Date of Award

12-2017

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Animal and Veterinary Sciences

Committee Member

Dr. Thomas R. Scott, Chair

Committee Member

Dr. Lance Beecher

Committee Member

Dr. Amy Messersmith-Love

Abstract

Tilapiine cichlids are the third largest farmed fish worldwide and are among the easiest and most profitable fish to farm. The most common pathogens affecting farmed tilapia are Streptococcus agalactiae and Streptococcus iniae, which together account for losses of more than 150 million dollars annually. Fish are at the highest risk for developing a Streptococcus infection when they are in high density stock conditions. Research indicates that the secondary effects of high stock density such as low dissolved oxygen and high ammonia levels are of less significance to infection and mortality than the damage that over stocking causes to the mucosal immune system. However, assays used to determine the effectiveness of the tilapiine mucosal immune system have proven unreliable. The present work has been undertaken to evaluate mucus collection procedures and antibacterial assay effectiveness. One “spot-on-lawn” assay, four disk diffusion assays, and four micro titer plate assays were chosen based upon common levels of use in the literature. The assays were executed; however, each of the disk diffusion assays failed to accurately measure antibacterial activity when controlled for the antibacterial activity of additives. The microtiter plate assays successfully measured limited antibacterial activity at lower growth reduction levels of 10-30%. Additionally, these assays were administered on samples which were collected from tilapia in an actual aquaponics facility in contrast to the majority of experiments which are conducted on fish that have been purposely housed in clean and controlled conditions within research facilities. This deviation from standard methods introduced additional variables which influence assay outcomes; therefore, future research should address these discrepancies.

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