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Fresh Food Consumption Increases Microbiome Diversity and Promotes Changes in Bacteria Composition on the Skin of Pet Dogs Compared to Dry Foods

Authors:

Abstract

The skin is the first barrier the body has to protect itself from the environment. There are several bacteria that populate the skin, and their composition may change throughout the dog’s life due to several factors, such as environmental changes and diseases. The objective of this research was to determine the skin microbiome changes due to a change in diet on healthy pet dogs. Healthy client-owned dogs (8) were fed a fresh diet for 30 days then dry foods for another 30 days after a 4-day transition period. Skin bacterial population samples were collected after each 30-day feeding period and compared to determine microbiome diversity. Alpha diversity was higher when dogs were fed the fresh diet compared to the dry foods. Additionally, feeding fresh food to dogs increased the proportion of Staphylococcus and decreased Porphyromonas and Corynebacterium. In conclusion, changing from fresh diet to dry foods promoted a relative decrease in skin microbiome in healthy pet dogs.
Citation: Leverett, K.; Manjarín, R.;
Laird, E.; Valtierra, D.;
Santiago-Rodriguez, T.M.; Donadelli,
R.; Perez-Camargo, G. Fresh Food
Consumption Increases Microbiome
Diversity and Promotes Changes in
Bacteria Composition on the Skin of
Pet Dogs Compared to Dry Foods.
Animals 2022,12, 1881. https://
doi.org/10.3390/ani12151881
Academic Editor: Giacomo Biagi
Received: 26 April 2022
Accepted: 19 July 2022
Published: 22 July 2022
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4.0/).
animals
Article
Fresh Food Consumption Increases Microbiome Diversity and
Promotes Changes in Bacteria Composition on the Skin of Pet
Dogs Compared to Dry Foods
Kennedy Leverett 1, Rodrigo Manjarín2, Erica Laird 3, Diana Valtierra 3, Tasha M. Santiago-Rodriguez 4,
Renan Donadelli 3and Gerardo Perez-Camargo 3, *
1Carlson College of Veterinary Medicine, Oregon State University, Corvallis, OR 97331, USA;
kennedyl@alumni.princeton.edu
2Animal Science Department, California Polytechnic State University, San Luis Obispo, CA 93407, USA;
rmanjari@calpoly.edu
3Freshpet, Bethlehem, PA 18017, USA; elaird@freshpet.com (E.L.); dvaltierra@freshpet.com (D.V.);
rdonadelli@freshpet.com (R.D.)
4Diversigen, Inc., Houston, TX 77046, USA; tsantiagoro@gmail.com
*Correspondence: gperezcamargo@freshpet.com
Simple Summary:
Dog skin is the first defense against the environment. There are several bacteria
that live on the skin and there are differences in their types and quantities depending on the dog.
Food is known to influence the bacteria in the intestine and the skin fat composition; however, it is
not known if diet can impact the bacteria on the skin. The objective of this study was to evaluate if
diet can change the bacteria on the skin of healthy dogs. Results from this study showed that there
was an increase in bacterium types and a change in their relative quantity when dogs were fed a fresh
dog food compared to these same dogs fed dry pet foods. This study was the first of its kind and
shone some light on how different pet foods impact skin microbiome.
Abstract:
The skin is the first barrier the body has to protect itself from the environment. There are
several bacteria that populate the skin, and their composition may change throughout the dog’s life
due to several factors, such as environmental changes and diseases. The objective of this research
was to determine the skin microbiome changes due to a change in diet on healthy pet dogs. Healthy
client-owned dogs (8) were fed a fresh diet for 30 days then dry foods for another 30 days after
a 4-day
transition period. Skin bacterial population samples were collected after each 30-day feeding
period and compared to determine microbiome diversity. Alpha diversity was higher when dogs
were fed the fresh diet compared to the dry foods. Additionally, feeding fresh food to dogs increased
the proportion of Staphylococcus and decreased Porphyromonas and Corynebacterium. In conclusion,
changing from fresh diet to dry foods promoted a relative decrease in skin microbiome in healthy
pet dogs.
Keywords: canine; microbiome diversity; pet food; skin bacteria populations
1. Introduction
The skin is the first barrier that animals have to defend themselves. In dogs, diseases
like pruritus, ulcers, pustules, and allergies commonly infect and affect the skin [
1
6
].
