, our team has built an open-source image analysis framework for super-resolution microscopy designed to combine high performance and ease of use. We named it NanoJ - a reference to the popular ImageJ software it was developed for. In this paper, we highlight the current capabilities of NanoJ for several essential processing steps: spatio-temporal alignment of raw data (NanoJ-Core), super-resolution image reconstruction (NanoJ-SRRF), image quality assessment (NanoJ-SQUIRREL), structural modelling (NanoJ-VirusMapper) and control of the sample environment (NanoJ-Fluidics). 
Type Of Technology Software 
Year Produced 2018 
Open Source License? Yes  
Impact NanoJ provides the technological basis to a series of high-performance analytical algorithm for super-resolution microscopy data analysis 
URL https://iopscience.iop.org/article/10.1088/1361-6463/ab0261/meta
 
Title NanoJ-Fluidics 
Description Fluorescence microscopy can reveal all aspects of cellular mechanisms, from molecular details to dynamics, thanks to approaches such as super-resolution and live-cell imaging. Each of its modalities requires specific sample preparation and imaging conditions to obtain high-quality, artefact-free images, ultimately providing complementary information. Combining and multiplexing microscopy approaches is crucial to understand cellular events, but requires elaborate workflows involving multiple sample preparation steps. We present a robust fluidics approach to automate complex sequences of treatment, labelling and imaging of live and fixed cells. Our open-source NanoJ-Fluidics system is based on low-cost LEGO hardware controlled by ImageJ-based software and can be directly adapted to any microscope, providing easy-to-implement high-content, multimodal imaging with high reproducibility. 
Type Of Technology Software 
Year Produced 2018 
Open Source License? Yes  
Impact NanoJ-Fluidics is now the basis for commercial technology in development by Abbelight 
URL https://www.biorxiv.org/content/10.1101/320416v1
 
Title NanoJ-SQUIRREL 
Description NanoJ-SQUIRREL is an analytical approach for quantifying image quality in super-resolution microscopy, provided as a GPU-enabled open-source ImageJ plugin. SQUIRREL requires two input images - a super-resolution image (or image stack) and the diffraction-limited equivalent of the same imaging volume. It then calculates an error-map, highlighting areas of the super-resolution image which exhibit poor agreement with the diffraction-limited image, and quality metrics for the super-resolution image. 
Type Of Technology Software 
Year Produced 2018 
Open Source License? Yes  
Impact NanoJ-SQUIRREL provides the technological basis to develop artificial intelligent self-driven microscopes. This is serving as a nucleator for collaborations with industry. 
URL https://bitbucket.org/rhenriqueslab/nanoj-squirrel/wiki/Home
 
Description Host laboratory for In2ScienceUK 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Schools
Results and Impact We are a volunteer laboratory for the In2ScienceUK programme, an award winning initiative which empowers students from disadvantaged backgrounds to achieve their potential and progress to STEM and research careers through high quality work placements and careers guidance
Year(s) Of Engagement Activity 2016,2017,2018
URL http://in2scienceuk.org/