Faecal microbiota changes associated with the moult fast in chinstrap and gentoo penguins
Faecal microbiota changes associated with the moult fast in chinstrap and gentoo penguins
Won Young LeeID 0 1
Hyunjun Cho 0 1
Mincheol Kim 0 1
Binu Mani Tripathi 0 1
Jin-Woo Jung 0 1
Hosung Chung 0 1
Jeong-Hoon Kim 0 1
0 Editor: Suzanne Lynn Ishaq, University of Oregon , UNITED STATES
1 Division of Polar Life Sciences, Korea Polar Research Institute , Incheon , Republic of Korea
In many seabirds, individuals abstain from eating during the moult period. Penguins have an intense moult that lasts for weeks, during which they are confined to land. Despite the importance for survival, it is still unclear how the faecal microbiota of Antarctic penguins changes in response to the moult fast. Here, we investigated the faecal microbiota of chinstrap (Pygoscelis antarcticus) and gentoo penguins (Pygoscelis papua) on King George Island, Antarctica. The bacterial community compositions during the feeding and moulting stages were compared for both species using bacterial 16S rRNA gene amplicon on an Illumina MiSeq platform. Our results showed that the moult fast altered the bacterial community structures in both penguin species. Interestingly, the bacterial community composition shifted in the same direction in response to the moult fast but formed two distinct clusters that were specific to each penguin species. A significant increase in bacterial diversity was observed in gentoo penguins, whereas no such change was observed for chinstrap penguins. By analysing the contribution of the ecological processes that determine bacterial community assembly, we observed that processes regulating community turnover were considerably different between the feeding and moulting stages for each penguin. At the phylum level, the relative abundances of Fusobacteria, Firmicutes and Proteobacteria were dominant in chinstrap penguins, and no significant changes were detected in these phyla between the feeding and moulting periods. Our results suggest that moult fast-induced changes in the faecal microbiota occur in both species.
Data Availability Statement: All relevant data are
within the paper and its Supporting Information
Funding: WYL, JWJ, HC, and JHK were supported
by Development of Environmental Monitoring
Techniques of Antarctic Specially Protected Area
(ASPA no. 171) funded by Ministry of Environment
Korea (PG18040) and Korea Polar Research
Institute (PE14290, PE14440). The funders had no
role in study design, data collection and analysis,
decision to publish, or preparation of the
Fasting behaviour is commonly observed in animals. For instance, many mammals hibernate
during the harsh winter when there is no available food supply, whilst seabirds have an
intensive moult-fast period on land to replace their feathers entirely. Especially for moulting birds,
large amounts of energy are required to produce new feathers and to maintain essential
physiological functions. Thus, the moult fast is a stressful period for individuals due to the energetic
Penguins are diving seabirds that also endure an intense moult that is confined to the land
]. Due to the reduced thermal insulation during the moult, penguins must stay on land with
no foraging in the sea. Thus, individuals utilize a large proportion of their body stores during
the moult fast [
]. In Antarctica, because of its cold and harsh environment, penguins are
predicted to be under more stress during the moult fast with respect to thermoregulation and
feather synthesis. Recently, researchers have begun to investigate the gut microorganisms
during the moult in penguins. Dewar et al. [
] examined the faecal bacterial community
composition of penguins in temperate and sub-Antarctic regions during the moult fast including the
little penguin, Eudyptula minor, in Australia and that of the king penguin, Aptenodytes
patagonicus, in South Georgia, respectively. They observed that the community composition of the
gastrointestinal microbiota was altered in both penguin species during fasting.
However, little is known regarding how ecological processes govern the microbial
community in the penguin gut ecosystem. The results of a few studies have indicated how ecological
processes govern the microbial community in the gut ecosystem, and deterministic and
stochastic processes were crucial in determining the composition of microbial communities [
]. Moreover, recent findings suggest that some microbial patterns can also be explained by
the same ecological mechanisms present in plants and animals [
]. In previous studies,
the assembly of ecological communities were shown to be governed by four major processes
(selection, dispersal, drift and mutation/speciation) [
]. When a serious ecological
disturbance occurs, the relative importance of these processes shift significantly within a specific
]. The gut ecosystem of penguins during the moulting period presents unique
features that make it especially attractive for addressing questions regarding the assembly of
microbial communities. Both penguin species investigated in this study are unable to feed
during the moulting period, and their food supply is limited. Because the lack of nutrition will
eventually constrain the microbial community composition, the moulting event will affect the
gut microbes by altering ecological processes for the microbial community in both penguin
In this study, we investigated how the faecal microbiota of Antarctic penguins changes
during the moult-fast period. We assayed two species, the chinstrap penguin, Pygoscelis
antarcticus, and the gentoo penguin, Pygoscelis papua, which are sympatric breeders in the Antarctic
Peninsula. The two penguin species share similar life histories. In our study area, both
penguins are highly dependent on Antarctic krill, Euphausia superba, and during the
chick-rearing period approximately 99% of prey is Antarctic krill [
]). It was previously reported that
different bacterial community compositions are present among four penguin species from
different subfamilies (king, gentoo, macaroni and little penguin [
]), and the authors suggested
that phylogeny and diet could be responsible for these differences. However, it remains
unknown whether closely related penguins with similar dietary habits share faecal
This study focused on two closely related penguin species of the genus Pygoscelis, which
offer an ideal system to assess how the composition of faecal bacterial communities varies
between closely related penguin species with similar dietary preferences during the moult-fast
period. In addition, we investigated the effects of moulting on the major ecological processes
that govern microbial communities in the gut of two closely related penguin species.
Materials and methods
This research was conducted under the approval from the Korean Ministry of Foreign Affairs
and Trade and according to the current laws of the Republic of Korea (?Act on Antarctic
2 / 15
Activities and Protection of Antarctic Environment?, certificate paper number: ILAD-4029
[2012.11.19]). The certificate paper permits conducting research in Antarctic Specially
Protected Area No. 171 (Nar?bski Point) and includes consideration and approval of handling
chinstrap and gentoo penguins for faecal sampling. Local ethics committee from Ministry of
Environment of the Republic of Korea reviewed and approved this work.
