Page 1
Influence of hand-rearing and bird age on the faecal microbiota of the 1
critically endangered kakapo 2
3
4
David W. Waitea, Daryl K. Easonb, Michael W. Taylora# 5
6
7
Centre for Microbial Innovation, School of Biological Sciences, The University of Auckland, Auckland, 8
New Zealanda; Research Development and Improvement Division, Department of Conservation, 9
Nelson, New Zealandb 10
11
12
Running Head: Development of the kakapo faecal microbiota over time and age 13
14
15
16
Please address correspondence to Michael W. Taylor 17
E-mail: [email protected] 18
Tel. (+64) 9 3737599 x82280 19
Fax (+64) 9 3737416 20
AEM Accepts, published online ahead of print on 16 May 2014Appl. Environ. Microbiol. doi:10.1128/AEM.00975-14Copyright © 2014, American Society for Microbiology. All Rights Reserved.
on July 7, 2018 by guesthttp://aem
.asm.org/
Dow
nloaded from
Page 2
Abstract 21
The critically endangered New Zealand parrot, the kakapo, is subject to an intensive management 22
regime aiming to maintain bird health and boost population size. Newly hatched kakapo chicks are 23
subject to human intervention and are frequently placed in captivity throughout their formative 24
months. Hand-rearing greatly reduces mortality among juveniles, but the potential long-term impact 25
on the kakapo gut microbiota is uncertain. To track development of the kakapo gut microbiota, 26
faecal samples from healthy, pre-fledged juvenile kakapo, as well as unrelated adults, were analysed 27
using 16S rRNA gene amplicon pyrosequencing. Following the original sampling, juvenile kakapo 28
underwent a period of captivity, so further sampling during and post-captivity aimed to elucidate the 29
impact of captivity on the juvenile gut microbiota. Variation in the faecal microbiota over a year was 30
also investigated, with resampling of the original juvenile population. Amplicon pyrosequencing 31
revealed a juvenile faecal microbiota enriched with particular lactic acid bacteria when compared to 32
the adults, although overall community structure did not differ significantly among kakapo of 33
different ages. Abundance of key OTUs was correlated with antibiotic treatment and captivity, 34
although the importance of these factors could not be proven unequivocally within the bounds of 35
this study. Finally, the microbial community structure of juvenile and adult kakapo changed over 36
time, reinforcing the need for continual monitoring of the microbiota as part of regular health 37
screening. 38
on July 7, 2018 by guesthttp://aem
.asm.org/
Dow
nloaded from
Page 3
Introduction 39
The kakapo (Strigops habroptilus) is a flightless, nocturnal parrot endemic to New Zealand. It 40
possesses few defences against introduced mammalian predators (1), has a slow reproductive rate 41
and usually lays only a single egg. Although kakapo were once common throughout New Zealand (2), 42
the population has declined to 125 individuals at the time of publishing, confined to three predator-43
free islands off the coast of New Zealand. Since the 1980s, kakapo have been subject to an intensive 44
management program focused on preserving the species and eventually restoring the population to 45
self-sustaining levels (3-5). In an effort to optimize management practices, the New Zealand 46
Department of Conservation has collaborated with researchers from a wide range of biological 47
disciplines, including behavioural ecology, physiology, genetics, nutrition and, recently, microbiology 48
(6-12). 49
50
The kakapo has an array of biological characteristics that make it an unusual animal to study. Apart 51
from being the world’s heaviest parrot, the only flightless parrot and the only parrot to carry out lek 52
breeding (6), the kakapo has been identified as a potential foregut fermenter due to its herbivorous 53
diet and lack of ceca (13). Microbially-mediated foregut fermentation is a common trait in mammals 54
but is rare among avians, with only the South American hoatzin known to perform this process (14). 55
Notable differences in feeding strategy do exist between the kakapo and hoatzin, however, with 56
kakapo rarely ingesting fibrous plant material, instead extracting the juices from shoots and leaves 57
and discarding the undigested ‘chews’ (15, 16). There is currently no empirical evidence to support 58
or dispute the occurrence of foregut fermentation in kakapo. Intriguingly, the reproductive cycle of 59
the kakapo is linked to the fruiting of particular native New Zealand trees. The rimu tree undergoes a 60
mast season every three or four years, during which time kakapo mate and rear young. While the 61
link between kakapo and rimu is well established, the causal link between these two phenomena is 62
unclear and is not simply a matter of additional dietary energy enabling reproduction (17). 63
64
The role of microbial symbionts in the gastrointestinal (GI) tract of vertebrates is well documented, 65
and a range of mechanisms through which microbes contribute to the nutrition (18-21) and 66
development of the host gut (22-24) have been identified. Our previous research into the GI-67
associated bacteria of the kakapo revealed a community dominated by only a handful of operational 68
taxonomic units (OTUs), mainly from the phyla Proteobacteria and Firmicutes and apparently lacking 69
in archaea (12, 25). The kakapo GI tract appears to have a low phylum-level diversity of bacteria 70
on July 7, 2018 by guesthttp://aem
.asm.org/
Dow
nloaded from
Page 4
compared to other birds (25, 26) and this has led to speculation of a population bottleneck on the 71
gut microbiota. The kakapo microbiota is not well understood, but it is likely that current 72
management practices have an impact on the microbial community as kakapo are removed from the 73
wild and given veterinary care at the first sign of sickness (27). This captivity results in a change in 74
diet and often includes antibiotic treatment, both of which are frequently linked to shifts in 75
microbial community structure (23, 28-31). 76
77
Of major relevance to kakapo microbiology is the fact that the developmental pattern of the kakapo 78
gut microbiota is completely unknown, thereby making it difficult to address questions regarding the 79
effect of diet or captivity on the gut microbiota. Previous research into the development of the gut 80
microbiota in other host species has reported that the microbiota of juveniles differs significantly 81
from that of adults in both avians and mammals (32-36), although it is not clear that this pattern is 82
reflected in the kakapo (12). In many avian species the juvenile microbiota is a dynamically changing 83
