The skin microbiome of cow-nose rays (Rhinoptera bonasus) in an aquarium touch-tank exhibit

Patrick J Kearns Corresp., 1 , Jennifer L Bowen 1 , Michael F Tlusty 2, 3

1 Biology Department, University of Massachusetts Boston, Boston, Massachusetts, USA 2 John H. Prescott Marine Lab, Anderson Cabot Center for Ocean Life, New England Aquarium, Boston, MA, USA 3 School for the Environment, University of Massachusetts Boston, Boston, MA, USA

Corresponding Author: Patrick J Kearns Email address: [email protected]

Public aquarium exhibits offer numerous educational opportunities for visitors while touch tank exhibits offer guests the ability to directly interact with marine life. However, despite the popularity of these exhibits, the effect of human interactions on the host-associated microbiome or the habitat microbiome remains unclear. Microbial communities, both host- associated and habitat associated can have great implications for host health and habitat function. To better understand the link between human interactions and the microbiome of a touch tank we used high-throughput sequencing of the 16S rRNA gene to analyze the microbial community on the dorsal and ventral surfaces of cow-nose rays (Rhinoptera bonasus) as well as its environment in a frequently visited touch tank exhibit at the New England Aquarium. Our analyses revealed a distinct microbial community associated with the skin of the ray that had lower diversity than the surrounding habitat. The ray skin was dominated by three orders: Burkholderiales (~55%), Flavobacteriales (~19%) and Pseudomonadales (~12%), suggesting a potentially important role of these taxa in ray health. Further, there was no difference between dorsal and ventral surface of the ray in terms of microbial composition or diversity, and a very low presence of common human- associated microbial taxa (<1.5%). Our results suggest that human contact has a minimal effect on the skin and habitat microbiome of the cow-nose ray and that the ray skin harbors a distinct and lower diversity microbial community than its environment.

PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2341v1 | CC BY 4.0 Open Access | rec: 5 Aug 2016, publ: 5 Aug 2016 1 The skin microbiome of cow-nose rays (Rhinoptera bonasus) in an aquarium touch-tank 2 exhibit

3

4 Patrick J. Kearns1, Jennifer L. Bowen1†, and Michael F. Tlusty2,3

5 1. Biology Department, University of Massachusetts Boston, Boston, MA 02125 USA. 6 2. John H. Prescott Marine Lab, Anderson Cabot Center for Ocean Life, New England 7 Aquarium, Boston, MA 02110. 8 3. School for the Environment, University of Massachusetts Boston, Boston, MA 02125.

9 † Current address: Department of Marine and Environmental Science, Northeastern University, 430

10 Nahant Road, Nahant, MA 01908, USA.

11

12 Correspondence and request for materials should be addressed to MFT ([email protected]).

13 Abstract

14 Public aquarium exhibits offer numerous educational opportunities for visitors while touch tank 15 exhibits offer guests the ability to directly interact with marine life. However, despite the 16 popularity of these exhibits, the effect of human interactions on the host-associated microbiome 17 or the habitat microbiome remains unclear. Microbial communities, both host-associated and 18 habitat associated can have great implications for host health and habitat function. To better 19 understand the link between human interactions and the microbiome of a touch tank we used 20 high-throughput sequencing of the 16S rRNA gene to analyze the microbial community on the 21 dorsal and ventral surfaces of cow-nose rays (Rhinoptera bonasus) as well as its environment in 22 a frequently visited touch tank exhibit at the New England Aquarium. Our analyses revealed a 23 distinct microbial community associated with the skin of the ray that had lower diversity than the 24 surrounding habitat. The ray skin was dominated by three orders: Burkholderiales (~55%), 25 Flavobacteriales (~19%) and Pseudomonadales (~12%), suggesting a potentially important role 26 of these taxa in ray health. Further, there was no difference between dorsal and ventral surface of 27 the ray in terms of microbial composition or diversity, and a very low presence of common 28 human-associated microbial taxa (<1.5%). Our results suggest that human contact has a minimal 29 effect on the skin and habitat microbiome of the cow-nose ray and that the ray skin harbors a 30 distinct and lower diversity microbial community than its environment.

