Nanovaccines to Combat Aeromonas hydrophila Infections in Warm-Water Aquaculture: Opportunities and Challenges

Polylactic-Co-glycolic Acid Polymer-Based Nano-Encapsulation Using Recombinant Maltoporin of Aeromonas hydrophila as Potential Vaccine Candidate

Aquaculture production has been incurring economic losses due to infectious diseases by opportunistic pathogens like Aeromonas hydrophila, a bacterial agent that commonly affects warm water aquacultured fish. Developing an effective vaccine with an appropriate delivery system can elicit an immune response that would be a useful disease management strategy through prevention. The most practical method of administration would be the oral delivery of vaccine developed through nano-biotechnology. In this study, the gene encoding an outer membrane protein, maltoporin, of A. hydrophila, was identified, sequenced, and studied using bioinformatics tools to examine its potential as a vaccine candidate. Using a double emulsion method, the molecule was cloned, over-expressed, and encapsulated in a biodegradable polymer polylactic-co-glycolic acid (PLGA). The immunogenicity of maltoporin was identified through in silico analysis and thus taken up for nanovaccine preparation. The encapsulation efficiency of maltoporin was 63%, with an in vitro release of 55% protein in 48 h. The particle size and morphology of the encapsulated protein exhibited properties that could induce stability and function as an effective carrier system to deliver the antigen to the site and trigger immune response. Results show promise that the PLGA-mediated delivery system could be a potential carrier in developing a fish vaccine via oral administration. They provide insight for developing nanovaccine, since sustained in vitro release and biocompatibility were observed. There is further scope to study the immune response and examine the protective immunity induced by the nanoparticle-encapsulated maltoporin by oral delivery to fish.

Genetics and Genomics of Infectious Diseases in Key Aquaculture Species

Diseases pose a significant and pressing concern for the sustainable development of the aquaculture sector, particularly as their impact continues to grow due to climatic shifts such as rising water temperatures. While various approaches, ranging from biosecurity measures to vaccines, have been devised to combat infectious diseases, their efficacy is disease and species specific and contingent upon a multitude of factors. The fields of genetics and genomics offer effective tools to control and prevent disease outbreaks in aquatic animal species. In this study, we present the key findings from our recent research, focusing on the genetic resistance to three specific diseases: White Spot Syndrome Virus (WSSV) in white shrimp, Bacterial Necrotic Pancreatitis (BNP) in striped catfish, and skin fluke (a parasitic ailment) in yellowtail kingfish. Our investigations reveal that all three species possess substantial heritable genetic components for disease-resistant traits, indicating their potential responsiveness to artificial selection in genetic improvement programs tailored to combat these diseases. Also, we observed a high genetic association between disease traits and survival rates. Through selective breeding aimed at enhancing resistance to these pathogens, we achieved substantial genetic gains, averaging 10% per generation. These selection programs also contributed positively to the overall production performance and productivity of these species. Although the effects of selection on immunological traits or immune responses were not significant in white shrimp, they yielded favorable results in striped catfish. Furthermore, our genomic analyses, including shallow genome sequencing of pedigreed populations, enriched our understanding of the genomic architecture underlying disease resistance traits. These traits are primarily governed by a polygenic nature, with numerous genes or genetic variants, each with small effects. Leveraging a range of advanced statistical methods, from mixed models to machine and deep learning, we developed prediction models that demonstrated moderate-to-high levels of accuracy in forecasting these disease-related traits. In addition to genomics, our RNA-seq experiments identified several genes that undergo upregulation in response to infection or viral loads within the populations. Preliminary microbiome data, while offering limited predictive accuracy for disease traits in one of our studied species, underscore the potential for combining such data with genome sequence information to enhance predictive power for disease traits in our populations. Lastly, this paper briefly discusses the roles of precision agriculture systems and AI algorithms and outlines the path for future research to expedite the development of disease-resistant genetic lines tailored to our target species. In conclusion, our study underscores the critical role of genetics and genomics in fortifying the aquaculture sector against the threats posed by diseases, paving the way for more sustainable and resilient aquaculture development.