All applicable international, national, and/or institutional guidelines for the care and use of
animals were followed.
Study site and sample collection
This study was conducted in a chinstrap and gentoo penguin colony at Nar?bski Point
(Antarctic Specially Protected Area, No. 171; 62?13'40"S-62?14'23"S, 58?45'25"W-58?47'00"W) in
Barton Peninsula on King George Island, Antarctica in January and February 2013. At this
site, there are approximately 3,000 and 2,500 breeding pairs of chinstrap and gentoo penguins,
respectively. For each penguin species, we collected faeces samples on two separate occasions,
the chick-guarding period during feeding (before the moult-fast) and after the chick-rearing
period, which occurs in the middle of the moult period during an approximately 2?3 week
fasting period [
]. Among the breeding adults, seven chinstrap and seven gentoo penguins
were randomly sampled during feeding (10th January of 2013) and six gentoo and five
chinstrap penguins during moulting (12th February), with 25 samples collected in total.
For faecal sampling, each penguin was restrained in a cotton bag with its flippers and legs
held tightly. Sterilized swab were gently inserted approximately 1?2 inches into the cloaca.
After sampling the faeces, the tip of the swab was stored into a 1.5 ml tube, and the tubes were
kept at -20?C.
DNA extraction and PCR amplification
Faecal DNA was extracted using a MO BIO PowerSoil DNA Isolation kit (MoBio Laboratories,
Carlsbad, CA, USA) following manufacturer?s instructions. The isolated DNA was stored at
-80?C in a deep freezer until PCR was performed. The bacterial community structure in each
faeces sample was assessed using an Illumina MiSeq sequencing platform targeting the V3-V4
region of the bacterial 16S rRNA gene, and the community compositions during feeding and
during moulting were compared within and between the two penguin species. The V3-V4
region of the bacterial 16S rRNA gene was amplified using primers the Bakt_341F (5?-CCTA
GGGGNGGCWGCAG-3?) and Bakt_805R (5?-GACTACHVGGGTATCTAATCC-3?) [
along with sequencing primer and adapter sequences for MiSeq sequencing.
Polymerase chain reaction (PCR) was performed in a 25 l? reaction volumes and contained
2.5 ?l of genomic DNA extract, 5 ?l of each primer (1 ?M), 12.5 ?l of KAPA HiFi Hotstart
ReadyMix (Kapa Biosystems Ltd., London, UK). The PCR thermocycling conditions used
were as follows: 95?C for 3 min for an initial denaturation followed by 25 cycles of 95?C for 30
s, 55?C for 30 s, and 72?C for 30 s, with a final extension of 72?C for 5 min. The resultant
amplicons were purified using AMPure XP beads (Beckman Coulter, Indianapolis, IN, USA).
The purified amplicons were indexed using Illumina Nextera XT index kit (Illumina, San
Diego, CA, USA) and then used for paired-end sequencing (2 ? 300 nt) with an Illumina
MiSeq system (Illumina, San Diego, CA, USA).
Data analysis and sequence processing
The paired-end 16S rRNA gene sequences were assembled using the assembler PANDAseq [
Merged reads were processed using mothur [
] following the mothur MiSeq SOP (http://www.
mothur.org/wiki/MiSeq_SOP). The sequences were aligned against the SILVA-aligned reference
3 / 15
sequences and were then further filtered to remove gaps. The sequences were de-noised using
the ?pre.cluster? command in mothur implementation of a pseudo-single linkage pre-clustering
algorithm from Huse and colleagues [
]. Putative chimeric sequences were detected and
removed via the Chimera Uchime algorithm contained within mothur [
] in de novo mode,
which first splits sequences into groups and then checks each sequence within a group using the
more abundant groups as references. Chimera-free sequences were taxonomically classified
down to the genus level based on EzBioCloud 16S database [
]. The quality-filtered sequences
were clustered into operational taxonomic units (OTUs) using an OptiClust algorithm with a
threshold of 97% sequence similarity. Non-bacterial reads assigned to Archaea and Eukaryotes
were excluded, and all of the singleton OTUs were removed from all datasets prior to further
analysis. The MiSeq sequence data used in this study are deposited in the MG-RAST server [
under project ID 84568 (https://www.mg-rast.org/linkin.cgi?project=mgp84568).
Predictive functional profiling by PICRUSt
The potential functional profiles of faecal microbiotas were predicted with PICRUSt v.1.1.0
], which uses an ancestral state reconstruction algorithm to predict metagenomic functional
profiles from 16S rRNA gene sequence data and a reference genome database. An OTU table
that was produced using a closed-reference OTU picking process was used as an input table.
The taxonomic information for each OTU was determined using the Greengenes database
] and then was used to show the relative distribution of shared OTUs. The OTU table
was first normalized by 16S rRNA gene copy number predictions and then the metagenomes
were predicted and summarised at the level 2 KO (KEGG Orthology) category.
All of the samples were standardized by random subsampling to 13,415 sequences per sample
using the ?sub.sample? command in mothur to correct for differences in number of reads
between samples. All bacterial sequences were rarefied to the lowest number of reads
generated from any sample. Bray-Curtis dissimilarities among all sample pairs were calculated on a
Hellinger-transformed OTU abundance matrix. Non-metric multidimensional scaling
(NMDS) was used to visualize the moulting effects on the bacterial community composition of
each penguin group using the ?metaMDS? function in the vegan R package [
]. A centroid in
the ordination space was calculated and ellipses illustrating standard deviations of the
community structures within each stage were drawn using the ?ordiellipse? function in R. The program
STAMP (version 2.1.3) was used to test for significant differences in the functional profiles
between different treatment groups [
]. Welch?s t-test  was performed to compare
functional profiles between two different treatment groups along with effect size measures and
confidence intervals set to 95%.
