Genotype-specific microbiome responses of Acropora cervicornis to nutrient enrichment and disease stress reveal candidate taxa linked to health

The success of coral restoration efforts is driven by environmental conditions and the genetics of outplanted corals, including their microbiomes. In this study, we investigated the composition of microbiomes associated with 10 genotypes of Acropora cervicornis . We tested how ammonium enrichment, disease exposure, their combination, and host health altered the microbiomes of these genotypes. Using a combination of 16S rRNA metabarcode sequencing, machine learning, and differential abundance analysis, we identified microbial taxa linked to genotype susceptibility and resistance. While nutrient enrichment alone produced only subtle changes in the microbial community, it resulted in significant increases in the abundance of Alteromonadales. In ammonium enrichment, genotype health was negatively correlated with Rhodobacterales, a putative opportunist. Genotypes most susceptible to the nutrient treatments (Acer2, Kelsey-1, and Cooper-9) also had higher relative abundances of Rhodobacterales. In disease treatments, a single taxon from the order Alteromonadales found in the homogenate used to induce disease was also associated with 75% of fragments and one control. Notably, this taxon was absent from genotype FM19 disease-treated fragments that did not develop tissue loss. When the corals were exposed to both nutrients and disease, Alteromonadales' abundance was highest and present in all genotypes. The bacteria order Rickettsiales was positively correlated with health in several genotypes, but FM19 had one of the highest correlation values and maintained a similar Rickettsiales relative abundance in treatment groups compared to the controls. Our study shows the importance of genotype-specific microbial associations and their interactions with environmental stressors. These results have important implications for the development of coral restoration strategies, particularly through the selection of genotypes with beneficial microbial signatures and the incorporation of microbiome analyses to understand phenotypic outcomes.