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Completed RESEARCH GRANT UKRI Gateway to Research

Live 3D Confocal Imaging in real time with high throughput, multipoint, targeted acquisition and AI-assisted quantification

£7.74M GBP

Funder Biotechnology and Biological Sciences Research Council
Recipient Organization University of Nottingham
Country United Kingdom
Start Date Nov 07, 2021
End Date May 05, 2023
Duration 544 days
Number of Grantees 9
Roles Co-Investigator; Principal Investigator
Data Source UKRI Gateway to Research
Grant ID BB/V019414/1
Grant Description

Imaging is a powerful tool used to understand and exploit the fundamental processes within cells and tissues. Since the microscope was discovered in the late 1500s, there have been many technical advances in the magnification and sensitivity it can achieve. It is now possible to track single molecules in real time within cells as small as bacteria using super resolution microscopy.

It is also possible to take a series of vertical images (optical slices) to build up a precise 3D reconstruction of tissue samples and microbes. If this is performed using confocal microscopy there is minimal background light from adjacent slices making the resolution and sensitivity of the final images precise. These advances are facilitating the elucidation of interactions between molecules (e.g. an antimicrobial with its target), interactions between host cells and invading microbes, processes within tumours and also the engineering of bacteria/fungi to generate products of use to us (e.g. biofuels).

Currently there is a bottleneck in the screening of (i) cells to identify which we can exploit, or (ii) novel compounds that we could develop into effective drugs. The delay is caused because the highest resolution microscopes only view one sample at a time. Developers are now building high resolution microscopes that process multiple samples automatically, enabling high throughput screening.

We are requesting support to purchase one of the newest generation of microscopes: a high throughput, high content imaging system (HCS).

Recently step change improvements in HCS have brought to the market HCS with confocal and super resolution capabilities that are guided by machine learning. The power of artificial intelligence (AI)-driven image acquisition is that the HCS can scan multiple samples at low resolution and be trained to focus in on interesting areas for high resolution imaging. In this way, the speed of the screening is increased and the automation reduces error.

Two additional features of this new generation of microscopes are particularly relevant for the research we propose to undertake. Firstly, the confocal HCS has a sterilizable sample holder. We will exploit this by installing the HCS in a laboratory with the safety containment required for the study of infectious microbes.

Secondly, the equipment includes a cabinet in which we can control the environment. This will enable us to provide the best conditions for maintaining the system under study e.g. low or high oxygen/humidity/optimal temperature (e.g. different microbes and 3D tissue models) and allow us to follow cellular process by undertaking time-lapse imaging at high resolution.

Equipment with the high specification requested will be the first such facility in the Midlands. Our application has the support of the Midlands Innovation network of Universities as well as considerable support from industry partners. Notably, the National Biofilm Innovation Centre is supporting our application because the 31 universities and >60 companies that it partners with would be able to exploit the HCS in their biofilm research.

We predict that a confocal HCS will make a real difference to the pipeline of new medicines (antibiotic, anti-viral, anti-biofilm, fungicides, anti-tumour) and exploitable products generated using microbes. These advances will improve the health and wealth of the nation.

The HCS will be managed by an experienced imaging team (SLIM) with a track record in maintaining and supporting the use of a portfolio of microscopes by internal and external scientists. SLIM will expand its thorough training programme to ensure users are fully skilled in HCS handling, and thereby support their career development and maximise the potential of the output from the HCS.

The availability of the HCS will be publicised through equipment catalogues and web pages to the research community and industry. The images created will be integrated into ongoing outreach activities.

All Grantees

University of Nottingham

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