community (37-39) that gradually develops towards the adult community structure (33, 36), but the 84
changes in microbiota as the subject ages vary by host. For example, chickens are enriched in 85
Lactobacillaceae in the first week of life (38), while juvenile turkeys appear to harbour a large 86
proportion of Clostridiales until around 10 weeks of age (39). Moreover, even genetically related 87
individuals undergo different developmental patterns when geographically isolated (40). In order to 88
better understand the temporal dynamics of the kakapo microbiota, and potentially gain insights 89
into the impact of human intervention, samples were collected from juvenile kakapo born during the 90
2011 breeding season, spanning four time points throughout the first year and a half of life. The aims 91
of this study were to compare differences in the juvenile and adult faecal microbiota, to understand 92
the time required for juvenile kakapo to develop a ‘normal’ adult gut microbiota, and to investigate 93
the potential effects of captivity on the juvenile microbiota. 94
on July 7, 2018 by guesthttp://aem
.asm.org/
Dow
nloaded from
Page 5
Materials and Methods 95
Sample collection 96
In the 2011 breeding season, 11 kakapo chicks were hatched on Codfish Island, off the coast of New 97
Zealand (46°47'S 167°38'E). Samples were collected from these juveniles at four time points, which 98
are summarised in Table 1. During the nesting period each juvenile required a period of captivity, 99
either due to low weight gain or sickness. While undergoing the period of captivity the juveniles 100
were fed a diet of fruit, Lactated Ringer’s solution and the proprietary parrot hand-rearing formula 101
Exact (Kaytee Products Inc, Chilton, WI). Eight of the captive juveniles were also treated with the 102
commercially available antibiotics Augmentin and Clavulox, which combine a β-lactam and β-103
lactamase inhibitor (Tables 1 and 2). Samples collected during this period were taken following five 104
days of captivity. Following release from captivity, juveniles were given a ‘recovery’ period of two 105
weeks, after which additional faecal samples were collected. A final sample was collected 106
approximately one year later, at which point the ‘juveniles’ had fledged from the nest and were now 107
independent adults. 108
Fresh faecal samples were also collected from adult kakapo in the same manner. Samples were 109
taken from adults with no history of sickness, and no history of captivity other than the original 110
translocation to Codfish Island, at time points coinciding with the Juvenile_First and Juvenile_Fourth 111
samplings. The adult age data areincomplete as some birds were born wild and only introduced to 112
Codfish Island later in life. However, the youngest adults sampled were born on Codfish Island in 113
2005, making the ‘adult’ kakapo representative of a substantially older sub-population than those 114
individuals representing the ‘juvenile’ dataset, even though at the Juvenile_Fourth time point the 115
original juvenile kakapo were mature kakapo. 116
Fresh faeces were collected aseptically during routine health inspections of the juveniles and stored 117
in sterile polypropylene tubes on ice until they were able to be frozen, a period of less than one hour 118
following collection. Sample sizes vary throughout the study due to difficulty with capture and 119
recapture of birds. 120
121
DNA extraction, PCR amplification and amplicon pyrosequencing 122
DNA extraction was performed on samples using a previously described bead-beating method (12). 123
PCR was performed using 16S rRNA gene-specific primers targeting Bacteria: 533f (5’-124
GTGCCAGCAGCYGCGGTMA-3’) and 907R (5’-CCGTCAATTMMYTTGAGTTT-3’) (41). Each primer was 125
synthesised with an FLX Titanium adaptor sequence (533f: CCA TCT CAT CCC TGC GTG TCT CCG AC, 126
on July 7, 2018 by guesthttp://aem
.asm.org/
Dow
nloaded from
Page 6
907R: CCT ATC CCC TGT GTG CCT TGG CAG TC) and a 10 bp multiplex identifier barcode (MID) was 127
attached to the forward primer using commercially available barcode sequences (Roche Diagnostics 128
Corporation, Branford, CT) . For each DNA extraction, three 25 µL PCR reactions were performed 129
with a specific barcoded primer. Reactions contained 20 mM Tris-HCl, 50 mM KCl, 1.5 mM MgCl2, 130
100 µM dNTP mixture, 2.5 µM of forward and reverse primer, 2% bovine serum albumin, 0.5 units 131
Taq polymerase and 10 ng of template DNA. Cycling conditions were as follows: initial denaturation 132
of 94°C for 5 min, 20 cycles of touchdown PCR (94°C for 30 s, 60°C for 30 s and 72°C for 45 s, with a 133
0.5°C decrease in annealing temperature per cycle), 10 cycles of 94°C for 30 s, 50°C for 30 s and 72°C 134
for 45 s, and a final elongation step of 72°C for 10 min, with one negative control run for each primer 135
pair. Following amplification, PCR products from each sample were pooled and purified using the 136
Agencourt AMPure XP bead system (Agencourt, Beckman Coulter, MA, USA), according to the 137
manufacturer’s instructions. Product size was measured using the Agilent DNA 1000 kit (Agilent 138
Technologies, Waldbronn, Germany) run on the Agilent 2100 Bioanalyzer platform. Purified product 139
was quantified using the Qubit Quant-iT DNA high-sensitivity assay and combined with fragment size 140
to equalise the number of molecules pooled per sequencing run. Samples were randomised across 141
sequencing runs and pyrosequencing was performed on a Roche GS-FLX Titanium platform (Roche, 142
NJ, USA) by Macrogen Inc (Seoul, South Korea). Sequence data were submitted to the NCBI 143
Sequence Read Archive under the accession numbers SAMN02369276 – 329 and SAMN02420182 – 144
88. 145
146
Bacterial community analysis 147
Sequence reads were processed using mothur version 1.31.2 (42). Briefly, pyrosequencing 148
flowgrams were denoised using the mothur implementation of AmpliconNoise (43). Sequences with 149
length <200 bp or homopolymers >8 bp were removed, as were sequences with more than one MID 150
barcode mismatch or two primer mismatches. Sequences were then aligned against a reference 151
database (http://www.mothur.org/wiki/Silva_reference_alignment) and sequences that could not 152
be aligned were removed. Chimeras identified using the UCHIME algorithm (44) were removed from 153
the data set and the remaining sequences classified using a previously reported method (41, 45). 154
Sequences classified as chloroplast were removed from the dataset, as were sequences that could 155
not be classified even to domain level. From a starting total of 216,759 sequences, the above-156