Permutational multivariate analysis of variance (PERMANOVA), a semiparametric
multivariate test, was used to assess differences in bacterial community structure between the
chinstrap and gentoo penguins during feeding and moulting using PRIMER 6 & PERMANOVA+
]. Species (chinstrap and gentoo) and stage (feeding and moulting) were included as fixed
factors, and p-values were obtained using 999 permutations. Welch?s two sample t-tests were
used to compare the feeding and moulting groups with respect to bacterial diversity and
relative abundance for the two penguin species.
To estimate the relative influence of stochastic and deterministic processes, we employed a
phylogenetic null modelling approach to calculate ?-nearest taxon index (?NTI). ?NTI is the
4 / 15
difference between the observed ?-mean nearest taxon distance (?MNTD) and the mean of the
null distribution of ?MNTD normalized by its standard deviation, and calculated using ?Picante?
R package and custom scripts as described earlier [
]. ?NTI values greater than +2 and less
than -2 indicate dominance of variable (more than expected phylogenetic turnover) and
homogenous selection (less than expected phylogenetic turnover), respectively; and values between +2
and -2 indicate dominance of stochastic processes. We employed a second null model in
combination with ?NTI referred as Bray-Curtis-based Raup-Crick (RCbray) as described by Stegen
et al.  to further partitioned stochastic processes into homogenizing dispersal, dispersal
limitation and undominated process (drift was referred to as ?undominated? processes in Stegen
et al. [
]). The percentage of pairwise comparisons with |?NTI| < 2 but RCbray > +0.95 or <
?0.95 indicate the relative influences of dispersal limitation or homogenizing dispersal,
respectively. On the other hand, the fraction of pairwise comparisons with |?NTI| < ?2 and |RCbray| <
0.95 indicate that the shift in community composition is resulted due to random drift.
A total of 1,516,737 high quality 16S rRNA gene sequences that were assigned to 19,990
operational taxonomic units (OTUs) at > 97% similarity level from 27 samples after the removal of
low quality and chimeric sequences. The bacterial read numbers and OTU richness in each
sample are shown in the supplementary material (S1 Table).
Faecal bacterial communities were distinctly structured by both factors (penguin species
and moult stage), and although the bacterial community structures shifted in the same
direction along the first NMDS axis in both penguin species, two distinct clusters specific to each
penguin species formed, suggesting a potential interaction effect of species ? moult (Table 1,
PERMANOVA, p = 0.006 for interaction of Species ? Moult stage; see NMDS plot in Fig 1).
Shannon?s diversity index, which measures the number of species and takes into account
species evenness, indicated that bacterial diversity did not change during the moult in
chinstrap penguins (Welch?s two sample t-test, t = -1.61, df = 10.36, p = 0.14; Fig 2) but increased
in gentoo penguins (Welch?s two sample t-test, t = -2.89, df = 6.91, p = 0.02; Fig 2).
By further quantifying the relative contributions of major ecological processes that structure
faecal microbiota, we observed that the processes regulating community turnover differ
considerably between the feeding and moulting stages for each penguin species (Fig 3). Generally,
the contributions of specific ecological processes showed similar patterns for both the feeding
and moulting stages in each species, but the magnitude of these contributions differed between
the two species. Variable selection was more pronounced in the feeding stage (chinstrap
penguins: 52.38%; gentoo penguins: 85.71%), whereas drift played an important role in the
assembly of the faecal microbiota at moulting stage in both penguin species (chinstrap: 46.67%;
Fig 1. NMDS plot of faecal bacterial community structures in chinstrap penguin and gentoo penguins during feeding and moulting. The bacterial structures formed
distinct clusters specific to each penguin species but shifted in the same direction (chinstrap penguin during feeding (n = 7) and moulting (n = 6) and gentoo penguins
during feeding (n = 7) and moulting (n = 5)); PERMANOVA, df = 1, mean square = 6069.3, Pseudo F = 1.92, p = 0.006 for interaction of Species ? Moult stage). Samples
were grouped by ellipses enclosing all points in each group using the ?ordiellipse? function in the vegan R package.
The relative abundances of major bacterial phyla, which represented more than 99% of all
sequences, are presented in Fig 4. In chinstrap penguins, Fusobacteria (64.69 and 55.28%),
Firmicutes (14.84 and 32.17%), and Proteobacteria (19.42 and 9.32%) were observed to be
abundant during feeding and moulting, respectively. No significant differences were observed in
the abundances of these phyla between the two stages (t-test, all p > 0.05). In the gentoo
penguins, Fusobacteria (64.92 and 38.53%), Firmicutes (17.31 and 45.09%), Proteobacteria (16.69
and 10.21%), and Bacteroidetes (0.21 and 4.95%) were dominant in samples from both the
feeding and moulting stages, respectively. Among these phyla, the relative abundance of
Firmicutes during the moulting stage compared to the feeding stage was significantly increased
(t6 / 15
Fig 2. Bacterial diversity (Shannon index) in chinstrap (left) and gentoo penguins (right) during the feeding and moulting stages. The lower quartiles represent 25%
of data and the upper quartiles represent 75% of data. The asterisk indicates the significant difference between the feeding and moulting gentoo penguin groups (p < 0.05).
test, t = 0.52, p = 0.04), while that of Fusobacteria was decreased (t-test, t = 0.51, p = 0.02) (Fig
4B). The relative abundances of the dominant families observed are presented in Fig 5. In the
chinstrap penguins, Fusobacteriaceae (64.68 and 55.26%), Lachnospiraceae (0.24 and 15.19%),
Clostridiaceae (9.23 and 9.68%), Peptostreptococcaceae (4.56 and 3.08%), and Pasteurellaceae
(12.90 and 0.69%) were detected in samples from the feeding and moulting stages, respectively.
