Captivity Reduces Diversity and Shifts Composition of the Brown Kiwi Microbiome

doi:10.21203/rs.3.rs-111427/v1

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Captivity Reduces Diversity and Shifts Composition of the Brown Kiwi Microbiome

https://doi.org/10.21203/rs.3.rs-111427/v1

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Background

Captive rearing is often critical for animals that are vulnerable to extinction in the wild. However, few studies have investigated the extent at which captivity impacts hosts and their gut microbiota, despite mounting evidence indicating that host health is affected by gut microbes. We assessed the influence of captivity on the gut microbiome of the Brown Kiwi (Apteryx mantelli), a flightless bird endemic to New Zealand. We collected wild (n = 68) and captive (n = 38) kiwi feces at seven sites on the north island of New Zealand.

Results

Using bacterial 16S rRNA and fungal ITS gene profiling, we found that captivity was a significant predictor of the kiwi gut bacterial and fungal communities. Captive samples had lower microbial diversity and different composition when compared to wild samples. History of coccidiosis, a gut parasite primarily affecting captive kiwi, showed a marginally significant effect.

Conclusions

Our findings demonstrate captivity’s potential to shape the Brown Kiwi gut microbiome, but further investigation is needed to elucidate the effects of these differences on welfare.

General Microbiology

Captive rearing

animals

gut microbiota

Brown Kiwi

Diet, behavior, habitat type, and environmental species pools can all influence the composition and diversity of gut microbiomes [1–4]. However, few studies have investigated the impact of captivity, a severe lifestyle shift, on gut microbiota. Reports on mice (Peromyscus maniculatus), horses (Equus ferus przewalskii and E. f. caballus), and non-human primates demonstrate captivity’s potential to impact gut microbiomes. Even fewer studies have investigated bird hosts particularly across spatially independent sites that vary by climate and vegetation, which are expected to differ in microbial species pools, a potential source for gut microbes [5–8].

Captive rearing is often necessary to conserve populations of threatened animal species. In the case of the Brown Kiwi (Apteryx mantelli), predation from introduced mammals have made it imperative for some chicks to be raised in captivity until individuals are large enough to defend themselves [9]. Although successful in increasing population size, consequences to kiwi health via modification of the gut microbiome remain largely unknown. Factors pervasive in captivity such as artificial diets, sterile built environments, human interaction, and medical intervention [6, 10, 11] may cause changes in the microbiome, but such changes have not been well described.

Altering microbial communities may have costs to host health as microbes continue to be recognized for their roles in immune function, pathogen defense, and digestion [12]. Coccidiosis, a gut parasite caused by protozoan Eimeria spp., is a common disease in captive kiwi [13]. However, the relationship between captivity, coccidia, and gut microbial communities has garnered little attention. We sought to compare gut bacteria and fungi between captive and wild kiwi. We tested the hypothesis that captivity status and history of coccidiosis would decrease diversity and modify composition of the gut microbiome.

Fresh fecal samples were collected from seven sites on the north island of New Zealand (Fig. 1a, Supplementary Table 1) during January – April 2019. Bacterial 16S rRNA (V4 region) [14] and fungal ITS genes [15] were amplified using isolated DNA from captive (n = 38) and wild kiwi fecal samples (n = 68).

To determine whether captivity influences kiwi gut microbiota, we used PERMANOVA and NMDS analyses. Bacterial communities clustered by captivity across spatially independent sites with little overlap between the ellipses (Fig. 1b, PERMANOVA, r² = 0.07, p = 0.001). Captivity significantly decreased alpha diversity of bacteria (Fig. 2a, ANOVA, p < 0.005) and fungi (Supplementary Fig. 1, ANOVA, p = 0.012) by 33% and 74% respectively. To assess the spread of variation among kiwi microbiomes in captive and wild treatments, we calculated distance to centroid, a metric for beta diversity. No discernible pattern was observed for bacteria (Supplementary Fig. 2a, ANOVA, p = 0.948), but a marginally significant pattern was detected in fungal communities (Supplementary Fig. 2b, ANOVA, p = 0.051). We also tested if site (a factor nested within captivity status) and history of coccidiosis (positive or negative) had an influence on variation in microbial communities using PERMANOVA (Supplementary Table 2). Site showed a significant effect on bacteria (r² = 0.129, p = 0.001) and fungi (r² = 0.183, p = 0.001). Coccidiosis history showed a marginally significant trend with bacteria (Fig. 2b, r² = 0.048, p = 0.095) and fungi (r² = 0.074, p = 0.087). Although bacterial phyla composition was variable within and across treatments, Firmicutes was more prevalent in wild kiwi, while Proteobacteria dominated in captive kiwi (Fig. 2c).