According to the Veterinary Practice News, in 2018 the average costs of treatment for atopic
dermatitis (first most common medical condition in dogs), benign skin neoplasia (third
most common), and pyoderma (fourth most common) were $255.00 USD, $377.00 USD,
and $128.00 USD, respectively [
7
]. The percentage of the population of dogs that suffer
from a skin condition is not known. However, there are pet food companies producing dog
foods that aim to aid in skin health. While in most of the cases the role the microbiome
Animals 2022,12, 1881. https://doi.org/10.3390/ani12151881 https://www.mdpi.com/journal/animals
Animals 2022,12, 1881 2 of 12
plays in the severity of such diseases is not known, Chermprapai and others [
8
] reported
an increase in the relative abundance of Staphylococcus,Psychrobacter,Trichococcus, and
Brachybacterium in dogs with atopic dermatitis compared to healthy dogs. Moreover,
DeCandia and co-workers [
9
] reported changes in skin microbiome of canids (coyotes, red
foxes, and gray foxes) when infected by mites (Sarcoptes scabiei), in addition to facilitating
secondary bacterial infections such as Staphylococcus pseudintermedius and Corynebacterium.
Aside from disease influencing microbiome, diet can change the dog skin fat composi-
tion [
10
12
] and lead to a change in bacterial populations as proposed by some research
with humans [
13
,
14
]. The usual targeted nutrients are fats and specific fatty acids. For
example, feeding high levels of eicosapentaenoic acid improved pruritus, alopecia, and
coat character compared to corn oil [
15
]. Similarly, when the dog food n-6:n-3 ratio was 1:1,
serum prostaglandin E3 (a proinflammatory eicosanoid from the metabolism of arachidonic
acid) concentration was decreased compared to baseline levels [
16
]. In addition, the authors
also reported an improvement in skin pruritus clinical scores [
16
]. Moreover, there are
commercial pet foods and supplements made specifically for skin (e.g., sensitive skin,
healthy skin and coat, skin, and coat care). However, to the authors’ knowledge, there are
no studies relating these dietary interventions and changes in skin microbiome.
Conversely, it is well understood how nutrition can change the intestinal bacteria
community [
17
19
], as the gastrointestinal tract (and its microbiome) has access to the
nutrients in the food before other organs. Fibers are the most common nutrient of interest
since they are not digested and absorbed by animals. Additionally, some novel research
in humans indicates a relationship between the gut and the skin [
20
]. Thus, diet could
also indirectly influence skin through changes in the gut microbiome. While dietary
supplements have been evaluated in dogs with skin issues [
15
,
21
], the effects of dietary
interventions in the microbiome of healthy dogs are yet to be investigated. Moreover, the
effects of different food types on dog skin microbiome have not been evaluated to date.
While complete and balanced diets in the US must comply with the Association of American
Feed Control Officials guidelines [
22
], it does not mean that they are made from the same
ingredients and manufactured through similar processes. Compared to the commonly
known dry foods, fresh foods are processed at relatively lower temperatures and pressures.
They also have a higher proportion of fresh meats, which increases the proportions of
protein and fat in the food. Finally, fresh foods must be refrigerated after processing to
prevent spoilage. Conversely, dry foods have higher proportions of carbohydrates and
lower fat contents. Moreover, the drying process allows these diets to be shelf stable. Thus,
a dry pet food will be made from different ingredients and through different processes than
a fresh diet. As a result, there are differences in the nutrient profile of the diets and the
nutrient availability to the animal [
23
], which could in turn influence the nourishment of
the animal.
When considering the research with dogs, the most common practice is the use of
kennel dogs to control variability of the environment and animals. However, kennel
conditions are different from house conditions and kennels have a limited number of
breeds used in their research. Since the environment is one of the key components known
to impact the microbiome [
24
], the ecological validity of microbiome research using kennel
dogs may be questioned when considering pet dogs. Therefore, the objective of this research
was to determine the effects of fresh vs. dry diet in the skin microbiome of healthy pet dogs.
The change from fresh dog food to dry diets decreased the skin microbiome diversity of
healthy pet dogs tested in this work.
2. Materials and Methods
2.1. Dog Recruitment and General Study Guidelines
This study was carried out in strict accordance with the recommendations in the
Guide for the Care and Use of Laboratory Animals of the National Institute of Health.
All dogs enrolled in the trial were the property of responsible adults. Eight pet dogs
were recruited from Bethlehem, PA, USA and Flemington, NJ, USA. The research protocol
Animals 2022,12, 1881 3 of 12
was explained to dog owners, and their conscious consent was required in the form of a
formal email to K.L. for the inclusion of their animals in the trial. Dog owners were aware
that they could remove their pets from the trial at any time if they desired to do so. The
demographics of the dogs are reported in Table 1. Treatment with systemic antifungals or
antibiotics three months prior to the start of the study was used as an exclusion criterion.
All dogs were castrated. Each dog owner was instructed to (1) feed the animals according
to diet manufacturer instructions, (2) adjust food intake to maintain the dog’s body weight
throughout the study, and (3) refrain from feeding table food or treats for the duration
of the study. Dog treats (Dog Joy, Freshpet Inc., Secaucus, NJ, USA) were provided to
all participants and they were instructed to follow the feeding guidelines as outlined on
the package.
