Microbiome determinants of productivity in aquaculture of whiteleg shrimp

Aquaculture is a rapidly growing industry essential for global food security, yet its productivity is often constrained by high mortality rates and inefficient growth. While the microbiome is known to influence host health and nutrient assimilation, its broader role in animal production remains poorly understood. Here, we take a data-driven approach to address this gap by systematically analyzing shrimp-associated microbiomes across hatcheries and farms. By integrating microbiome data with machine learning, we demonstrate that microbial communities are powerful predictors of key production outcomes, shaping shrimp survival and growth. Our findings suggest that the microbiome could serve as a diagnostic tool for assessing production conditions and optimizing management strategies. In addition, machine learning techniques offer a promising avenue for identifying beneficial microbes and developing targeted microbiome therapies to enhance aquaculture sustainability and efficiency.