Among these, only Pasteurellaceae decreased significantly after moulting (t-test, t = 0.51,
p = 0.03). In the gentoo penguins, Fusobacteriaceae (64.92 and 38.51%), Lachnospiraceae (1.53
and 28.73%), Peptostreptococcaceae (12.48 and 2.68%), Clostridiaceae (1.40 and 10.77%), and
Pasteurellaceae (7.51 and 0.37%) were detected during feeding and moulting, respectively.
Among these taxa, the abundance of Lachnospiraceae increased significantly after moulting
(ttest, t = 0.50, p < 0.001), whereas that of Pasteurellaceae decreased significantly after moulting
(t-test, t = 0.51, p = 0.02). The taxonomic profiles at the genus levels of chinstrap and gentoo
penguins, which are belonging to the major families, were provided in the supplementary
material (S1 Fig).
The PICRUSt results revealed the predicted functional pathway changes during penguin
feeding and moulting (S2 Fig and S1 Table). In the chinstrap penguins, the relative abundances
7 / 15
Fig 3. Summary of the contributions of the ecological processes that determine bacterial community assembly of the faecal microbiota in chinstrap and gentoo
penguins. The percent of turnover in bacterial community assembly was governed by various deterministic (homogeneous and variable selection) and stochastic processes
(dispersal limitation, homogenizing dispersal and drift).
of the membrane transport and metabolism functional pathways decreased, whereas that of
transport and catabolism, folding, sorting and degradation, glycan biosynthesis and
Fig 4. Relative abundances of dominant bacterial phyla in the chinstrap (a) and gentoo penguin (b) faecal bacterial communities
during feeding (empty bar) and moulting (grey bar). The relative abundances of major phyla (upper) and genera (bottom) accounted
for more than 99% of total number of OTUs (chinstrap penguin, feeding (n = 7) and moulting (n = 6); gentoo penguin, feeding (n = 7)
and moulting (n = 5); t-tests, asterisks indicate significance with a p-value of less than 0.05).
8 / 15
Fig 5. Relative abundances of dominant bacterial families in the chinstrap (a) and gentoo penguin (b) faecal
bacterial communities during feeding (empty bar) and moulting (grey bar). The relative abundances of major phyla
(upper) and genera (bottom) accounted for more than 99% of total number of OTUs (chinstrap penguin, feeding
(n = 7) and moulting (n = 6); gentoo penguin, feeding (n = 7) and moulting (n = 5); t-tests, asterisks mean significance
of p-value less than 0.05).
metabolism and cellular processes and signalling increased. In the gentoo penguins, the
relative abundances of many metabolic pathways decreased, including, cell mobility, amino acid
metabolism, biosynthesis of other secondary metabolites, carbohydrate metabolism and lipid
metabolism. In contrast, the relative abundances of other pathways increased, including
genetic information processing, translation, nucleotide metabolism, replication and repair,
folding, and sorting and degradation.
In our study, the bacterial faecal community structures between chinstrap and gentoo
penguins were observed to be significantly different between the feeding and moulting stages. The
results of previous studies of the faecal bacteria of penguins also indicated the interspecific
differences (king, gentoo, macaroni and little penguins [
]) at different habitats. In this study,
the chinstrap and gentoo penguins studied are close sympatric breeders in the same genus
(Pygoscelis) and share very similar food sources (this population exclusively feeds on Antarctic
krill, E. superba [
]). Despite the close phylogenetic relationship and similar diet, the two
penguin species exhibited different faecal bacterial communities during the feeding and moulting
stages (Fig 1).
By evaluating OTU richness, we detected a significant increase in bacterial diversity in
gentoo but not chinstrap penguins during the moulting stage. This result may have occurred from
the abundances of the dominant bacterial taxa having decreased due to resource depletion
during feeding, allowing other minor taxa to have increased in abundance during the moulting
stage. Increased microbial diversity resulting from fasting has been reported in various taxa
]; pythons [
]; tilapia, toads, and mice [
]), but it has been shown that this is
not a universal effect across taxa [
]. Fasting may also decrease microbial density resulting
from decreased levels of food in the gut (hamsters [
]; reindeers [
]) and reduced intestinal
size (blackcaps, Sylvia atricapilla [
] and domestic broilers [
]). Thus limited nutrient
availability may promote increased competition among taxa and result in increased bacterial
By quantifying the relative contributions of ecological processes that structure faecal
microbiota in both investigated penguin species, we observed that processes regulating community
turnover differed considerably by moulting period. Generally, variable selection and drift are
two major ecological processes that structure faecal microbiota in these closely related
Antarctic penguin species. The selection process was pronounced during the feeding period (before
moulting) in both penguin species, while drift play an important role in the assembly of the
9 / 15
gut microbiota during the moulting period. One of the possible explanations of these findings
could be that nutrient poor conditions in gut of moulting penguins reduced abundance of gut
microbiota and that communities with smaller population sizes were more susceptible to drift
]. However, the causes of variation in the magnitude of the contribution of ecological
processes that determine community assembly of the gut microbiota in both penguins are
unclear. Because both penguin species share similar diets, this variation may be due to the
different roles of bacterial taxa that dominated in each penguin species.
