The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.
Bacteria Associated with Mucus and Tissues of the Coral Oculina patagonica in Summer and Winter
Abstract
The relative abundance of bacteria in the mucus and crushed tissue of the Mediterranean coral Oculina patagonica was determined by analyses of the 16S rRNA genes of isolated colonies and from a 16S rRNA clone library of extracted DNA. By SYBR gold staining, the numbers of bacteria in mucus and tissue samples were 6.2 × 10 7 and 8.3 × 10 8 /cm 2 of coral surface, respectively, 99.8% of which failed to produce colonies on Marine Agar. From analysis of mucus DNA, the most-abundant bacterium was Vibrio splendidus , representing 68% and 50% of the clones from the winter and summer, respectively. After removal of mucus from coral by centrifugation, analyses of DNA from the crushed tissue revealed a large diversity of bacteria, with Vibrio species representing less than 5% of the clones. The most-abundant culturable bacteria were a Pseudomonas sp. (8 to 14%) and two different α-proteobacteria (6 to 18%). Out of a total 1,088 16S rRNA genes sequenced, 400 different operational taxonomic units were identified (>99.5% identity). Of these, 295 were novel (<99% identical to any sequences in the GenBank database). This study provides a comprehensive database for future examinations of changes in the bacterial community during bleaching events.
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Metadata
- Authors
- Koren, O., & Rosenberg, E.
- Venue
- Applied and Environmental Microbiology
- Publisher
- American Society for Microbiology
- Published
- 2006-08
- Volume
- 72
- Issue
- 8
- Pages
- 5254-5259
- ISSN
- 0099-2240 (ISSN-L)
- 1098-5336
- OpenAlex
- W2136811216
- Cited by
- 264
- References
- 21
- FWCI
- 13.49
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
