Development of a microbiome based health score for non-invasive monitoring of farmed Atlantic salmon (Salmo salar)
Luis E. LeóniD, Catalina Lorca, Francisco FuentesiD, Agustin PinaiD, María Ignacia Ortúzar, Diego GutierreziD, Juan Antonio UgaldeiD, Alejandro BisquerttiD
Abstract
The sustainability of Atlantic salmon (Salmo salar) farming is threatened by infectious diseases, environmental stressors, feed limitations, and regulatory or economic constraints. Although current health monitoring is improving with AI-powered camera systems that analyze behavior and nutrition, these tools typically identify stress responses rather than early signs of disease states. Because the microbial community undergoes successional reassembly in response to physiological disruptions before host barriers are breached, the microbiome offers a proactive early warning approach. In this study, a comparative cohort design was employed using a total of 171 individuals (n= 85 "healthy"; n=86 "lesioned") collected from a commercial marine facility and classified based on external clinical signs. The microbiome of multiple body sites (gills, skin, urogenital pore, and mucosa) from healthy and lesioned salmon were profiled using 16S rRNA amplicon sequencing. No differences in alpha diversity were observed between tissues and conditions. However, beta diversity was significantly different in clinical status, and the interaction of tissue with the status. Conversely, the mucosa and urogenital microbiomes were compositionally similar to each other, as were the gill and skin microbiomes, suggesting that urogenital swabs could serve as a non-invasive proxy for gut microbiome profiling, and skin for gill microbiomes. Several supervised models were trained on these profiles and used to classify salmon status with high accuracy. Based on these data, two Salmon Microbiome Health Score were developed that accurately differentiated the two cohorts. These scores are proposed as a novel biomarker, enabling proactive health management in aquaculture and complementing emerging technological monitoring systems.
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