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The gut microbiome correlates with conspecific aggression in a small population of rescued dogs (Canis familiaris)


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Aggression is a serious behavioral disorder in domestic dogs that endangers both dogs and humans. The underlying causes of canine aggression are poorly resolved and require illumination to ensure effective therapy. Recent research links the compositional diversity of the gut microbiome to behavioral and psychological regulation in other mammals, such as mice and humans. Given these observations, we hypothesized that the composition of the canine gut microbiome could associate with aggression. We analyzed fecal microbiome samples collected from a small population of pit bull type dogs seized from a dogfighting organization. This population included 21 dogs that displayed conspecific aggressive behaviors and 10 that did not. Beta-diversity analyses support an association between gut microbiome structure and dog aggression. Additionally, we used a phylogenetic approach to resolve specific clades of gut bacteria that stratify aggressive and non-aggressive dogs, including clades within Lactobacillus , Dorea , Blautia , Turicibacter, and Bacteroides . Several of these taxa have been implicated in modulating mammalian behavior as well as gastrointestinal disease states. Although sample size limits this study, our findings indicate that gut microorganisms are linked to dog aggression and point to an aggression-associated physiological state that interacts with the gut microbiome. These results also indicate that the gut microbiome may be useful for diagnosing aggressive behaviors prior to their manifestation and potentially discerning cryptic etiologies of aggression.
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Submitted 12 June 2018
Accepted 13 November 2018
Published 9 January 2019
Corresponding author
Thomas J. Sharpton,
Academic editor
Angelo Piato
Additional Information and
Declarations can be found on
page 12
DOI 10.7717/peerj.6103
2019 Kirchoff et al.
Distributed under
Creative Commons CC-BY 4.0
The gut microbiome correlates with
conspecific aggression in a small
population of rescued dogs (Canis
Nicole S. Kirchoff1, Monique A.R. Udell2and Thomas J. Sharpton1,3
1Department of Microbiology, Oregon State University, Corvallis, OR, United States of America
2Department of Animal and Rangeland Science, Oregon State University, Corvallis, OR,
United States of America
3Department of Statistics, Oregon State University, Corvallis, OR, United States of America
Aggression is a serious behavioral disorder in domestic dogs that endangers both dogs
and humans. The underlying causes of canine aggression are poorly resolved and
require illumination to ensure effective therapy. Recent research links the compositional
diversity of the gut microbiome to behavioral and psychological regulation in other
mammals, such as mice and humans. Given these observations, we hypothesized
that the composition of the canine gut microbiome could associate with aggression.
We analyzed fecal microbiome samples collected from a small population of pit bull
type dogs seized from a dogfighting organization. This population included 21 dogs
that displayed conspecific aggressive behaviors and 10 that did not. Beta-diversity
analyses support an association between gut microbiome structure and dog aggression.
Additionally, we used a phylogenetic approach to resolve specific clades of gut bacteria
that stratify aggressive and non-aggressive dogs, including clades within Lactobacillus,
Dorea,Blautia,Turicibacter, and Bacteroides. Several of these taxa have been implicated
in modulating mammalian behavior as well as gastrointestinal disease states. Although
sample size limits this study, our findings indicate that gut microorganisms are linked to
dog aggression and point to an aggression-associated physiological state that interacts
with the gut microbiome. These results also indicate that the gut microbiome may be
useful for diagnosing aggressive behaviors prior to their manifestation and potentially
discerning cryptic etiologies of aggression.
Subjects Animal Behavior, Bioinformatics, Microbiology
Keywords Gut microbiome, Aggression, Fecal microbiota, Dog, Gut-brain axis
Domestic dogs (Canis familiaris) have coexisted with humans for over 14 thousand years
(Nobis, 1979), and remain among the most popular companion animals, especially in the
Western world where millions can be found living in human homes (American Pet Products
Association, 2014). Even larger populations of free-roaming and village dogs can be found
living among humans around the world (Coppinger & Coppinger, 2001). In recent years,
dogs have been studied for their capacity to form strong bonds with humans and other
How to cite this article Kirchoff NS, Udell MAR, Sharpton TJ. 2019. The gut microbiome correlates with conspecific aggression in a
small population of rescued dogs (Canis familiaris).PeerJ 7:e6103
species, resulting in a range of prosocial, cooperative, and communicative behaviors (Udell
& Wynne, 2008). However, dog aggression towards humans, other dogs, or other animals
remains a common behavioral problem (Bamberger & Houpt, 2006) that can pose serious
risks to animals, owners, and other humans including neighbors, friends, or veterinary
staff. Aggressive interactions, especially those involving bites, may lead to physical harm,
psychological trauma, disease transmission, or even fatality in bitten humans and other
dogs (Overall & Love, 2001;Hampson et al., 2009;Brooks, Moxon & England, 2010;Ji et al.,
2010). Aggressive behavior also poses risks to the aggressor dog, as aggression is a common
reason for relinquishment to animal shelters, where poor progress on mitigation of the
behavior, assuming the shelter is even equipped to intervene, often leads to euthanasia
(Salman et al., 2000). Consequently, understanding the factors and mechanisms responsible
for dog behaviors that are incompatible with success in anthropogenic environments has
much potential to benefit both species.
Dog aggression is often divided into categories, including dominance aggression, fear
aggression, food or possessive aggression, and territorial aggression (Blackshaw, 1991;
Houpt, 2006;Lockwood, 2016) based on the form of the behavior and the identified or
presumed context or consequences associated with specific aggressive acts. However, the
factors that predict aggression in one dog, but not in another, under similar conditions
(for example, in a standard behavior evaluation) are less well understood. Current research
suggests that environmental, experiential, and owner specific variables are important
predictors of aggression in dogs (Roll & Unshelm, 1997;Hsu & Sun, 2010). However,
underlying biological correlates including genetics, sex, hormone levels, neuter status,
nutrition, and neurological health have also been identified (Sherman et al., 1996;DeNapoli
et al., 2000;Duffy, Hsu & Serpell, 2008;Rosado et al., 2010). While behavior modification or
environmental change can significantly reduce aggressive behavior in at least some contexts
(Sherman et al., 1996;Mohan-Gibbons, Weiss & Slater, 2012), underlying physiological
mechanisms including pain, elevated stress levels, reduced thresholds for aggression, or
impulsivity could impede behavioral treatment or lead to resumption of the behavior if left
unidentified. Therefore, further elucidating the physiological underpinnings of aggression
in dogs may be critical to mitigating aggressive behavior, especially for situations where
other treatment and training options are ineffective on their own. The limited research
in this area shows that aggression associates with high levels of cortisol and low levels
of serotonin (5HT) (Rosado et al., 2010;León et al., 2012;Roth et al., 2016). Stress in
dogs is often detected by measuring cortisol levels and is thought to be a component
associated with behavioral problems such as anxiety as well as aggression (Rooney, Clark &
Casey, 2016). Accordingly, many dogs diagnosed with aggression are also diagnosed with
anxiety (Bamberger & Houpt, 2006). Behaviors associated with anxieties in dogs include
increased heart rate, trembling, increased salivation, pacing, circling, transient anorexia,
inappropriate elimination, excessive vocalization, destructiveness, and restlessness (Stelow,
2018). Dogs with anxiety may also present with aggressive behaviors such as lunging
(Stelow, 2018). There remains much to learn about the underlying causes of aggressive
behavior, which limits the development of new preventative strategies, diagnostics, and
therapeutic interventions.
