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Marine and Freshwater Research Marine and Freshwater Research Society
Advances in the aquatic sciences
RESEARCH ARTICLE

Host-associated microbiota of yellow stingrays (Urobatis jamaicensis) is shaped by their environment and life history

Lee J. Pinnell https://orcid.org/0000-0002-6238-3313 A , Francis J. Oliaro A and William Van Bonn https://orcid.org/0000-0001-5309-3595 A B
+ Author Affiliations
- Author Affiliations

A A. Watson Armour III Center for Animal Health and Welfare, John G. Shedd Aquarium, 1200 S Lake Shore Drive, Chicago, IL 60605, USA.

B Corresponding author. Email: bvanbonn@sheddaquarium.org

Marine and Freshwater Research 72(5) 658-667 https://doi.org/10.1071/MF20107
Submitted: 10 April 2020  Accepted: 23 September 2020   Published: 19 November 2020

Abstract

Insights gained from the unique scientific opportunities presented by public zoos and aquaria can help inform conservation and management decisions for wild populations and provide a rationale for decisions on exhibit design and maintenance for managed populations. This study has shown the diversity and composition of the microbiota associated with three different populations of yellow stingrays (Urobatis jamaicensis); wild rays (W), aquarium-housed rays originally caught in the wild (WC), and aquarium-born rays (AB). The microbial communities of wild rays were more diverse and had a different structure than did both WC and AB ray populations. Importantly, differences also existed between the two populations of aquarium-housed rays. There were significantly lower abundances of Bacteroidetes in skin-associated communities from WC rays v. AB rays, whereas there were significantly higher abundances of Vibrionaceae in cloaca-associated communities of WC rays v. those born in the aquarium. Additionally, the diversity of cloacal microbial communities was significantly lower in WC rays than aquarium-born rays. Findings from this study have demonstrated that a move from a wild to managed environment alters the host–microbe relationship in yellow stingrays and have lent support towards the refinement of aquarium disinfection strategies and expansion of cooperative breeding programs in the zoo and aquarium community.

Keywords: bacteria, ecology, elasmobranchs, microbiology.


References

Alfano, N., Courtiol, A., Vielgrader, H., Timms, P., Roca, A. L., and Greenwood, A. D. (2015). Variation in koala microbiomes within and between individuals: effect of body region and captivity status. Scientific Reports 5, 10189.
Variation in koala microbiomes within and between individuals: effect of body region and captivity status.Crossref | GoogleScholarGoogle Scholar | 25960327PubMed |

Allison, S. D., and Martiny, J. B. H. (2008). Resistance, resilience, and redundancy in microbial communities. Proceedings of the National Academy of Sciences of the United States of America 105, 11512–11519.
Resistance, resilience, and redundancy in microbial communities.Crossref | GoogleScholarGoogle Scholar | 18695234PubMed |

Bagchi, S., Vlaeminck, S. E., Sauder, L. A., Mosquera, M., Neufeld, J. D., and Boon, N. (2014). Temporal and spatial stability of ammonia-oxidizing Archaea and Bacteria in aquarium biofilters. PLoS One 9, e113515.
Temporal and spatial stability of ammonia-oxidizing Archaea and Bacteria in aquarium biofilters.Crossref | GoogleScholarGoogle Scholar | 25479061PubMed |

Benjamini, Y., and Hochberg, Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society – B, Methodological 57, 289–300.
Controlling the false discovery rate: a practical and powerful approach to multiple testing.Crossref | GoogleScholarGoogle Scholar |