The relative abundances of dominant bacterial phyla or families showed distinct patterns in
each penguin species. At the phylum level, no significant changes were observed in the faecal
microbiota of the chinstrap penguins between the two sampling periods. However, the relative
abundance of Firmicutes increased and that of Proteobacteria decreased in gentoo penguins
after moulting. This result was not observed in previous studies of king and little penguins [
At the family level, Pasteurellaceae, which belong to the phylum Proteobacteria, decreased
during the moult in both species (chinstrap penguins, 12.90 to 0.69%; gentoo penguins, 7.51 to
0.37%). Pasteurellaceae is a large group of gram-negative chemoorganotrophic, facultatively
anaerobic, and fermentative bacteria [
]. During the moult, the growth of
chemoorganotrophic bacteria could be negatively affected by the limited food supply. Fusobacteriaceae and
Clostridiaceae, two primary families in both species, are widely known pathogens in
vertebrates and were both reported to be abundant in the guts of black and turkey vultures [
]. Both vultures and alligators feed on decaying prey. Interestingly, genes
encoding tissue-degrading enzymes were detected in the gut metagenome of the turkey vulture [
Furthermore, by outcompeting other bacteria, these bacterial families may contribute to the
carrion digestion while tolerating bacterial toxins [
]. We speculate that these bacteria
may play roles in digesting remained food in the gut under restricted food conditions but the
mechanisms may differ from that of the scavenging birds.
In contrast, the abundance of the family Lachnospiraceae, which belong to the phylum
Firmicutes, increased during the moult for both species, but was only significant for the gentoo
penguins (chinstrap penguins, 0.24 to 15.19%; gentoo penguins, 1.53 to 28.73%).
Lachnospiraceae is a family of bacteria in the order Clostridiales that is commonly present in chicken caeca
] and produce butyric acid in human [
]. The results of a recent study showed that dietary
sodium butyrate improves intestinal development in broilers and functions by modulating the
microbial community [
]. Moreover, it has been increasing identified that a higher level of
Lachnospiraceae stabilizes the intestinal environment by retarding the accumulation of lactate
]. The growth of Lachnospiraceae bacteria family during the moulting period could be
positively affected by the limitation of food supply. For both penguin species, the phyla
Fusobacteria, Firmicutes, Proteobacteria, Bacteroidetes and Tenericutes were dominant (more than
99% of sequences) in the feeding stage samples. These results agree with those obtained for the
faecal bacterial compositions of king, gentoo, macaroni and little penguins (Bacteroidetes,
Firmicutes, Proteobacteria, and Fusobacteria ; S2 Table) and the stomach bacterial
compositions of chinstrap and Adelie penguins (Fusobacteria, Firmicutes, Tenericutes and
]; S2 Table). The major bacterial phyla associated with penguins have been
reported to be distinct from those of other birds. While Fusobacteria is commonly detected as
a major taxon in penguin studies during breeding season (S2 Table), including in this study,
the shared major bacterial phyla in wild birds are Firmicutes, Proteobacteria, Bacteroidetes and
]. It may be that the distinctive dominance of Fusobacteria in penguins has
an important role in penguin biology. Interestingly, members of the phylum Fusobacteria are
known butyrate-producing bacteria, and their ecological importance was discussed in previous
studies for fatty acid metabolism during the moult fast [
] and for chick survival at early
10 / 15
growing stages [
]. Thus, Fusobacteria is also regarded to be an important bacterial taxon that
affect gentoo and chinstrap penguins during the feeding and moulting stages.
What are the mechanisms that cause the observed changes in penguin faecal bacterial
communities during the moult fast? The initial step is the lack of a food supply by the host animals,
which may provide different environmental conditions for bacteria. During the moulting
period, the penguins excrete greenish liquid faeces, the colour of which is due to bile [
environmental change could decrease the dominant bacterial taxa during feeding and increase
those that prefer the environmental conditions of the gut during moulting. In this study, we
suggest that fasting behaviour involves changes faecal microbiota. However, the hormonal
changes and immune responses in penguins during this period have yet to be elucidated, and
these data may provide important information on why such bacterial changes occur.
The PICRUSt results showed the functional pathway changes that occurred during the two
sample periods, and both species exhibited decreases in metabolic pathways (membrane
transport and metabolism in chinstrap penguins; amino acid metabolism, biosynthesis of other
secondary metabolites, carbohydrate metabolism and lipid metabolism in gentoo penguins) and
increases in biosynthetic replication and repair pathways (folding, sorting and degradation in
chinstrap penguins; replication and repair, folding, sorting and degradation in gentoo
penguins) during the moult. This result may indicate that faecal bacteria were under low-nutrient
conditions with no external energy supply and the presence of bile acids, which influence the
pH in the gut. The results of a previous metagenomics study showed that starvation may
induce the enrichment of microbial genes related to antibiotic activity and host genes related
to the immune system [
]. However, it should be noted that these changes may not reflect
changes in gene expression, due to the limitation of the computational predictions and the
expected modelling using a reference genome database.
In summary, we observed that the moult-fast altered the faecal bacterial community
structure of two Antarctic penguin species. In response to the moult-fast period, the bacterial
community composition shifted in the same direction but formed two distinct clusters specific to
each species of penguin. However, increased bacterial diversity was only detected in the gentoo
penguins, suggesting that moult-fast periods in penguin species can change the faecal
microbiota and that specific bacterial phyla or families may play roles in determining the bacterial
community structure in both the pre-moult and post-moult periods. Moreover, although the
contribution of the ecological processes that determine gut microbiota community assembly
in both penguin species showed similar patterns, the magnitude of these contributions were
different between the two species. This result might be due to the specific roles of dominant
bacterial taxa in each species.
In future studies, metagenomic analyses will be necessary to reveal the functional roles of
microorganisms in moulting penguins. Penguins also have a fasting period during incubation,
and male king penguins were observed to maintain a pH value at 6 and reduced gastric
motility throughout the three-week incubation fasting period to preserve stomach contents [
Thus, it would be interesting to study how gut microbiota changes with other fasting periods.
S1 Fig. Taxonomic profiles at the genus levels of chinstrap and gentoo penguin faecal bacterial
communities during feeding and moulting, belonging to the major families (A)
Fusobacteriaceae, (B) Lachnospiraceae, (C) Peptostreptococcaceae, (D) Clostridiaceae, and (E)
11 / 15
S2 Fig. Predicted functional pathway changes during feeding (green bar) and moulting
(yellow bar) by PICRUSt in gentoo (A) and chinstrap (B) penguins.