Kirchoff et al. (2019), PeerJ, DOI 10.7717/peerj.6103 2/16
Emerging evidence suggests that the gut microbiome may interact with mammalian
physiology to influence behavior (Cryan & O’Mahony, 2011;Mayer et al., 2014;Foster et
al., 2016). These interactions include aspects of physiology that are relevant to mammalian
aggression. For example, treatments with a broad-spectrum antibiotic disrupted the
gut microbiome and decreased aggressive behavior in Siberian hamsters (Sylvia et al.,
2017). Additionally, germ-free and specific-pathogen free mice exhibit different anxiety
levels (Heijtz et al., 2011;Neufeld et al., 2011). Other studies have found that specific
strains of bacteria (i.e., probiotics) improve the health of the host by modulating anxiety
phenotypes and stress hormones such as glucocorticoids. For example, administration of
Lactobacillus rhamnosus (JB-1) reduced anxiety related behavior in mice, and Bacteroides
fragilis NCTC 9343 improves anxiety-like behavior in a mouse model known to exhibit
anxiety-like behaviors (Bravo et al., 2011;Hsiao et al., 2013). Moreover, gut bacteria can
produce neuroactive substances, such as precursors of monoamine neurotransmitters
that act on the gut-brain axis to potentially impact behavior, including anxiety (Heijtz
et al., 2011;Evrensel & Ceylan, 2015;Carabotti et al., 2015;O’Mahony et al., 2015). For
example, the gut microbiome produces tryptophan, which impacts host serotonin levels
and behaviors linked to serotonergic neurotransmission (O’Mahony et al., 2015;Yano et
al., 2015). Several studies show an inverse relationship between the serotonin metabolite,
5-hydroxyindoleacetic acid (5-HIAA), and aggressive behaviors (Coccaro et al., 2015).
Collectively, these observations indicate that the gut microbiome and aggressive behavior
may be linked in mammals.
To date, no studies have investigated the association between the gut microbiome and
aggression in dogs, which is a first necessary step towards ultimately ascertaining whether
the gut microbiome mediates aggression. Prior work points to a potential interaction
between the microbiome and canine aggression. For example, diet is a strong modulator
of gut microbial composition in many animals (David et al., 2013) and specific dietary
components are associated with aggression including diets that reduce aggressive behaviors
in dogs (DeNapoli et al., 2000;Re, Zanoletti & Emanuele, 2008). Additionally, the canine
gut microbiome associates with other health conditions such as inflammatory bowel disease
and acute diarrhea (Suchodolski et al., 2012) leading to discomfort or pain that could also
contribute to irritability or aggression. Here, we conducted an exploratory analysis of fecal
samples originating from a small shelter-housed population of pit bull type dogs seized
from organized dogfighting to determine if canine aggression could be predicted based on
the composition of the gut microbiome.
Sample collection
A single fecal sample was collected from the kennel of each of 31 pit bull type dogs
residing at a temporary shelter while in protective custody. The inner core of the feces
was sampled in order to minimize potential bacterial contamination given that the feces
were in contact with the kennel floor. This population served as the focus of this pilot
study because it enabled control over as many factors as possible, including breed type,
Kirchoff et al. (2019), PeerJ, DOI 10.7717/peerj.6103 3/16
environment, diet, and medical care, while providing access to a population with a relatively
more frequent aggressive phenotype compared to typical populations. Upon intake into
the shelter and prior to the initiation of this study, an animal welfare agency catalogued
various parameters of each individual, which were used in this study’s analysis as covariate
data (Table S1). Animal welfare employees collected feces using aseptic technique within
an hour of defecation and immediately froze them at 18 C to 20 C to fix bacterial
growth and preserve the DNA content. Fecal samples were shipped to Oregon State
University and stored at 20 C. Thirty of the dogs were on a diet of Iams Proactive Health
minichunks adult kibble (chicken-based formula) and one dog was on a diet of Iams
Puppy. Fourteen males and 17 females received a behavior evaluation conducted by the
animal welfare agency shortly after intake that categorized these dogs as intraspecifically
aggressive (n=21) or non-aggressive (n=10). Aggressive dogs displayed aggression during
one of three scenarios: an introduction to a life-size dog plush, introduction to a dog of
the same sex behind a barrier, and introduction to a dog of the same sex without a barrier.
Aggressive displays toward the life-size dog plush included growling, snarling, biting, biting
and holding, biting and shaking combined with tense behavior inconsistent with object
play, and aggressive displays toward the same sex dogs included growling and lunging,
lunging and snarling, climbing on withers and growling, attempting to bite, and biting.
Non-aggressive dogs did not display aggression towards the dog plush or another dog
(Text S1). Data from these evaluations were sent to Oregon State University along with
the stool samples for analysis. With the exception of the collection and processing of fecal
material, this study did not involve any manipulation of, measurement of, or contact with
dogs that had not already occurred.
Ethical statement
No animal subjects, animal handling, or study specific animal interactions were required
for the purpose of this study. Dog fecal samples were collected from shelter kennels after
natural deposit. Previously collected behavioral data from the animal welfare agency’s
records were used in analysis. Therefore, this study was determined to be exempt from
institutional animal care and use review by Oregon State University’s ethical review board.
Fecal DNA extraction and 16S sequencing
DNA was extracted from fecal samples using the QIAGEN DNeasy R
PowerSoil R
isolation kit (QIAGEN, Germantown, MD USA) as per manufacturer instruction with
the exception of an additional heat incubation of 10 min at 65 C immediately before
the bead beating step. The 16S rRNA gene was amplified from the extracted DNA with
PCR and primers designed to target the V4 region (Caporaso et al., 2012). Amplicons were
subsequently quantified using the Qubit R
HS kit (Thermo Fisher, Waltham, MA USA) and
then pooled and cleaned using the UltraClean R
PCR clean-up kit (MO BIO, Carlsbad, CA
USA). These cleaned amplicons were then sequenced on an Illumina MiSeq (v3 chemistry)
instrument. This sequencing generated 3.31 million 150 bp single end reads (median reads
per sample =78,272).
Kirchoff et al. (2019), PeerJ, DOI 10.7717/peerj.6103 4/16
Bioinformatic and statistical analyses
The QIIME (v1.8.0) bioinformatics pipeline was used to quality control raw sequences
as well as quantify the diversity of microorganisms isolated from the fecal samples. The
Illumina-generated sequences were demultiplexed and quality filtered (i.e., sequences
with a Phred quality score less than 20 were removed) with the QIIME script The script then assigned sequences
to Operational Taxonomic Units (OTUs) based on the alignment of sequences to the
Greengenes (v13_8) reference database using a 97% similarity threshold with the UCLUST
algorithm (v1.2.22). With the script, samples were subject to
rarefaction through random sub-sampling of sequences at a depth of 40,000 reads, which
corresponded to the lowest sequencing depth obtained across samples. The BIOM table
generated from the script was imported into R and potentially
spurious OTUs were filtered by removing those that (1) were found in fewer than three
samples and (2) were observed fewer than 20 times across all samples from all subsequent
analyses. The resulting OTU matrix was subsequently processed using the
script to calculate the weighted and unweighted UniFrac distances between all pairs of
samples (Lozupone & Knight, 2005). Alpha diversity was calculated in R (v3.2.3) using the
diversity function in the vegan package (v2.3-3).
