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Abstract Anthropogenic climate change has had devastating effects on the Florida and Caribbean reef systems, in part due to increased disease outbreaks. Climate change exacerbates marine diseases by expanding pathogen ranges and heightening host susceptibility through environmental stress. Specifically, there has been a stark rise in marine disease events outbreaks targeting multiple coral species, resulting in high mortality rates and declining reef biodiversity. Although many of these diseases present similar visual symptoms, they exhibit varying mortality rates and require distinct treatment protocols. Advances in coral transcriptomics research have enhanced our understanding of coral responses to various diseases, but more sophisticated methods are required to classify diseases that appear visually similar. This study provides the first machine learning (ML) model that can classify two common coral diseases: stony coral tissue loss disease (SCTLD) and white plague (WP). Using various algorithms, 463 gene expression biomarkers were identified, with 275 unique to SCTLD and 167 unique to WP, revealing distinct immune responses between the two diseases. The final ML model was built with partial least squares discriminant analysis (PLS-DA) and the identified biomarkers were tested and validated with samples collected in situ. It achieved high predictive performance, with an Area Under the Receiver Operating Characteristic (ROC) Curve (AUC) of 0.9895, an average overall error rate of 0.0754, and an average balanced error rate (BER) of 0.0799. This study provides a preliminary disease classification model that reliably distinguishes between SCTLD and WP and offers valuable insights into their underlying cellular responses. Additionally, the identified biomarkers provide a foundation for the development of rapid diagnostic tools to identify and mitigate future coral disease outbreaks. 

ABSTRACT Marine disturbance events are often influenced by the environment, making it difficult to parse abiotic and biotic drivers. This is particularly true of disease infection and spread in coral reef environments, where pathogens are challenging to isolate and transmission may occur through the movement of water masses. Here we assess mesoscale conditions related to coral community disturbance from 2001 to 2023 on isolated reefs, using the Flower Garden Banks (FGB) as a case study. During the study period, relative to other western Atlantic reefs, this high latitude coral reef system experienced relatively few disturbance events (2 disease events, 1 hypoxia event, and 6 thermal stress events) and lower coral mortality, allowing it to maintain remarkably high coral cover. We explore mesoscale oceanographic features during the study period, predominantly the northwest extension of the Loop Current (LC), to understand its connection to disturbance events at FGB. LC position was linked to disease and hypoxia events, but not consistently to thermal stress events. Low LC extension, as seen in 2016, may have facilitated the transport of freshwater river output across the GoM resulting in a hypoxia event at FGB. To examine the influence of circulation and upstream connectivity to disease at FGB, we used a biophysical Lagrangian particle tracking model to backtrack virtual disease agents from FGB over 23 years of hydrodynamic forcing. Our results highlight a link between observed coral disease incidence at FGB, seasonality, and a 30‐day connectivity window to reefs of the Mesoamerican Reef. Operational biophysical and oceanographic models can provide a valuable tool for reef disturbance prediction and monitoring. These models are likely to become increasingly relevant as climate change alters the behavior of ocean circulation, with implications for reef connectivity, disease dispersal, freshwater inputs, and the management of these and other isolated coral reefs. 

Gene expression profiles are correlated to disease phenotypes in resistant and susceptible corals. 

Abstract Stony coral tissue loss disease (SCTLD), one of the most pervasive and virulent coral diseases on record, affects over 22 species of reef-building coral and is decimating reefs throughout the Caribbean. To understand how different coral species and their algal symbionts (family Symbiodiniaceae) respond to this disease, we examine the gene expression profiles of colonies of five species of coral from a SCTLD transmission experiment. The included species vary in their purported susceptibilities to SCTLD, and we use this to inform gene expression analyses of both the coral animal and their Symbiodiniaceae. We identify orthologous coral genes exhibiting lineage-specific differences in expression that correlate to disease susceptibility, as well as genes that are differentially expressed in all coral species in response to SCTLD infection. We find that SCTLD infection induces increased expression of rab7 , an established marker of in situ degradation of dysfunctional Symbiodiniaceae, in all coral species accompanied by genus-level shifts in Symbiodiniaceae photosystem and metabolism gene expression. Overall, our results indicate that SCTLD infection induces symbiophagy across coral species and that the severity of disease is influenced by Symbiodiniaceae identity. 