31

32

33 Running head: Ray microbiome

PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2341v1 | CC BY 4.0 Open Access | rec: 5 Aug 2016, publ: 5 Aug 2016 34

35 Introduction

36 In an effort to deepen the connection between visitors and the animals on exhibit, many zoos and 37 aquariums have touch-tanks. These are exhibits where visitors can have direct contact with any 38 number of animals. Many of the touch-tank exhibits in aquariums are themed around 39 elasmobranchs, and are popular because they allow visitors to enter the exhibit and encounter 40 animals they otherwise would likely never touch. These exhibits are important to promote 41 science education within public aquariums because they allow visitors to practice the application 42 of scientific reasoning (Kisiel et al. 2012), as well as engage in lengthier ecology discussions 43 when guided by a trained interpreter (Kopczak et al. 2015).

44 Despite the popularity of touch tanks, there is a paucity of research about animal health in these 45 exhibits. The few studies focusing on elasmobranchs in and associated with touch tanks 46 examined shark growth rates (Payne and Rufo 2012), plasma biochemistry values (Persky et al. 47 2012), goiter onset (Morris et al. 2012), stingray abscess development (Clarke III et al. 2013), 48 behavior (Casamitjana 2004), as well as the human stress response and emotional responses to 49 contact with the animals (Sahrmann et al. 2015). Casamitjana (2004) suggested that touch tank 50 exhibits may be maladaptive to elasmobranchs and other studies reported that abnormalities are 51 occasionally observed (Persky et al. 2012; Morris et al. 2012). Other studies have shown that 52 animals can breed on exhibit, suggesting that basic biological needs are being met (Payne and 53 Rufo 2012). In any exhibit where there is contact between animals and visitors, concern for both 54 animal and visitor health and safety is paramount.

55 One way that visitors may affect aquatic animals in touch tanks is through the addition of novel 56 bacteria that may take up residence on the animal. All animals have a thin biofilm of microbes on 57 their epithelial layer. The microbial communities (microbiome) on the host may provide 58 protection against pathogens and disease and therefore promote animal health and well-being ( 59 Nayak 2010; Cho and Blaser 2012; Russell et al. 2014; Llewellyn et al. 2015). The assumption 60 within animal husbandry is that maintenance of a healthy biofilm (e.g. slime coat maintenance in 61 fish) is a key aspect of proper care of the exhibit animals (Schmidt et al. 2015). Thus, 62 elasmobranch touch-tanks offer a potential challenge to animal husbandry where visitor contact 63 may reduce the functional biofilm of the exhibit animals and potentially introduce novel bacteria 64 that could be harmful to animals on exhibit.

65 To examine if the skin microbiome of exhibit animals is affected by contact with visitors, we 66 characterized the microbial communities on the dorsal and ventral surface of cow-nose rays 67 (Rhinoptera bonasus; hereafter, rays) being held in a touch-tank exhibit at the New England 68 Aquarium. We hypothesized that if human contact had an effect on the ray skin microbiome, the 69 dorsal surface of the rays would be altered and potentially contain a larger proportion of human- 70 associated bacteria compared to the ventral surface, since only the dorsal surface of the rays is in

PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2341v1 | CC BY 4.0 Open Access | rec: 5 Aug 2016, publ: 5 Aug 2016 71 direct contact with human hands. Additionally, we hypothesized that the ray skin microbiome 72 would be conserved among different individuals and would be distinct from the microbial 73 communities found in the exhibit environment. We expected that the rays would harbor a 74 reduced subset of the microbial taxa found in their environment. Our results demonstrate that 75 cow-nose rays have distinct skin microbial communities that are consistent across several 76 animals, and that there is no evidence that the skin microbiome of cow-nose rays in the New 77 England Aquarium are significantly altered by human contact.

78 Methods

79 Sample collection

80 The New England Aquarium touch tank exhibit features a 25,000-gallon tank where visitors can 81 interact with rays and other tank organisms along 40% of the periphery. The Aquarium has 82 nearly 1.3 million visitors per year, and an estimated 50% visit the touch tank. We sampled ray 83 skin microbiomes in the morning, prior to opening the exhibit to visitors, thus the rays had been 84 untouched since the previous evening (14hr untouched). Dorsal and ventral surfaces of cow-nose 85 rays were swabbed for their microbiome during a routine spine clipping procedure that was 86 overseen by veterinary staff at the aquarium in September 2013. Rays (n= 5) were removed from 87 the water, gently swabbed with cotton-tipped applicators on both surfaces (independent 5 cm 88 swaths), clipped, and returned to the water. To document the microbiome of the ray environment, 89 two 1-liter water samples were collected, one at the inflow pipe and one immediately in front of 90 the outflow. Each liter of water was filtered on site through a 0.22 µM SterivexTM filter. We also 91 collected gravel from the tank using a sterile 15-mL centrifuge tube as well as a swab of biofilm 92 growing on the tank wall. All samples were placed into cryovials (swabs and sediment) or 93 whirlpack bags (water filters) and stored on dry ice until they were returned to the lab and stored 94 at -80°C until nucleic acid extraction.

