The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
Topographical Mapping of the Rainbow Trout (Oncorhynchus mykiss) Microbiome Reveals a Diverse Bacterial Community with Antifungal Properties in the Skin
Open accessAbstract
The mucosal surfaces of wild and farmed aquatic vertebrates face the threat of many aquatic pathogens, including fungi. These surfaces are colonized by diverse symbiotic bacterial communities that may contribute to fight infection. Whereas the gut microbiome of teleosts has been extensively studied using pyrosequencing, this tool has rarely been employed to study the compositions of the bacterial communities present on other teleost mucosal surfaces. Here we provide a topographical map of the mucosal microbiome of an aquatic vertebrate, the rainbow trout ( Oncorhynchus mykiss ). Using 16S rRNA pyrosequencing, we revealed novel bacterial diversity at each of the five body sites sampled and showed that body site is a strong predictor of community composition. The skin exhibited the highest diversity, followed by the olfactory organ, gills, and gut. Flectobacillus was highly represented within skin and gill communities. Principal coordinate analysis and plots revealed clustering of external sites apart from internal sites. A highly diverse community was present within the epithelium, as demonstrated by confocal microscopy and pyrosequencing. Using in vitro assays, we demonstrated that two Arthrobacter sp. skin isolates, a Psychrobacter sp. strain, and a combined skin aerobic bacterial sample inhibit the growth of Saprolegnia australis and Mucor hiemalis , two important aquatic fungal pathogens. These results underscore the importance of symbiotic bacterial communities of fish and their potential role for the control of aquatic fungal diseases.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Structure, function and diversity of the healthy human microbiome
The Human Microbiome Project Consortium (2012) · Nature · doi:10.1038/nature11234 · Cited by 11,726
Greengenes, a Chimera-Checked 16S rRNA Gene Database and Workbench Compatible with ARB
DeSantis, T. Z., Hugenholtz, P., Larsen, N., Rojas, M., Brodie, E. L., Keller, K., Huber, T., Dalevi, D., Hu, P., & Andersen, G. L. (2006) · Applied and Environmental Microbiology · doi:10.1128/aem.03006-05 · Cited by 10,891
Bacterial Community Variation in Human Body Habitats Across Space and Time
Costello, E. K., Lauber, C. L., Hamady, M., Fierer, N., Gordon, J. I., & Knight, R. (2009) · Science · doi:10.1126/science.1177486 · Cited by 3,231
Reciprocal interactions of the intestinal microbiota and immune system
Maynard, C. L., Elson, C. O., Hatton, R. D., & Weaver, C. T. (2012) · Nature · doi:10.1038/nature11551 · Cited by 1,598
Sellon, R. K., Tonkonogy, S., Schultz, M., Dieleman, L. A., Grenther, W., Balish, E., Rennick, D. M., & Sartor, R. B. (1998) · Infection and Immunity · doi:10.1128/iai.66.11.5224-5231.1998 · Cited by 1,483
Role of gastrointestinal microbiota in fish
Nayak, S. K. (2010) · Aquaculture Research · doi:10.1111/j.1365-2109.2010.02546.x · Cited by 1,073 · cited 1×
“Arthrobacter has been previously identified as a member of the fish microbiota (69, 70, 71).”
BackgroundAnalysis of the lung microbiome in the “healthy” smoker and in COPD.
Erb-Downward, J. R., Thompson, D. L., Han, M. K., Freeman, C. M., McCloskey, L., Schmidt, L. A., Young, V. B., Toews, G. B., Curtis, J. L., Sundaram, B., et al. (2011) · PLoS ONE · doi:10.1371/journal.pone.0016384 · Cited by 973
Koren, O., Knights, D., Gonzalez, A., Waldron, L., Segata, N., Knight, R., Huttenhower, C., & Ley, R. E. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002863 · Cited by 508 · cited 1×
“ratios of major groups of bacteria (15).”
The microbiome extends to subepidermal compartments of normal skin
Nakatsuji, T., Chiang, H.-I., Jiang, S. B., Nagarajan, H., Zengler, K., & Gallo, R. L. (2013) · Nature Communications · doi:10.1038/ncomms2441 · Cited by 450 · cited 1×
“We found a strikingly diverse bacterial community living inside the epithelium, a finding that is in concordance with mammalian studies showing that skin commensals live deep in the dermal layers of the skin (64).”
ResultCompartmentalized and systemic control of tissue immunity by commensals
Belkaid, Y., & Naik, S. (2013) · Nature Immunology · doi:10.1038/ni.2604 · Cited by 382
Cited by
Xu, Z., Takizawa, F., Parra, D., Gómez, D., von Gersdorff Jørgensen, L., LaPatra, S. E., & Sunyer, J. O. (2016) · Nature Communications · doi:10.1038/ncomms10728 · Cited by 286
Immunoglobulins, Mucosal Immunity and Vaccination in Teleost Fish
Yu, Y., Wang, Q., Huang, Z., Ding, L., & Xu, Z. (2020) · Frontiers in Immunology · doi:10.3389/fimmu.2020.567941 · Cited by 284
Legrand, T. P. R. A., Wynne, J. W., Weyrich, L. S., & Oxley, A. P. A. (2020) · Reviews in Aquaculture · doi:10.1111/raq.12375 · Cited by 265
Ikeda-Ohtsubo, W., Brugman, S., Warden, C. H., Rebel, J. M. J., Folkerts, G., & Pieterse, C. M. J. (2018) · Frontiers in Nutrition · doi:10.3389/fnut.2018.00090 · Cited by 115
Metadata
- Authors
- Lowrey, L., Woodhams, D. C., Tacchi, L., & Salinas, I.
- Venue
- Applied and Environmental Microbiology
- Publisher
- American Society for Microbiology
- Published
- 2015-10
- Volume
- 81
- Issue
- 19
- Pages
- 6915-6925
- ISSN
- 0099-2240 (ISSN-L)
- 1098-5336
- OpenAlex
- W2112421313
- Cited by
- 276
- References
- 10
- FWCI
- 8.52
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Topographical Mapping of the Rainbow Trout (Oncorhynchus mykiss) Microbiome Reveals a Diverse Bacterial Community with Antifungal Properties in the Skin. https://app.cochat.ai/papers/10.1128/aem.01826-15
- The paper
- Lowrey, L., Woodhams, D. C., Tacchi, L., & Salinas, I. (2015). Topographical Mapping of the Rainbow Trout (Oncorhynchus mykiss) Microbiome Reveals a Diverse Bacterial Community with Antifungal Properties in the Skin. Applied and Environmental Microbiology. https://doi.org/10.1128/aem.01826-15
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
