Comparison of Preservation and Extraction Methods on Five Taxonomically Disparate Coral Microbiomes - Pratte, Zoe A.; Kellogg, Christina A. (Frontiers in Marine Science, 2021)
All animals are host to a multitude of microorganisms that are essential to the animal’s health. Host-associated microbes have been shown to defend against potential pathogens, provide essential nutrients, interact with the host’s immune system, and even regulate mood. However, it can be difficult to preserve and obtain nucleic acids from some host-associated microbiomes, making studying their microbial communities challenging. Corals are an example of this, in part due to their potentially remote, underwater locations, their thick surface mucopolysaccharide layer, and various inherent molecular inhibitors. This study examined three different preservatives (RNAlater, DNA/RNA Shield, and liquid nitrogen) and two extraction methods (the Qiagen PowerBiofilm kit and the Promega Maxwell RBC kit with modifications) to determine if there was an optimum combination for examining the coral microbiome. These methods were employed across taxonomically diverse coral species, including deep-sea/shallow, stony/soft, and zooxanthellate/azooxanthellate: Lophelia pertusa, Paragorgia johnsoni, Montastraea cavernosa, Porites astreoides, and Stephanocoenia intersepta. Although significant differences were found between preservative types and extraction methods, these differences were subtle, and varied in nature from coral species to coral species. Significant differences between coral species were far more profound than those detected between preservative or extraction method. We suggest that the preservative types presented here and extraction methods using a bead-beating step provide enough consistency to compare coral microbiomes across various studies, as long as subtle differences in microbial communities are attributed to dissimilar methodologies. Additionally, the inclusion of internal controls such as a mock community and extraction blanks can help provide context regarding data quality, improving downstream analyses.