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Microbiota of the Major South Atlantic Reef Building Coral Mussismilia

  • Environmental Microbiology
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Abstract

The Brazilian endemic scleractinian corals, genus Mussismilia, are among the main reef builders of the South Atlantic and are threatened by accelerating rates of disease. To better understand how holobiont microbial populations interact with corals during health and disease and to evaluate whether selective pressures in the holobiont or neutral assembly shape microbial composition, we have examined the microbiota structure of Mussismilia corals according to coral lineage, environment, and disease/health status. Microbiota of three Mussismilia species (Mussismilia harttii, Mussismilia hispida, and Mussismilia braziliensis) was compared using 16S rRNA pyrosequencing and clone library analysis of coral fragments. Analysis of biological triplicates per Mussismilia species and reef site allowed assessment of variability among Mussismilia species and between sites for M. braziliensis. From 173,487 V6 sequences, 6,733 coral- and 1,052 water-associated operational taxonomic units (OTUs) were observed. M. braziliensis microbiota was more similar across reefs than to other Mussismilia species microbiota from the same reef. Highly prevalent OTUs were more significantly structured by coral lineage and were enriched in Alpha- and Gammaproteobacteria. Bacterial OTUs from healthy corals were recovered from a M. braziliensis skeleton sample at twice the frequency of recovery from water or a diseased coral suggesting the skeleton is a significant habitat for microbial populations in the holobiont. Diseased corals were enriched with pathogens and opportunists (Vibrios, Bacteroidetes, Thalassomonas, and SRB). Our study examines for the first time intra- and inter-specific variability of microbiota across the genus Mussismilia. Changes in microbiota may be useful indicators of coral health and thus be a valuable tool for coral reef management and conservation.

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Acknowledgments

JT and SCF thank the MIT Center for Environmental Health Sciences (US National Institute of Environmental Health Sciences NIEHS grant P30-ES002109) MIT SeaGrant and MISTI-Brazil programs for funding. JT thanks Jonathan Friedman for helpful discussion regarding analysis of neutral community assembly. FLT and GG thank CNPq, FAPERJ, CAPES, and US Embassy for grants. We thank the ICOMM-LACAR project for 454 pyrosequencing.

Conflict of Interest

The authors declare no conflict of interests.

Author information

Author notes

  1. Samodha C. Fernando

    Present address: Department of Animal Science, University of Nebraska, Lincoln, NE, 68583, USA

Authors and Affiliations

  1. Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Room 48-331, 15 Vassar Street, Cambridge, MA, 02139, USA

    Samodha C. Fernando, Jia Wang, Kimberly Sparling & Janelle R. Thompson

  2. Institute of Biology, Federal University of Rio de Janeiro (UFRJ), Av. Carlos Chagas Fo. S/N–CCS–IB–BIOMAR–Lab de Microbiologia–BLOCO A (Anexo) A3–sl 102, Cidade Universitária, Rio de Janeiro, 21941-599, RJ, Brazil

    Gizele D. Garcia, Rodrigo L. de Moura & Fabiano L. Thompson

  3. Laboratory of Hydrobiology, Institute of Biology, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil

    Rodolfo Paranhos

  4. Department of Engineering and Environment, Federal University of Paraíba (UFPB), Paraíba, Brazil

    Ronaldo B. Francini-Filho

  5. Centro de Gestão Tecnológica - CT2, Rua Moniz de Aragão, no.360 - Bloco 2 Ilha do Fundão - Cidade Universitária, Rio de Janeiro, 21941-972, RJ, Brazil

    Fabiano L. Thompson

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Table S1

Water quality parameters for Sebastião Gomes (SG) and Parcel dos Abrolhos (PAB) reefs (XLS 23 kb)

Table S2

V6 tags removed using secondary structure alignment and delta G values (XLS 22 kb)

Table S3

RFLP screen of 16S rRNA clone libraries prepared from Mussismilia corals (XLS 22 kb)

Table S4

Taxonomic affiliation of cloned 16S rRNA gene sequences and corresponding V6 tag OTUs (XLS 41 kb)

Table S5

Permutational Analysis of Variance of microbiota structure from Mussismilia corals grouped by species and reef site with data filtered by occurrence of OTUs in multiple coral individuals (XLS 33 kb)

Table S6

Excel file with all OTUs, and abundances, with classification from RDP (XLS 2583 kb)