Abstract Stony coral tissue loss disease (SCTLD) is a widespread and deadly disease that affects nearly half of Caribbean coral species. To understand the microbial community response to this disease, we performed a disease transmission experiment on US Virgin Island (USVI) corals, exposing six species of coral with varying susceptibility to SCTLD. The microbial community of the surface mucus and tissue layers were examined separately using a small subunit ribosomal RNA gene-based sequencing approach, and data were analyzed to identify microbial community shifts following disease acquisition, potential causative pathogens, as well as compare microbiota composition to field-based corals from the USVI and Florida outbreaks. While all species displayed similar microbiome composition with disease acquisition, microbiome similarity patterns differed by both species and mucus or tissue microhabitat. Further, disease exposed but not lesioned corals harbored a mucus microbial community similar to those showing disease signs, suggesting that mucus may serve as an early warning detection for the onset of SCTLD. Like other SCTLD studies in Florida, Rhodobacteraceae, Arcobacteraceae, Desulfovibrionaceae, Peptostreptococcaceae, Fusibacter, Marinifilaceae, and Vibrionaceae dominated diseased corals. This study demonstrates the differential response of the mucus and tissue microorganisms to SCTLD and suggests that mucus microorganisms may be diagnostic for early disease exposure. 

Stony coral tissue loss disease (SCTLD) is a widespread and deadly disease that affects nearly half of Caribbean coral species. To understand the microbial community response to this disease, we performed a disease transmission experiment on US Virgin Island (USVI) corals, exposing six species of coral with varying susceptibility to SCTLD. The microbial community of the surface mucus and tissue layers were examined separately using a small subunit ribosomal RNA gene-based sequencing approach, and data were analyzed to identify microbial community shifts following disease acquisition, potential causative pathogens, as well as compare microbiota composition to field-based corals from the USVI and Florida outbreaks. While all species displayed similar microbiome composition with disease acquisition, microbiome similarity patterns differed by both species and mucus or tissue microhabitat. Further, disease exposed but not lesioned corals harbored a mucus microbial community similar to those showing disease signs, suggesting that mucus may serve as an early warning detection for the onset of SCTLD. Like other SCTLD studies in Florida, Rhodobacteraceae, Arcobacteraceae, Desulfovibrionaceae, Peptostreptococcaceae, Fusibacter, Marinifilaceae, and Vibrionaceae dominated diseased corals. This study demonstrates the differential response of the mucus and tissue microorganisms to SCTLD and suggests that mucus microorganisms may be diagnostic for early disease exposure. 

Coral disease has progressively become one of the most pressing issues affecting coral reef survival. In the last 50 years, several reefs throughout the Caribbean have been severely impacted by increased frequency and intensity of disease outbreaks leading to coral death. A recent example of this is stony coral tissue loss disease which has quickly spread throughout the Caribbean, devastating coral reef ecosystems. Emerging from these disease outbreaks has been a coordinated research response that often integrates ‘omics techniques to better understand the coral immune system. ‘Omics techniques encompass a wide range of technologies used to identify large scale gene, DNA, metabolite, and protein expression. In this review, we discuss what is known about coral immunity and coral disease from an ‘omics perspective. We reflect on the development of biomarkers and discuss ways in which coral disease experiments to test immunity can be improved. Lastly, we consider how existing data can be better leveraged to combat future coral disease outbreaks. 

Abstract Disease outbreaks have caused significant declines of keystone coral species. While forecasting disease outbreaks based on environmental factors has progressed, we still lack a comparative understanding of susceptibility among coral species that would help predict disease impacts on coral communities. The present study compared the phenotypic and microbial responses of seven Caribbean coral species with diverse life-history strategies after exposure to white plague disease. Disease incidence and lesion progression rates were evaluated over a seven-day exposure. Coral microbiomes were sampled after lesion appearance or at the end of the experiment if no disease signs appeared. A spectrum of disease susceptibility was observed among the coral species that corresponded to microbial dysbiosis. This dysbiosis promotes greater disease susceptiblity in coral perhaps through different tolerant thresholds for change in the microbiome. The different disease susceptibility can affect coral’s ecological function and ultimately shape reef ecosystems.