Bolyen, E., Rideout, J. R., Dillon, M. R., Bokulich, N. A., Abnet, C. C., Al-Ghalith, G. A., Alexander, H., Alm, E. J., Arumugam, M., Asnicar, F., Bai, Y., Bisanz, J. E., Bittinger, K., Brejnrod, A., Brislawn, C. J., Brown, C. T., Callahan, B. J., Caraballo-Rodríguez, A. M., Chase, J., Cope, E. K., Da Silva, R., Diener, C., Dorrestein, P. C., Douglas, G. M., Durall, D. M., Duvallet, C., Edwardson, C. F., Ernst, M., Estaki, M., Fouquier, J., Gauglitz, J. M., Gibbons, S. M., Gibson, D. L., Gonzalez, A., Gorlick, K., Guo, J., Hillmann, B., Holmes, S., Holste, H., Huttenhower, C., Huttley, G. A., Janssen, S., Jarmusch, A. K., Jiang, L., Kaehler, B. D., Kang, K. B., Keefe, C. R., Keim, P., Kelley, S. T., Knights, D., Koester, I., Kosciolek, T., Kreps, J., Langille, M. G. I., Lee, J., Ley, R., Liu, Y. X., Loftfield, E., Lozupone, C., Maher, M., Marotz, C., Martin, B. D., McDonald, D., McIver, L. J., Melnik, A. V., Metcalf, J. L., Morgan, S. C., Morton, J. T., Naimey, A. T., Navas-Molina, J. A., Nothias, L. F., Orchanian, S. B., Pearson, T., Peoples, S. L., Petras, D., Preuss, M. L., Pruesse, E., Rasmussen, L. B., Rivers, A., Robeson, M. S., Rosenthal, P., Segata, N., Shaffer, M., Shiffer, A., Sinha, R., Song, S. J., Spear, J. R., Swafford, A. D., Thompson, L. R., Torres, P. J., Trinh, P., Tripathi, A., Turnbaugh, P. J., Ul-Hasan, S., van der Hooft, J. J. J., Vargas, F., Vázquez-Baeza, Y., Vogtmann, E., von Hippel, M., Walters, W., Wan, Y., Wang, M., Warren, J., Weber, K. C., Williamson, C. H. D., Willis, A. D., Xu, Z. Z., Zaneveld, J. R., Zhang, Y., Zhu, Q., Knight, R., and Caporaso, J. G. (2019). Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2 Nature Biotechnology 37, 852–857.
Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2Crossref | GoogleScholarGoogle Scholar | 31341288PubMed |

Bik, H. M., Alexiev, A., Aulakh, S. K., Bharadwaj, L., Flanagan, J., Haggerty, J. M., Hird, S. M., Jospin, G., Lang, J. M., Sauder, L. A., Neufeld, J. D., Shaver, A., Sethi, A., Eisen, J. A., and Coil, D. A. (2019). Microbial community succession and nutrient cycling responses following perturbations of experimental saltwater aquaria. MSphere 4, e00043-19.
Microbial community succession and nutrient cycling responses following perturbations of experimental saltwater aquaria.Crossref | GoogleScholarGoogle Scholar | 30787117PubMed |

Buckley, K. A., Crook, D. A., Pillans, R. D., Smith, L., and Kyne, P. M. (2018). Sustainability of threatened species displayed in public aquaria, with a case study of Australian sharks and rays. Reviews in Fish Biology and Fisheries 28, 137–151.
Sustainability of threatened species displayed in public aquaria, with a case study of Australian sharks and rays.Crossref | GoogleScholarGoogle Scholar |

Callahan, B. J., McMurdie, P. J., Rosen, M. J., Han, A. W., Johnson, A. J., and Holmes, S. P. (2016). DADA2: high-resolution sample inference from Illumina amplicon data. Nature Methods 13, 581–583.
DADA2: high-resolution sample inference from Illumina amplicon data.Crossref | GoogleScholarGoogle Scholar | 27214047PubMed |

Caporaso, J. G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F. D., Costello, E. K., Fierer, N., Pena, A. G., Goodrich, J. K., Gordon, J. I., Huttley, G. A., Kelley, S. T., Knights, D., Koenig, J. E., Ley, R. E., Lozupone, C. A., McDonald, D., Muegge, B. D., Pirrung, M., Reeder, J., Sevinsky, J. R., Turnbaugh, P. J., Walters, W. A., Widmann, J., Yatsunenko, T., Zaneveld, J., and Knight, R. (2010). QIIME allows analysis of high-throughput community sequencing data. Nature Methods 7, 335–336.
QIIME allows analysis of high-throughput community sequencing data.Crossref | GoogleScholarGoogle Scholar | 20383131PubMed |

