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Diseases have caused unprecedent mortality in Caribbean coral communities. White band disease (WBD) has killed up to 95% of all endangered Caribbean Acroporids since it was first observed in 1979. Despite the devastating impacts of WBD, its etiology is currently unknown although recent research identified two bacterial strains – ASVs classified as aCysteiniphilum litoraleand aVibriosp., as the most likely pathogens. To better understand the disease etiology of WBD, we pretreated corals with antibiotics to determine how prophylactic use of antibiotics impacts the transmission of WBD in a replicated tank-based experiment. We found the prophylactic use of antibiotics led to significantly reduced infection rates in disease exposed corals with a 30-percentage point decrease in the infection rate. Analyses of 16S rRNA amplicon gene sequencing data in the disease exposed corals demonstrated that antibiotic pretreatment resulted in coral microbiomes which were less speciose and contained relatively fewerVibriospp. than untreated corals, indicating that the benefit of the antibiotic pretreatment was its ability to reduce the relative abundance of intrinsic secondary opportunists and/or opportunistic pathogens suggesting their likely importance to the etiology of WBD. We propose two distinct etiologies involving either an extrinsic keystone pathogen (Cysteiniphilum litorale) or overgrowth of intrinsic opportunistic pathogens (Vibriospp.). Future research should isolate these strains to confirm the etiology of white band disease. 

Abstract White band disease (WBD) has decimated the Caribbean staghorn coral, Acropora cervicornis, since its emergence in 1979, but its etiology remains unknown. Numerous WBD pathogen candidates from over nine bacterial families have been implicated, with a multi-year field study recently identifying Cysteiniphilum litorale as the likely pathogen. Here, we use 16S rRNA gene amplicon sequencing to profile changes in the bacterial communities in a tank-based transmission experiment in the Florida Keys using 50 nursery-raised staghorn coral genotypes with varying disease resistances to determine whether any bacteria in the native staghorn coral microbiomes were associated with WBD resistance and to identify bacterial amplicon sequencing variants (ASVs) associated with WBD exposure and transmission. We found no significant associations, positive or negative, between any bacterial ASV, genus, or family and disease resistance in native staghorn coral microbiomes but did identify nine bacterial ASVs strongly associated with disease outcome in the tank-based transmission experiment. ASV 65, classified as Cysteiniphilum litorale, showed strong disease associations consistent with pathogenicity, including being significantly associated with WBD transmission within disease-exposed tanks (i.e. more abundant on diseased fragments) and being significantly more abundant on the diseased experimental dose than the healthy dose. The V3-V4 16S rRNA gene sequence for ASV 65 differed by only 1 of 415 bp from the C. litorale ASV identified as the putative WBD pathogen in the recent multi-year study from Panama, suggesting a rare Caribbean-wide strain-level pathogen association. Eight additional disease-associated ASVs were identified as potential opportunistic pathogens and included ASVs from the families Vibrionaceae and Colwelliaceae. 

Abstract Coral diseases contribute to the rapid decline in coral reefs worldwide, and yet coral bacterial pathogens have proved difficult to identify because 16S rRNA gene surveys typically identify tens to hundreds of disease‐associate bacteria as putative pathogens. An example is white band disease (WBD), which has killed up to 95% of the now‐endangered CaribbeanAcroporacorals since 1979, yet the pathogen is still unknown. The 16S rRNA gene surveys have identified hundreds of WBD‐associated bacterial amplicon sequencing variants (ASVs) from at least nine bacterial families with little consensus across studies. We conducted a multi‐year, multi‐site 16S rRNA gene sequencing comparison of 269 healthy and 143 WBD‐infectedAcropora cervicornisand used machine learning modelling to accurately predict disease outcomes and identify the top ASVs contributing to disease. Our ensemble ML models accurately predicted disease with greater than 97% accuracy and identified 19 disease‐associated ASVs and five healthy‐associated ASVs that were consistently differentially abundant across sampling periods. Using a tank‐based transmission experiment, we tested whether the 19 disease‐associated ASVs met the assumption of a pathogen and identified two pathogenic candidate ASVs—ASV25Cysteiniphilum litoraleand ASV8Vibriosp. to target for future isolation, cultivation, and confirmation of Henle‐Koch's postulate via transmission assays.