S1 Table. Summary of sample information and MiSeq amplicon sequencing results across
S2 Table. Summary of previous studies on penguin gut microbiota.
We thank logistic help from overwintering members at King Sejong Station during the field
Data curation: Hyunjun Cho, Jin-Woo Jung, Jeong-Hoon Kim.
Formal analysis: Won Young Lee, Hyunjun Cho, Mincheol Kim, Binu Mani Tripathi.
Funding acquisition: Hosung Chung, Jeong-Hoon Kim.
Methodology: Jin-Woo Jung, Jeong-Hoon Kim.
Software: Hyunjun Cho.
Supervision: Won Young Lee.
Writing ? original draft: Won Young Lee, Hyunjun Cho.
Writing ? review & editing: Jeong-Hoon Kim.
12 / 15
13 / 15
Welch BL. The generalization of student?s? problem when several different population variances are
involved. Biometrika. 1947; 34(1/2):28?35. PMID: 20287819
14 / 15
1. Cherel Y , Charrassin JB , Challet E . Energy and protein requirements for molt in the king penguin Aptenodytes patagonicus . Am J Physiol Regul Integr Comp Physiol . 1994 ; 266 ( 4 ): R1182 - R8 . https://doi. org/10.1152/ajpregu. 1994 . 266 .4. R1182 PMID : 8184961 .
2. Green JA , Butler PJ , Woakes AJ , Boyd IL . Energetics of the moult fast in female macaroni penguins Eudyptes chrysolophus . J Avian Biol . 2004 ; 35 ( 2 ): 153 - 161 . https://doi.org/10.1111/j.0908- 8857 . 2004 . 03138 .x
3. Croxall JP . Energy costs of incubation and moult in petrels and penguins . J Anim Ecol . 1982 ; 51 ( 1 ): 177 - 194 . https://doi.org/10.2307/4318
4. Groscolas R . Changes in plasma lipids during breeding, molting, and starvation in male and female emperor penguins (Aptenodytes forsteri) . Physiol Biochem Zool . 1982 ; 55 ( 1 ): 45 - 55 . https://doi.org/10. 1086/physzool.55.1. 30158442
5. Strange IJ . Breeding ecology of the rockhopper penguin (Eudyptes crestatus) in the Falkland Islands . Gerfaut. 1982 .
6. Sparks J , Soper T . Penguins: Taplinger; 1967 .
7. Dewar ML , Arnould JPY , Krause L , Trathan P , Dann P , Smith SC . Influence of fasting during moult on the faecal microbiota of penguins . PLoS One . 2014 ; 9 ( 6 ):e99996. https://doi.org/10.1371/journal.pone. 0099996 PMID: 24979619
8. Dethlefsen L , Eckburg PB , Bik EM , Relman DA . Assembly of the human intestinal microbiota . Trends Ecol Evol . 2006 ; 21 ( 9 ): 517 - 523 . https://doi.org/10.1016/j.tree. 2006 . 06 .013 PMID: 16820245
9. Yan Q , van der Gast CJ , Yu Y. Bacterial community assembly and turnover within the intestines of developing zebrafish . PLoS One . 2012 ; 7 ( 1 ):e30603. https://doi.org/10.1371/journal.pone. 0030603 PMID: 22276219
10. Stegen JC , Lin X , Konopka AE , Fredrickson JK . Stochastic and deterministic assembly processes in subsurface microbial communities . ISME J . 2012 ; 6 : 1653 - 1664 . https://doi.org/10.1038/ismej. 2012 .22 PMID: 22456445
11. Wang J , Shen J , Wu Y , Tu C , Soininen J , Stegen JC , et al. Phylogenetic beta diversity in bacterial assemblages across ecosystems: deterministic versus stochastic processes . ISME J . 2013 ; 7 : 1310 - 1321 . https://doi.org/10.1038/ismej. 2013 .30 PMID: 23446837
12. Zhou J , Deng Y , Zhang P , Xue K , Liang Y , Van Nostrand JD , et al. Stochasticity, succession, and environmental perturbations in a fluidic ecosystem . Proc Natl Acad Sci . 2014 ; 111 ( 9 ) E836 - E845 . https:// doi.org/10.1073/pnas.1324044111 PMID: 24550501
13. Vellend M . Conceptual synthesis in community ecology . Q Rev Biol . 2010 ; 85 ( 2 ): 183 - 206 . https://doi. org/10.1086/652373. PMID: 20565040
14. Hanson CA , Fuhrman JA , Horner-Devine MC , Martiny JBH . Beyond biogeographic patterns: processes shaping the microbial landscape . Nat Rev Microbiol . 2012 ; 10 : 497 - 506 . https://doi.org/10.1038/ nrmicro2795 PMID: 22580365
15. Ferrenberg S , O'Neill SP , Knelman JE , Todd B , Duggan S , Bradley D , et al. Changes in assembly processes in soil bacterial communities following a wildfire disturbance . ISME J . 2013 ; 7 : 1102 - 1111 . https://doi.org/10.1038/ismej. 2013 .11 PMID: 23407312
16. Kokubun N , Takahashi A , Mori Y , Watanabe S , Shin H-C. Comparison of diving behavior and foraging habitat use between chinstrap and gentoo penguins breeding in the South Shetland Islands, Antarctica . Mar Biol . 2010 ; 157 ( 4 ): 811 - 825 . https://doi.org/10.1007/s00227-009-1364-1
17. Dewar ML , Arnould JPY , Dann P , Trathan P , Groscolas R , Smith S . Interspecific variations in the gastrointestinal microbiota in penguins . Microbiologyopen . 2013 ; 2 ( 1 ): 195 - 204 . https://doi.org/10.1002/ mbo3.66 PMID: 23349094
18. Williams TD . Annual variation in breeding biology of gentoo penguins, Pygoscelis papua , at Bird Island, South Georgia. J Zool . 1990 ; 222 ( 2 ): 247 - 258 . https://doi.org/10.1111/j.1469- 7998 . 1990 .tb05675.x