mentioned procedures led to a final total of 208,121 high-quality sequence reads for further 157
analysis. 158
159
on July 7, 2018 by guesthttp://aem
.asm.org/
Dow
nloaded from
Page 7
Following these initial quality control steps, sequence data were binned into genus- and species-160
approximating OTUs using definitions of ≥95% and ≥97% sequence similarity (OTU0.95 and OTU0.97), 161
respectively. Yue-Clayton theta, Jaccard (46) and phylogeny-based UniFrac distances (47) were 162
calculated between each group using each OTU definition. Average distances between communities 163
were calculated by randomly subsampling 1,400 sequences per sample and calculating distance 164
measures 10,000 times. Apparent changes in community structure were tested using analysis of 165
molecular variance (AMOVA) (48, 49). Changes in OTU0.97 abundance between sample groups were 166
tested using metastats (50), but are only reported if the OTU of interest had a relative abundance of 167
≥1% of the obtained sequences across any sample, as rarer OTUs were frequently only observed in a 168
single kakapo individual and therefore were not informative when surveying the overall microbiota. 169
Correlations between OTUs that differed significantly between captive and wild individuals were 170
measured using the Point-Biserial correlation coefficient in the R software environment (version 171
2.15.2 [http://www.r-project.org]). 172
173
Coverage of sequencing was estimated by calculating Good’s Coverage index after subsampling the 174
OTU0.97 table to a depth of 1,400 OTUs per sample. Richness and diversity estimators were also 175
calculated on the subsampled data using Shannon’s diversity and evenness, Simpson diversity index, 176
Chao1 and ACE estimators. In order to test how well previous clone-library data represented the full 177
faecal microbiota, representative OTU0.97 sequences were mapped against full-length clone 178
sequences using usearch (51) with a minimum similarity value of 0.97. The results of the usearch 179
mapping were recorded both in terms of the total proportion of reads that were mapped against the 180
clone-library data, and as a proportion of the total number of OTU0.97 generated during analysis. 181
182
The core microbiota was calculated by scoring the presence/absence of each OTU in each sample 183
then calculating presence as a proportion of all samples. An overall core was calculated using all 184
available wild samples (excluding Juvenile_Second), as well as separate cores consisting of 185
exclusively adult kakapo (Adult_First, Adult_Second, Juvenile_Fourth) and exclusively healthy 186
juvenile kakapo (Juvenile_First, Juvenile_Third). A final core was calculated from the captive, 187
antibiotic-treated kakapo (n = 8) but not from the untreated pair of birds, due to the low sample 188
size. The core microbiota was categorised as the ‘core’ microbes present in >90% of individuals 189
surveyed and the ‘variable’ microbes present in >60% of individuals surveyed. All other OTUs were 190
considered either transient or individual specific. 191
on July 7, 2018 by guesthttp://aem
.asm.org/
Dow
nloaded from
Page 8
Results 192
The kakapo microbiota is of low diversity and dominated by Firmicutes and 193
Proteobacteria 194
Amplicon pyrosequencing yielded an average of 4648 sequences per sample, compared to ~77 195
obtained via clone libraries in our previous paper (12). Good’s Coverage values show that amplicon 196
pyrosequencing was able to describe essentially the entire microbiota of each sample group, while 197
ecological diversity measures indicate an uneven bacterial community of low diversity (Table 3). This 198
unevenness was reflected in the low Shannon evenness calculated for each sample. The Shannon 199
evenness index is a ratio of the Shannon diversity index of a sample compared to the maximum 200
possible Shannon index in the sample, with a value of 1 being perfectly even. The evenness of all 201
samples was low according to this metric (Table 3) and this was apparent visually (Figure 1). 202
Community richness (Chao1 and ACE) were lowest during the juvenile captivity period, although this 203
was not reflected clearly in the diversity estimators. Similarly, when amplicon sequences were 204
mapped to previous kakapo gut microbiota clone-library data, the diversity within the clone-library 205
accounted for a comparatively large proportion of the total reads sequenced, but a much lower 206
proportion of the total OTUs (Table 3). Similar to previous findings, the phylum-level membership 207
consisted predominantly of Proteobacteria and Firmicutes. In contrast to the clone-library data, 208
Bacteroidetes and Actinobacteria were also frequently, though not universally, detected (in ~70% 209
and ~33% of samples, respectively). 210
211
In order to create a baseline for future kakapo microbiology research, we defined core and variable 212
communities of OTUs that were observed in the kakapo faecal microbiota (Table 4). The ‘core’ 213
microbiota consisted of OTUs present in >90% of individuals sampled and the ‘variable’ microbiota in 214
>60% of individuals. These groupings were further stratified by age (adult core, juvenile core), and 215
treatment core was calculated for juvenile kakapo under the influence of antibiotics (treated core). 216
In all core calculations of wild birds, two OTUs were classified as ‘core’, taxonomically assignedas 217
Escherichia and Streptococcus. The ‘variable’ microbiota differed between juvenile and adult birds 218
with more OTUs recruiting to the variable microbiota of juveniles, consistent with the higher 219
diversity and richness indices reported in the juvenile population (Table 3). The treated core 220
microbiota differed from that of the juvenile core, and accounted for more of the microbiota than in 221
wild samples. It is important to note that the classification scheme used was only based on 222
presence/absence of OTUs and did not account for their relative abundance in the sample, although 223
abundance carries biological significance in the interpretation of these data. With a single exception, 224
on July 7, 2018 by guesthttp://aem
.asm.org/
Dow
nloaded from
Page 9
core OTUs accounted for >5% of the amplicon reads in their respective grouping (Table 4). Some 225
variable OTUs, including OTU02 in the antibiotic-treated microbiota, OTU04 in the adult microbiota 226
and OTU06 in the wild juvenile microbiota accounted for a large proportion of the microbiota in 227
some individuals, but were not commonly observed amongst different individuals. 228
229
The microbial community structure does not vary between juvenile and adult 230
