Award: OCE-1928817

Award Title: RAPID: Collaborative Research: Predicting the Spread of Multi-Species Coral Disease Using Species Immune Traits
Funding Source: NSF Division of Ocean Sciences (NSF OCE)
Program Manager: Daniel Thornhill

Outcomes Report

Infectious disease is a significant and increasing threat to hard corals, particularly in the Caribbean, playing a major role in changing the structure in reef community composition. However, some coral species and even individuals within species have the ability to resist disease mortality and their corresponding immune traits may provide a basis for predicting coral community dynamics on reefs disturbed by disease. One of the most devastating coral disease outbreaks to date, stony coral tissue loss disease (SCTLD), continues to spread throughout Caribbean reefs causing widespread mortality. Knowing what makes some corals more resistant to diseases such as SCTLD, and then developing predictive models of coral communities, will provide scientists and resource managers with the tools to better protect and recover these valuable and highly threatened ecosystems. The main goal of the present project was to identify which coral immune traits predict disease resistance and be used to subsequently model future community composition on reefs affected by disease. Using results from a SCTLD transmission experiment conducted in the United States Virgin Islands, six coral species were identified as highly susceptible (Colpophyllia natans and Orbicella annularis), intermediately susceptible (Porites astreoides, Pseudodiploria strigosa, and Siderastrea siderea), or low susceptibility (Montastraea cavernosa). Traits collected from these corals and considered within the model consisted of gene expression of the coral host and dominant algal symbiont clade, histological measurements, 16S sequences, ITS2 sequences, and virus-like transcripts. We used machine learning methods to determine what traits most influenced a coral’s susceptibility group membership. Based on the distributions of the influential traits for each susceptible species, our trait-space model predicts coral community compositions post-SCTLD outbreak by using the traits of the most resistant species like a "disease-filter." The top three coral holobiont traits included two highly variable symbiont genes and one lineage specific coral host gene. This suggests that the genes most likely responding to the disease exposure of the host’s most dominant algal symbiont, as well as one host gene that is most likely mediated by evolved differences among species, play the most important roles in determining resistance to SCTLD and affect post-outbreak coral community assemblages. Results of this study can help identify individual corals and reefs that may be more likely to persist after major disease outbreaks, such as SCTLD, to better understand how species composition may change under the more frequent disease outbreaks predicted to occur in future climate change scenarios. Last Modified: 03/01/2023 Submitted by: Erinn M Muller

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Principal Investigator: Erinn M. Muller (Mote Marine Laboratory)