EAPSI: Reconstructing the evolutionary history of coral-microbe associations to identify microbial taxa important to the health of their coral host

Mcminds Ryan C, Jefferson OR

Investigators

Abstract

Coral reef ecosystems are in a state of rapid global decline. Research has suggested that many important stressors, including elevated sea temperatures, nutrient loading, and disease, may harm corals by disrupting their natural associations with bacteria and other microbes. Microbes as a whole have been shown to play important roles in coral health by providing essential nutrients, resisting pathogens, and even by cueing development. However, it has been challenging to identify the specific microbial taxa that provide these benefits. The health consequences to corals of stressor-mediated microbial community shifts are thus difficult to assess. This project will attempt to discover physiologically important microbes by reconstructing the evolutionary history of coral-microbe associations and identifying signatures of natural selection for particular associations. The research will be conducted in collaboration with Dr. David Bourne, a noted expert in coral microbiology, at the Australian Institute of Marine Science. The diverse reefs of Australia harbor up to 15 of the 21 major coral clades, providing a unique opportunity to sample a broad selection of tissue from evolutionarily divergent but geographically concurrent coral species. Currently, the microbiomes of only 3 of these clades have received any significant attention. A baseline description of these communities, created using high throughput sequencing of marker-genes and metagenomes, will allow the identification of taxa that cluster within particular coral clades. This analysis will be performed by treating microbial taxa and functions as character traits that can be tested against a null model of neutral evolution. Future studies will be able to focus on these taxa as putative mutualists, whose disruption may reduce coral health. This research will eventually allow more accurate prediction of the environmental effects of various environmental stressors. This NSF EAPSI award is funded in collaboration with the Australian Academy of Science.