individuals, but changes with time 231
Adult and juvenile community structures were not significantly different from each other under any 232
distance/OTU combination when juvenile and adult samples from matching time points were 233
compared. Comparing the juvenile samples sequentially revealed no differences in community 234
structure (AMOVA, all distances, all OTUs). The community structures of the first and last juvenile 235
samples were significantly different (p < 0.001, all distances, all OTUs) and this difference was also 236
observed for the adult samples (p < 0.001, all distances, all OTUs). The progression of the community 237
structure through time is visualised in Figure 2. 238
239
Relative OTU abundance changes within the faecal microbiota 240
Although the community structure overall did not vary significantly between early juvenile and adult 241
sample groups, statistically significant changes in the relative abundances of OTUs were detected. 242
Six OTUs, generally classified as lactic acid bacteria, were present at significantly higher levels in the 243
Juvenile_First microbiota than in the time-equivalent Adult_First (Table 5). These OTUs reduced in 244
abundance in the juvenile microbiota and there were no significantly different OTU abundances 245
between the Adult_First and Juvenile_Third communities. We conclude that the apparent increase 246
in abundance of these OTUs is associated with the young age of the Juvenile_First cohort, with the 247
exception of two OTUs (Table 5, asterisk) that were observed in only two of the individuals 248
comprising the Juvenile_First cohort and that may represent individual-specific variation in the 249
microbiota. 250
251
The potentially confounding effects of captivity on the microbiota of Juvenile_Second and its 252
subsequent development was a cause for concern within this study, although given the nature of 253
kakapo conservation this was unavoidable. Due to the differential treatment of juveniles in captivity, 254
and the rich wild-type data from the Adult_First, Juvenile_First and Juvenile_Third groups, some 255
inference can be made from the data, although pending additional testing with an adequate control 256
on July 7, 2018 by guesthttp://aem
.asm.org/
Dow
nloaded from
Page 10
group these findings remain speculative. OTUs that fluctuated significantly throughout the captivity 257
period are reported in Figure 3 and are summarised as follows: OTU03 (Streptococcus) showed a 258
strong, negative correlation with the β-lactam antibiotic treatment kakapo group when compared to 259
any non-treated group (rpb = -0.45, p = 0.009) and a weaker, statistically insignificant correlation with 260
captivity overall (rpb = -0.16, p = 0.37). Conversely, OTU05 (Enterococcus) was enriched in the 261
antibiotic-treated (rpb = 0.7, p < 0.0001) and captive kakapo (rpb = 0.59, p = 0.0003) when compared 262
to non-treated groups. Samples obtained from the captivity without antibiotic treatment showed no 263
differences that could not be explained by the observed differences between Juvenile_First and 264
Juvenile_Third or the lack of difference between Juvenile_Third and Adult_First (i.e. some OTUs 265
were enriched in the youngest juvenile samples, but not in the later samples or adult samples, 266
implying that individual age was driving the decline in abundance). 267
on July 7, 2018 by guesthttp://aem
.asm.org/
Dow
nloaded from
Page 11
Discussion 268
The gut microbiota of the kakapo is likely to contribute greatly to the health and well-being of the 269
bird, however until recently (12, 25) it remained virtually unstudied. Here we document, for the first 270
time, temporal changes in the bacterial communities within the kakapo GI tract, but do not find 271
consistent differences between juvenile and adult birds at a community-wide level. Amplicon 272
pyrosequencing confirms our previous conclusion that the kakapo microbiota is an uneven, low-273
diversity community. Although differences in experimental factors and sampling depth mean that 274
between-study comparisons must be treated with caution, the diversity and richness estimators 275
calculated in this study are nonetheless low compared to those obtained from other avians. A recent 276
analysis of the emu hindgut reported a mean Shannon diversity index of 3.4 (kakapo = 0.95) and 277
Chao1 richness of 624 (kakapo = 60.5) (52), while clone-library based analysis of the chicken cecum 278
reported a Chao1 value of 121 (53). Molecular analysis of the hoatzin cecum (54) reported a median 279
inverse Simpson diversity of >400 (kakapo = 1.78). Kakapo and hoatzin are frequently compared, 280
with the kakapo occasionally mentioned as a potential candidate for avian foregut fermentation. 281
Despite the marked difference in microbial diversity between the kakapo and hoatzin hindgut, the 282
taxonomic differences between these microbiota are not great. Hierarchical clustering of phylotyped 283
data obtained from hoatzin hindgut analysis (54) reveals no separation between the kakapo juvenile 284
and adult faecal microbiota and the hoatzin ceca microbiota (Supplemental Figure 1). While the 285
microbiota of the adult kakapo crop is unknown it is interesting to observe a degree of convergence 286
in the hindgut microbiota of these two geographically isolated birds. 287
288
The greater sequencing depth afforded by amplicon pyrosequencing has allowed us to examine the 289
microbiota in greater detail than our previous effort (12). Indeed, while the core microbiota in the 290
current analysis consisted of only Gammaproteobacteria and Firmicutes, members of additional 291
phyla were also frequently detected in the birds tested. Representatives of the Bacteroidetes were 292
detected in approximately 70% of samples, although often at levels lower than our previous 293
methodology was capable of detecting (12). This finding is somewhat at odds with our previous 294
conclusions, and emphasises the value of increased sequencing depth, even in apparently low-295
diversity environments. Bacteroidetes-associated OTUs occurred in an individual-specific manner so 296
although Bacteroidetes were observed in many samples, no Bacteroidetes-OTUs classified into the 297
kakapo core microbiota. In other avian systems, the most abundant bacterial phyla detected with 298
molecular methods are the Firmicutes and Bacteroidetes, followed by Actinobacteria and 299
Proteobacteria (26), which is notably different to the bacterial community profile of the kakapo. The 300
on July 7, 2018 by guesthttp://aem
.asm.org/
Dow
nloaded from
Page 12
