Literature DB >> 27845496

Characterization of the microbiota associated to Pecten maximus gonads using 454-pyrosequencing.

Aide Lasa1, Alex Mira2, Anny Camelo-Castillo2, Pedro Belda-Ferre2, Jesús L Romalde1.   

Abstract

A next-generation sequencing (NGS) approach was used to study the microbiota associated to Pecten maximus broodstock, applying pyrosequencing of PCR-amplified V1-V4 16S rRNA gene regions. We analysed the resident bacterial communities in female and male scallop gonads before and after spawning. DNA samples were amplified and quality-filtered reads were assigned to family and genus taxonomic levels using the Ribosomal Database Project classifier. A total of 18,520 sequences were detected, belonging to 13 phyla, including Proteobacteria (55%), Bacteroidetes (11,7%), Firmicutes (3%), Actinobacteria (2%) and Spirochaetes (1,2%), and 110 genera. The major fraction of the sequences detected corresponded to Proteobacteria, Beta- and Gammaprotebacteria being the most abundant classes. The microbiota of P. maximus gonad harbour a wide diversity, however differences on male and female samples were observed, where female gonad samples show a larger number of genera and families. The dominant bacterial genera appeared to be Delftia, Acinetobacter, Hydrotalea, Aquabacterium, Bacillus, Sediminibacterium, Sphingomonas, and Pseudomonas that were present among the four analysed samples. This next generation sequencing technique, applied for the first time in P. maximus (great scallop) gonads was useful for the study of the bacterial communities in this mollusc, unravelling the great bacterial diversity in its microbiota. [Int Microbiol 19(2): 93-99(2016)]. Copyright© by the Spanish Society for Microbiology and Institute for Catalan Studies.

Entities:  

Keywords:  Pecten maximus; aquaculture; gonads microbiota; molluscs pathogens; next-generation sequencing (NGS)

Mesh:

Substances:

Year:  2016        PMID: 27845496     DOI: 10.2436/20.1501.01.267

Source DB:  PubMed          Journal:  Int Microbiol        ISSN: 1139-6709            Impact factor:   2.479


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