We conducted a simper analysis [16] to determine the most influential OTUs that differentiate captive and wild kiwi samples for both bacteria and fungi. Eighty-seven bacterial OTUs and fifteen fungal OTUs accounted for about 70% of the differences between wild and captive samples (Supplementary Tables 3 and 4). Using a multinomial species classification method (clamtest) [16] we categorized OTUs into four classes: rare, generalist, wild specialist, and captive specialist. For bacterial OTUs, 10% were classed as generalist, 53% as rare, 20% as wild specialist, and 17% as captive specialist (Fig. 3a, Supplementary Table 5). For fungal OTUs, 0% were classed as generalist, 47% as rare, 27% as wild specialist, and 27% as captive specialist (Fig. 3b, Supplementary Table 5).

Our results indicate that captivity changes both bacterial and fungal communities in the Brown Kiwi gut. Bacterial composition clustered by captivity (Fig. 1b), suggesting that kiwi from the wild are more similar to each other than their captive counterparts, even across geographically distinct sites. The consequences of reduced microbial diversity between wild and captive kiwi remain unclear, but several studies have linked dysbiosis to higher disease prevalence in a variety of animals from humans to corals [17, 18]. Coccidiosis history showed a marginally significant effect. However, these results may be affected by small sample size. Our results suggest a potential link between changes in the microbiome to disease states that requires further exploration.

The shift in dominant bacterial phyla, Firmicutes to Proteobacteria, from wild to captive samples may be caused by sterile captive facilities and probiotic supplementation, a common practice particularly after antibiotics. Frequent surface disinfection [10] and probiotic treatment [19] have been shown to increase Proteobacteria in human subjects. Lactobacillus (OTU 49), a common genus in probiotics, was grouped as a captive specialist. Other captive-associated taxa include Corynebacterium (OTU 62), which has been found in the cloaca of penguins and the preen gland of turkeys [20], and Bacteroides (OTU 544), normally found in animal hosts but can include potential pathogens [21]. One wild specialist was Bacillaceae (OTU 101), a family associated with soil and plant pathogen defense [22], suggesting kiwi are ingesting environmental microbes when foraging [23]. Blautia (OTU 290) is a genus found in the human gut and associated with visceral fat accumulation [24]. Faecalitalea cylindroides (OTU 687), a butryrate producing microbe, has been detected in chicken [25]. These taxa may be indicative of nutrient acquisition in the wild, where food may be less available.

No fungal OTUs were categorized as generalists suggesting fungi in kiwi reflect their local environment. Some captive specialists include Cladosporium (OTU 151) and Aureobasidium (OTU 2), both associated with indoor environments and plant material [26, 27], implicating the contribution of added soil and ferns to enclosures. Trichosporon (OTU 171), another captive specialist, is a common human skin taxa [28], suggesting close human interaction may shape kiwi fungi. One wild specialist, Rhizopogon (OTU 159), has been identified as a dietary component of small mammals, suggesting kiwi may be consuming and dispersing these fungi [29]. Preussia (OTU 181) and Saitozyma podzolica (OTU 37), both associated with soil and litter, were grouped as wild specialists [30, 31].

In captivity, factors that shape gut microbial communities may include artificial diet, sterile built environments, and human interaction [6, 10]. A follow-up study investigating the establishment of gut microbes throughout kiwi development with sampling of the captive environment can elucidate how factors inherent to captivity contribute to the kiwi gut microbiome. Overall, our data suggest that captivity influences the gut microbiome of the Brown Kiwi with potential for health and disease assessment for captive-reared individuals.

Study system

Captive

The National Kiwi Hatchery is located at the Rainbow Springs Nature Park in Rotorua, New Zealand. It is the leading facility in kiwi husbandry, egg incubation, and kiwi rearing. The facility has hatched and reared nearly 2000 kiwi eggs. Otorohanga Kiwi House is located in Otorohanga, New Zealand. Both facilities are a part of the Operation Nest Egg (ONE) program.

Wild

Ponui Island is located 30 kilometers east of Auckland, New Zealand. 14 Brown Kiwi were introduced to the island by the New Zealand Wildlife Service in 1964, where populations have been increasing, establishing one of the densest populations of kiwi at an estimated 1500 individuals. Motuarohia Island is located in the Bay of Islands, 4 kilometers northeast of Russell, New Zealand. Moturua Island is east of Motuarohia in the Bay of Islands. Puketi Forest is located in the Northland region of New Zealand. Rakaumangamanga is located near the Bay of Islands. All these sites are home to a number of Brown Kiwi individuals.

Sample collection

Fresh fecal samples (n = 108) were collected using sterile spatulas. The interior of the fecal pellet was collected to ensure minimal environmental exposure. Fecal samples were stored in 5 mL Eppendorf tubes suspended in molecular grade ethanol and when accessible refrigerated in -4ºC. DNA was extracted using Macherey-Nagel NucleoSpin Soil Kit (Macherey-Nagel, Duren, Germany) on Agilent extraction robot, suspended in TE buffer, and stored in -4ºC.