95 DNA extraction and sequencing

96 DNA was extracted from ray skin swabs, sediment, and biofilm samples using the MoBio 97 PowerSoil® DNA total Isolation Kit (Carlsbad, CA USA) following manufacturer’s instructions. 98 Water samples were extracted using the MoBio PowerWater® Total DNA Isolation Kit 99 following the manufacturer’s instructions. DNA extractions were verified on a 1.5% agarose gel 100 stained with ethidium bromide. To assess bacterial community composition, genomic DNA was 101 amplified by polymerase chain reaction in triplicate using universal bacterial primers 515F and 102 806R (Caporaso et al. 2011) following conditions outlined by Caporaso et al. (2011) using 103 Illumina adaptors and 12-bp GoLay barcodes on the reverse primers. Proper product formation 104 was verified with electrophoresis and purified with the Qiagen PCR purification kit (Qiagen, 105 Valencia, CA, USA). Samples were quantified fluorometrically with a Qubit (ThermoFisher, 106 Waltham, MA, USA) and pooled in equal molar amounts for sequencing on the Illumina MiSeq 107 with paired-end, 151-bp sequencing using V2 chemistry (Caporaso et al. 2012).

PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2341v1 | CC BY 4.0 Open Access | rec: 5 Aug 2016, publ: 5 Aug 2016 108 Sequence processing and analysis

109 A total of 495,524 reads (average length 253bp +/- 0.12bp) were first quality filtered following a 110 previously published protocol (Boulich et al. 2013, Kearns et al. In Press) in QIIME (version 111 1.9; Caporaso et al. 2010a) following joining of paired end reads with fastq-join (Aronesty et al 112 2011). Reads were then screened for chimeras using USEARCH (Edgar et al. 2011) with both de 113 novo and reference based methods and chimeric reads were discarded. After quality filtering a 114 total of 491,746 sequences remained. Operational taxonomic units (OTUs) were picked with 115 USEARCH (Edgar et al. 2011) at 97% sequence identity and we discarded OTUs appearing only 116 once across the dataset. Taxonomy was assigned with UCLUST (Edgar 2011) using the 117 GreenGenes database (version 13.5). A representative sequence was chosen, aligned with PyNast 118 (Caporaso et al. 2010b), and a phylogenetic tree was constructed using FastTree (Price et al. 119 2010).

120 We calculated beta diversity using weighted UniFrac (Louzopone and Knight 2005) on an OTU 121 table normalized to the lowest sequencing depth (16,500 sequences). Weighted UniFrac is 122 similar to other beta diversity metrics in that it calculates pair-wise similarity, however UniFrac 123 incorporates phylogenetic information of the microbial taxa, providing a more information rich 124 estimation of community similarity. Results of the beta diversity analyses were visualized with a 125 principal coordinates analysis (PCoA). To assess significance of sample groups we used a non- 126 parametric multivariate analysis of variance (MANOVA) with 10,000 permutations (adonis, 127 Anderson 2002). Alpha diversity metrics, including Shannon Diversity Index and phylogenetic 128 diversity, were calculated on a rarefied OTU table (steps of 100, 10,000 restarts at each step) and 129 significant differences in alpha diversity were assessed using a one-way ANOVA in R (R Core 130 Team 2012). Shannon Diversity provides an estimate of total species richness and evenness but 131 does not include any assessment of the relatedness of microbial taxa. Phylogenetic diversity, 132 however, includes an estimation of phylogenetic relatedness by calculating the total branch 133 length between microbial taxa.

134 Core microbiome and significantly different OTUs

135 To focus on specific OTUs important to the ray skin, we defined a core microbiome of OTUs 136 that were present in all ray samples. The results of the core microbiome analysis were visualized 137 with a venn diagram constructed in R. To assess significant differences in OTU frequencies 138 among sample types we used a non-parametric ANOVA (Kruskal-Wallis test) in QIIME, 139 defining significance with a Bonferoni corrected p-value <0.05.