Intersample similarity was visualized using principal coordinates analysis (PCoA) based
on the Bray–Curtis dissimilarity index using the vegan (v2.3-3) package in R (v3.2.3).
The association between sample covariates, including dog aggression, and intersample
similarity was quantified with the envfit function in the vegan package. Kruskal–Wallis
tests, as implemented by the coin package (version 1.1-2), were used to identify OTUs
and phylotypes that stratify samples by covariate factors. Phylogenetic clades that associate
with aggression were identified by assembling a reference-guided 16S sequence phylogeny
via FastTree as previously described (O’Dwyer, Kembel & Sharpton, 2015), using Claatu
to resolve monophyletic clades that are conserved in aggressive or non-aggressive dogs
(FDR < 0.05) (Gaulke et al., 2018), and Kruskal–Wallis tests to ascertain if these conserved
clades are differentially abundant across these populations. The taxonomy of these clades
was determined by identifying the most resolved taxonomy label that is shared among
all members of the clade. Multiple tests were corrected using the qvalue package (version
2.2.2). Phylotypes or clades with a p-value less than 0.05 and a q-value less than 0.2 were
designated as those that stratify samples.
To determine possible differences in gut microbial composition between aggressive and
non-aggressive dogs, we compared stool microbiomes that were sampled from 21 aggressive
dogs and 10 non-aggressive dogs. A Principal Coordinates Analysis (PCoA) using the
weighted UniFrac metric shows separation of the aggressive and non-aggressive samples
based on 95% confidence interval ellipses (Fig. 1;Figs. S1;S2). The separation between
aggressive and non-aggressive samples in the PCoA plot was confirmed by environmental
fit (p=0.0250, R2=0.1297) and PERMANOVA (p=0.0346, R2=0.0349) analyses.
Kirchoff et al. (2019), PeerJ, DOI 10.7717/peerj.6103 5/16
−0.4 −0.2 0.0 0.2 0.4
−0.3 −0.2 −0.1 0.0 0.1
PC1 (46%)
PC2 (12%)
Not Aggressive
Figure 1 Aggressive and non-aggressive dogs differ in beta-diversity using the weighted UniFrac
metric. Visualization of the phylogenetic differences in fecal microbiota of aggressive (green) and non-
aggressive (purple) dogs using principal coordinates analysis (PCoA) of OTU abundances and weighted
UniFrac distance. The separation between aggressive and non-aggressive samples in the PCoA plot was
confirmed with an environmental fit analysis (p=0.0250, R2=0.1297), which supports aggression status
as being a variable that is separating the microbial composition of the samples. The gut microbiome
structure of aggressive and non-aggressive dogs is also significantly different with the weighted UniFrac
metric using PERMANOVA (p=0.0346, R2=0.0349). Ellipses are based on 95% confidence intervals and
standard error.
Full-size DOI: 10.7717/peerj.6103/fig-1
Alternative measures of beta-diversity marginally support these results. For example,
using a Bray–Curtis dissimilarity metric finds a similar trend (PERMANOVA, p=0.0957,
R2=0.0573). Other study covariates were tested for their association with the fecal
microbial composition. Dog age did not associate with microbial composition (weighted
UniFrac, PERMANOVA, p=0.1763, R2=0.0652). Conversely, the sex of the dogs did
associate with microbial composition when using unweighted UniFrac (PERMANOVA,
p=0.0400, R2=0.0652), but not when using weighted UniFrac (PERMANOVA,
p=0.1424, R2=0.0582). Unlike the differences in beta-diversity between aggressive
and non-aggressive dogs, no significant differences were detected in alpha diversity based
on the Shannon index when comparing behavioral groups (p=0.5258).
The bacterial phylotypes that were observed across the dog fecal samples were compared
between behavioral groups to resolve those phylotypes that vary in association with
aggression (Fig. 2). Firmicutes, Fusobacteria, Bacteroidetes, and Proteobacteria were the
dominant phyla in all fecal samples. The relative abundances of these predominant phyla
also significantly differed across aggressive and non-aggressive dogs (p< 0.05, q< 0.1).
Specifically, Proteobacteria and Fusobacteria manifested higher relative abundance in
non-aggressive dogs, while Firmicutes was relatively more abundant in aggressive dogs.
These trends were driven by variation in a small number of more granular phylotypes
(Fig. 3). The family Lactobacillaceae was more abundant in aggressive dogs, while the
family Fusobacteriaceae was more abundant in non-aggressive dogs (p< 0.05, q< 0.2).
Consistently, the genus Lactobacillus was more abundant in aggressive dogs, while the genus
Kirchoff et al. (2019), PeerJ, DOI 10.7717/peerj.6103 6/16
f__Bifidobacteriaceae g__Bifidobacterium
Log 2 ratio of median proportions
Number of OTUs
Figure 2 Many of the most relatively abundant phylotypes in our dog fecal samples are significantly different across aggressive and non-
aggressive dogs. A metacoder (Foster, Sharpton & Grünwald, 2017) heattree illustrates the variation in microbiome phylotypes between the
aggressive and non-aggressive dog populations. Nodes in the heattree correspond to phylotypes, as indicated by node labels, while edges link
phylotypes in accordance to the taxonomic hierarchy. Node sizes correspond to the number of OTUs observed within a given phylotype. Colors
represent the log fold difference of a given phylotype’s median relative abundance in the aggressive dogs as compared to the non-aggressive dogs.
Specifically, darker green represents higher relative abundance of aggressive OTUs and darker brown represents higher relative abundance of
non-aggressive OTUs.
Full-size DOI: 10.7717/peerj.6103/fig-2
Fusobacteria was more abundant in non-aggressive dogs (p< 0.05, q< 0.2). Additional
separation between aggressive and non-aggressive dogs was observed at the OTU level.
Specifically, seven OTUs significantly differed between aggressive and non-aggressive dogs
(p<0.05, q<0.1), including four OTUs from the genus Dorea, two OTUs from the
genus Lactobacillus, and one OTU from Turicibacter. All of the phylotypes and OTUs that
Kirchoff et al. (2019), PeerJ, DOI 10.7717/peerj.6103 7/16
Bacteroides (Node 874)
Lactobacillus (Node 3489)
Aggressive Non-Aggressive
Aggressive Non-Aggressive
Figure 3 The abundance of monophyletic clades within phylotypes stratify aggressive and non-
aggressive dogs. (A) illustrates a subtree within the Bacteroides phylotype containing node 874 (red
branches), which is a monophyletic clade that is both common to and relatively more abundant amongst
the non-aggressive individuals than the aggressive individuals. The heat map adjacent to this subtree
illustrates the log10 relative abundance of each lineage in this subtree across the individuals subject to our
investigation. The red rectangle highlights the relative abundance of the lineages within node 874. The
vertical blue line separates aggressive and non-aggressive individuals. (B) illustrates a similar subtree, but
in this case, it has been extracted from within the Lactobacillus phylotypes and highlights a monophyletic
clade (node 3489) that is common to and relatively more abundant amongst the aggressive dogs.