Caporaso J. G. Lauber C. L. Walters W. A. Berg-Lyons D. Lozupone C. A. Turnbaugh P. J. Fierer N. Knight R. (2011). Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample Proceedings of the National Academy of Sciences 108, 4516–4522.
Global patterns of 16S rRNA diversity at a depth of millions of sequences per sampleCrossref | GoogleScholarGoogle Scholar |

Caporaso, J. G., Lauber, C. L., Walters, W. A., Berg-Lyons, D., Huntley, J., Fierer, N., Owens, S. M., Betley, J., Fraser, L., Bauer, M., Gormley, N., Gilbert, J. A., Smith, G., and Knight, R. (2012). Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. The ISME Journal 6, 1621–1624.
Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms.Crossref | GoogleScholarGoogle Scholar | 22402401PubMed |

Carda-Diéguez, M., Ghai, R., Rodríguez-Valera, F., and Amaro, C. (2017). Wild eel microbiome reveals that skin mucus of fish could be a natural niche for aquatic mucosal pathogen evolution. Microbiome 5, 162.
Wild eel microbiome reveals that skin mucus of fish could be a natural niche for aquatic mucosal pathogen evolution.Crossref | GoogleScholarGoogle Scholar | 29268781PubMed |

Cardona, C., Lax, S., Larsen, P., Stephens, B., Hampton-Marcell, J., Edwardson, C. F., Henry, C., Van Bonn, B., and Gilbert, J. A. (2018). Environmental sources of bacteria differentially influence host-associated microbial dynamics. mSystems 3, e00052-18.
Environmental sources of bacteria differentially influence host-associated microbial dynamics.Crossref | GoogleScholarGoogle Scholar | 29854953PubMed |

Chen, J., Bittinger, K., Charlson, E. S., Hoffmann, C., Lewis, J., Wu, G. D., Collman, R. G., Bushman, F. D., and Li, H. (2012). Associating microbiome composition with environmental covariates using generalized UniFrac distances. Bioinformatics 28, 2106–2113.
Associating microbiome composition with environmental covariates using generalized UniFrac distances.Crossref | GoogleScholarGoogle Scholar | 22711789PubMed |

Clayton, J. B., Vangay, P., Huang, H., Ward, T., Hillmann, B. M., Al-Ghalith, G. A., Travis, D. A., Long, H. T., Tuan, B. V., Minh, V. V., Cabana, F., Nadler, T., Toddes, B., Murphy, T., Glander, K. E., Johnson, T. J., and Knights, D. (2016). Captivity humanizes the primate microbiome. Proceedings of the National Academy of Sciences of the United States of America 113, 10376.
Captivity humanizes the primate microbiome.Crossref | GoogleScholarGoogle Scholar | 27573830PubMed |

Doane, M. P., Haggerty, J. M., Kacev, D., Papudeshi, B., and Dinsdale, E. A. (2017). The skin microbiome of the common thresher shark (Alopias vulpinus) has low taxonomic and gene function β-diversity. Environmental Microbiology Reports 9, 357–373.
The skin microbiome of the common thresher shark (Alopias vulpinus) has low taxonomic and gene function β-diversity.Crossref | GoogleScholarGoogle Scholar | 28418094PubMed |

Gibson, K. M., Nguyen, B. N., Neumann, L. M., Miller, M., Buss, P., Daniels, S., Ahn, M. J., Crandall, K. A., and Pukazhenthi, B. (2019). Gut microbiome differences between wild and captive black rhinoceros: implications for rhino health. Scientific Reports 9, 7570.
Gut microbiome differences between wild and captive black rhinoceros: implications for rhino health.Crossref | GoogleScholarGoogle Scholar | 31138833PubMed |

Givens, C. E., Ransom, B., Bano, N., and Hollibaugh, J. T. (2015). Comparison of the gut microbiomes of 12 bony fish and 3 shark species. Marine Ecology Progress Series 518, 209–223.
Comparison of the gut microbiomes of 12 bony fish and 3 shark species.Crossref | GoogleScholarGoogle Scholar |

