Inferring Functional Potential of 16S rRNA in Coral Disease

To infer the functional potential of 16S rRNA gene data among AH, DU, and DL, the program Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt2) was used in QIIME2-2021.11 [82 (link)]. Only SCTLD-susceptible corals were evaluated and only ASVs that were present in at least 100 samples were selected. The picrust2 full-pipeline was used with the hidden state set to “mp” and the placement tool to place sequences into a tree set to “epa-ng.” The outputs were predicted metagenomes for Kyoto Encyclopedia of Genes and Genomes (KEGG [83 (link)]) orthologs and MetaCyc pathway [84 (link)] abundances. To assess the differential abundance of these outputs among disease states, the R package Maaslin2 was utilized [85 ]. For both KEGG and MetaCyc tests, data were log-transformed, a random effect was set to coral species, and the data were subsequently analyzed with a linear model. In the KEGG assessment, the minimum abundance = 0.05 and the minimum prevalence = 0.1. There were no minimums set for the MetaCyc test due to the lower number of pathways found in MetaCyc. The top 10 predicted pathways were selected based on values with the lowest Padj and effect sizes < −0.5 and >0.5. The top pathways were manually annotated on KEGG and MetaCyc websites.

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Rosales S.M., Huebner L.K., Evans J.S., Apprill A., Baker A.C., Becker C.C., Bellantuono A.J., Brandt M.E., Clark A.S., del Campo J., Dennison C.E., Eaton K.R., Huntley N.E., Kellogg C.A., Medina M., Meyer J.L., Muller E.M., Rodriguez-Lanetty M., Salerno J.L., Schill W.B., Shilling E.N., Stewart J.M, & Voss J.D. (2023). A meta-analysis of the stony coral tissue loss disease microbiome finds key bacteria in unaffected and lesion tissue in diseased colonies. ISME Communications, 3, 19.

Publication 2023

Asvs Coral Genes Genomes Metagenomes Reconstruction Rrna gene Tree

Corresponding Organization :

Other organizations : National Oceanic and Atmospheric Administration, University of Miami, NOAA Atlantic Oceanographic and Meteorological Laboratories, Florida Fish and Wildlife Conservation Commission, United States Geological Survey, Woods Hole Oceanographic Institution, Florida International University, University of the Virgin Islands, Florida Keys Community College, Mote Marine Laboratory, Institut de Biologia Evolutiva, Pompeu Fabra University, Pennsylvania State University, University of Florida, George Mason University, Harbor Branch Oceanographic Institute, Florida Atlantic University

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Variable analysis

independent variables

Disease states (AH, DU, and DL)

dependent variables

Predicted metagenomes for KEGG orthologs
MetaCyc pathway abundances

control variables

Coral species (random effect)

Annotations

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