Full-size DOI: 10.7717/peerj.6103/fig-3
significantly associated with aggression are included in Table S2 (phylotypes) and Table S3
To better resolve taxa that stratify aggressive and nonaggressive dogs, we used a
phylogenetic approach that defines taxa as monophyletic clades of bacteria that are
prevalently observed across members of the aggressive or nonaggressive populations. These
clades represent evolutionary groupings of bacteria that often correspond to intermediate
levels of taxonomy (e.g., between species and genus) that are defined by the shared ancestry
Kirchoff et al. (2019), PeerJ, DOI 10.7717/peerj.6103 8/16
and ecology of clade members. Moreover, by focusing on prevalent clades, which are those
that are observed in more individuals within a population than expected by chance (Gaulke
et al., 2018), we are able to resolve bacterial taxa that are especially common to at least
one population. This property of a high prevalence of behavior-stratifying gut microbes
may be a desirable characteristic when searching for potentially diagnostic indicators of
aggression status.
Of the 578 clades that are prevalent in either aggressive or non-aggressive dogs, 96
significantly differ in abundance between the two populations (q<0.2). Of these clades,
39 have a mean relative abundance that is significantly higher in the gut microbiomes
of aggressive dogs, while 57 have a higher relative abundance in non-aggressive dog
microbiomes. A complete list of clades that associate with behavior can be found in
Table S4. Of particular note is our finding that nine clades with the genus Bacteroides
are elevated in the gut microbiomes of non-aggressive dogs compared to aggressive dogs.
This finding indicates that the relative abundance of these lineages within Bacteroides may
predict aggression status and that their depletion may contribute to aggression. We also
find that the genus Lactobacillus contains 25 clades that are relatively abundant in aggressive
canines. Similar patterns are observed for clades within the family Paraprevotellaceae. These
observations indicate that aggression may be associated with an increase in specific lineages
within Lactobacillus and Paraprevotellaceae and they may express traits that interact with
aggression-associated aspects of canine physiology. Moreover, we find that the genus
Turicibacter contains both aggression-elevated and aggression-depleted clades (Fig. S3),
indicating that descendants of this genus may have recently evolved traits that contribute
to their differential association with canine behavior.
Accumulating evidence indicates that the gut microbiome acts as an agent of the nervous
system and influences affective disorders such as anxiety and depression (Clapp et al., 2017).
However, it is unknown if the gut microbiome similarly relates to animal aggression.
Our exploratory analysis of a population of rescued, sheltered-housed dogs links the
composition of the gut microbiome to conspecific aggression in canines. While this
associative study cannot disentangle cause and effect, it holds important implications for
clinical practices surrounding canines, as its results indicate that: (a) the gut microbiome
may contribute to aggression or its severity, and that manipulation of the microbiome (e.g.,
by probiotic administration) may alleviate the behavior; (b) the physiology of aggressive
dogs results in different gut microbiome compositions, which indicates that the microbiome
may facilitate predictive diagnosis of aggressive behavior and preventative intervention; or
(c) aggression and the gut microbiome are similarly associated with a cryptic physiological
or environmental covariate, such as inflammation or cortisol levels, which may help discern
the physiological underpinnings of canine aggression. Future studies should build upon this
exploratory investigation to discern the mechanisms underlying the relationship between
canine aggression and the gut microbiome.
Our investigation finds that the composition of the gut microbiome differs between
aggressive and non-aggressive dogs in the population that we studied. The rescued,
Kirchoff et al. (2019), PeerJ, DOI 10.7717/peerj.6103 9/16
shelter-housed dogs included in this investigation proved useful for this study because
they included aggressive and non-aggressive individuals and were taken into the shelter
at the same time, maintained in the same facility, mostly exposed to the same diet, and
generally of consistent breed type. Despite our attempt to homogenize the sources of
variation amongst these dogs, we observed extensive variation in the composition of the
gut microbiome within each behavioral cohort. This intra-cohort variation indicates that
the stool samples we studied are subject to cryptic factors that associate with microbiome
composition (e.g., early life history (Rodríguez et al., 2015)). This is unsurprising given
that individuals living outside of a laboratory setting (including pet and shelter dogs,
as well as humans) are subject to genetic and environmental diversity that cannot fully
be controlled for. That said, the identification of significant differences between these
populations under naturalistic conditions heightens the applied value of these findings. We
were able to measure other factors that may influence the gut microbial composition of
these dogs besides aggression and found that dog sex partially explains the inter-individual
variation in the unweighted UniFrac dissimilarity of gut microbiome samples. Considering
this result alongside the finding that aggression status links to the weighted UniFrac
dissimilarity of the same samples indicates that, of the covariates measured in this study,
sex explains the types of microbes that are present in the gut of these dogs while aggression
status explains which of the microbes dominates their gut community. These observations
suggest that dog sex, aggression, and gut microbiome composition are intertwined, and
align with prior work that observed sex-dependent effects on how disruption of the gut
microbiome affects animal aggression (Sylvia et al., 2017). Also, because prior experiences
can impact the gut microbiome and because we do not know the prior experiences of
these individuals, future studies may find that aggression is not linked to the microbiome
in other dogs. Such a finding would indicate that there are contextual dependencies
underlying the aggression-microbiome connection observed in this study. Additionally,
researchers should observe if there is a consistent connection between canine aggression
and microbial composition while correcting for possible confounding variables such as age
and diet, measuring additional forms of aggression, such as aggression towards humans,
and studying greater numbers of pit bull breed type dogs or including different dog breeds
in study populations. Future efforts should consider larger populations and measure
more diverse covariates per individual to disentangle the properties that influence the gut
microbiome’s apparent relationship with aggression.
Several taxa found in our study were also observed in other canine gut microbiome
studies. For example, the most abundant phyla, Firmicutes, Fusobacteria, Bacteroidetes, and
Proteobacteria, were also dominant in fecal samples from previous canine gut microbiome
studies (Deng & Swanson, 2015). Additionally, several taxa significantly differ in their
relative abundance between aggressive and nonaggressive dogs. For instance, we find
that that lineages within the genus Bacteroides are elevated in non-aggressive dogs, which
might be expected given that species within this genus, such as Bacteroides fragilis, have
been shown to modulate mammalian behavior in prior investigations (Hsiao et al., 2013).