Janse, M., Firchau, B., and Mohan, P. J. (2004). Elasmobranch nutrition, food handling, and feeding techniques. In ‘The Elasmobranch Husbandry Manual: Captive Care of Sharks, Rays and their Relatives’. (Eds M. Smith, D. Warmolts, D. Thoney, and R. Hueter.) pp. 183–200. (Ohio Biological Survey, Inc.: Columbus, OH, USA)

Ji, P., Parks, J., Edwards, M. A., and Pruden, A. (2015). Impact of water chemistry, pipe material and stagnation on the building plumbing microbiome. PLoS One 10, e0141087.
Impact of water chemistry, pipe material and stagnation on the building plumbing microbiome.Crossref | GoogleScholarGoogle Scholar | 26659441PubMed |

Jones, J., DiBattista, J. D., Stat, M., Bunce, M., Boyce, M. C., Fairclough, D. V., Travers, M. J., and Huggett, M. J. (2018). The microbiome of the gastrointestinal tract of a range-shifting marine herbivorous fish. Frontiers in Microbiology 9, 2000.
The microbiome of the gastrointestinal tract of a range-shifting marine herbivorous fish.Crossref | GoogleScholarGoogle Scholar | 30210475PubMed |

Kang, H., Kim, H., Joung, Y., and Joh, K. (2017). Lewinella maritima sp. nov., and Lewinella lacunae sp. nov., novel bacteria from marine environments. International Journal of Systematic and Evolutionary Microbiology 67, 3603–3609.
Lewinella maritima sp. nov., and Lewinella lacunae sp. nov., novel bacteria from marine environments.Crossref | GoogleScholarGoogle Scholar | 28875904PubMed |

Kearns, P., Bowen, J., and Tlusty, M. (2017). The skin microbiome of cow-nose rays (Rhinoptera bonasus) in an aquarium touch-tank exhibit. Zoo Biology 36, 226–230.
The skin microbiome of cow-nose rays (Rhinoptera bonasus) in an aquarium touch-tank exhibit.Crossref | GoogleScholarGoogle Scholar | 28544080PubMed |

Kim, Y., Van Bonn, W., Aw, T. G., and Rose, J. B. (2017). Aquarium viromes: viromes of human-managed aquatic systems. Frontiers in Microbiology 8, 1231.
Aquarium viromes: viromes of human-managed aquatic systems.Crossref | GoogleScholarGoogle Scholar | 28713358PubMed |

Lavoie, C., Courcelle, M., Redivo, B., and Derome, N. (2018). Structural and compositional mismatch between captive and wild Atlantic salmon (Salmo salar) parrs’ gut microbiota highlights the relevance of integrating molecular ecology for management and conservation methods. Evolutionary Applications 11, 1671–1685.
Structural and compositional mismatch between captive and wild Atlantic salmon (Salmo salar) parrs’ gut microbiota highlights the relevance of integrating molecular ecology for management and conservation methods.Crossref | GoogleScholarGoogle Scholar | 30344635PubMed |

Lozupone, C., Lladser, M. E., Knights, D., Stombaugh, J., and Knight, R. (2011). UniFrac: an effective distance metric for microbial community comparison. The ISME Journal 5, 169–172.
UniFrac: an effective distance metric for microbial community comparison.Crossref | GoogleScholarGoogle Scholar | 20827291PubMed |

McIlroy, S. J., and Nielsen, P. H. (2014). The Family Saprospiraceae. In ‘The Prokaryotes: Other Major Lineages of Bacteria and the Archaea’. (Eds E. Rosenberg, E. F. DeLong, S. Lory, E. Stackebrandt, and F. Thompson.) pp. 863–889. (Springer: Berlin, Germany.)

McMurdie, P. J., and Holmes, S. (2013). phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS One 8, e61217.
phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data.Crossref | GoogleScholarGoogle Scholar | 23630581PubMed |

Murtagh, F., and Legendre, P. (2014). Ward’s hierarchical agglomerative clustering method: which algorithms implement Ward’s criterion? Journal of Classification 31, 274–295.
Ward’s hierarchical agglomerative clustering method: which algorithms implement Ward’s criterion?Crossref | GoogleScholarGoogle Scholar |

