Organisations Involved: QUB (Belfast) and Agrisearch

Project Code: D-96-18


Bovine Mastitis (BM) is an inflammatory condition of the udder, typically caused by the host’s immune response to a microbial infection. This results in impaired herd performance and welfare which presents significant challenges to the dairy industry. BM is the leading cause of economic losses, both directly and indirectly from factors including increased veterinary and labour costs and reduced milk yield and quality. The associated large-scale use of broad-spectrum antibiotics represents a major cause of increasing microbial resistance (AMR) in agriculture and human health. Antibiotic treatment is initiated on diagnosis, prior to microbiology results, to minimise the pain and suffering of the cow. This therapeutic approach contributes to the spread of AMR within the farm, through the dissemination of bacteria in animal waste to the environment, and through the carriage of bacteria by farm workers.


Mass spectrometric characterisation of microorganisms using metabolic constituents and lipids were first proposed more than 40 years ago as a means of identification. Despite the initial success, the concept was abandoned – mainly due to the expenses and instability of these instruments. Recent advances in mass spectrometric technology has reinvigorated research in this field. Desorption Electrospray Ionization (DESI) was successfully used for the analysis of bacterial cells following minima sample preparation, and Rapid Evaporative Ionization Mass Spectrometry (REMIS) was successfully used for the analysis of large bacterial and fungal strain collection without any sample preparation. The latter has also been demonstrated to be able to analyse various biological samples ranging from biological fluids through to tissues and stool samples.

There is clear imperative to develop a system for rapid microbial diagnosis of BM, directly from a suspected milk sample. The rapid identification of pathogens will allow timely appropriate treatments to be delivered thereby reducing the use of empirical prescribing practices and the consequent development of AMR.

The aim of this project is to develop a REIMS Analysis for Pathogen Identification in Dairy Disease (RAPID) platform to diagnose BM. By identifying cases and the causative agent, the RAPID diagnostic tool will address the shortfalls associated with current methodology. The project will also explore the wider potential applications of REIMS to the dairy industry in areas such as milk quality analysis and monitoring of lameness in herds.

Project Outline:

Rapid evaporative ionisation mass spectrometry (REIMS) is an ambient ionisation technique that allows for the analysis of a sample in <10 seconds without substantial sample preparation. This presents itself as an ideal technology to bring the power of mass spectrometry analysis to the dairy industry, holding potential for rapid, low-cost analysis of milk samples for a breadth of applications. This partnership between the industry body AgriSearch and QUB will aim to develop REIMS in three key areas of unmet need in the dairy industry. The focus will be developing REIMS as a platform for the identification of the pathogen for bovine mastitis to allow for faster and more targeted treatment of infection and reducing the requirement for the use of broad-spectrum antibiotics. To explore the breadth of potential REIMS applications, two sub-projects will be pursued for examining milk quality and potential biomarkers for lameness in a longitudinal study of a dairy herd.

Project Objectives:

The four objectives of the proposed research project are:

  • Method development of REIMS for diary milk analysis (10% of time): will form the first stage of the project and develop and robust and validated methodology for the analysis of milk samples using REIMS utilising a laser for sample heating and mobilisation. This will determine the optimal volume of milk for analysis, laser power and pulsatile parameters, and mass spectrometry operating conditions. This will further allow the student to develop skills and experience in data analysis workflows specific for REIMS.
  • Bovine mastitis diagnosis and treatment management (50% of time): will constitute the main portion of the research programme. Bovine milk samples will be collected from dairy farms which are part of the Agrisearch network and through AFBI from cows with suspected and confirmed mastitis and healthy controls. The effect of novel methods for the control of mastitis, such as antimicrobial peptides, will be modelled and the effect on milk composition measured.
  • Development of REIMS for milk quality analysis (20% of time): will explore the potential of REIMS to act as a rapid screening tool for the fatty acid and complex lipid composition of milk samples as a metric of milk quality in comparison to traditional gas chromatography mass spectrometry analysis. Potential applications to the detection of contaminated and/or adulterated milk will be explored.
  • Discovery of markers for lameness detection (20% of time): will be conducted as a longitudinal study on a dairy herd with regular samples collected and analysed using REIMS. This cohort will be used to identify potential biomarkers that are indicative of potential lameness prior to observable clinical symptoms.