Moreover, the genus Dorea elevates in non-aggressive dogs compared to aggressive dogs,
which is notable because Dorea manifests a reduced abundance in dogs afflicted with
Kirchoff et al. (2019), PeerJ, DOI 10.7717/peerj.6103 10/16
inflammatory bowel disease (Jergens et al., 2010) and other enteropathies (Suchodolski,
2011), and because psychological disorders are frequently comorbid with gastrointestinal
inflammation (Bannaga & Selinger, 2015;Clapp et al., 2017). However, our observations
of which taxa stratify these cohorts are not always consistent with prior investigations
of microbial taxa that associate with mammalian behavior. As an example, we find that
members of Lactobacillus are more abundant in the gut microbiomes of aggressive dogs,
which might defy expectations given that prior research of specific strains of Lactobacillus
rhamnosus have been found to reduce stress-associated corticosterone levels and anxiety
related behavior in mice and is known to produce GABA neurotransmitters (Bravo et al.,
2011). Similarly, the genus Fusobacterium is typically thought to elicit pro-inflammatory
effects inside the gut (Bashir et al., 2016); here, we find that Fusobacterium is more abundant
in the stool of non-aggressive dogs. That said, it is challenging to determine the physiological
role of specific microbiota from 16S sequences given that an organism’s interaction with
its host may be context dependent (Schubert, Sinani & Schloss, 2015) and may rapidly
diversify (Conley et al., 2016). Indeed, our analysis of monophyletic clades of gut bacteria
that associate with aggression finds that closely related clades can manifest opposite
patterns of association with behavior, such as that of Turicibacter. Additionally, the limited
population size may challenge the discovery of taxa that statistically stratify cohorts. Despite
this, these taxa represent compositional distinctions between aggressive and non-aggressive
dogs in our population. Further study of their physiological role may help clarify whether
or how they influence canine aggression as well as their probiotic suitability and therapeutic
capacity towards alleviating aggression in dogs.
Our results indicate that there are statistical associations between aggression status and
the gut microbiome. For example, microbial composition differs based on aggressive and
non-aggressive evaluations. Additionally, the relative abundances of specific bacterial taxa
and lineages are different across aggressive and non-aggressive groups. These observations
are important because they indicate that either (a) aggressive dogs manifest physiological
conditions in the gut that influence the composition of the gut microbiome, (b) the
composition of the gut microbiome may influence aggressive behavior, or (c) that aggressive
dogs are subject to some biased covariate relative to non-aggressive dogs that also influences
the gut microbiome. Future studies should seek to confirm that these findings are consistent
in additional populations of dogs, and seek to discriminate between these possibilities.
Additionally, future studies should expand the size of the populations being studied,
measure a diverse array of physiological covariates to tease out aggression-specific effects
and discern mechanisms of interactions, identify and test specific bacterial strains as
probiotics that could alleviate aggression, and consider using metagenomic analyses to
deduce the potential functional role of the microbiome in these interactions.
Ultimately, our results indicate that the composition of the gut microbiome associates
with conspecific canine aggression in this group of dogs. These results pave the way for
future investigations to ascertain whether similar results are seen in other dog populations
Kirchoff et al. (2019), PeerJ, DOI 10.7717/peerj.6103 11/16
and if the microbiome can be used to develop diagnostics, preventative strategies, and
therapeutics of aggression.
We thank Dr. Pamela Reid for her advice and discussions regarding dog behavior. We also
thank Dr. Christopher A. Gaulke and Dr. Yuan Jiang for their helpful comments.
The National Science Foundation (Grant 1557192) and institutional funds to Thomas J.
Sharpton supported this work. The funders had no role in study design, data collection
and analysis, decision to publish, or preparation of the manuscript.
Grant Disclosures
The following grant information was disclosed by the authors:
The National Science Foundation: Grant 1557192.
Institutional funds.
Competing Interests
The authors declare there are no competing interests.
Author Contributions
Nicole S. Kirchoff analyzed the data, prepared figures and/or tables, authored or reviewed
drafts of the paper, approved the final draft.
Monique A.R. Udell conceived and designed the experiments, contributed
reagents/materials/analysis tools, authored or reviewed drafts of the paper, approved the
final draft.
Thomas J. Sharpton conceived and designed the experiments, analyzed the data,
contributed reagents/materials/analysis tools, prepared figures and/or tables, authored
or reviewed drafts of the paper, approved the final draft.
DNA Deposition
The following information was supplied regarding the deposition of DNA sequences:
Oregon State University CGRB, Sharpton Lab Public Repository:
Data Availability
The following information was supplied regarding data availability:
Sharpton Lab Repository:
Kirchoff et al. (2019), PeerJ, DOI 10.7717/peerj.6103 12/16
Supplemental Information
Supplemental information for this article can be found online at
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... The effects of microbiome disruption on socio-sexual behaviours such as sexual preferences and ROLE OF THE GUT MICROBIOME ON SOCIO-SEXUAL BEHAVIOURS 18 aggression have yet to be explored among common rodent laboratory animals. To date, only two studies have asked whether there is an association between the gut microbiome and aggression, one in dogs (Kirchoff et al., 2019) and the other in hamsters (Sylvia et al., 2017). Kirchoff repeated antibiotic treatment and found that repeated (14 days; with a recovery phase after single treatment) but not single (7 days) treatments caused a marked decrease in the frequency of attacks and overall aggression scores in male hamsters, which returned to normal levels following recovery. ...
... We did not assess whether 7 days is sufficient to affect aggressive behaviour; however, 14-20 days of antibiotic treatment similarly decreased male aggression in our study. Sylvia et al. (2017) is the only rodent study available for reference, although studies in dogs suggest that the abundance of specific gut bacteria, including Lactobacillus and Dorea, are associated with aggressive behaviours (Kirchoff et al., 2019). Thus, future work may consider whether these bacteria also play a role in the display of male-typical aggression in mice. ...
... These results suggest that sex differences in the gut microbiome contribute to sex differences in behaviour. Thus, it is possible that the male microbiota may contain a high abundance of specific microbes associated with male-typical olfactory preference and territorial aggression, as found in dogs (Kirchoff et al., 2019), and thus when transplanted into ABX males, reversed the antibioticinduced behaviour changes. Alternatively, the absence of microbiota and/or a female-specific microbiota composition may decrease aggressive behaviours in mice. ...
Full-text available
The gut microbiome is host to trillions of microorganisms that influence the brain and behaviour via the gut-brain axis. Gonadal hormones drive sex differences in the gut microbiota composition that translates into sex-dependent effects on behaviour when depleted. To date, these studies have primarily examined the gut's depletion on psychiatric disorders, including anxiety and depressive-like behaviours in rodents. The current study explored the role of gut microbiota on socio-sexual behaviours in male and female mice. Broad-spectrum antibiotic (ABX) in drinking water was used to deplete the microbiota in either early development (embryonic day 16 to postnatal day 21) or adulthood (day 60 to 81) while the control group received normal drinking water. Compared to control males, early and adult ABX decreased male territorial aggression, while adulthood ABX also decreased sexual odor preferences among males. Next, I examined whether these decreases in socio-sexual behaviour among males following ABX resulted from the depletion of the gut microbiota, rather than other non-specific effects of antibiotics, and/or whether these behavioural deficits could be due to decreases in androgens. To do so, cecal microbiota transplantation with same and opposite-sex control cecum contents or testosterone treatment was provided to adult antibiotic-treated males. Microbiota transplant with male cecum restored both olfactory preference and male aggression among adult ABX males. Female microbiota partially restored olfactory preference but not aggression among ABX males, while testosterone treatment was insufficient to rescue any of these behaviours. In adult ABX females, male microbiota transplant did not alter socio-sexual behaviours, but testosterone treatment increased male-typical sexual behaviours. Together, the results suggest a sex-dependent role for the gut microbiome in the display of sex-typical behaviours in mice that is independent of androgen. ROLE OF THE GUT MICROBIOME ON SOCIO-SEXUAL BEHAVIOURS iii
... While there have been intriguing studies from lab animal models showing a potential connection between the gut microbiome and behavior or mental health, implicating the socalled "gut-brain axis" 1,2 , there is a dearth of studies investigating the microbiome-behavior relationship in working dogs. Some recent small-scale studies in non-working dogs have found that undesirable canine behaviors (i.e., aggression, anxiety) are associated with certain characteristics of the canine gut microbiome 3,4 . However, it is critical to note when thinking about the microbiome's impact on behavior that the behavioral traits of working dogs and companion dogs have critical differences 5 . ...