140 To further assess the effect of human interaction with the ray skin microbiome we compared the 141 taxonomic composition of the ray skin to previously published work on the human skin 142 microbiome (Grice et al. 2009; Oh et al. 2014). We generated taxonomic profiles from these 143 datasets as described above and filtered our dataset using QIIME. We defined a taxonomic match 144 to the human skin microbiome with a similarity threshold of 95%, such that if the OTUs present

PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2341v1 | CC BY 4.0 Open Access | rec: 5 Aug 2016, publ: 5 Aug 2016 145 in our study were 95% similar to the OTUs from the human skin they were considered a match. 146 We tested significant differences with a one-way ANOVA in R.

147 Results

148 Diversity and community composition

149 Following clustering at 97% sequence identity, a total of 14,535 OTUs were recovered from all 150 sample types. Alpha diversity metrics including the Shannon Diversity Index and phylogenetic 151 diversity were greater for the environmental samples than for the ray skin microbiome samples 152 (Table 1; ANOVA, p<0.01, F=4.35). Shannon values in the tank environment ranged from 6.4- 153 9.3 with higher diversity found in the biofilm, sediment, and outlet water than in the water 154 entering the tank. Although Shannon diversity was high in the biofilm, the Phylogenetic 155 Diversity of the tank biofilm was low suggesting that it was likely constructed of closely related 156 taxa. By contrast, Shannon values for the rays’ dorsal and ventral surfaces ranged between 3.42 157 and 5.43 and phylogenetic diversity ranged from 24.20 to 63.57 (Table 1). There was no 158 significant difference in diversity observed between the dorsal and ventral surfaces of the rays, 159 indicating a minimal effect of human contact on the diversity of bacteria on the ray skin 160 microbiome.

161 Similarly, the ray skin microbial community structure did not demonstrate any observable 162 influence of human contact. A principal coordinates analysis based on weighted UniFrac 163 similarity indicated that the cow-nose ray skin microbiome was distinct from its environment 164 (Fig. 1; adonis, F=14.21, p<0.001). There was, however, no significant difference between the 165 dorsal and ventral surfaces of the ray body (p>0.5, F=2.29).

166 Taxonomic Composition

167 Ray skin was typically dominated by the Betaproteobacterial order Burkholderiales (~55%) and 168 had a consistent presence of the orders Flavobacteriales (~19%) and Pseudomonadales (~12%; 169 Fig. 2). However, the ventral sample from ray 1 (Figure 2) had a considerable presence of 170 Gammaproteobacteria from the order Vibrionales (62.3%), replacing the consistent presence of 171 the three dominant orders. Additionally, the most abundant orders in the ray skin microbiome 172 (Burkholderiales, Flavobacteriales, and Pseuomonadales), were significantly less abundant in the 173 surrounding environment (Kruskal-Wallis test; p<0.01, F=23.2) suggesting these taxa may play 174 an important role in the ray skin microbiome.

175 Communities from the ray tank environment were considerably different from those found on the 176 ray directly. The input water was dominated by the Gammaproteobacterial order Vibrionales, 177 but this order was not found abundant in the sediment, biofilm, or in the outlet water, suggesting 178 that the conditions in the tank do not appear to be conducive to the growth of this order. While 179 the order Vibrionales order was found in considerable abundance on the dorsal surface of ray 1, 180 the inlet water was dominated by a member of the genus Vibrio, while the ventral surface of ray

PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2341v1 | CC BY 4.0 Open Access | rec: 5 Aug 2016, publ: 5 Aug 2016 181 1 was dominated by the genus Salinivibrio. The outlet water, sediment and biofilms all had large 182 proportion of the Alphaproteobacterial order Rhodobacterales, and the outlet water and biofilms 183 had abundant taxa associated with the Gammaproteobacterial order Thiotrichales, whereas the 184 sediment had abundant Alteromonadales instead. The biofilm also displayed a large portion of 185 taxa associated with the Oceanospirillales (Fig. 2) that were in relatively low abundance in the 186 rest of the samples.

