The Future of Aquaculture: KAMI SYS and Innovation Against Microbial Evolution

?5. Data and Research Gaps

Effectively addressing the threats posed by pathogenic microorganisms and viruses in aquaculture requires precise and systematic data-driven management. However, the current availability of data in aquaculture systems is limited both in quality and quantity, creating barriers to understanding the interactions between pathogens, beneficial microbes, and environmental factors. To enhance our understanding of the complexity of aquaculture ecosystems and establish sustainable management strategies, the following data gaps and research challenges must be addressed.

5.1 Limitations of Metagenomics and Microbial Profiling

Metagenomics and other advanced analytical techniques are increasingly essential for understanding microbial community dynamics in aquaculture environments. However, technical and financial constraints have limited the widespread use of these methods.

• Importance of Metagenomics: Metagenomics is a powerful tool for analyzing the genetic composition and functional characteristics of all microorganisms in an aquaculture environment. It enables the monitoring of specific pathogen distributions and the evaluation of beneficial microbial stability. For instance, 16S rRNA sequencing is effective for analyzing microbial community composition but has limitations in understanding functional traits. More in-depth insights can be obtained through metatranscriptomics and metaproteomics, which analyze gene expression and protein levels in microbial populations.
• Limitations and Challenges: Metagenomics is restricted by high costs and complex data processing, making it feasible only for small-scale studies. The interpretation of results requires interdisciplinary expertise in microbiology, ecology, and aquaculture, which limits its applicability. Larger databases and long-term studies are needed to understand functional interactions between pathogens and beneficial microbes in aquaculture environments.

Professional Suggestion: Regularly perform metagenomic data collection and analysis in large-scale aquaculture facilities, and integrate the results into a centralized database to analyze pathogen occurrence patterns and the ecological roles of beneficial microbes systematically.

5.2 Gaps in Research on Environmental Factors and Pathogen Evolution

Physical and chemical conditions in aquaculture environments, such as temperature, salinity, and pH, significantly influence pathogen survival and transmission. However, there is a lack of quantitative studies on the relationship between these environmental factors and pathogen evolution.

• Insufficient Dynamic Environmental Data: Environmental variables such as temperature, salinity, dissolved oxygen (DO), and chemical oxygen demand (COD) fluctuate in aquaculture systems and directly influence pathogen activity. Most aquaculture systems lack automated monitoring systems or IoT-based sensors that can accurately track these changes in real time.
• Climate Change and Pathogen Evolution: Extreme weather conditions caused by climate change, such as rising sea temperatures and heavy rainfall, accelerate pathogen evolution. For instance, Vibrio species exhibit increased infection rates and virulence at higher temperatures. Research into the physiological changes of pathogens under climate change and the reduced survival of beneficial microbes is still limited.

Professional Suggestion: Develop climate simulation models to evaluate the evolutionary responses of pathogens and the resilience of beneficial microbes, providing the basis for sustainable management strategies in future aquaculture environments.

5.3 Need for Case Studies and Global Data Sharing

As aquaculture becomes increasingly globalized, the spread of pathogenic microorganisms has expanded from local issues to international challenges. However, there is insufficient focus on regional case studies and international data-sharing platforms.

• Lack of Case Studies: Case studies analyzing the characteristics and transmission pathways of pathogens in specific regions often rely on short-term observations, with insufficient long-term data accumulation. Collecting regional data on pathogen genetic changes, antibiotic resistance patterns, and the activity of beneficial microbes is essential for analyzing global patterns.
• Importance of Global Data Sharing: International platforms (e.g., based on FAO or OIE frameworks) are required to share pathogen occurrence data. Recording key pathogens (e.g., WSSV, AHPND) and beneficial microbial data in standardized formats and integrating this information into a global database will enable more effective research and management.

Professional Suggestion: Establish international collaborations to centralize pathogen monitoring data and integrate it with AI-based analytical tools to develop regional and global disease management strategies.

Conclusion: A Holistic Approach to Addressing Data Gaps

Optimizing disease management in aquaculture requires filling the gaps in metagenomics, environmental factor analysis, and case study data. Additionally, building platforms for international data sharing and analysis can help predict regional disease patterns and global transmission pathways.

Addressing these data gaps is crucial to ensuring the sustainability of the aquaculture industry. Multidisciplinary research and technological integration will enhance systematic data management and analysis, enabling early detection of pathogen threats, maximizing the roles of beneficial microbes, and ultimately protecting the health and productivity of aquaculture species.

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