A holistic time-series analysis of stony coral tissue loss disease

As stony coral tissue loss disease (SCTLD) continues to devastate coral populations across Florida and the Caribbean, the causative agent remains unidentified. This lack of identification hinders the development of targeted treatments and reliable diagnostic tools. Despite extensive analyses across diverse sample sets, no pathogen(s) has been definitively linked to SCTLD. This may be due to the disease’s complexity, potentially involving multiple microbial agents and environmental stressors, as well as variability across reefs and coral colonies. To address these challenges, this project adopted a holistic, standardized approach to sample collection and analysis. By using a consistent set of SCTLD samples across multiple analyses, we aimed to generate directly comparable datasets that could reveal patterns normally obscured by environmental variability in field samples. To minimize confounding factors, experiments were conducted in closed aquarium systems using naïve, healthy corals collected from regions before the arrival of SCTLD. The use of naïve corals also reduced the risk of pre-existing SCTLD-associated microbes in healthy tissue. Infection was induced in the lab by housing naïve corals with diseased fragments from the field. Samples were collected at five timepoints to capture the progression of disease. Each experimental tank had a corresponding control tank containing only healthy corals under identical conditions, except with a healthy fragment instead of a diseased one. 

Key Findings: 

Transcriptome & Proteomics: RNA virus detection tools identified hundreds of viral candidates, with 19 high-confidence viral populations found across samples. Proteomic analysis supported viral presence and helped build species-specific reference databases. 

Metabolomics: Early metabolic shifts were observed in Montastraea cavernosa corals 48 hours post-exposure—before visible symptoms—highlighting potential biomarkers for early disease detection. Key compounds included lyso-PAF, acylcarnitines, and DGCC lipids, indicating immune and metabolic stress responses. 

Histology: SCTLD was confirmed in all disease donor samples and several exposed corals. Histological markers included lytic necrosis, degraded endosymbionts, and globules from granular amoebocytes. 

TEM: Diseased corals exhibited significant reductions in starch and lipid reserves, increased crystal formation, suggesting these as potential indicators of disease progression. However, the presence of viral-like particles (VLPs) did not appear to significantly correlate with health state. 

Microbiome: Disease-exposed corals showed dynamic microbial shifts, with enrichment of anaerobic bacteria over time. Vibrio coralliilyticus was present but not dominant, suggesting a limited role in disease progression for these experiments. 

Conclusions: The dataset provides a critical baseline for future disease response and environmental stress studies. Continued integration of multi-omics data is essential to identify causative agents and biomarkers, which will be the focus for the next stages of this project. Preliminary findings also suggest the emergence of a distinct disease—Orbicella acute tissue loss disease (OATLD) - warranting further investigation.