Publications and Research
Document Type
Article
Publication Date
5-8-2018
Abstract
Background
Marine and aquaculture industries are important sectors of the food production and global trade. Unfortunately, the fish food industry is challenged with a plethora of infectious pathogens. The freshwater and marine fish communities are rapidly incorporating novel and most up to date techniques for detection, characterization and treatment strategies. Rapid detection of infectious diseases is important in preventing large disease outbreaks.
Main text
One hundred forty-six articles including reviews papers were analyzed and their conclusions evaluated in the present paper. This allowed us to describe the most recent development research regarding the control of diseases in the aquatic environment as well as promising avenues that may result in beneficial developments. For the characterization of diseases, traditional sequencing and histological based methods have been augmented with transcriptional and proteomic studies. Recent studies have demonstrated that transcriptional based approaches using qPCR are often synergistic to expression based studies that rely on proteomic-based techniques to better understand pathogen-host interactions. Preventative therapies that rely on prophylactics such as vaccination with protein antigens or attenuated viruses are not always feasible and therefore, the development of therapies based on small nucleotide based medicine is on the horizon. Of those, RNAi or CRISPR/Cas- based therapies show great promise in combating various types of diseases caused by viral and parasitic agents that effect aquatic and fish medicine.
Conclusions
In our modern times, when the marine industry has become so vital for feed and economic stability, even the most extreme alternative treatment strategies such as the use of small molecules or even the use of disease to control invasive species populations should be considered.
Comments
This work was originally published in BMC veterinary research.
© The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated