Metagenomic insights into the taxonomy, function, and dysbiosis of prokaryotic communities in octocorals

Abstract

Background: In octocorals (Cnidaria Octocorallia), the functional relationship between host health and its symbiotic consortium has yet to be determined. Here, we employed comparative metagenomics to uncover the distinct functional and phylogenetic features of the microbiomes of healthy Eunicella gazella, Eunicella verrucosa, and Leptogorgia sarmentosa tissues, in contrast with the microbiomes found in seawater and sediments. We further explored how the octocoral microbiome shifts to a pathobiome state in E. gazella.

Results: Multivariate analyses based on 16S rRNA genes, Clusters of Orthologous Groups of proteins (COGs), Protein families (Pfams), and secondary metabolite-biosynthetic gene clusters annotated from 20 Illumina-sequenced metagenomes each revealed separate clustering of the prokaryotic communities of healthy tissue samples of the three octocoral species from those of necrotic E. gazella tissue and surrounding environments. While the healthy octocoral microbiome was distinguished by so-far uncultivated Endozoicomonadaceae, Oceanospirillales, and Alteromonadales phylotypes in all host species, a pronounced increase of Flavobacteriaceae and Alphaproteobacteria, originating from seawater, was observed in necrotic E. gazella tissue. Increased abundances of eukaryotic-like proteins, exonucleases, restriction endonucleases, CRISPR/Cas proteins, and genes encoding for heat-shock proteins, inorganic ion transport, and iron storage distinguished the prokaryotic communities of healthy octocoral tissue regardless of the host species. An increase of arginase and nitric oxide reductase genes, observed in necrotic E. gazella tissues, suggests the existence of a mechanism for suppression of nitrite oxide production by which octocoral pathogens may overcome the host's immune system.

Conclusions: This is the first study to employ primer-less, shotgun metagenome sequencing to unveil the taxonomic, functional, and secondary metabolism features of prokaryotic communities in octocorals. Our analyses reveal that the octocoral microbiome is distinct from those of the environmental surroundings, is host genus (but not species) specific, and undergoes large, complex structural changes in the transition to the dysbiotic state. Host-symbiont recognition, abiotic-stress response, micronutrient acquisition, and an antiviral defense arsenal comprising multiple restriction endonucleases, CRISPR/Cas systems, and phage lysogenization regulators are signatures of prokaryotic communities in octocorals. We argue that these features collectively contribute to the stabilization of symbiosis in the octocoral holobiont and constitute beneficial traits that can guide future studies on coral reef conservation and microbiome therapy. Video Abstract.

Keywords: Eunicella; Gorgonians; Holobiont; Host-microbe interactions; Leptogorgia; Necrosis; Secondary metabolism; Symbiosis.

Fig. 1

Prokaryotic community composition of octocoral samples, seawater, and sediment. Family-level community profiles of healthy (EG_H) and necrotic (EG_N) Eunicella gazella tissue, healthy Eunicella verrucosa (EV01-EV04), and Leptogorgia sarmentosa (LS06-LS08) specimens as well as seawater (SW01-SW04) and sediment samples (SD01-SD03). Relative abundances are displayed for taxa representing more than 3% of the total dataset reads. Taxa with abundances below 3% across the data are collectively labeled as “rare families”

Fig. 2

Multivariate analysis of the prokaryotic community profiles. Ordinations are shown at the taxonomic (phylotype, OTU) (a and b) and functional (Pfam and COG) (c and d) levels. In a, sediment samples were included in the ordination analysis while b shows the same ordination without sediment data. Principal coordinates analyses (PCoA) were performed using the Bray-Curtis similarity matrix calculated from Hellinger-transformed abundance data. All ordinations are shown in Eigenvalue scale. Healthy octocoral samples are represented by colored circles (salmon — healthy Eunicella gazella (EG15_H - EG18H); orange — healthy Eunicella verrucosa (EV01 - EV04); olive — healthy Leptogorgia sarmentosa (LS06 - LS08)), necrotic E. gazella (EG15_N - EG18_N) by red triangles, sediment (SD01 - SD03) by black diamonds, and seawater (SW01 - SW04) by blue asterisks. Discrete grouping of the sample categories was statistically supported by one-way PERMANOVA tests with each 999 permutations

