Advances in land-based Marine Aquaponics or Integrated Multi-Trophic Aquaculture (IMTA) systems have been developing over the past ten years. This restorative approach to aquaculture food production incorporates environmental principals and has the potential to produce food, while improving the environment. Expanding the development of environmentally friendly and sustainable aquaculture systems is needed to reduce fishing pressure on declining wild fish populations and meet the growing demand for safe and sustainable seafood. Mote Aquaculture Research Park (Mote) scientists, in partnership with the National Mariculture Center (NMC) in Israel, the University of South Florida’s College of Engineering (USF) and Auburn University are evaluating the potential for periphyton biofilms to not only increase water quality, but to enhance the disease resistance and growth of the cultured species.
Fish pathogens are a significant cause of loss and cost in aquaculture. Frequently, pathogens accumulate in high nutrient areas, such as in the microbial community of the nitrifying biofilter in recirculating aquaculture systems (RAS). Previous research at Mote shows that microbial communities of periphyton may help to reduce the number of pathogens in the system, preventing their establishment in the RAS biofilms. Validation of the effect of biofilter combination is necessary to establish where pathogens are residing within the RAS and if periphyton is useful for remediating fish pathogens. Two trials were carried out on two separate 2500 L pilot scale RAS for different biofilter combinations with samples taken over two different time periods per trial. The combinations tested in trials were periphyton only and periphyton in combination with a nitrifying biofilter. Samples were extracted with Qiagen EarthSoil Kits and validated on a Nanopore Nanodrop. High resolution classification of fish pathogens using the hsp70 gene and next generation sequencing was carried out to precisely examine fish pathogens in periphyton biofilters and nitrifying biofilters. Results will be compiled by OTU and into stacked bar charts, then compared for significant differences. Multivariate statistics will be applied to find differences in samples by carrying out Principle Component Analysis, GUSTA ME, Mantel dissimilatory, cluster, and redundancy testing in the R programming environment. The diversity will be analyzed with the alpha, beta, and gamma ecological functions. Picrust2 will be applied to the metagenome to predict microbial functions. The results will show if pathogens are residing in the RAS biofilter and what their role is in the microbial ecology.