Fighting Antibiotic Resistance with Digital Microfluidics – Innovators ep.6

Fighting Antibiotic Resistance with Digital Microfluidics – Innovators ep.6


By the year 2050 as many as 10 million
lives could be lost through the inability to use what we now have as
common antibiotics. And furthermore, in the O’Niell report, one of the
recommendations was that antibiotics should no longer be prescribed without a
fast diagnostic tool that will inform the doctor as to whether or not they are
required. In our lab at the University of
Southampton, we do research at the interface of physical sciences,
engineering, and life sciences. Our interest in diagnostics stemmed from a collaboration that we have with Public Health England, principally around trying
to develop a tool that will allow us to improve the diagnostics of urinary tract
infections and whether the bacteria that are present in UTIs carry genes that
confer resistance to antimicrobials or antibiotics. The technology that we use was developed by Sharp, and it borrows the same principles that are used in
mobile phone displays. In those displays you have little transistors. Those are used to control the images. We use those same transistors to control the movement and position of
droplets in our devices. We call this ‘digital microfluidics’. Each electrode, in
theory, can have one droplet and we have around 17,000 electrodes on these
devices, so you can imagine the number of reactions or any sort of biological assay
you can do on these devices. in terms of the work that we’re doing
with RPA; one of the key advantages of recombinase polymerase amplification is its robustness to sample matrix. So, in principle, you could use that RPA
amplification for a number of different assay platforms in a number of
different scenarios. The good thing about using RPA is that it’s isothermal, so you just need to maintain the entire device 37 degrees. We’ve used these devices to run RPA assays where we’ve dispensed droplets, mixed them under direct software control, the reagents with the sample, and we’ve been able to detect a single copy of antimicrobial resistant gene present in the DNA sample within 15
minutes. We’ve used our platform to identify three different genes; some of the commonest genes that confer antimicrobial resistance to bacteria. The goal would really be to have a diagnostic test that
the GP could use, in a few minutes, to identify whether there really is an
infection and which is the most appropriate antibiotic to prescribe.

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