functional implications of this differing community composition compared to that of other 301
herbivorous birds is a matter for future investigation, and knowledge of the core bacteria that 302
comprise the kakapo microbiota will be of benefit for potential future kakapo bacteriotherapy and 303
probiotic development (25). 304
305
The lack of differentiation between juvenile and adult community structures is an interesting finding, 306
as strong differences have been reported in other avian systems in which the juveniles were of a 307
similar age to those studied here (32, 36), or older (33). Despite the lack of difference in community 308
structure, some OTUs varied significantly in abundance between younger and older birds, likely 309
reflecting at least some role of bird age in shaping the microbiota. Due to concerns regarding the 310
handling of nesting adults, adults sampled in this study were not the parents of the studied juveniles 311
and to the authors’ knowledge there was no contact between these juvenile and adult birds. We 312
speculate that this apparently homogenous bacterial community may be due to the small size of 313
Codfish Island, with all adult kakapo utilising an almost identical diet. It has been observed that 314
kakapo on Codfish Island share overlapping home ranges, with individuals often sharing feeding 315
stations when supplemental feed is provided. Further study into the development of the juvenile 316
microbiota may better resolve this pattern by using a finer time-scale to investigate the community 317
structure much sooner after hatching. Although age did not appear to influence community 318
structure, the relative abundance of particular OTUs (including those within the core microbiota) 319
varied with age and time, consistent with the wider avian literature (32, 38, 39). In general, microbial 320
OTUs that were classified as part of the overall core microbiota were present at high levels within 321
the faecal samples and in each sample grouping the core and variable OTUs represented over half of 322
the microbiota (Table 4), indicating that these microbes are likely of biological significance to the 323
kakapo. It was interesting to note that the core microbiota of the juvenile samples accounted for 324
more of the total microbiota and comprised more OTUs than that of the adults. The core microbiota 325
was even more conserved in the antibiotic-treated kakapo, which may be a consequence of a 326
reduction in available niches brought on by a controlled diet and antibiotic pressure. 327
328
The need to maintain the health of juvenile kakapo is clearly paramount from a conservation 329
standpoint, and accordingly it was not possible to maintain a wild juvenile control group when 330
individuals needed to be taken into captivity. With the entire juvenile kakapo population in captivity, 331
there was no adequate control group for comparison other than the adult group, but we 332
on July 7, 2018 by guesthttp://aem
.asm.org/
Dow
nloaded from
Page 13
nevertheless attempted to identify significant changes in the microbiota that correlated with this 333
period. Studying kakapo that were captive but not treated with antibiotics allowed us to tease apart 334
the influence of diet and antibiotic treatment, albeit with a smaller sample size than is ideal. The 335
reported changes in the microbiota were more strongly correlated with antibiotic treatment (OTU03 336
rpb = -0.45, OTU05 rpb = 0.7) than captivity in general (OTU03 rpb = -0.16, OTU05 rpb = 0.59), implying 337
that antibiotic treatment was the primary factor driving the observed differences during captivity. 338
We also observed changes in the microbiota of captive, antibiotic-treated individuals, which adds 339
further evidence that captivity alters the kakapo microbiota. The lack of a juvenile control group 340
makes these findings tentative, but there appears to be no long-term impact of these changes as the 341
bacterial community structures of treated juveniles and untreated adults converged in later samples 342
and no differences in relative OTU abundance were detected between adults and juveniles following 343
release from captivity. In future breeding seasons it would be desirable to attempt to repeat this 344
experiment with finer time scales and more rigid control groups to validate these data (bird health 345
permitting). 346
347
A previous meta-analysis (55) has reported that microbial communities vary through time across a 348
range of natural ecosystems. Consistent with this observation, the kakapo faecal microbiota varied 349
over time, with juvenile and adult samples differing after approximately one year between samples. 350
It is possible that this change is related to the change in diet, as reproduction in the kakapo 351
correlates with the fruiting of specific trees native to New Zealand. In addition, supplementary 352
feeding is a common practice during breeding seasons and these changes in kakapo ecology provide 353
a mechanism that may account for the apparent changes in gut microbiota over time. When 354
comparing differences between the early and later samples, a Proteobacteria-associated OTU 355
(Figure 3 , OTU02) was only sporadically observed in the early samples but was one of the most 356
abundant OTUs at the final time point (Figure 1). This OTU could not be classified below the phylum 357
level, with results generally alternating between the classes Betaproteobacteria and 358
Gammaproteobacteria. Additional chimera testing was performed using both UCHIME and the 359
chimera.slayer command in mothur against the SILVA gold database 360
(http://www.mothur.org/wiki/Silva_reference_files), but this OTU was not determined to be 361
chimeric in either test. The presence and identity of this OTU will be important in future analysis of 362
the kakapo microbiota as its identity may be better resolved with longer sequence data or a 363
different amplicon region. Changes in the microbiota over time carry significance for the wider field 364
on July 7, 2018 by guesthttp://aem
.asm.org/
Dow
nloaded from
Page 14
of disease ecology, as they emphasise the need for up to date knowledge of animal-associated 365
microbiota in order to better enable pathogen detection (56). 366
367
Cut-off values of 95% and 97% sequence similarity are commonly reported in the literature, although 368
there is concern over what value is appropriate (57-59). In order to account for potential biases 369
introduced by the level of OTU similarity, sequence data were binned into two different OTU 370
definitions (OTU0.95, OTU0.97) and statistical testing performed between each sample group using 371