Fig. 3

Bacterial phylotypes which are significantly enriched in healthy (a) or necrotic (c) Eunicella gazella tissue. For comparison, the respective abundances of some of these phylotypes (OTUs) in the other octocoral species, sediment, and seawater are shown in b and d. Bars represent average proportions (%) ± standard errors. Paired t-tests (a and c) or one-way ANOVAs (b and d) followed by Bonferroni tests were used to check for significant differences between sample groups. Statistical significance was established at P-values ≤ 0.05. Letters or asterisks above error bars indicate significant differences (*P ≤ 0.05; **P ≤ 0.01; ***P ≤ 0.001). Respective P-values are presented in the graphs. All phylotypes shown here are among the top ten phylotypes respectively enriched in healthy or in necrotic E. gazella tissue (Additional file 2: Table S4b,c) that contributed most to the dissimilarities between these microbiomes, as revealed by SIMPER and “Indicspecies” analyses

Fig. 4

Gene functions which are enriched in the microbiomes of healthy or necrotic Eunicella gazella tissue. Average proportions (%) ± standard errors of Clusters of Orthologous Groups of proteins (COGs) that are significantly augmented in the microbiomes of healthy (a) or necrotic (b) Eunicella gazella tissue. If a given function was represented by more than one COG entry across the dataset, the proportions of these functionally belonging COGs were summed, and the number of COGs that contributed to each bar chart is given below chart titles (see Additional file 2: Table S7(C) for the COG entries used). If only one COG entry contributed to a chart, the respective COG ID is given. Paired t-tests were used to check for significant differences between sample groups. Statistical significance was established at P-values ≤ 0.05. Asterisks above error bars indicate significant differences (*P ≤ 0.05; **P ≤ 0.01; ***P ≤ 0.001). Respective P-values are presented in the graphs

Fig. 5

Secondary metabolite coding potential in the prokaryotic communities of healthy and necrotic octocoral samples and seawater. a Distribution of biosynthetic gene clusters (BGCs, N = 462) across these 17 assembled, metagenomes. The BGC counts per compound class were obtained using antiSMASH version 5.0. b Principal component analysis (PCA) biplot based on the BGCs (arrows) found in the metagenomes of the microbiomes of healthy (EG_H, salmon circles) and necrotic (red triangles; EG_N) Eunicella gazella tissue, healthy Eunicella verrucosa (orange circles; EV01 - EV04), healthy Leptogorgia sarmentosa (olive circles; LS06 - LS08), and seawater (blue asterisks; SW01 - SW04). c Similarity network of 455 BGCs predicted by antiSMASH and grouped into biosynthetic gene cluster families (GCFs) across seven major compound classes using the BiG-SCAPE algorithm. The network was rendered in Cytoscape. Nodes represent amino acid sequences of BGC domains, and their different shapes indicate the origin of the sampled metagenome. BGC classes are color-coded with number of GCFs per class given in brackets. A majority of the GCFs (“Others,” N = 169) could not be classified using current BiG-SCAPE BGC nomenclature. Most GCFs were composed by only one BGC (singletons), with GCFs containing two or more BGCs represented through BGC networks inferred from protein sequence homology. PKS, polyketide synthase; NRPS, non-ribosomal peptide synthetase; RiPPs, ribosomally synthesized and post-translationally modified peptides; hserlactone, homoserine lactone; CDPS, tRNA-dependent cyclodipeptide synthases; hglE-KS, heterocyst glycolipid synthase-like PKS; LAP, linear azol(in)e-containing peptides