... Microbiome markers were also statistically associated with motivation, aggression, cowardice, sociability, and obedience to one trainer vs many, and some of these associations agree with findings in previous studies 3,4,28 . When prediction models were developed with machine learning, the best models were for motivation, sociability, and GI issues, whereas the models that did not show predictive capability were for job performance and stress levels. ...
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Dogs have a key role in law enforcement and military work, and research with the goal of improving working dog performance is ongoing. While there have been intriguing studies from lab animal models showing a potential connection between the gut microbiome and behavior or mental health there is a dearth of studies investigating the microbiome-behavior relationship in working dogs. The overall objective of this study was to characterize the microbiota of working dogs and to determine if the composition of the microbiota is associated with behavioral and performance outcomes. Freshly passed stools from each working canine (Total n = 134) were collected and subject to shotgun metagenomic sequencing using Illumina technology. Behavior, performance, and demographic metadata were collected. Descriptive statistics and prediction models of behavioral/phenotypic outcomes using gradient boosting classification based on Xgboost were used to study associations between the microbiome and outcomes. Regarding machine learning methodology, only microbiome features were used for training and predictors were estimated in cross-validation. Microbiome markers were statistically associated with motivation, aggression, cowardice/hesitation, sociability, obedience to one trainer vs many, and body condition score (BCS). When prediction models were developed based on machine learning, moderate predictive power was observed for motivation, sociability, and gastrointestinal issues. Findings from this study suggest potential gut microbiome markers of performance and could potentially advance care for working canines.
... Specifically, five studies detected an increase related to the genus Bacteroides [39] or specific species within the genus [35,[41][42][43], the most common of which was B. uniformis. Similarly, a study comparing the gut microbiota composition of aggressive and non-aggressive dogs determined a different abundance of members of the genus Bacteroides in these two groups [56]. In some studies, the increased levels of the genus Bacteroides were associated with neuropsychiatric diseases such as major depressive disorder and autism spectrum disease [57,58]. ...
The impact of the microbiome on brain function and behavior has recently become an important research topic. We searched for a link between the gut microbiome and impulsive and violent behavior. We focused on critical factors influencing the microbiome establishment that may affect human health later in life, i.e., delivery mode, early-life feeding, and early antibiotic exposure. We searched PubMed, Web of Science, and the Cochrane Library. We included original human studies examining adults and children with impulsive and/or violent behavior that assessed the gut microbiota composition of participants, delivery mode, infant feeding mode, or early antibiotic exposure. Bibliographic searches yielded 429 articles, and 21 met the eligibility criteria. Two studies reported data on patients with schizophrenia with violent behavior, while 19 studies reported data on patients with attention-deficit hyperactivity disorder (ADHD). The results showed several bacterial taxa associated with ADHD symptomatology and with violent behavior in patients with schizophrenia. No association was found between delivery mode and impulsive behavior, nor did any articles relate infant feeding mode to violent human behavior. Those studies investigating early antibiotic exposure yielded ambiguous results. The heterogeneity of the data and the different methodologies of the included studies limited the external validity of the results. We found few studies that addressed the possible microbiome involvement in the pathophysiology of impulsive and violent behavior in humans. Our review revealed a gap in knowledge regarding links between the gut microbiome and these extreme behavioral patterns.
... Gut dysbacteriosis with leaky gut seems to play a vital role in the pathophysiology. Even though there are four animal-based studies revealing the link between aggressive behaviors and gut microbiota [22][23][24][25], only one patient-based clinical study preliminarily pointed to the possible correlation among aggression onset and gut dysbacteriosis [26]. In this study enrolling 42 ScZ patients (26 with violence and 16 without violence) without antipsychotics discontinuation before samples collecting, no significantly statistical difference in fecal microbiota richness, α-diversity and β-diversity were presented between the two groups [26]. ...
Full-text available
Background The pathophysiological mechanisms of aggression are manifold and they may closely interconnect. Current study aimed to determine the gut microbiota and its metabolites, and clarify their correlations with inflammation, oxidation, leaky gut and clinical profiles underlying aggression in schizophrenia (ScZ). Methods Serum and stool specimens from ScZ inpatients with (ScZ-Ag, 25 cases) and without aggression (NScZ-Ag, 25 cases) were collected. Systemic inflammation, oxidation and leaky gut biomarkers were determined by ELISA, gut microbiota by 16S rRNA sequencing, short-chain fatty acids (SCFAs) by gas chromatography-mass spectrometry analysis and neurotransmitters by liquid chromatograph mass spectrometry analysis. Results Significantly higher systemic pro-inflammation, pro-oxidation and leaky gut biomarkers were observed in ScZ-Ag than NScZ-Ag group (all P<0.001). Compared to NScZ-Ag group, the alpha-diversity and evenness of fecal bacterial community were much lower, the abundance of fecal genera Prevotella was significantly increased, while that Bacteroides, Faecalibacterium, Blautia, Bifidobacterium,Collinsella and Eubacterium_coprostanoligenes were remarkably reduced in ScZ-Ag group (all corrected P<0.001). Meanwhile, 6 SCFAs and 6 neurotransmitters were much lower in ScZ-Ag group (all P<0.05). Finally, a few strongly positive or negative correlations among altered gut microbiota, SCFAs, systemic pro-inflammation, leaky gut, pro-oxidation and aggression severity were detected. Conclusions These results demonstrate that pro-inflammation, pro-oxidation and leaky gut phenotypes relating to enteric dysbacteriosis and microbial SCFAs feature the aggression onset or severity in ScZ individuals.
... Behavior abnormalities such as aggressiveness are most frequently observed in mentally stressed dogs that present anxiety disorders, which indicates imbalance in the gut microbial composition [68]. Indeed, transferring gut microbiota also transforms the mood of the donor. ...
Full-text available
Fecal microbiota transplantation (FMT) is an emerging therapeutic option for a variety of diseases, and is characterized as the transfer of fecal microorganisms from a healthy donor into the intestinal tract of a diseased recipient. In human clinics, FMT has been used for treating diseases for decades, with promising results. In recent years, veterinary specialists adapted FMT in canine patients; however, compared to humans, canine FMT is more inclined towards research purposes than practical applications in most cases, due to safety concerns. Therefore, in order to facilitate the application of fecal transplant therapy in dogs, in this paper, we review recent applications of FMT in canine clinical treatments, as well as possible mechanisms that are involved in the process of the therapeutic effect of FMT. More research is needed to explore more effective and safer approaches for conducting FMT in dogs.
