Bridging the Gaps: Systems-level approaches to antimicrobial resistance
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Bridging the Gaps: Systems-level approaches to antimicrobial resistance


Novel diagnostic solutions based on machine learning and mass spectrometry to fight the increase of drug-resistant bacterial strains causing bovine mastitis

Tania Dottorini (Veterinary Medicine and Science), Martin Green (Veterinary Medicine and Science), Andrew Bradley (Veterinary Medicine and Science), Richard Emes (Veterinary Medicine and Science), Philip Quinlan (Computer Science) and Jurgen Mitsch (Computer Science).

The issue

Bovine mastitis is a serious illness afflicting dairy cows. Conventional tests used to identify the infection require considerable time, usually 48 hours or longer. Though there are faster testing methods they fail to distinguish between subspecies of bacteria and cannot determine whether the bacteria is resistant to certain antibiotics. As a result of a lack of fast, affordable and effective testing, veterinarians must often rely on broad-spectrum antibiotics, which increase the pressure on antibiotics and contribute to the increase in antimicrobial resistance.

The research

Recent research has shown that Matrix-Assisted Laser Desorption/Ionization – Time of Flight Mass Spectrometry (MALDI-TOF MS) is one way of overcoming these problems, but only detects the presence of specific bacterial fingerprints in a sample. This necessitates the need for further research to make it a useful tool for veterinarians.

This research aims to see if it is possible to use MALDI-TOF MS to discriminate between penicillin-resistant and non-resistant strains of Staphylococcus aureus. This will be done by isolating signature patterns obtained from isolates, and then developing a prototype diagnostic tool that recognises the presence of specific strains.

The impact

By identifying specific strains of bacteria using a method that returns quick diagnostic data, the mass treatment of dairy cows with broad-spectrum antibiotics could be avoided. This would have a dramatic effect on the likelihood of resistance appearing in these animals, and help prevent the spread of antimicrobial resistance in the wider ecosystem.

If you are interested in finding out more about this research or about Bridging the Gaps please be in contact with Harry Moriarty in the first instance.

Bridging the Gaps: Antimicrobial Resistance

School of Mathematical Science
The University of Nottingham
University Park
Nottingham, NG7 2RD

telephone: +44 (0) 115 748 6317