Metabarcoding

Using a metabarcoding approach, we amplified a highly variable region (V4) of the bacterial 16S rRNA gene using 515F/806R primers [14] and the fungal ITS gene [15]. We used a SeraMag solution to clean PCR products to isolate bacterial and fungal DNA [32]. We pooled DNA according to the number of samples. Qubit (dsDNA HS Assay Kit, Invitrogen, Carlsbad, United States) was used to quantify DNA concentration and libraries were diluted to 4 nM prior to final pooling. We used LabChip GX Touch Nucleic Acid Analyzer to determine DNA concentration and assess quality. Samples were sequenced using Illumina MiSeq platform at Auckland Genomics Facility (University of Auckland), phiX spike 10%, 250 × 2 cycles. Bioinformatics pipeline Claident was used to demultiplex raw sequences. Pear merged paired end reads. VSEARCH filtered noisy reads, removed chimeras, and clustered sequences into operational taxonomic units (OTUs). Claident generated an OTU and assigned taxonomy with RDP classifier database [33].

Statistical analysis

We calculated Shannon index to test for a relationship between microbial alpha diversity and captivity. To better understand the intraspecific variation in microbial composition and assess if certain bird species have higher variance than others, we calculated beta diversity using a multivariate version of Levene’s test for homogeneity of variances. We reported the distance to centroid value.

We used R packages phyloseq and vegan [16, 34]. We used non-metric dimensional scaling (NDMS) with Bray-Curtis dissimilarity matrices to reduce multivariate data and spatially visualize microbial communities. NMDS was used to find patterns across captivity. We used permutational analysis of the variance (PERMANOVA) also with Bray-Curtis distance matrices to determine whether different factors, such as captivity status (wild/captive), site (geographic area), microsite (i.e. in brooder box, soil, etc.), age (days old of captive individuals), weight (mass in grams for captive individuals), collection date, and history of coccidiosis (positive/negative) can explain microbial community variance. We conducted a simper analysis [16] to determine which OTUs explain over 70% of the differences between treatments. We used a clamtest [16] to categorize bacterial and fungal OTUs into groups: generalist, too rare, and treatment specialist (wild-, captive-, positive-, negative-). Positive and negative correspond to individual kiwi who have had a history of coccidiosis.

OTU: Operational taxonomic unit; PCR: Polymerase chain reaction; DNA: Deoxyribonucleic nucleic acid; rRNA: Ribosomal ribonucleic acid; PERMANOVA: permutational analysis of the variance; NMDS: non-metric multidimensional scaling

Acknowledgements

We thank Ana Podolyan, Caroline Mitchell, Katherine Trought, Eva Weber, and Carina Davis at Manaaki Whenua Landcare Research for their expertise in the lab. Thank you to Malin Undin, Janneke Klute, Yi Luo, Emily Thompson, and Natasha Bansal for their help in field sampling. We appreciate the Chamberlain family for access to kiwi on their property. Ngai Tai (Ponui Island), Te Patukeha and Ngati Kuta (Rakaumangamanga, Moturua and Motuarohia) and Ngati Toro (Puketi) provided support and permission to collect fecal samples in their rohe (tribal areas) used in this study. Thank you to Emma Bean and Helen McCormick at the National Kiwi Hatchery and Ngāi Tahu for their continued support of the National Kiwi Hatchery and Jo Russell at the Otorohanga Kiwi House. Thank you to the Fukami Lab at Stanford University for their helpful feedback on the manuscript.

Author’s contributions

PASJ, MKD, and IC designed the study. PASJ and IC collected fecal samples. PASJ performed the molecular work including DNA extractions, PCR, and library preparation. PASJ and MKD completed the bioinformatics. PASJ conducted the statistical analyses. PASJ wrote the manuscript with feedback from MKD and IC.

Funding

This work was supported by Birds New Zealand grant for PASJ & MKD, MBIE Strategic Science Investment Fund supported MKD, and the Stanford Center for Conservation Biology for PASJ. All captive research performed is covered under the Zoo and Aquarium Association of New Zealand permit and wild kiwi research is covered under the Department of Conservation permits 38796-FAU and 70826-CAP.

Availability of data and materials

The datasets generated and/or analyzed during the current study are available in a github repository, https://github.com/psanjuan/kiwi_microbiome_2019.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no conflict of interest.

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Captivity Reduces Diversity and Shifts Composition of the Brown Kiwi Microbiome

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Version 1

Abstract

Figures

Background

Results

Discussion

Conclusions

Methods

Study system

Captive

Wild

Sample collection

Metabarcoding

Statistical analysis

Abbreviations

Declarations

Acknowledgements

Author’s contributions

Funding

Availability of data and materials

Ethics approval and consent to participate

Consent for publication

Competing interests

References

Supplementary Files

Status:

Version 1