Laser-based technology could identify best antibiotic for each patient

Dr Callum Highmore is a first author on the new paper

Southampton researchers have shown a technique they developed could rapidly identify the most effective antibiotic for each patient.

The study results, published in the journal npj Antimicrobials and Resistance, could be used to create a faster test to determine which antibiotic a patient should be given.

This would help reduce the overuse of unnecessary and ineffective antibiotics – one of the main drivers of antimicrobial resistance (AMR).

Preventing delays

AMR is a global public health challenge that threatens to reverse advances made in modern medicine over the past 80 years.

It was associated with 4.95 million deaths in 2019. This is estimated to increase to 10 million annually by 2050.

AMR occurs when bacteria develop defences that make them ‘resistant’ to a certain antibiotic, meaning they are not killed by it.

Currently, the main way to identify which antibiotic will treat a particular infection are antibiotic sensitivity tests. These require any bacteria causing the infection to be cultured in a laboratory. Antibiotics are then added to see which are most effective at killing the bacteria.

Many infections are caused by a virus instead of bacteria. In these cases, no antibiotic will be effective at treating the infection. This is because antibiotics cannot kill viruses.

The current testing process can take up to 48 hours (two days). GPs therefore often prescribe an antibiotic in the interim to prevent the patient’s infection from getting worse. Since they have little to go on, this antibiotic is often ineffective at treating that particular infection.

The prevalence of AMR is accelerated by overuse of unnecessary or ineffective antibiotic treatments. This delay in getting test results therefore contributes to overuse of antibiotics and exacerbates the rise of AMR.

Testing the new method

The researchers previously developed a technique called Multi-excitation Raman spectroscopy (MX-Raman). This uses lasers to analyse the composition of a single drop of a bodily fluid.

This technology can be used to analyse the composition of a patient’s sample. The lasers create tiny vibrations within the molecules, with different molecules vibrating in different ways. It can provide results in seconds.

The new study was the next stage of a collaboration between experts from the University of Southampton and University Hospital Southampton. It was delivered within the NIHR Southampton Biomedical Research Centre and the National Biofilms Innovation Centre.

In this study, the team analysed 20 isolates of the bacteria Pseudomonas aeruginosa taken from the lungs of people with cystic fibrosis to see if MX-Raman could speed up infection diagnosis.

The researchers used a combination of MX-Raman and computational analysis analyse each bacterial sample. This allowed them to accurately identify which samples contained antibiotic resistant bacteria, and which antibiotics would be most effective at treating each participant’s infection.

“These are excellent results that show our MX-Raman method is effective at identifying antimicrobial resistance in real clinical pathogens,” said Dr Callum Highmore, who was a first author on the paper.

“We now aim to build on this success to develop a much faster diagnostic test for direct use on patient samples, helping to cut unnecessary antibiotic use and stem the rise in antimicrobial resistance.”