Abstract

Iron overload disorder (IOD) affects many wildlife species cared for ex situ. Two of the four rhinoceros species in human care, Sumatran rhinoceros (Dicerorhinus sumatrensis) and black rhinoceros (Diceros bicornis), are susceptible, whereas the other two, white rhinoceros (Ceratotherium simum) and greater one-horned (GOH) rhinoceros (Rhinoceros unicornis), are relatively resistant to IOD. Complex interrelationships exist between mammalian hosts, their indigenous gut microbiota, metabolome, physical condition, and iron availability. The goal of this study was to gain insight into these relationships within the family Rhinocerotidae. Specific objectives were to (1) characterize the gut microbiome and metabolome of four rhinoceros species; (2) compare the microbiome and metabolome of IOD-susceptible and IOD-resistant rhinoceros species; and (3) identify variation in the microbiome and metabolome associated with compromised health or disease in IOD-susceptible rhinoceroses. Fecal samples were collected from 31 rhinoceroses (Sumatran rhinoceros, n = 3; black rhinoceros, n = 6; GOH rhinoceros, n = 9; white rhinoceros, n = 13) located at five facilities, and matched fecal aliquots were processed for microbiome and metabolome analyses using 16S rRNA gene sequencing and nuclear magnetic resonance spectroscopy, respectively. Despite the phylogenetic disparity and dissimilar zoo diets of the hosts, the structure of the fecal microbiota of the two IOD-susceptible rhinoceros species were more closely related to each other than to those of the two IOD-resistant species (Bray–Curtis dissimilarity; IOD-susceptible vs. IOD-resistant p-value < 0.001). In addition, IOD-susceptible rhinoceroses exhibited less microbial diversity than their IOD-resistant relatives (Shannon diversity; p-value < 0.001) which could have health implications. Of note, the black rhinoceros was distinct among the four rhinoceros species with the most divergent fecal metabolome; interestingly, it contained higher concentrations of short chain fatty acids. Neither age nor sex were associated with differences in microbial community composition (p = 0.253 and 0.488, respectively) or fecal metabolomic profile (p = 0.634 and 0.332, respectively). Differences in the distal gut microbiomes between IOD-resistant and IOD-susceptible rhinoceroses support hypotheses that gut microbes play a role in host iron acquisition, and further studies and experiments to test these hypotheses are warranted.

Highlights

  • Iron overload disease has been identified in a wide range of wildlife species maintained ex situ including birds, tapirs, primates, bats, dolphins, pinnipeds, rodents, rhinoceroses, and lagomorphs

  • 97–98% of all reads were successfully mapped to a bacterial phylum for white, black, and greater onehorned (GOH) rhinoceroses, only 88% of Sumatran rhinoceros reads were mapped to a phyla (Supplementary Table 1A) due to a few unidentified amplicon sequence variant (ASV) with high read counts

  • The majority of ASVs mapped to the family level and above were found across rhinoceros species (Supplementary Table 1B), including those affiliated with the orders Bacteroidales and Clostridiales and the Families Ruminococcaceae, Spirochaetaceae, and Coriobacteriaceae

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Summary

Introduction

Iron overload disease has been identified in a wide range of wildlife species maintained ex situ including birds, tapirs, primates, bats, dolphins, pinnipeds, rodents, rhinoceroses, and lagomorphs (reviewed by Clauss and Paglia, 2012). IOD affects two of the four rhinoceros species maintained in zoos, the black rhinoceros (Diceros bicornis) (Olias et al, 2012; Paglia and Tsu, 2012) and the Sumatran rhinoceros (Dicerorhinus sumatrensis) (Paglia and Tsu, 2012; Roth et al, 2017). Both species are browsers in the wild with diets consisting primarily of shrubs, bushes, leaves, twigs, tree branches, and bark (Hall-Martin et al, 1982; Van Strien, 1986). The analogous condition in obese humans is associated with hyperferritinemia, metabolic changes and even hemosiderosis in some cases (Aigner et al, 2015; Datz et al, 2017)

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