Supervisors:
- Professor Chris Secombes (IBES)
- Dr Bertrand Collet (MSS)
- Catherine Collins (MSS)
Full time PhD student:
- Rachel Chance 2014-2017
During traditional disease challenge experiments, fish are infected with the pathogen of interest and sequentially sacrificed in order to obtain information regarding the disease progression and host immune responses. This PhD project will focus on the development of a novel, non-lethal sampling methodology which will significantly reduce the number of animals used in ectoparasite challenge experiments.
The ectoparasite selected to act as a model for the development of this methodology is the amoeboid protozoan Paramoeba perurans, etiological agent of amoebic gill disease (AGD). Initially emerging from Tasmania in the 1980s, AGD has spread across the globe, causing significant loses to stocks of salmonid species in aquaculture systems throughout Europe, North and South American, and Oceania. Pathology of AGD includes:
- Abnormal rates of mucus production
- Severe gill epithelial hyperplasia (increase in the amount of organic tissue as a result from cell proliferation)
- Gill hypertrophy (increase in the cell size); oedema (abnormal accumulation of fluid)
- Interlamellar vesicle formation
- Appear dyspnoeic (difficulty breathing, with an increase in opercula movements)
Initial in vitro work will focus upon culturing the amoeba and detecting any change in growth or viability when repeatedly exposed to anaesthetics. Atlantic Salmon, Salmo salar, will be PIT-tagged to allow for individual identification throughout the challenge. Each fish will be regularly anaesthetized in order to collect non-lethal samples of small blood extractions and mucosal swabbings which will be analysed using a variety of techniques to investigate the immune response and disease progression in each individual.
Following an individual throughout the course of an infection improves:
- Linking of response dynamics to infection outcome
- Reduces inter-fish variability
- Prevents masking of patterns
- Increases statistical robustness
- Reduces the need for further animal studies in future