Prediction of the ecological state by culturing microbes at the seafloor

The impact of human activity on the seafloor poses a significant threat to marine life. Current methods for monitoring human impact involve physically sampling seafloor substrates, which is time, cost and labor-intensive. The analysis time (approx. 3 months) from sampling to results is a bottleneck for efficient ocean environmental management. To address this bottleneck, we have developed a substrate-independent approach for seafloor monitoring, reducing the analysis time to less than two weeks. Alginate beads placed in a protective cage, are deployed on the seafloor for one week. The microbes that grow on the beads provide an indication of the ecological state. Using this in situ cultivation principle, we evaluated 420 samples form 5 aquaculture sites, representing 3 soft -, 1 mixed - and 1 hard bottom site(s). The microbiota composition was determined by 16S rRNA gene analyses. Partial Least Square Discriminant Analysis (PLSDA) was used to predict the macrofauna ecological state based on the microbial composition. We found a strong association between microbiota on the beads and macrofauna ecological state, with a cross-validated accuracy of classification of 0.95. Overall, our study provides a promising proof of principle for in situ culturing as a novel and simplified approach to predict the seafloor ecological state in an economic and efficient manner.