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. 2017 Oct 1;6(10):1-7.
doi: 10.1093/gigascience/gix077.

The sponge microbiome project

Affiliations

The sponge microbiome project

Lucas Moitinho-Silva et al. Gigascience. .

Erratum in

  • Erratum to: The sponge microbiome project.
    Moitinho-Silva L, Nielsen S, Amir A, Gonzalez A, Ackermann GL, Cerrano C, Astudillo-Garcia C, Easson C, Sipkema D, Liu F, Steinert G, Kotoulas G, McCormack GP, Feng G, Bell JJ, Vicente J, Björk JR, Montoya JM, Olson JB, Reveillaud J, Steindler L, Pineda MC, Marra MV, Ilan M, Taylor MW, Polymenakou P, Erwin PM, Schupp PJ, Simister RL, Knight R, Thacker RW, Costa R, Hill RT, Lopez-Legentil S, Dailianis T, Ravasi T, Hentschel U, Li Z, Webster NS, Thomas T. Moitinho-Silva L, et al. Gigascience. 2018 Dec 1;7(12):giy145. doi: 10.1093/gigascience/giy145. Gigascience. 2018. PMID: 30521034 Free PMC article. No abstract available.

Abstract

Marine sponges (phylum Porifera) are a diverse, phylogenetically deep-branching clade known for forming intimate partnerships with complex communities of microorganisms. To date, 16S rRNA gene sequencing studies have largely utilised different extraction and amplification methodologies to target the microbial communities of a limited number of sponge species, severely limiting comparative analyses of sponge microbial diversity and structure. Here, we provide an extensive and standardised dataset that will facilitate sponge microbiome comparisons across large spatial, temporal, and environmental scales. Samples from marine sponges (n = 3569 specimens), seawater (n = 370), marine sediments (n = 65) and other environments (n = 29) were collected from different locations across the globe. This dataset incorporates at least 268 different sponge species, including several yet unidentified taxa. The V4 region of the 16S rRNA gene was amplified and sequenced from extracted DNA using standardised procedures. Raw sequences (total of 1.1 billion sequences) were processed and clustered with (i) a standard protocol using QIIME closed-reference picking resulting in 39 543 operational taxonomic units (OTU) at 97% sequence identity, (ii) a de novo clustering using Mothur resulting in 518 246 OTUs, and (iii) a new high-resolution Deblur protocol resulting in 83 908 unique bacterial sequences. Abundance tables, representative sequences, taxonomic classifications, and metadata are provided. This dataset represents a comprehensive resource of sponge-associated microbial communities based on 16S rRNA gene sequences that can be used to address overarching hypotheses regarding host-associated prokaryotes, including host specificity, convergent evolution, environmental drivers of microbiome structure, and the sponge-associated rare biosphere.

Keywords: 16S rRNA gene; archaea; bacteria; marine sponges; microbial diversity; microbiome; symbiosis.

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Figures

Figure 1:
Figure 1:
Global sample collection sites. Bubbles indicate collection sites of (A) marine sponges, (B) seawater, and (C) marine sediment samples. Bubble sizes are proportional to number of samples as indicated.
Figure 2:
Figure 2:
Microbial taxonomic profile of marine sponge samples processed with Mothur. (A) SILVA, (B) Greengenes, and (C) RDP taxonomies are shown. OTU sequence counts were grouped according to phylum and class. Taxa with relative abundances ≤0.5% were grouped as “others.” Classes with relative abundances >1% are shown in the legend (phylum “;” class). Relative abundances are represented on the x-axes.
Figure 3:
Figure 3:
Unweighted UniFrac Principal Coordinates Analysis (PCA) of samples from sponges (“animal-associated habitat”), kelp forest, and ocean water. Samples were rarefying to 10 000 sequences per sample. A movie showing the PCA plot in 3D is provided in the supporting information.
Figure 4:
Figure 4:
Output of the enrichment analysis through the online server www.spongeemp.com. Top line shows taxonomic assignment for the user-submitted sequence in the second line. Pie charts below show the total number of samples (right) and the number of samples where the submitted sequence is present (left) based on the scientific names of the host, followed by the significantly enriched host names containing the submitted sequence (using either presence/absence binomial test or relative frequency–based ranksum test). At the bottom, fields can be opened to show results of the enrichment analyses for other metadata types (e.g., country).

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