187 Core Microbiome

188 To further assess the similarity between the dorsal and ventral surfaces of the ray we calculated 189 the core microbiome (Fig. 3, Tables 2 and 3). The core microbiome of the ray skin consisted of 190 48 OTUs. Many OTUs (22 of 48) were shared between the ventral and dorsal ray skin while the 191 remaining OTUs were unique to either surface. The abundance of the shared OTUs did not vary 192 significantly between the dorsal and ventral surface of the rays (Kruskal-Wallis test, p>0.3). 193 Moreover, they accounted for, on average, 89% of the sequences from both surfaces of the rays. 194 The OTUs that were unique to either surface of the rays, while significantly different between 195 the two surfaces (Kruskal-Wallis test; p<0.01) were in low abundance, with no OTU accounting 196 for more than 0.5% of the sequences from a given sample (Fig. 4).

197 Human influences on community composition

198 To assess whether there was evidence of human skin-associated bacteria on the microbiome of 199 the rays and their environment, we compared our data to previously published data on the human 200 skin microbiome (Grice et al. 2009; Oh et al. 2014; Table 4). Our results revealed a small 201 percentage of taxa in the sediment (0.96%), water (0.43%), tank biofilm (0.43%), and ray skin 202 (1.18%) that were commonly associated with human skin (Table 4). Further, there was no 203 difference between the dorsal and ventral surfaces in the number of human-associated microbial 204 taxa. This result suggested that human interactions do no significantly introduce human- 205 associated bacteria to the ray skin and the touch tank habitat. Three OTUs, OTUs 4, 9, and 33 206 were identified as common components of the human skin microbiome and were also a part of 207 the core skin microbiome of the cow-nose rays. Collectively, however, they accounted for only 208 735 sequences out of the >125,000 sequences that were identified as a part of the ray skin core 209 microbiome.

210 Discussion

211 In recent years, host-associated microbial communities have received extensive attention due to 212 their important role in immune defense and host wellness (Cho and Blaser 2012). The 213 microbiome is a little studied characteristic of public aquarium exhibits, but has great 214 implications as an indicator of animal health. Human interactions may introduce foreign and 215 potentially pathogenic bacteria to animal skin and understanding the effects of human contact on 216 aquarium animal microbiomes can provide valuable information about the health of the animals 217 on exhibit. The goals of our study were to identify the skin associated microbiome of the cow-

PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2341v1 | CC BY 4.0 Open Access | rec: 5 Aug 2016, publ: 5 Aug 2016 218 nose ray and determine the effect of human interactions on the microbiome of the ray and its 219 habitat at the New England Aquarium.

220 The microbial communities associated with cow-nose rays displayed distinct communities and 221 lower diversity than water, sediment, and biofilm communities collected from within their tank 222 (Table 1, Figure 2). Our results suggest habitat filtering of skin microbial communities due to 223 lower niche space typically available on hosts (Rawls et al. 2006; Ogilvie et al. 2012; Frazenburg 224 et al. 2013). The filtering of taxa due to similar environmental conditions has been show to select 225 for constricted lineages of microbial taxa in host-associated and environmental microbial 226 communities (Webb et al. 2002; Cornwell et al. 2006; Horner-Devine and Bohannan 2006; Kraft 227 et al. 2007; Larsen et al. 2015; Schmidt et al. 2015). The presence of several 228 Gammaproteobacterial orders (Vibrionales, Thiotrichales, Alteromonadales, and 229 Oceanospirillales) in the tank and their absence or low abundance on the ray skin suggests 230 selection against these microbial taxa by the ray. Further, the consistent presence of the orders 231 Burkholderiales, Flavobacteriales, and Pseuomonadales (Fig. 2) and their very low abundance in 232 the environment suggests these taxa may be beneficial to maintaining the health of the ray skin 233 and are likely adapted to living on ray skin. All three of these orders are predominantly 234 heterotrophic bacteria, while members of the Pseudomondales order have been consistently 235 shown to produce a myriad of extracellular compounds that have antibacterial and antifungal 236 properties (Holmström and Kjelleberg 1999). Our results suggest these three orders are likely 237 important to protection and maintenance of ray health.