19. Williams T , Boersma P . Magellanic penguin: The penguins . Oxford University Press, Oxford; 1995 . 249 -258 p.
20. Huse SM , Dethlefsen L , Huber JA , Welch DM , Relman DA , Sogin ML . Exploring microbial diversity and taxonomy using SSU rRNA hypervariable tag sequencing . PLoS Genet . 2008 ; 4 ( 11 ):e1000255. https:// doi.org/10.1371/journal.pgen. 1000255 PMID: 19023400
21. Masella AP , Bartram AK , Truszkowski JM , Brown DG , Neufeld JD . PANDAseq: paired-end assembler for illumina sequences . BMC Bioinformatics . 2012 ; 13 ( 1 ): 31 . https://doi.org/10.1186/ 1471 -2105-13-31
22. Schloss PD , Westcott SL , Ryabin T , Hall JR , Hartmann M , Hollister EB , et al. Introducing mothur: opensource, platform-independent, community-supported software for describing and comparing microbial communities . Appl Environ Microbiol . 2009 ; 75 ( 23 ): 7537 - 7541 . https://doi.org/10.1128/AEM.01541-09 PMID: 19801464
23. Huse SM , Welch DM , Morrison HG , Sogin ML . Ironing out the wrinkles in the rare biosphere through improved OTU clustering . Environ Microbiol . 2010 ; 12 ( 7 ): 1889 - 1898 . https://doi.org/10.1111/j.1462- 2920 . 2010 . 02193 . x PMID : 20236171
24. Edgar RC , Haas BJ , Clemente JC , Quince C , Knight R. UCHIME improves sensitivity and speed of chimera detection . Bioinformatics . 2011 ; 27 ( 16 ): 2194 - 2200 . https://doi.org/10.1093/bioinformatics/btr381 PMID: 21700674
25. Yoon S-H , Ha S-M , Kwon S , Lim J , Kim Y , Seo H , et al. Introducing EzBioCloud: a taxonomically united database of 16S rRNA gene sequences and whole-genome assemblies . Int J Syst Evol Microbiol . 2017 ; 67 ( 5 ): 1613 - 1617 . Epub 2017/05/30. https://doi.org/10.1099/ijsem.0.001755 PMID: 28005526 .
26. Meyer F , Paarmann D , D'Souza M , Olson R , Glass EM , Kubal M , et al. The metagenomics RAST server-a public resource for the automatic phylogenetic and functional analysis of metagenomes . BMC Bioinformatics . 2008 ; 9 ( 1 ): 386 . https://doi.org/10.1186/ 1471 -2105-9-386
27. Langille MGI , Zaneveld J , Caporaso JG , McDonald D , Knights D , Reyes JA , et al. Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences . Nat Biotechnol . 2013 ; 31 : 814 . https://doi.org/10.1038/nbt.2676 PMID: 23975157
28. DeSantis TZ , Hugenholtz P , Larsen N , Rojas M , Brodie EL , Keller K , et al. Greengenes, a chimerachecked 16S rRNA gene database and workbench compatible with ARB . Appl Environ Microbiol . 2006 ; 72 ( 7 ): 5069 - 5072 . https://doi.org/10.1128/AEM.03006-05 PMID: 16820507
29. Oksanen J , Blanchet FG , Kindt R , Legendre P , O'hara R , Simpson GL , et al. vegan: community ecology package . R package version 1 . 17 - 2 . 2010 ; 23 : 2010 .
30. Parks DH , Tyson GW , Hugenholtz P , Beiko RG . STAMP: statistical analysis of taxonomic and functional profiles . Bioinformatics . 2014 ; 30 ( 21 ): 3123 - 3124 . https://doi.org/10.1093/bioinformatics/btu494 PMID: 25061070
32. Clarke K , Gorley RJP -E, Plymouth. Primer. 2006 .
33. Stegen JC , Lin X , Fredrickson JK , Chen X , Kennedy DW , Murray CJ , et al. Quantifying community assembly processes and identifying features that impose them . ISME J . 2013 ; 7: 2069 - 2079 . https:// doi.org/10.1038/ismej. 2013 .93 PMID: 23739053
34. Tripathi BM , Stegen JC , Kim M , Dong K , Adams JM , Lee YK . Soil pH mediates the balance between stochastic and deterministic assembly of bacteria . ISME J . 2018 ; 12 : 1072 - 1083 . https://doi.org/10. 1038/s41396-018 -0082-4 PMID: 29515169
35. Stegen JC , Lin X , Fredrickson JK , Konopka AE . Estimating and mapping ecological processes influencing microbial community assembly . Front Microbiol . 2015 ; 6 : 370 . https://doi.org/10.3389/fmicb. 2015 . 00370 PMID: 25983725
36. Sonoyama K , Fujiwara R , Takemura N , Ogasawara T , Watanabe J , Ito H , et al. Response of gut microbiota to fasting and hibernation in Syrian hamsters . Appl Environ Microbiol . 2009 ; 75 ( 20 ): 6451 . https:// doi.org/10.1128/AEM.00692-09 PMID: 19700553
37. Costello EK , Gordon JI , Secor SM , Knight R . Postprandial remodeling of the gut microbiota in Burmese pythons . ISME J . 2010 ; 4 : 1375 . https://doi.org/10.1038/ismej. 2010 .71 PMID: 20520652
38. Kohl KD , Amaya J , Passement CA , Dearing MD , McCue MD . Unique and shared responses of the gut microbiota to prolonged fasting: a comparative study across five classes of vertebrate hosts . FEMS Microbiol Ecol . 2014 ; 90 ( 3 ): 883 - 894 . https://doi.org/10.1111/ 1574 - 6941 .12442 PMID: 25319042
39. Aagnes TH , S?rmo W , Mathiesen SD . Ruminal microbial digestion in free-living, in captive lichen-fed, and in starved reindeer (Rangifer tarandus tarandus) in winter . Appl Environ Microbiol . 1995 ; 61 ( 2 ): 583 . PMID: 7574599
40. Karasov William H , Pinshow B , Starck JM , Afik D . Anatomical and histological changes in the alimentary tract of migrating blackcaps (Sylvia atricapilla): A comparison among fed, fasted, food-restricted, and refed birds . Physiol Biochem Zool . 2004 ; 77 ( 1 ): 149 - 160 . https://doi.org/10.1086/381465 PMID: 15057725
41. Thompson KL , Applegate TJ . Feed withdrawal alters small-intestinal morphology and mucus of broilers . Poult Sci . 2006 ; 85 ( 9 ): 1535 - 1540 . https://doi.org/10.1093/ps/85.9.1535 PMID: 16977838
42. Vellend M , Srivastava DS , Anderson KM , Brown CD , Jankowski JE , Kleynhans EJ et al. Assessing the relative importance of neutral stochasticity in ecological communities . Oikos . 2014 ; 123 : 1420 - 1430 . https://doi.org/10.1111/oik.01493
43. Evans S , Martiny JB , Allison SD . Effects of dispersal and selection on stochastic assembly in microbial communities . ISME J . 2017 ; 11 : 176 - 185 . https://doi.org/10.1038/ismej. 2016 .96 PMID: 27494293
44. Pohl S. DNA relatedness among members of Haemophilus, Pasteurella and Actinobacillus . In: Donachie W, Lainson FA , Hodgson JC , editors. Haemophilus, Pasteurella and Actinobacillus . London: Academic Press; 1981 . pp. 245 - 253 .
