Advancements in metagenomics next-generation sequencing during fish pathogen infection

Recent advancements in metagenomics have changed the perspective of fish pathogen infection, offering rapid and accurate detection of pathogens, which is a paramount necessity in an exponentially growing aquaculture industry. Traditional methods limit this ability as they depend on isolation and culture-based methods, which are time-consuming, hindering the timely response and the inability to identify non-culturable pathogens effectively. Integrating the metagenomic technique offers a promising solution, providing a transformative approach to pathogen detection, allowing researchers to identify known and novel pathogens directly from fish samples without the need for prior isolation or culture, enabling comprehensive pathogen detection, and monitoring in real time. The primary purpose of this chapter is to present how metagenomic technologies help explore the complexities of fish microbiomes, how they help identify the shifts in pathogenic profiles, and how they can be used in monitoring the progress of infections. Metagenomics supports comprehensive disease prevention and management frameworks by facilitating early diagnosis, monitoring pathogen resistance, and tracking epidemiological trends. This capability is particularly important in increasing antibiotic resistance, as it allows for the identification of resistant strains and the evaluation of treatment efficacy over time. These advancements not only streamline the research process but also facilitate the integration of metagenomic data into practical applications for disease management in aquaculture, enhancing the sustainability and productivity of aquaculture systems. The chapter anticipates several innovative developments in advanced metagenomic applications for fish health. In conclusion, the insights gained from this chapter will be instrumental in shaping future strategies for disease management in aquaculture, ultimately benefiting both human populations and aquatic ecosystems.