LAP-MALDI MS Profiling and Identification of Potential Biomarkers for the Detection of Bovine Tuberculosis.
Sophie E LellmanChristopher K ReynoldsA K Barney JonesNick TaylorRainer CramerPublished in: Journal of agricultural and food chemistry (2023)
Detecting bovine tuberculosis (bTB) primarily relies on the tuberculin skin test, requiring two separate animal handling events with a period of incubation time (normally 3 days) between them. Here, we present the use of liquid atmospheric pressure (LAP)-MALDI for the identification of bTB infection, employing a three-class prediction model that was obtained by supervised linear discriminant analysis (LDA) and tested with bovine mastitis samples as disease-positive controls. Noninvasive collection of nasal swabs was used to collect samples, which were subsequently subjected to a short (<4 h) sample preparation method. Cross-validation of the three-class LDA model from the processed nasal swabs provided a sensitivity of 75.0% and specificity of 90.1%, with an overall classification accuracy of 85.7%. These values are comparable to those for the skin test, showing that LAP-MALDI MS has the potential to provide an alternative single-visit diagnostic platform that can detect bTB within the same day of sampling.
Keyphrases
- mass spectrometry
- liquid chromatography
- machine learning
- mycobacterium tuberculosis
- high resolution
- pulmonary tuberculosis
- multiple sclerosis
- chronic rhinosinusitis
- wound healing
- ms ms
- hiv aids
- deep learning
- bioinformatics analysis
- single cell
- ionic liquid
- adverse drug
- particulate matter
- molecularly imprinted
- tandem mass spectrometry
- climate change
- risk assessment
- real time pcr
- antiretroviral therapy
- structural basis
- quantum dots