Coral reefs host hundreds of thousands of animal species that are increasingly threatened by anthropogenic disturbances. These animals host microbial communities at their surface, playing crucial roles for their fitness. However the diversity of such microbiomes is mostly described in a few coral species, and still poorly defined in other invertebrates and vertebrates. Given the diversity of animal microbiomes, and the diversity of host species inhabiting coral reefs, the contribution of such microbiomes to the total microbial diversity of coral reefs could be important, yet potentially vulnerable to the loss of animal species.

Analysis of the surface microbiome from 74 taxa, including teleost fishes, hard and soft corals, crustaceans, echinoderms, bivalves and sponges, revealed that more than 90% of their prokaryotic phylogenetic diversity was specific and not recovered in surrounding plankton.

Estimate of the total diversity associated to coral reef animal surface microbiomes reached up to 2.5% of current estimates of Earth prokaryotic diversity. Therefore, coral reef animal surfaces should be recognized as a hotspot of marine microbial diversity. Loss of the most vulnerable reef animals expected under present-day scenarios of reef degradation would induce an erosion of 28% of the prokaryotic richness, with unknown consequences on coral reef ecosystem functioning.

Sampling was conducted in November 2015 in Mayotte lagoon shallow (depth <10 meters) barrier and fringing coral reefs in Western Indian Ocean. We sampled the most abundant taxa from each of the main animal groups of the coral reef (teleost fishes, Anthozoa, crustaceans, echinoderms, mollusks and sponges) within a radius of 50 m around each site. The skin microbiome was collected by swabbing the entire untouched side of the body of fish, by exposing to air a specimen of corals to collect mucus, or by swabbing entirely other types of collected invertebrates. All samples were stored on board at -5°C in an electric cooler during the day, then at -80°C back to the lab until DNA extraction.For each of 6 days of sampling, six 200-mL samples of seawater were collected 50 cm below sea surface (3 samples) and at 30 cm from the sea bottom (3 samples). Seawater samples were stored in a dark cooler (4°C) and filtrated within 6 hours through a 47 mm 0.2 µm polycarbonate membrane (Whatman, Clifton, USA) and filter was frozen at -80°C until DNA extraction.

DNA extraction was performed using the Maxwell® 16 Bench-top extraction system following manufacturer’s instructions, and eluted in 50 µL of elution buffer. The V4 region of the 16S rDNA gene was amplified using the prokaryotic primers modified for Illumina sequencing 515F (5’-C TTT CCC TAC ACG ACG CTC TTC CGA TCT - GTG CCA GCM GCC GCG GTA A- 3’) and the modified version of 806R by Apprill et al. (5’ – G GAG TTC AGA CGT GTG CTC TTC CGA TCT - GGA CTA CNV GGG TWT CTA AT - 3’), with PuRe Taq Ready-To-Go PCR Beads. Equimolar amounts of sample DNA amplified from each reef type were separately pooled and sequenced in two separated runs by an external laboratory (INRA GeT-PlaGE platform, Toulouse, France) on an Illumina platform using the 2×250 bp MiSeq chemistry.

Sequence reads were processed using the ‘DADA2’ R-package version 1.2 (Callahan et al. 2016) and R software v3.4.3 Forward reads were trimmed at their 5’ extremity to remove forward and reverse primers, then trimmed according to a quality score of 2, and filtered to remove reads containing more than 2 expected errors, before de-replication and merging forward and reverse primers. Chimeras were then removed and remaining Amplicon Sequence Variants (ASVs) were taxonomically classified using the SILVA database v132 [4], and non-prokaryotic sequences were removed.

The dataset is a .rData file. To open it, simply open R (https://www.r-project.org/), go to the directory where you stored the file and run the command:

setwd("/your/directory/")

load("SM3-ps_Chiarello_et_al2020.rData")

The data is formatted in format specific from phyloseq R-package, a convenient package for microbiome data analysis. The package must be installed and loaded before before loading the dataset:

library(phyloseq)

Please visit phyloseq webpage (https://joey711.github.io/phyloseq/) for more information about phyloseq format and installation instructions.