45. Roggenbuck M , Baerholm Schnell I , Blom N , Baelum J , Bertelsen MF , Sicheritz-Ponte?n T , et al. The microbiome of New World vultures. Nat Commun . 2014 ; 5 : 5498 . https://doi.org/10.1038/ncomms6498 PMID: 25423494
46. Keenan SW , Engel AS , Elsey RM . The alligator gut microbiome and implications for archosaur symbioses . Sci Rep . 2013 ; 3 : 2877 . https://doi.org/10.1038/srep02877 PMID: 24096888
47. Hird SM . Evolutionary biology needs wild microbiomes . Front Microbiol . 2017 ; 8 ( 725 ). https://doi.org/ 10.3389/fmicb. 2017 .00725
48. Torok VA , Hughes RJ , Mikkelsen LL , Perez-Maldonado R , Balding K , MacAlpine R , et al. Identification and characterization of potential performance-related gut microbiotas in broiler chickens across various feeding trials . Appl Environ Microbiol . 2011 ; 77 ( 17 ): 5868 . https://doi.org/10.1128/AEM.00165-11 PMID: 21742925
49. Meehan CJ , Beiko RG . A phylogenomic view of ecological specialization in the Lachnospiraceae, a family of digestive tract-associated bacteria . Genome Biol Evol . 2014 ; 6 ( 3 ): 703 - 713 . https://doi.org/10. 1093/gbe/evu050 PMID: 24625961
50. Wu W , Xiao Z , An W , Dong Y , Zhang B. Dietary sodium butyrate improves intestinal development and function by modulating the microbial community in broilers . PLoS One . 2018 ; 13 ( 5 ):e0197762. https:// doi.org/10.1371/journal.pone. 0197762 PMID: 29795613
51. Roesch LFW , Lorca GL , Casella G , Giongo A , Naranjo A , Pionzio AM , et al. Culture-independent identification of gut bacteria correlated with the onset of diabetes in a rat model . ISME J . 2009 ; 3 : 536 . https:// doi.org/10.1038/ismej. 2009 .5 PMID: 19225551
52. Koh A , De Vadder F , Kovatcheva-Datchary P , Ba? ckhed F. From dietary fiber to host physiology: shortchain fatty acids as key bacterial metabolites . Cell . 2016 ; 165 ( 6 ): 1332 - 1345 . https://doi.org/https://doi. org/10.1016/j.cell. 2016 . 05 .041 PMID: 27259147
53. Yew WC , Pearce DA , Dunn MJ , Samah AA , Convey P . Bacterial community composition in Ade?lie (Pygoscelis adeliae) and Chinstrap (Pygoscelis antarctica) Penguin stomach contents from Signy Island, South Orkney Islands . Polar Biol . 2017 ; 40 ( 12 ): 2517 - 2530 . https://doi.org/10.1007/s00300-017- 2162-8
54. Grond K , Sandercock BK , Jumpponen A , Zeglin LH . The avian gut microbiota: community, physiology and function in wild birds . J Avian Biol . 2018 ; 49 ( 11 ):e01788. https://doi.org/10.1111/jav.01788
55. Dewar ML , Arnould JPY , Allnutt TR , Crowley T , Krause L , Reynolds J , et al. Microbiota of little penguins and short-tailed shearwaters during development . PLoS One . 2017 ; 12 ( 8 ):e0183117. https://doi.org/10. 1371/journal.pone. 0183117 PMID: 28806408
56. Lee WY . Avian gut microbiota and behavioral studies . Korean J Ornithol . 2015 ; 22 ( 1 ): 1 - 11 .
57. Xia JH , Lin G , Fu GH , Wan ZY , Lee M , Wang L , et al. The intestinal microbiome of fish under starvation . BMC Genomics . 2014 ; 15 ( 1 ): 266 . https://doi.org/10.1186/ 1471 -2164-15-266
58. Thouzeau C , Peters G , Le Bohec C , Le Maho Y. Adjustments of gastric pH, motility and temperature during long-term preservation of stomach contents in free-ranging incubating king penguins . J Exp Biol . 2004 ; 207 ( 15 ): 2715 . https://doi.org/10.1242/jeb.01074.