238 The microbial communities present on ray skin displayed a strong core of taxa dominated by 239 Proteobacteria (Burkoldariales and Pseudomonadales) and Flavobacteria, taxonomic groups that 240 have been seen on other groups of fish. For example, the skin microbiome of the rainbow trout 241 (Oncorhynchus mykiss) contained approximately ~15% of taxa from the Burkholderiales order 242 and ~40% from the Flavobacterales order (Lowrey et al. 2015) in comparison to our ~55% and 243 ~19% respectively, suggesting this group of taxa may be important to other fish groups, both 244 freshwater and marine. However, the third dominant order in our study, Pseudomonadales, was 245 not in meaningful abundance on the Black Molly (Poecilia sphenops), the rainbow trout (Lowrey 246 et al. 2015), the Gulf Killifish (Fundulus grandis; Larsen et al. 2015), or other bony fish/sharks 247 (Givens et al. 2015). Further, members of the Vibrio order appear to be abundant on the skin of 248 many fish species (Givens et al. 2015; Larsen et al. 2015; Lowrey et al. 2015), however their 249 abundance outside of the bottom of ray 1 (Fig. 2) was low in the rays we studied (<3%). This 250 may suggest these taxa are only beneficial to some fish and not others. Relative to other studies 251 on fish microbiomes, our study was conducted in the controlled setting of the New England 252 Aquarium. While the touch tank receives water from the Atlantic Ocean, there may be filtering 253 of microbial taxa potentially altering the ray microbiome. Future work on this group of fish in 254 their natural environment could further solidify the true composition of their skin microbiome.

255 Investigations into host-associated microbiomes have demonstrated that alterations to diet, 256 disease, or other environmental perturbations can have profound effects on microbial community

PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2341v1 | CC BY 4.0 Open Access | rec: 5 Aug 2016, publ: 5 Aug 2016 257 composition and diversity (Ley et al. 2005; Schmidt et al. 2015; Larsen et al. 2015). The rays in 258 our study are housed in an Elasmobranch touch-tank in the New England Aquarium where they 259 receive extensive contact by visitors on a daily basis. We demonstrated that there was no 260 significant difference in diversity or community composition between the dorsal and ventral skin 261 microbiome of the cow-nose ray (Table 1, Figure 2). Additionally, comparison to the human 262 microbiome revealed a very low percentage (<3%) of taxa that are commonly associated with 263 human skin, of which only 3 were found in the core microbiome (OTUs 4, 9, 33; Table 4). 264 Human skin associated bacteria were also a low percentage of sediment, biofilm, and water 265 communities (0.96, 0.43, and ~0.43% respectively). Taken together, our results indicate that 266 human contact with the dorsal surface of the ray on a daily basis has minimal effect on the ray 267 microbiome or its habitat, suggesting resistance to invasion by human associated bacteria.

268 Similar studies demonstrated environmental perturbations such as changes in salinity, disease 269 state, and temperature can have dramatic effects on microbial communities associated with fish 270 (Altinok and Grizzle 2001; Larsen et al. 2014; Schmidt et al. 2015). The apparent lack of a 271 significant response in the cow-nose ray skin microbiome to human contact may be because 272 human contact is a weak perturbation and one that the rays normally experience when interacting 273 with their environment. Conversely, our ray samples were collected prior to the exhibit opening 274 and the ray’s had not been touched for 14 hours prior to sampling and we may see a stronger 275 response closely following a human-ray interaction. However, this lack of difference first thing 276 in the morning indicates that any potential human-induced shift in ray skin microbiome is 277 ameliorated after a brief period of no contact and indicates the robustness of these communities 278 as a part of host defenses.

279 In conclusion, our results demonstrate a distinct difference in community composition and 280 diversity of cow-nose ray skin relative to their environment. Ray skin was dominated by three 281 main orders (Burkholderiales, Flavobacteriales, and Pseuomonadales) and the composition of the 282 ray skin microbiome was not affected by visitor contact at the aquarium. It will be important to 283 understand how the microbiome of animals compares to that of the exhibit environment, how the 284 microbiome can be altered through routine exhibit procedures (filtration, as animals shift onto 285 touch-tank exhibits), and how it changes with veterinary procedures such as chemical treatment 286 for parasites or disease. Ultimately, understanding the microbiome of exhibit animals may allow 287 for a more sophisticated index of health and well-being.