Table 1. Demographic information of dogs enrolled in the study.
Dog ID Breed Sex Age (Years)
D010 Mixed Male 1
D011 Goldendoodle Male 3
D012 Australian Cattle Male 8
D013 Mixed Female 2
D014 Mixed Male 0.8
D015 Mixed Male 5
D016 American Bully Male 5
D017 American Bully Female 4
2.2. Feeding Protocol and Diet Nutrient and Ingredient Compositions
The trial took place between September and November 2020. All dogs were fed by
their owners as instructed by E.L. and K.L. All dogs were fed the Freshpet Select Sen-
sitive Stomach and Skin roll (FPS, steam cooked for approximately 15 min at 100
C)
for 30 consecutive days
, followed by their regular dry food diet (DRY, extruded) for an
additional
30 consecutive days
. A 4-day transition period was implemented to switch diets,
during which 25% of FPS was replaced by DRY each day. FPS and DRY food samples were
collected from each participant and sent to a commercial laboratory (Midwest Laboratories,
Omaha, NE, USA) for analysis of moisture (AOAC 930.15), crude protein (
AOAC 990.03
),
acid hydrolyzed fat (modified AOAC 954.02), ash (AOAC 942.05), total dietary fiber (modi-
fied AOAC 991.43), insoluble and soluble fibers (modified
AOAC 991.43
), fatty acid profile
(AOAC 996.06), and zinc (modified AOAC 985.01). The analyzed proximate nutrient
composition is presented in Table 2, selected nutrients known to impact skin health are
presented in Table 3, and the list of ingredients of each diet in descending order of inclusion
is provided in Supplemental Material.
Table 2.
Moisture and macro nutrient content on dry matter basis of the experimental diets (%),
metabolizable energy data (kcal/kg diet), and zinc (mg/kg of diet on a dry matter basis).
Nutrient DRY 1 DRY 2 DRY 3 DRY 4 DRY 5 DRY
Average FPS
Moisture 7.9 9.9 7.6 10.4 6.4 8.5 76.3
Crude Protein 37.2 33.8 40 26.8 28.4 33.0 43.9
Fat 20.5 11.8 19.7 15.4 13.2 16.1 21.4
Ash 10.1 7.8 9.6 7.2 5.7 8.1 7.9
Total Dietary Fiber 12.2 10.9 12.0 8.0 14.2 11.5 11.8
Insoluble Fiber 9.8 8.9 9.4 6.6 12.1 9.4 6.3
Soluble Fiber 2.4 2.0 2.6 1.5 2.1 2.1 5.5
Nitrogen-free Extract 119.4 35.8 19.8 42.5 38.5 31.2 17.7
Metabolizable Energy
2
, Dry Basis
(Wet Basis)
3724
(3429)
3439
(3099)
3768
(3481)
3735
(3346)
3464
(3242)
3616
(3308)
3975
(942)
Zinc 265 289 232 208 222 243 215
1
Nitrogen-free extract = 100-Moisture-Crude protein-Fat-Ash-Total dietary fiber.
2
Metabolizable Energy estimated
based on the Modified Atwater values of 3.5 for crude protein and nitrogen-free extract and 8.5 for fat, as outlined
by the AAFCO.
Animals 2022,12, 1881 4 of 12
Table 3. Selected fatty acids content (% of dry matter) of experimental diets.
Nutrient DRY 1 DRY 2 DRY 3 DRY 4 DRY 5 DRY
Average FPS
Saturated fats 6.58 2.71 5.78 6.63 3.29 5.00 6.82
Monosaturated fats 8.41 4.64 8.49 5.84 4.72 6.42 8.85
Polyunsaturated fats 3.94 3.18 3.87 1.28 4.22 3.30 5.21
ω-6 fatty acids 3.65 2.50 3.20 1.18 3.35 2.78 4.78
ω-3 fatty acids 0.26 0.67 0.63 0.10 0.85 0.50 0.39
ω-6: ω-3 ratio 114.04 3.73 5.08 11.80 3.94 5.56 12.26
Linoleic acid 3.51 2.38 3.06 1.14 3.26 2.67 4.32
α-Linolenic acid 0.23 0.42 0.44 0.09 0.82 0.40 0.24
Arachidonic acid 0.08 0.06 0.08 0.02 0.04 0.06 0.35
Eicosapentaenoic acid nd 20.07 0.09 nd nd 0.03 10.03
Docosahexaenoic acid nd 0.14 0.08 nd nd 0.04 10.09
1ω
-6:
ω
-3 ratio calculated as
ω
-6 fatty acids divided by
ω
-3 fatty acids.
2
nd considered in the average value
as zero.