... Evidence from animal model studies also reveals support for a relationship between aggressive behavior and alterations in the gut microbiota. Recently, two small studies found that the composition of the gut microbiome is associated with aggressive behavior in dogs(Kirchoff et al., 2019;Mondo et al., 2020).Researchers studying Siberian hamsters took a step further on the path from establishing correlation to figuring out causation: they investigated how manipulation of the hamsters' microbiome affected these animals' aggressive behavior(Ren et al., 2020;Sylvia et al., 2017).Sylvia et al. (2017) hypothesized that a broad-spectrum antibiotic treatment-in this case enrofloxacin-would manipulate the gut microbiome and potentially affect social behavior in male and female hamsters. After administering repeated antibiotic treatments, the male hamsters showed a decrease in aggressive behavior, but their levels of aggression returned to normal after recovery. ...
Research in biosocial criminology and other related disciplines has established links between nutrition and aggressive behavior. In addition to observational studies, randomized trials of nutritional supplements like vitamins, omega‐3 fatty acids, and folic acid provide evidence of the dietary impact on aggression. However, the exact mechanism of the diet‐aggression link is not well understood. The current article proposes that the gut microbiome plays an important role in the process, with the microbiota–gut–brain axis serving as such a mediating mechanism between diet and behavior. Based on animal and human studies, this review synthesizes a wide array of research across several academic fields: from the effects of dietary interventions on aggression, to the results of microbiota transplantation on socioemotional and behavioral outcomes, to the connections between early adversity, stress, microbiome, and aggression. Possibilities for integrating the microbiotic perspective with the more traditional, sociologically oriented theories in criminology are discussed, using social disorganization and self‐control theories as examples. To extend the existing lines of research further, the article considers harnessing the experimental potential of noninvasive and low‐cost dietary interventions to help establish the causal impact of the gut microbiome on aggressive behavior, while adhering to the high ethical standards and modern research requirements. Implications of this research for criminal justice policy and practice are essential: not only can it help determine whether the improved gut microbiome functioning moderates aggressive and violent behavior but also provide ways to prevent and reduce such behavior, alone or in combination with other crime prevention programs.
... They could serve as a model of spontaneous pathologies for investigating new therapeutic pathways. In particular, Kirchoff et al. studied a cohort of 21 conspecifically aggressive dogs and showed that the composition of the gut microbiota differed between aggressive and non-aggressive dogs [123]. More precisely, Proteobacteria and Fusobacteria displayed greater relative abundances in samples from non-aggressive animals, whereas Firmicutes were more abundant in samples from aggressive dogs. ...
From a “microbiota-gut-brain axis” perspective, animal models suggest that gut microbiota affects aggression. Behavioral studies using germ-free mice indicate that maintaining a healthy gut microbiota early in development can subsequently mitigate aggressive behavior in the host. Mice pups, whose gut microbiota was affected by antibiotics from gestation through weaning, exhibited aggression; hamsters whose maternal gut microbiota was disturbed by antibiotics were similarly affected. However, few clinical or animal studies have reported targeting aggression through gut microbiota intervention. Based on animal models, probiotic and prebiotic supplementation and fecal microbiota transplantation are hypothesized as possible therapeutic options to reduce aggression. Therapeutic efficacy may be greatest if intervention occurs early in development. In addition, stabilizing the maternal gut microbiota may prevent or reduce future aggression in offspring. This chapter reviews the effects of the gut microbiota on host aggression, focusing on animal studies.
From a “microbiota-gut-brain axis” perspective, animal models suggest that gut microbiota affects aggression. Behavioral studies using germ-free mice indicate that maintaining a healthy gut microbiota early in development can subsequently mitigate aggressive behavior in the host. Mice pups, whose gut microbiota was affected by antibiotics from gestation through weaning, exhibited aggression; hamsters whose maternal gut microbiota was disturbed by antibiotics were similarly affected. However, few clinical or animal studies have reported targeting aggression through gut microbiota intervention. Based on animal models, probiotic and prebiotic supplementation and fecal microbiota transplantation are hypothesized as possible therapeutic options to reduce aggression. Therapeutic efficacy may be greatest if intervention occurs early in development. In addition, stabilizing the maternal gut microbiota may prevent or reduce future aggression in offspring. This chapter reviews the effects of the gut microbiota on host aggression, focusing on animal studies.
Behavior can change as a result of medical problems or physiological changes, and behavior changes are likely to be the first signs of stress, disease, and poor welfare in any animal. If shelter operations, behavior, and/or medical staff identify behaviors that may have an underlying medical cause, they can be addressed immediately, relieving suffering and increasing the adoptability of the animal. Conversely, if medical conditions that cause or exacerbate problematic behaviors are missed, time may be wasted on training or attempted behavior modification, thus prolonging suffering and time spent in the shelter. Only by safeguarding both physical and emotional health can we improve overall quality of life for animals in our care, facilitate their placement in homes, and help prevent their return to the shelter.
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Our knowledge of how the gut microbiome relates to mammalian evolution benefits from the identification of gut microbial taxa that are unexpectedly prevalent or unexpectedly conserved across mammals. Such taxa enable experimental determination of the traits needed for such microbes to succeed as gut generalists, as well as those traits that impact mammalian fitness. However, the punctuated resolution of microbial taxonomy may limit our ability to detect conserved gut microbes, especially in cases in which broadly related microbial lineages possess shared traits that drive their apparent ubiquity across mammals. To advance the discovery of conserved mammalian gut microbes, we developed a novel ecophylogenetic approach to taxonomy that groups microbes into taxonomic units based on their shared ancestry and their common distribution across mammals. Applying this approach to previously generated gut microbiome data uncovered monophyletic clades of gut bacteria that are conserved across mammals. It also resolved microbial clades exclusive to and conserved among particular mammalian lineages. Conserved clades often manifest phylogenetic patterns, such as cophylogeny with their host, that indicate that they are subject to selective processes, such as host filtering. Moreover, this analysis identified variation in the rate at which mammals acquire or lose conserved microbial clades and resolved a human-accelerated loss of conserved clades. Collectively, the data from this study reveal mammalian gut microbiota that possess traits linked to mammalian phylogeny, point to the existence of a core set of microbes that comprise the mammalian gut microbiome, and clarify potential evolutionary or ecologic mechanisms driving the gut microbiome’s diversification throughout mammalian evolution.
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The bidirectional communication between the central nervous system and gut microbiota, referred to as the gut-brain-axis, has been of significant interest in recent years. Increasing evidence has associated gut microbiota to both gastrointestinal and extragastrointestinal diseases. Dysbiosis and inflammation of the gut have been linked to causing several mental illnesses including anxiety and depression, which are prevalent in society today. Probiotics have the ability to restore normal microbial balance, and therefore have a potential role in the treatment and prevention of anxiety and depression. This review aims to discuss the development of the gut microbiota, the linkage of dysbiosis to anxiety and depression, and possible applications of probiotics to reduce symptoms.
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Community-level data, the type generated by an increasing number of metabarcoding studies, is often graphed as stacked bar charts or pie graphs that use color to represent taxa. These graph types do not convey the hierarchical structure of taxonomic classifications and are limited by the use of color for categories. As an alternative, we developed metacoder, an R package for easily parsing, manipulating, and graphing publication-ready plots of hierarchical data. Metacoder includes a dynamic and flexible function that can parse most text-based formats that contain taxonomic classifications, taxon names, taxon identifiers, or sequence identifiers. Metacoder can then subset, sample, and order this parsed data using a set of intuitive functions that take into account the hierarchical nature of the data. Finally, an extremely flexible plotting function enables quantitative representation of up to 4 arbitrary statistics simultaneously in a tree format by mapping statistics to the color and size of tree nodes and edges. Metacoder also allows exploration of barcode primer bias by integrating functions to run digital PCR. Although it has been designed for data from metabarcoding research, metacoder can easily be applied to any data that has a hierarchical component such as gene ontology or geographic location data. Our package complements currently available tools for community analysis and is provided open source with an extensive online user manual.