288 Acknowledgments

289 We would like to thank staff members of the New England Aquarium for granting access and 290 assistance in sampling the rays, in particular Dr. C Innis and SL Bailey. We would also like to 291 thank Sarah Feinman and Samantha Brown for laboratory assistance, as well as Jeff Dusenberry 292 and the UMass Boston High Performance Computing facility for access and assistance in using 293 their cluster. This work was funded by the University of Massachusetts Boston Civic

PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2341v1 | CC BY 4.0 Open Access | rec: 5 Aug 2016, publ: 5 Aug 2016 294 Engagement Scholars Initiative. Sequences from their dataset can be found in Qiita under study 295 number 10572.

296

297 References

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423 Figures and Tables

PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2341v1 | CC BY 4.0 Open Access | rec: 5 Aug 2016, publ: 5 Aug 2016 424 Table 1- Alpha diversity metrics, including Shannon Diversity Index and phylogenetic diversity, 425 for the samples in this study. Number in parentheses are the standard deviation of both dorsal 426 (top) and ventral (bottom) ray samples.

427

Shannon Phylogenetic diversity Sediment 9.28 193.91 Inlet 6.40 20.41 Outlet 8.66 191.94 Biofilm 8.74 55.84 Ray Top 5.16 (1.39) 49.24 (12.47) Ray Bottom 4.13 (0.5) 33.69 (11.25)

Ray1 Top 4.20 29.81 Ray1 Bottom 3.42 31.13 Ray3 Top 5.01 39.16 Ray3 Bottom 4.39 27.57 Ray4 Top 3.56 24.20 Ray4 Bottom 4.27 28.52 Ray5 Top 5.43 63.57 Ray5 Bottom 3.74 25.46 Ray12 Top 4.59 49.48 Ray12 Bottom 4.85 55.80 428

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PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2341v1 | CC BY 4.0 Open Access | rec: 5 Aug 2016, publ: 5 Aug 2016 430 Table 2- Taxonomic composition of OTUs that comprise the core OTUs in figure 3B. OTUs are 431 significantly different between dorsal and ventral surfaces of the rays (Kruskal-Wallis test, 432 p<0.01).

433

OTU Phylum Class Order Family Genus/Species OTU.1 Proteobacteria Betaproteobacteria Rhodocyclales Rhodocyclaceae Dechloromonas OTU.2 Firmicutes Bacilli Bacillales Bacillaceae Geobacillus OTU.3 Proteobacteria Betaproteobacteria Burkholderiales Comamonadaceae OTU.4 Firmicutes Bacilli Lactobacillales Streptococcaceae Streptococcus OTU.5 Proteobacteria Gammaproteobacteria Xanthomonadales Xanthomonadaceae Stenotrophomonas OTU.6 Proteobacteria Gammaproteobacteria Pseudomonadales Pseudomonadaceae OTU.7 Firmicutes Clostridia Clostridiales Ruminococcaceae OTU.8 Proteobacteria Alphaproteobacteria Rhizobiales Methylobacteriaceae OTU.9 Proteobacteria Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas OTU.10 Proteobacteria Alphaproteobacteria Sphingomonadales Sphingomonadaceae Sphingobium OTU.11 Proteobacteria Betaproteobacteria Burkholderiales Comamonadaceae Comamonas OTU.12 Proteobacteria Betaproteobacteria Burkholderiales Oxalobacteraceae OTU.13 Proteobacteria Betaproteobacteria Burkholderiales Comamonadaceae OTU.14 Proteobacteria Gammaproteobacteria Pseudomonadales Moraxellaceae Acinetobacter Bacteroidetes Flavobacteriia Flavobacteriales Weeksellaceae Elizabethkingia OTU.15 meningoseptica Proteobacteria Gammaproteobacteria Pseudomonadales Moraxellaceae Acinetobacter OTU.16 rhizosphaerae OTU.17 Proteobacteria Betaproteobacteria Rhodocyclales Rhodocyclaceae Dechloromonas OTU.18 Proteobacteria Betaproteobacteria Burkholderiales Comamonadaceae OTU.19 Proteobacteria Betaproteobacteria Rhodocyclales Rhodocyclaceae Dechloromonas OTU.20 Proteobacteria Betaproteobacteria Burkholderiales Comamonadaceae OTU.21 Proteobacteria Gammaproteobacteria Pseudomonadales Pseudomonadaceae OTU.22 Actinobacteria Rubrobacteria Rubrobacterales Rubrobacteraceae Rubrobacter OTU.23 Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae OTU.24 Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae OTU.25 Proteobacteria Betaproteobacteria Rhodocyclales Rhodocyclaceae Zoogloea OTU.26 Proteobacteria Gammaproteobacteria Pseudomonadales Moraxellaceae Acinetobacter 434

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437 Table 3: Taxonomic composition of OTUs that comprise the core OTUs in figure 3B. OTUs are 438 not significantly different between dorsal and ventral surfaces of the rays (Kruskal-Wallis test, 439 p>0.1).

