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Uncovering the hidden marine sponge microbiome by applying a multi-primer approach

Marine sponges (phylum Porifera) are hosts to microorganisms that make up to 40–60% of the mesohyl volume. The challenge is to characterise this microbial diversity more comprehensively. To accomplish this, a new method was for the first time proposed to obtain sequence coverage of all the variable...

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Detalles Bibliográficos
Autores principales: Yang, Qi, Franco, Christopher M. M., Zhang, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6470215/
https://www.ncbi.nlm.nih.gov/pubmed/30996336
http://dx.doi.org/10.1038/s41598-019-42694-w
Descripción
Sumario:Marine sponges (phylum Porifera) are hosts to microorganisms that make up to 40–60% of the mesohyl volume. The challenge is to characterise this microbial diversity more comprehensively. To accomplish this, a new method was for the first time proposed to obtain sequence coverage of all the variable regions of the 16S rRNA gene to analyze the amplicon-based microbiomes of four representative sponge species belonging to different orders. The five primer sets targeting nine variable regions of the 16S rRNA gene revealed a significant increase in microbiome coverage of 29.5% of phylum level OTUs and 35.5% class level OTUs compared to the community revealed by the commonly used V4 region-specific primer set alone. Among the resulting OTUs, 52.6% and 61.3% were unaffiliated, including candidate OTUs, at the phylum and class levels, respectively, which demonstrated a substantially superior performance in uncovering taxonomic ‘blind spots’. Overall, a more complete sponge microbiome profile was achieved by this multi-primer approach, given the significant improvement of microbial taxonomic coverage and the enhanced capacity to uncover novel microbial taxa. This multi-primer approach represents a fundamental and practical change from the conventional single primer set amplicon-based microbiome approach, and can be broadly applicable to other microbiome studies.