Mylniczenko, N. D., Harris, B., Wilborn, R. E., and Young, F. A. (2007). Blood culture results from healthy captive and free-ranging elasmobranchs. Journal of Aquatic Animal Health 19, 159–167.
Blood culture results from healthy captive and free-ranging elasmobranchs.Crossref | GoogleScholarGoogle Scholar | 18201057PubMed |

Oh, H.-M., Lee, K., and Cho, J.-C. (2009). Lewinella antarctica sp. nov., a marine bacterium isolated from Antarctic seawater. International Journal of Systematic and Evolutionary Microbiology 59, 65–68.
Lewinella antarctica sp. nov., a marine bacterium isolated from Antarctic seawater.Crossref | GoogleScholarGoogle Scholar | 19126725PubMed |

Patin, N. V., Pratte, Z. A., Regensburger, M., Hall, E., Gilde, K., Dove, A. D. M., and Stewart, F. J. (2018). Microbiome dynamics in a large artificial seawater aquarium. Applied and Environmental Microbiology 84, e00179-18.
Microbiome dynamics in a large artificial seawater aquarium.Crossref | GoogleScholarGoogle Scholar | 29523545PubMed |

Roura, Á., Doyle, S. R., Nande, M., and Strugnell, J. M. (2017). You are what you eat: a genomic nalysis of the gut microbiome of captive and wild Octopus vulgaris paralarvae and their zooplankton prey. Frontiers in Physiology 8, 362.
You are what you eat: a genomic nalysis of the gut microbiome of captive and wild Octopus vulgaris paralarvae and their zooplankton prey.Crossref | GoogleScholarGoogle Scholar | 28620315PubMed |

Smith, K. F., Schmidt, V., Rosen, G. E., and Amaral-Zettler, L. (2012). Microbial diversity and potential pathogens in ornamental fish aquarium water. PLoS One 7, e39971.
Microbial diversity and potential pathogens in ornamental fish aquarium water.Crossref | GoogleScholarGoogle Scholar | 22970112PubMed |

Stephens, B. (2016). What have we learned about the microbiomes of indoor environments? mSystems 1, e00083-16.
What have we learned about the microbiomes of indoor environments?Crossref | GoogleScholarGoogle Scholar | 27822547PubMed |

Van Bonn, W., LaPointe, A., Gibbons, S. M., Frazier, A., Hampton-Marcell, J., and Gilbert, J. (2015). Aquarium microbiome response to ninety-percent system water change: clues to microbiome management. Zoo Biology 34, 360–367.
Aquarium microbiome response to ninety-percent system water change: clues to microbiome management.Crossref | GoogleScholarGoogle Scholar | 26031788PubMed |

Walters, W., Hyde, E. R., Berg-Lyons, D., Ackermann, G., Humphrey, G., Parada, A., Gilbert, J. A., Jansson, J. K., Caporaso, J. G., Fuhrman, J. A., Apprill, A., and Knight, R. (2016). Improved bacterial 16S rRNA gene (V4 and V4–5) and fungal internal transcribed spacer marker gene primers for microbial community surveys. mSystems 1, e00009-15.
Improved bacterial 16S rRNA gene (V4 and V4–5) and fungal internal transcribed spacer marker gene primers for microbial community surveys.Crossref | GoogleScholarGoogle Scholar | 27822518PubMed |

West, A. G., Waite, D. W., Deines, P., Bourne, D. G., Digby, A., McKenzie, V. J., and Taylor, M. W. (2019). The microbiome in threatened species conservation. Biological Conservation 229, 85–98.
The microbiome in threatened species conservation.Crossref | GoogleScholarGoogle Scholar |

Woodhams, D. C., Bletz, M. C., Becker, C. G., Bender, H. A., Buitrago-Rosas, D., Diebboll, H., Huynh, R., Kearns, P. J., Kueneman, J., Kurosawa, E., LaBumbard, B. C., Lyons, C., McNally, K., Schliep, K., Shankar, N., Tokash-Peters, A. G., Vences, M., and Whetstone, R. (2020). Host-associated microbiomes are predicted by immune system complexity and climate. Genome Biology 21, 23.
Host-associated microbiomes are predicted by immune system complexity and climate.Crossref | GoogleScholarGoogle Scholar | 32014020PubMed |