440

OTU Phylum Class Order Family Genus/Species OTU.27 Proteobacteria Gammaproteobacteria Pseudomonadales Moraxellaceae Enhydrobacter OTU.28 Proteobacteria Alphaproteobacteria Sphingomonadales Sphingomonadadeae Novosphingobium OTU.29 Proteobacteria Gammaproteobacteria Pseudomonadales Moraxellaceae Psychrobacter OTU.30 Firmicutes Bacilli Lactobacillales OTU.31 Firmicutes Bacilli Lactobacillales OTU.32 Proteobacteria Betaproteobacteria Rhodocyclales Rhodocyclaceae Methyloversatilis OTU.33 Proteobacteria Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas OTU.34 Proteobacteria Gammaproteobacteria Vibrionales Vibrionaceae Salinivibrio OTU.35 Firmicutes Bacilli Lactobacillales Aerococcaceae Facklamia OTU.36 Proteobacteria Gammaproteobacteria Pseudomonadales Pseudomonadaceae OTU.37 Proteobacteria Betaproteobacteria Burkholderiales Comamonadaceae OTU.38 Firmicutes Bacilli Bacillales OTU.39 Proteobacteria Gammaproteobacteria Enterobacteriales Enterobacteriaceae Trabulsiella OTU.40 Proteobacteria Betaproteobacteria Burkholderiales Comamonadaceae OTU.41 Proteobacteria Gammaproteobacteria Enterobacteriales Enterobacteriaceae OTU.42 Proteobacteria Gammaproteobacteria Xanthomonadales Xanthomonadaceae OTU.43 Proteobacteria Gammaproteobacteria Vibrionales Vibrionaceae Vibrio shilonii OTU.44 Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae OTU.45 Proteobacteria Betaproteobacteria Rhodocyclales Rhodocyclaceae Dechloromonas OTU.46 Bacteroidetes Flavobacteriia Flavobacteriales Weeksellaceae Cloacibacterium OTU.47 Proteobacteria Gammaproteobacteria Pseudomonadales Moraxellaceae Acinetobacter OTU.48 Proteobacteria Betaproteobacteria Burkholderiales Comamonadaceae Limnohabitans 441

442

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444 Table 4: Percentage of sequences found in samples previously found in human skin microbiome 445 (Grice et al. 2009; Oh et al. 2014). For ray samples, numbers in parentheses are standard error of 446 the mean.

Sample % human associated Sediment 0.96 Biofilm 0.43 Inlet water 0.41 Outlet water 0.45 Ray top 1.06 (+/- 1.41) Ray bottom 1.29 (+/- 0.90) 447

448

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PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2341v1 | CC BY 4.0 Open Access | rec: 5 Aug 2016, publ: 5 Aug 2016 450 Figure Legends

451 Figure 1. Principal coordinates analysis of Weighted Unifrac Similarity for the dorsal (open 452 symbols) and ventral surfaces (closed symbols) of five rays from the New England Aquarium 453 Touch Tank. Microbial communities of the cow-nose ray tank environment (inlet and outlet 454 water, biofilm, and sediment, are also depicted (black symbols).

455 Figure 2. Stacked bar plot showing the top 25 most abundant bacterial orders accounting for 90% 456 of all sequences. The remaining 10% of sequences are place in the ‘other’ category.

457 Figure 3. Venn diagram of the core skin microbiome of the cow-nose rays (A). Core microbiome 458 is defined as bacterial taxa found in all samples within a category. The relative abundance of 459 OTUs present in the core microbiome of the ray skin. OTUs core to all ray samples (B) and 460 OTUs core to only one surface of the ray (C). Taxa in (C) are present on either all the dorsal or 461 all the ventral surfaces, but are not present in all of the opposite surfaces. All taxa in (B) are not 462 significantly different between the dorsal and ventral surfaces, while the taxa in (C) are 463 significantly different as determined by a Kruskal-Wallis test.

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