Fig. S1

Analysis of V6 secondary structure predictions to improve quality control. A) Distribution of ΔG’s for the most stable secondary structure of the 16S rRNA V6 region predicted using the CLC RNA Workbench secondary structure prediction tool (CLC bio USA, Cambridge, MA) with respect to frequency of reads in the current dataset (red) and the V6 reference database at VAMPS (blue). A ΔG value of −4.5 kcal/mol was identified as the minimum ΔG needed to form an acceptable secondary structure. 1.55 % of the reads were removed manually due to misalignment of secondary structure and/or anomalously high delta G values for the V6 stem-loop structure. B) Predicted secondary structures for representative 16S rRNA V6 OTUs. (JPEG 421 kb)

Fig. S2

Maximum likelihood tree of cloned and sequenced 16S rRNA genes from each coral species/reef. 16S rRNA from sequenced isolates were included for comparison (E. coli region from 515 to 1,300 nt). Sequences were clustered into ribotype groups at 97 % identity and a representative sequence was used for phylogenetic analysis. Type strains are indicated for phylogenetic comparison. Bootstrap values >50 % are indicated at branch nodes. Ribotype clusters containing sequences that match 16S V6 tag sequences from this study are highlighted in red and the corresponding V6 tag OTUs are indicated (JPEG 632 kb)

Fig. S3

Rarefaction analysis of each sample based on V6 OTUs generated at 97 % identity indicated that diversity was undersampled despite the deep-sequencing approach. The coral skeleton and sample PMHS2-3 had notably higher richness than other samples while PMBR2-1 and the white plague sample appeared to approach saturation. Rarefaction curves were generated using Mothur v.1.9.0. Abbreviations used: PMBR = M. braziliensis from Parcel dos Abrolhos reef, GMBR = M. braziliensis from Sebastiao Gomes reef, PMHS = M. hispida from Parcel dos Abrolhos reef, PMHA = M. harttii from Parcel dos Abrolhos reef (JPEG 352 kb)

Fig. S4

Identification of populations associated with healthy M. braziliensis. A) Distribution of 15 populations present in n = 6 M. braziliensis. B) The set of OTUs that was only observed in association with the healthy M. braziliensis samples may be enriched in populations that serve as bioindicators for a healthy holobiont. Thirty-six microbial OTUs satisfied the condition of being observed in the majority of healthy M. braziliensis samples (at least four of the six) but not observed in the skeleton or diseased sample. These OTUs may include stable associates of healthy coral tissue that are disrupted during disease. Heat maps indicate frequency of OTU sequences in the dataset. OTU abundances were standardized to 10,000 sequences per sample, subjected to a log(X + 1) transformation followed by addition of 1E-6 to each datapoint to eliminate zeros. Hierarchical clustering of OTUS was carried out in Multi Experiment Viewer (MeV) version 4.6 implementing the Pearson correlation and average linkage method. Taxonomic assignments are based on RDP classifier (bootstraps in brackets) or by match to a cloned 16S rRNA sequence (nucleotide identity given in %) (JPEG 1010 kb)

Fig. S5

Comparison of the distribution of OTUs in 12 healthy Mussismilia corals to a model of neutral community assembly. A) The mean relative abundance of HC-OTUs and the frequency with which the 7,525 HC-OTUs appear among the 12 healthy Mussismilia corals (i.e., prevalence) are plotted for observed data (points) and modeled data (line) based on fitting parameter mN as calculated in Sloan et al. (2006). B) Distribution of R^2 values obtained when fitting 50 simulated communities generated with the fitted parameter mN. The simulated datasets fit the neutral model significantly better than the observed data (p < 0.02); thus, a locally neutral community assembly model can be rejected for our dataset (JPEG 313 kb)

Fig. S6

The average richness of bacterial OTUs (S) in increasing numbers of Mussismilia coral samples was calculated from (i) the total OTU abundance or from OTU abundance in the dataset downsampled without replacement to 583 sequences. Species accumulation was calculated using the species accumulation function in Primer6 with 1,000 permutations considering all coral samples (n = 12) (open symbols) or restricted to M. braziliensis corals only (n = 6) (crossed symbols). A linear relationship was observed between log-transformed estimates of OTUs observed and number of coral samples under all conditions (R^2 > 0.998). Based on this regression, the exponent (z) was 0.82 to 0.85 (JPEG 344 kb)

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Fernando, S.C., Wang, J., Sparling, K. et al. Microbiota of the Major South Atlantic Reef Building Coral Mussismilia . Microb Ecol 69, 267–280 (2015). https://doi.org/10.1007/s00248-014-0474-6

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  • DOI: https://doi.org/10.1007/s00248-014-0474-6

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