each OTU cut-off. The overall robustness of a finding was not only based on the statistical 372
significance but also whether a finding was consistent across different OTU definitions and distance 373
calculations. Statistically significant findings were preserved across OTU definition, giving confidence 374
that the conclusions regarding community structure were not merely artefacts of the bioinformatic 375
approach. 376
377
Overall our findings suggest that the faecal community structure of kakapo is not influenced by host 378
age per se, but does change through time. That age is not a significant factor in shaping the 379
community structure of the kakapo microbiota contrasts with patterns seen in other avian hosts, 380
although age-related differences in OTU abundance indicate that age still plays a role in shaping at 381
least a subset of the kakapo microbiota, although possibly on a shorter timescale than normally 382
observed. By comparing our juvenile data to data obtained from adult kakapo, we have teased apart 383
age- and time-based differences and established a working core set of bacteria for further study in 384
kakapo microbiology. Finally, in confirming that the microbiota changes over time we have 385
reaffirmed the need for continuous sampling of the microbiota of this endangered bird in order to 386
ensure that knowledge of the ‘healthy’ microbiota is accurate. The described data - in combination 387
with ongoing ecological and genetic studies - should contribute to the management and ultimately 388
the survival of this ancient parrot. 389
on July 7, 2018 by guesthttp://aem
.asm.org/
Dow
nloaded from
Page 15
Acknowledgements 390
This work was supported by funding from The University of Auckland Faculty Research Development 391
Fund (grant 9841 3626187). D.W.W. was supported by a University of Auckland Doctoral 392
Scholarship. 393
394
We gratefully thank Ron Moorhouse, Deidre Vercoe and Jo Ledington (Department of Conservation) 395
for their support with this project. We also thank Peter Deines and Siân Morgan-Waite for helpful 396
comments on this manuscript. 397
on July 7, 2018 by guesthttp://aem
.asm.org/
Dow
nloaded from
Page 16
Figure Legends 398
Figure 1. Phylogenetic distribution of bacterial OTUs in the kakapo faecal microbiota 399
High-level taxonomic information is provided as per classification. OTUs are defined as groups of 16S 400
rRNA gene sequences that share >97% similarity and are ordered by phylum, then sub-ordered by 401
class. For clarity only the 50 most abundant OTUs are plotted, representing 98.0% of the total reads, 402
with 477 OTUs comprising the remainder of the reads following removal of singletons. OTU 403
abundances are scaled as a proportion of all sequences in the respective sample. OTU02 (mentioned 404
in the manuscript) is noted with an asterisk (*). 405
406
Figure 2. Changes in community structure in wild kakapo samples 407
Non-metric multidimensional scaling of the weighted UniFrac distances between individual samples 408
obtained from wild kakapo. Left: distances calculated based on OTU0.97 (stress = 0.15, r2 = 0.90). 409
Right: distances calculated based on OTU0.95 (stress = 0.15, r2 = 0.91). 410
411
Figure 3. Statistically significant changes in relative OTU abundance during captivity 412
Groups Captive+AB and Captive-AB refer to the cohort Juvenile_Second split by whether or not 413
antibiotics were administered. Excluding changes in OTU abundance that could be attributed to bird 414
age, only OTU03 and OTU05 were significantly different in antibiotic-treated samples compared to 415
all other kakapo samples (including captive kakapo without antibiotic treatment). 416
on July 7, 2018 by guesthttp://aem
.asm.org/
Dow
nloaded from
Page 17
Table Legends 417
Table 1. Sample sizes and mean individual age and additional notes taken at the time of sampling. 418
For ‘adult’ kakapo, age data is incomplete but the youngest adults were ≥6 years old in 2011. 419
420
Table 2. List of individuals sampled at each point in the juvenile survey. Individuals marked with an 421
asterisk (*) received antibiotic treatment with the commercially available antibiotic formulas 422
Augmentin and Clavulox. 423
424
Table 3. Common diversity and richness estimators as calculated using OTUs of ≥97% sequence 425
similarity. The median value for each sample group is reported. Reads Mapped refers to the 426
proportion of amplicon sequences that could be mapped to pre-existing clone-library data. OTUs 427
Mapped refers to the number of representative OTUs that could be mapped to pre-existing clone-428
library data. 429
430
Table 4. The differences in core kakapo microbiota based on different partitioning of samples. OTU 431
labels are provided to allow consistency between other tables that report OTU abundances and 432
changes. Values report the mean relative abundance (%) of an OTU in the overall microbiota for its 433
grouping. Bolded and underlined values denote ‘core’ OTUs in their group, while regular values 434
indicate an OTU was variable. The final row reports the total proportion of the microbiota which is 435
accounted for by these OTUs (%). 436
437
Table 5. Statistically significant changes in OTU abundance between sample groups of interest. 438
Statistical testing and q-value corrections were performed across the entire OTU table, but only 439
OTUs that accounted for ≥1% of the bacterial community are reported. OTUs marked with asterisk 440
(*) were observed in 2 or less individuals within the Juvenile_First cohort and thus may reflect 441
random inter-individual variation rather than a cohort-related difference. OTU labels are provided to 442
allow consistency between other tables that report OTU abundances and changes. 443
444
445
on July 7, 2018 by guesthttp://aem
.asm.org/
Dow
nloaded from
Page 18
References 446 1. Lloyd BD, Powlesland RG. 1994. The decline of kakapo Strigops habroptilus and 447 attempts at conservation by translocation. Biol Cons 69:75-85. 448 2. Wood JR. 2006. Subfossil kakapo (Strigops habroptilus) remains from near Gibraltar 449 Rock, Cromwell Gorge, Central Otago, New Zealand. Notornis 53:191-193. 450 3. Clout MN, Merton DV. 1998. Saving the Kakapo: the conservation of the world's most 451 peculiar parrot. Bird Conserv Int 8:281-296. 452 4. Powlesland RG, Merton DV, Cockrem JF. 2006. A parrot apart: the natural history of 453 the kakapo (Strigops habroptilus), and the context of its conservation management. 454 Notornis 53:3-26. 455 5. Eason DK, Elliott GP, Merton DV, Jansen PW, Harper GA, Moorhouse RJ. 2006. 456 Breeding biology of kakapo (Strigops habroptilus) on offshore island sanctuaries, 1990-457 2002. Notornis 53:27-36. 458 6. Merton DV, Morris RB, Atkinson IAE. 1984. Lek behaviour in a parrot: the kakapo 459
