Divergent microbiota of echinoid eggs separated by the Isthmus of Panama

Relationships between animals and their associated microbiota are dependent on the evolutionary history of the host and on the environment. The majority of studies tend to focus on one of these factors and rarely consider how both determine the community composition of the associated bacteria. One "natural experiment" to test how evolutionary history, shared environments, and the interaction between these factors drive community composition is to compare geminate species pairs. Echinoids separated by the Isthmus of Panama are suitable for this comparison due to the known evolutionary history and differences in oceanographic characteristics of the Caribbean Sea and Pacific Ocean. By comparing the egg-associated microbiota of the Echinometra and Diadema geminate species pairs, we show that each pair of geminate species associates with a distinct bacterial community in a pattern consistent with phylosymbiosis, and that the interaction between the evolutionary history of the host and the environment best explain differences in these communities. Moreover, we found that particular microbial taxa differed considerably between, but not within, oceans and that the microbiota of the two Caribbean Echinometra species were dominated by the phototrophic Oxyphotobacteria. Taken together, data presented here support the hypothesis that the microbiota associated with geminate species are another characteristic of these taxa that diverged in ~2.8 million years of isolation.Funding provided by: National Science FoundationCrossref Funder Registry ID: http://dx.doi.org/10.13039/100000001Award Number: Funding provided by: Human Frontier Science ProgramCrossref Funder Registry ID: http://dx.doi.org/10.13039/501100000854Award Number: RGY0079/2016Funding provided by: Smithsonian InstitutionCrossref Funder Registry ID: http://dx.doi.org/10.13039/100000014Award Number:Total DNA extraction Ampylificaiton of the 16S rRNA gene for bacteria using primers for the V3/V4 region Sequencing via MiSe