Integrating CRISPR-Cas Technology into Organic Electronics for Rapid Point-of-Care Genotyping

Lead Research Organisation: University of Manchester
Department Name: School of Medical Sciences

Abstract

This proposal aims to address a critical unmet need in the treatment of infections in newborn babies. Gentamicin is an antibiotic that is effective in the treatment of a wide range of infections and is used in 100,000 babies per year. This treatment is required in the first hour, "the golden hour" of a baby being seen in the intensive care unit. However, 1 in 500 babies carry a change in their RNR1 gene that predisposes them to complete and irreversible deafness. Genetic testing for this change takes a minimum of two days and so a result is not available in time to prevent the hearing loss in these babies by allowing use of a different antibiotic.

In 2020, our team developed the world's first point of care genetic test that can be carried out at the baby's bedside. This test takes 26 minutes and allows safe use of the antibiotic. In a recent study, we showed that the test worked by preventing deafness in three babies and by not delaying antibiotic treatment. Despite the success of this system, we need to develop a different system that is quicker to ensure that there are no delays to effective treatment. As such, there is a clear unmet need for new technological solutions to deliver even more rapid point-of-care genetic testing this is called the Research Problem.

In this study, we propose to develop a novel, rapid point-of-care device that is capable of detecting changes in the RNR1 gene more quickly than the current approach. This device will combine a novel gene recognition technology with an organic electronic device platform that is capable of rapid (< 1 min) electronic readout of the gene change of interest. We call this the Research Solution. This research will develop the electronic device and test it with DNA from cheek swab samples, to show that it can be used with human samples.

Overall, this proposal aims to develop a next generation diagnostic tool that could support the implementation of rapid genetic testing in mainstream clinical practice, improving outcomes for patients and the healthcare system. Indeed, the device that we propose to develop here could be used for the testing other gene changes important in human health, where a result is required rapidly.

Technical Summary

This proposal addresses a critical unmet need in acute neonatal medicine: pharmacogenetic guided antibiotic prescribing to avoid lifelong deafness. In 2020, our group developed and deployed a rapid point of care test, utilizing established detection technology, to identify an RNR1 mitochondrial gene variant that pre-disposes to antibiotic induced hearing loss. This test was implemented in Neonatal Intensive Care Units across the North West of the UK, representing the first assessment of a pharmacogenetic test in acute healthcare management, anywhere in the world. Despite the success of this system, with an assay time of 26 minutes, more ubiquitous integration across healthcare necessitates faster turnaround times. As such, there is a clear unmet need for new technological solutions to deliver rapid point-of-care genotyping (Research Problem).

In this research we propose to develop a novel, rapid and re-programable point of care device to detect RNR1 variants. This system will combine a novel gene recognition method based on the CRISPR-Cas gene editing technology, with an organic electronics device platform that is capable of rapid (< 1 min) electronic readout of genotype (Technical Solution).

The first component of this research programme will involve the design of gene sequences applicable to the CRISPR-Cas system and incorporation into electrolyte-gated organic field effect transistor (EGOFET) devices. These devices will then be tested using synthetic target DNA to identify the variant of interest. Subsequently, the devices will be tested with samples from individuals with and without the variant to test clinical validity.

Following demonstration of this platform for RNR1 variant detection it could be rapidly adapted for other genetic variants where a rapid clinical result is required, leading to a next generation diagnostic tool to support the implementation of genomics in clinical practice, improving outcomes for patients and the healthcare system.

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