Strigops habroptilus of New Zealand. Ibis 126:277-283. 460 7. Moorhouse RJ, Powlesland RG. 1991. Aspects of the ecology of Kakapo Strigops 461
habroptilus liberated on Little Barrier Island (Hauturu), New Zealand. Biol Conserv 462
56:349-365. 463 8. McNab BK, Salisbury CA. 1995. Energetics of New Zealand's temperate parrots. NZ J 464 Zool 22:339-349. 465 9. Atkinson IAE, Merton DV. 2006. Habitat and diet of kakapo (Strigops habroptilis) in the 466 Esperance Valley, Fiordland, New Zealand. Notornis 53:37-54. 467 10. Cockrem JF. 2006. The timing of breeding in the kakapo (Strigops habroptilus). Notornis 468
53:153-159. 469 11. Cottam Y, Merton DV, Hendriks W. 2006. Nutrient composition of the diet of parent-470 raised kakapo nestlings. Notornis 53:90-99. 471 12. Waite DW, Deines P, Taylor MW. 2012. Gut microbiome of the critically endangered 472 New Zealand parrot, the kakapo (Strigops habroptilus). PLoS ONE 7:e35803. 473 13. Clench MH, Mathias JR. 1995. The avian cecum: A review. Wilson Bull. 107:93-121. 474 14. Grajal A, Strahl SD, Pabra R, Dominguez MG, Neher A. 1989. Foregut fermentation in 475 the hoatzin, a neotropical leaf-eating bird. Science 245:1236-1238. 476 15. Oliver WRB. 1955. New Zealand Birds, 2 ed. A.H. & A.W. Reed, Wellington, New Zealand. 477 16. Horrocks M, Salter J, Braggins J, Nichol S, Moorhouse R, Elliott G. 2008. Plant 478 microfossil analysis of coprolites of the critically endangered kakapo (Strigops 479
habroptilus) parrot from New Zealand. Rev Palaeobot Palynol 149:229-245. 480
on July 7, 2018 by guesthttp://aem
.asm.org/
Dow
nloaded from
Page 19
17. Houston D, McInnes K, Elliott G, Eason D, Moorhouse R, Cockrem J. 2007. The use of 481 a nutritional supplement to improve egg production in the endangered kakapo. Biol 482 Conserv 138:248-255. 483 18. Hill MJ. 1997. Intestinal flora and endogenous vitamin synthesis. Eur J Cancer Prev 484
6:S43-S45. 485 19. Turnbaugh PJ, Ley RE, Mahowald MA, Magrini V, Mardis ER, Gordon JI. 2006. An 486 obesity-associated gut microbiome with increased capacity for energy harvest. Nature 487
444:1027-1031. 488 20. Torok VA, Hughes RJ, Mikkelsen LL, Perez-Maldonado R, Balding K, MacAlpine R, 489
Percy NJ, Ophel-Keller K. 2011. Identification and characterization of potential 490 performance-related gut microbiotas in broiler chickens across various feeding trials. 491 Appl Environ Microbiol 77:5868-5878. 492 21. Stanley D, Denman SE, Hughes RJ, Geier MS, Crowley TM, Chen H, Haring VR, Moore 493
RJ. 2012. Intestinal microbiota associated with differential feed conversion efficiency in 494 chickens. Appl Microbiol Biotechnol 96:1361-1369. 495 22. Stappenbeck TS, Hooper LV, Gordon JI. 2002. Developmental regulation of intestinal 496 angiogenesis by indigenous microbes via Paneth cells. Proc Natl Acad Sci U S A 497
99:15451-15455. 498 23. Rahimi S, Grimes JL, Fletcher O, Oviedo E, Sheldon BW. 2009. Effect of a direct-fed 499 microbial (Primalac) on structure and ultrastructure of small intestine in turkey poults. 500 Poult Sci 88:491-503. 501 24. Cao GT, Xiao YP, Yang CM, Chen AG, Liu TT, Zhou L, Zhang L, Ferket PR. 2012. Effects 502 of Clostridium butyricum on growth performance, nitrogen metabolism, intestinal 503 morphology and cecal microflora in broiler chickens. J Anim Vet Adv 11:2665-2671. 504 25. Waite DW, Deines P, Taylor MW. 2013. Quantifying the impact of storage procedures 505 for faecal bacteriotherapy in the critically endangered New Zealand parrot, the kakapo 506 (Strigops habroptilus). Zoo Biol 32:620-625. 507 26. Kohl KD. 2012. Diversity and function of the avian gut microbiota. J Comp Physiol B 508
182:591-602. 509 27. Eason DK, Moorhouse RJ. 2006. Hand-rearing kakapo (Strigops habroptilus), 1997-510 2005. Notornis 53:116-125. 511 28. Tannock GW. 1997. Gastrointestinal Microbiology. Chapman and Hall, New York. 512 29. Dethlefsen L, Huse S, Sogin ML, Relman DA. 2008. The pervasive effects of an 513 antibiotic on the human gut microbiota, as revealed by deep 16S rRNA sequencing. PLoS 514 Biology 6:e22109. 515
on July 7, 2018 by guesthttp://aem
.asm.org/
Dow
nloaded from
Page 20
30. Hammons S, Oh PL, Martínez I, Clark K, Schlegel VL, Sitorius E, Scheideler SE, 516
Walter J. 2010. A small variation in diet influences the Lactobacillus strain composition 517 in the crop of broiler chickens. Syst Appl Microbiol 33:275-281. 518 31. Hill DA, Hoffmann C, Abt MC, Du Y, Kobuley D, Kirn TJ, Bushman FD, Artis D. 2010. 519 Metagenomic analyses reveal antibiotic-induced temporal and spatial changes in 520 intestinal microbiota with associated alterations in immune cell homeostasis. Mucosal 521 Immunol 3:148-158. 522 32. Gong J, Yu H, Liu T, Gill JJ, Chambers JR, Wheatcroft R, Sabour PM. 2008. Effects of 523 zinc bacitracin, bird age and access to range on bacterial microbiota in the ileum and 524 caeca of broiler chickens. J Appl Microbiol 104:1372-1382. 525 33. Godoy-Vitorino F, Goldfarb KC, Brodie EL, Garcia-Amado MA, Michelangeli F, 526
Domínguez-Bello MG. 2010. Developmental microbial ecology of the crop of the 527 folivorous hoatzin. ISME J 4:611-620. 528 34. Lozupone C, Stombaugh JU, Gordon JI, Jansson JK, Knight R. 2012. Diversity, stability 529 and resilience of the human gut microbiota. Nature 489:220 - 230. 530 35. Yatsunenko T, Rey FE, Manary MJ, Trehan I, Dominguez-Bello MG, Contreras M, 531
Magris M, Hidalgo G, Baldassano RN, Anokhin AP, Heath AC, Warner B, Reeder J, 532
Kuczynski J, Caporaso JG, Lozupone CA, Lauber C, Clemente JC, Knights D, Knight R, 533
Gordon JI. 2012. Human gut microbiome viewed across age and geography. Nature 534
486:222 - 227. 535 36. van Dongen WFD, White J, Brandl HB, Moodley Y, Merkling T, Leclaire S, Blanchard 536
P, Danchin É, Hatch SA, Wagner RH. 2013. Age-related differences in the cloacal 537 microbiota of a wild bird species. BMC Ecol 13:11. 538 37. Van Der Wielen PWJJ, Keuzenkamp DA, Lipman LJA, Van Knapen F, Biesterveld S. 539 2002. Spatial and temporal variation of the intestinal bacterial community in 540 commercially raised broiler chickens during growth. Microb Ecol 44:286-293. 541 38. Lu J, Idris U, Harmon B, Hofacre C, Maurer JJ, Lee MD. 2003. Diversity and succession 542 of the intestinal bacterial community of the maturing broiler chicken. Appl Environ 543 Microbiol 69:6816-6824. 544 39. Scupham AJ. 2007. Succession in the intestinal microbiota of preadolescent turkeys. 545 FEMS Microbiol Ecol 60:136-147. 546 40. Stanley D, Geier MS, Hughes RJ, Denman SE, Moore RJ. 2013. Highly variable 547 microbiota development in the chicken gastrointestinal tract. PLoS ONE 8:e84290. 548 41. Simister R, Taylor MW, Tsai P, Fan L, Bruxner TJ, Crowe ML, Webster N. 2012. 549 Thermal stress responses in the bacterial biosphere of the Great Barrier Reef sponge, 550