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Introduction. Age is the primary risk factor for major human chronic diseases, including cardiovascular disorders, cancer, type 2 diabetes, and neurodegenerative diseases. Chronic, low-grade, systemic inflammation is associated with aging and the progression of immunosenescence. Immunosenescence may play an important role in the development of age-related chronic disease and the widely observed phenomenon of increased production of inflammatory mediators that accompany this process, referred to as “inflammaging.” While it has been demonstrated that the gut microbiome and immune system interact, the relationship between the gut microbiome and age remains to be clearly defined, particularly in the context of inflammation. The aim of our study was to clarify the associations between age, the gut microbiome, and pro-inflammatory marker serum MCP-1 in a C57BL/6 murine model. Results. We used 16S rRNA gene sequencing to profile the composition of fecal microbiota associated with young and aged mice. Our analysis identified an association between microbiome structure and mouse age and revealed specific groups of taxa whose abundances stratify young and aged mice. This includes the Ruminococcaceae, Clostridiaceae, and Enterobacteriaceae. We also profiled pro-inflammatory serum MCP-1 levels of each mouse and found that aged mice exhibited elevated serum MCP-1, a phenotype consistent with inflammaging. Robust correlation tests identified several taxa whose abundance in the microbiome associates with serum MCP-1 status, indicating that they may interact with the mouse immune system. We find that taxonomically similar organisms can exhibit differing, even opposite, patterns of association with the host immune system. We also find that many of the OTUs that associate with serum MCP-1 stratify individuals by age. Discussion. Our results demonstrate that gut microbiome composition is associated with age and the pro-inflammatory marker, serum MCP-1. The correlation between age, relative abundance of specific taxa in the gut microbiome, and serum MCP-1 status in mice indicates that the gut microbiome may play a modulating role in age-related inflammatory processes. These findings warrant further investigation of taxa associated with the inflammaging phenotype and the role of gut microbiome in the health status and immune function of aged individuals.
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It is challenging to measure long-term endocrine stress responses in animals. We investigated whether cortisol extracted from dog hair reflected the levels of activity and stress long-term, during weeks and months. Hair samples from in total 59 German shepherds were analysed. Samples for measuring cortisol concentrations were collected at three occasions and we complemented the data with individual scores from the Canine Behavioural Assessment and Research Questionnaire (C-BARQ). Generalised linear mixed model (GLMM) results showed that hair cortisol varied with season and lifestyle: competition dogs had higher levels than companion, and professional working dogs, and levels were higher in January than in May and September. In addition, a positive correlation was found between the cortisol levels and the C-BARQ score for stranger-directed aggression (r = 0.31, P = 0.036). Interestingly, the factor “playing often with the dog” (r = −0.34, P = 0.019) and “reward with a treat/toy when the dog behaves correctly” (r = −0.37, P = 0.010) correlated negatively with cortisol levels, suggesting that positive human interactions reduce stress. In conclusion, hair cortisol is a promising method for revealing the activity of the HPA-axis over a longer period of time, and human interactions influence the cortisol level in dogs.
Clinicians play an important role in diagnosing problem behaviors as a precursor to treating them. This requires a protocol for gathering historical behavioral and health information, direct observation and examination of the animal, and a broad knowledge base of medical and behavioral differential diagnoses for those findings. Aggression and anxiety are the most commonly reported behavior problems in dogs. In cats, elimination problems and aggression are the most prevalent. Other important diagnoses for these species are cognitive dysfunction and abnormal repetitive behaviors.
The causes of fear and anxiety in working dogs are multifactorial and may include inherited characteristics that differ between individuals (e.g. Goddard and Beilharz, 1982; 1984a,b), influences of the environment (Lefebvre et al., 2007), and learned experiences during particular sensitive periods (Appleby et al., 2002) and throughout life. Fear-related behavior compromises performance, leads to significant numbers of dogs failing to complete training (e.g., Murphy, 1995; Batt et al., 2008), early withdrawals from working roles (Caron-Lormier et al., 2016), and can jeopardize dog and handler safety. Hence, amelioration of fear and anxiety is critical to maintain dogs in working roles and to ensure their well-being. Although current methods of selection and training are seemingly effective at producing many dogs which work in a remarkable array of environments, some dogs do not make the grade, and longevity of service is not always maximized. Programs should strive for optimal efficiency and they need to continually analyze the value of each component of their program, seek evidence for its value and explore potential evidence-based improvements. Here we discuss scientific evidence for methods and strategies which may be of value in reducing the risk of fear behaviors developing in the working dog population and suggest potentially valuable techniques and future research to explore the benefit of these approaches. The importance of environmental influences, learning opportunities, and effects of underlying temperament on the outward expression of fear and anxiety should not be underestimated. Identification of characteristics which predict resilience to stress are valuable, both to enable careful breeding for these traits and to develop predictive tests for puppies and procured animals. It is vitally important to rear animals in optimal environments and introduce them to a range of stimuli in a positive, controlled, and gradual way, as these can all help minimize the number of dogs which develop work-inhibiting fears. Future research should explore innovative methods to best measure the relative resilience of dogs to stressful events. This could include developing optimal exposure protocols to minimize the development of fear and anxiety, and exploring the influence of social learning and the most effective elements of stimulus presentation.
The gut microbiome is a diverse, host-specific, and symbiotic bacterial environment that is critical for mammalian survival and exerts a surprising yet powerful influence on brain and behavior. Gut dysbiosis has been linked to a wide range of physical and psychological disorders, including autism spectrum disorders and anxiety, as well as autoimmune and inflammatory disorders. A wealth of information on the effects of dysbiosis on anxiety and depression has been reported in laboratory model systems (e.g., germ-free mice); however, the effects of microbiome disruption on social behaviors (e.g., aggression) of non-model species that may be particularly important in understanding many aspects of physiology and behavior have yet to be fully explored. Here we assessed the sex-specific effects of a broad-spectrum antibiotic on the gut microbiome and its effects on social behaviors in male and female Siberian hamsters (Phodopus sungorus). In Experiment 1, we administered a broad-spectrum antibiotic on a short-term basis and found that antibiotic treatment altered the microbial communities in the gut in male and female hamsters. In Experiment 2, we tested the effects of single versus repeated antibiotic treatment (including a recovery phase) on behavior, and found that two, but not one, treatments caused marked decreases in aggressive behavior, but not other social behaviors, in males; aggression returned to normal levels following recovery. Antibiotic-treated females, in contrast, showed decreased aggression after a single treatment, with all other social behaviors unaffected. Unlike males, female aggression did not return to normal during either recovery period. The present findings demonstrate that modest antibiotic treatment results in marked disruption of the gut microbiome in hamsters, akin to research done in other rodent species and humans. Further, we show that treatment with a broad-spectrum antibiotic, which has dysbiotic effects, also has robust, sex-specific effects on aggression, a critical behavior in the survival and reproductive success of many rodent species.