Rhopaloeides odorabile. Environ Microbiol 14:3232-3246. 551
on July 7, 2018 by guesthttp://aem
.asm.org/
Dow
nloaded from
Page 21
42. Schloss PD, Westcott SL, Ryabin T, Hall JR, Hartmann M, Hollister EB, Lesniewski 552
RA, Oakley BB, Parks DH, Robinson CJ, Sahl JW, Stres B, Thallinger GG, Van Horn 553
DJ, Weber CF. 2009. Introducing mothur: Open-source, platform-independent, 554 community-supported software for describing and comparing microbial communities. 555 Appl Environ Microbiol 75:7537-7541. 556 43. Quince C, Lanzen A, Davenport RJ, Turnbaugh PJ. 2011. Removing noise from 557 pyrosequenced amplicons. BMC Bioinformatics 12. 558 44. Edgar RC, Haas BJ, Clemente JC, Quince C, Knight R. 2011. UCHIME improves 559 sensitivity and speed of chimera detection. Bioinformatics 27:2194-2200. 560 45. Schmitt S, Tsai P, Bell J, Fromont J, Ilan M, Lindquist N, Perez T, Rodrigo A, Schupp 561
PJ, Vacelet J, Webster N, Hentschel U, Taylor MW. 2012. Assessing the complex 562 sponge microbiota: Core, variable and species-specific bacterial communities in marine 563 sponges. ISME J 6:564-576. 564 46. Yue JC, Clayton MK. 2005. A similarity measure based on species proportions. Commun 565 Stat Theory Methods 34:2123-2131. 566 47. Lozupone C, Knight R. 2005. UniFrac: A new phylogenetic method for comparing 567 microbial communities. Appl Environ Microbiol 71:8228-8235. 568 48. Excoffier L, Smouse PE, Quattro JM. 1992. Analysis of molecular variance inferred 569 from metric distances among DNA haplotypes: application to human mitochondrial DNA 570 restriction data. Genetics 131:479 - 491. 571 49. Anderson MJ. 2001. A new method for non-parametric multivariate analysis of 572 variance. Austral Ecol 26:32-46. 573 50. White JR, Magarajan N, Pop M. 2009. Statistical methods for detecting differentially 574 abundant features in clinical metagenomic samples. PLoS Comput Biol 5:e1000352. 575 51. Edgar RC. 2010. Search and clustering orders of magnitude faster than BLAST. 576 Bioinformatics 26:2460 - 2461. 577 52. Bennett DC, Tun HM, Kim JE, Leung FC, Cheng KM. 2013. Characterization of cecal 578 microbiota of the emu (Dromaius novaehollandiae). Vet Microbiol 166:304-310. 579 53. Gong J, Weiduo S, Forster RJ, Huang R, Yu H, Yin Y, Tang C, Han Y. 2007. 16S rRNA 580 gene-based analysis of mucosa-associated bacterial community and phylogeny in the 581 chicken gastrointestinal tracts: from crops to ceca. FEMS Microbiol Ecol 59:147-157. 582 54. Godoy-Vitorino F, Goldfarb KC, Karaoz U, Leal S, Garcia-Amado MA, Hugenholtz P, 583
Tringe SG, Brodie EL, Dominguez-Bello MG. 2012. Comparative analyses of foregut 584 and hindgut bacterial communities in hoatzins and cows. ISME J 6:531-541. 585 55. Shade A, Caporaso JG, Handelsman J, Knight R, Fierer N. 2013. A meta-analysis of 586 changes in bacterial and archaeal communities with time. ISME J 7:1493-1506. 587
on July 7, 2018 by guesthttp://aem
.asm.org/
Dow
nloaded from
Page 22
56. Belden LK, Harris RN. 2007. Infectious diseases in wildlife: the community ecology 588 context. Front Ecol Environ 5:533 - 539. 589 57. Keswani J, Whitman WB. 2001. Relationship of 16S rRNA sequence similarity to DNA 590 hybridization in prokaryotes. Int J Syst Evol Microbiol 51:667-678. 591 58. Stackebrandt E, Ebers J. 2006. Taxonomic parameters revisited: tarnished gold 592 standards. Microbiol Today 33:152-155. 593 59. Koeppel AF, Wu M. 2013. Surprisingly extensive mixed phylogenetic and ecological 594 signals among bacterial Operational Taxonomic Units. Nucleic Acids Res 41:5175-5188. 595
on July 7, 2018 by guesthttp://aem
.asm.org/
Dow
nloaded from
Page 23
on July 7, 2018 by guesthttp://aem
.asm.org/
Dow
nloaded from
Page 24
on July 7, 2018 by guesthttp://aem
.asm.org/
Dow
nloaded from
Page 25
on July 7, 2018 by guesthttp://aem
.asm.org/
Dow
nloaded from
Page 26
Sample Label Individuals Mean Age Sample year Description
Juvenile_First 8 16 days 2011 Faecal sample from wild juvenile kakapo.
Juvenile_Second 10 51 days 2011
Faecal sample from captive juvenile kakapo fed an artificial diet of Lactated Ringer’s solution and fresh fruit. Eight juveniles were also treated with antibiotics during captivity (Augmentin and Clavulox).
Juvenile_Third 5 69 days 2011 Faecal sample from juvenile kakapo ~2.5 weeks following release.
Juvenile_Fourth 8 569 days
2012 Faecal sample from juvenile kakapo during the next round of health screening. At this point individuals were mature, independent birds.
Adult_First 10 - 2011 Faecal sample from wild adult kakapo collected at the same time as Juvenile_First.
Adult_Second 7 - 2012 Faecal sample from wild adult kakapo collected at the same time as Juvenile_Fourth.
on July 7, 2018 by guesthttp://aem
.asm.org/
Dow
nloaded from
Page 27
Juvenile_First Juvenile_Second Juvenile_Third Juvenile_Fourth Hakatere Atareta Atareta Hakatere Ian Hakatere* Ian Ian Ihi Ian* Taonga Ihi Stella Ihi* Tutoko Stella Taonga Stella* Waikawa Tia Tia Taonga* Tutoko Tutoko Tia* Waa Waa Tutoko* Waikawa
Waa* Waikawa
on July 7, 2018 by guesthttp://aem
.asm.org/
Dow
nloaded from
Page 28
Sample Group Good’s
Coverage Shannon Diversity
Shannon Evenness
Simpson Diversity
Chao1 Estimator
ACE Estimator
Reads Mapped (%)
OTUs Mapped (%)
Adult_First 0.995 0.73 0.10 0.63 25.2 38 99.4 46.4
Adult_Second 0.979 1.10 0.15 0.52 100.1 228.8 24.8 8.9
Juvenile_First 0.991 0.90 0.12 0.49 33.3 110.3 95.4 39.0
Juvenile_Second 0.998 0.88 0.12 0.61 9.8 17.4 88.4 53.9
Juvenile_Third 0.984 1.17 0.16 0.42 42.2 224.1 99.0 27.7
Juvenile_Fourth 0.973 0.91 0.12 0.71 152.5 348.7 10.9 7.1
on July 7, 2018 by guesthttp://aem
.asm.org/
Dow
nloaded from
Page 29
OTU Label OTU Taxonomy Overall Adult Juvenile (wild) Juvenile (antibiotics)
OTU01 Escherichia 34.45 38.17 29.03 0.84
OTU02 Unclassified Proteobacteria OTU 42.46
OTU03 Streptococcus 16.33 5.81 31.69 0.89
OTU04 Clostridium 5.73 8.74 1.33
OTU05 Enterococcus 1.04 0.05 37.97
OTU06 Lactobacillus 12.24 9.75
OTU07 Clostridium 7.62
OTU10 Pseudomonas 1.29
OTU11 Lactobacillus 3.20
Total 57.55 52.72 83.25 95.11
on July 7, 2018 by guesthttp://aem
.asm.org/
Dow
nloaded from
Page 30
Mean Relative Abundance (%)
OTU Label OTU Taxonomy Juvenile_First Adult_First q-value
OTU06 Lactobacillus 11.16 0.01 <0.001
OTU07 Clostridium 4.49 0.00 <0.001
OTU10 Pseudomonas 1.41 0.01 <0.001
OTU16 Lactobacillus* 1.91 0.00 <0.001
OTU19 Lactobacillus 2.58 0.01 <0.001
OTU50 Clostridium* 1.78 0.00 <0.001
on July 7, 2018 by guesthttp://aem
.asm.org/
Dow
nloaded from