2.3. Skin Microbiome Sample Collection
To measure changes in skin bacterial populations, swab samples from the internal ear,
interdigital area of the front paw, and the groin area were collected on each dog following
the 30-day feeding of FPS and DRY diets. During both sample collections dog owners were
present, and they observed the procedure throughout the duration of the sampling. Samples
were taken on the right side of the animals using a sterile BBL
CultureSwab
(BD
Corporate, Franklin Lakes, NJ, USA) by rubbing the swab on each sampling
site 40 times
and rotating the swab by one quarter every 10 strokes [
4
]. Immediately after collection,
samples were placed on ice and transported to Freshpet (Bethlehem, PA, USA), where they
were frozen and stored at
20
C until DNA extraction. Dog owners were asked to refrain
from bathing or deodorizing the animals from 1 week before each swabbing period. To
decrease the contamination with foreign bacteria, the person collecting the samples visually
inspected the area to ensure that the area selected for collection was not recently licked by
the dog or had any material that was not skin and hair.
2.4. DNA Extraction and Analysis
DNA extraction was carried out at the University of Arkansas for Medical Sciences
(Little Rock, AR, USA). DNA was extracted using DNeasy
®
PowerSoil
®
Kit Quick-Start (Qi-
agen, Hilden, Germany) according to manufacturer instructions. Samples were amplified
and the 16S rRNA hypervariable 4 (V4) region was tagged through PCR using 96 unique
combinations of 8 forward and 12 reverse barcoded primers, as previously described [
25
].
PCR cycling settings were the following: initial denaturation at 94
C for 3 min; touchdown
cycling for 30 cycles of 94
C for 45 s, 80–50
C for 60 s, 72
C for 90 s, decreasing 1
C each
cycle; 12 cycles of 94
C for 45 s, 50
C for 60 s, 72
C for 90 s; and a final extension of 72
C
for 10 min. PCR products were quantified with Quant-iT
PicoGreen
dsDNA (Invitro-
gen, Carlsbad, CA, USA). Equal nanograms of each library were pooled, and amplicons of
approximately 300 nt in length were selected using Agencourt AMPure XP magnetic beads
(Beckman Coulter, Brea, CA, USA). Final libraries were sent to Princeton University Ge-
nomics Core Facility (Princeton, NJ, USA) for paired-end amplicon sequencing (
2×150 nt
)
on an Illumina MiSeq machine (Illumina, San Diego, CA, SA).
2.5. Data Processing and Taxonomic Composition
Raw data was demultiplexed in Princeton University’s High Throughput Sequencing
Database using a paired-end, dual-indexed barcode splitter that allowed one nucleotide
mismatch between expected and observed barcode sequences. Demultiplexed reads were
imported into QIIME2 version 2021.4 [
26
], and the dada2 denoise-paired function [
27
] was
used to correct sequencing errors and combine paired-end reads for taxonomic feature
identification. A rooted tree of taxonomic features was created using the QIIME2 function
Animals 2022,12, 1881 5 of 12
fasttree [
28
], then composition was determined, and taxonomy was assigned with the
q2-feature-classifier plugin [
29
] and a classify-sklearn naïve Bayes classifier pre-trained
on Greengenes 13_8 [
30
]. This classifier clustered samples at 99% similarity and trimmed
sequences to only include 250 bases from the 16S V4 region. Microbiome alpha diversity
analyses were performed using the core diversity_analyses.py script in the Quantitative
Insights Into Microbial Ecology (QIIME1) [
24
] to determine observed operational taxonomic
units (OTUs), Shannon, and Chao1 indexes.
2.6. Statistical Methods
To investigate taxa contribution to overall differences between groups, raw counts at
the genus level were imported into Primer-e software (Albany, New Zealand), standardized
to relative composition (so sample totals are 100%), square root-transformed, and analyzed
with a Bray-Curtis similarity distance matrix. A non-parametric permutational analysis
of variance (PERMANOVA; Primer-e) was used for testing the null hypothesis of no
difference between groups under a reduced model, 9999 permutations, and type III sum
of squares [
31
]. An analysis of similarity percentages (SIMPER; Primer) with a cut-off
value of 70% was used to select genera contributing to the overall microbiome dissimilarity
between FPS and DRY [
31
]. Diet-induced changes in genera selected by SIMPER were
further analyzed with %Polynova SAS Macro [
32
]. Data are presented as fold change by
DRY compared to FPS. The average values of FPS and DRY fed dogs were considered
significant when p< 0.05.
3. Results
Dog D013 was excluded from the analysis due to surgery and postoperative antibiotic
treatment during the study.
Nutrient composition on a dry matter basis of dry pet foods and FPS is reported
on Tables 2and 3. The FPS diet had a greater moisture content than DRY. Moreover, on
average, FPS had a higher protein and fat content and a lower carbohydrate concentration
than DRY, whereas the ash content was similar. While total dietary fiber was similar among
diets, the soluble fiber content of FPS was between 2.1 and 3.8 times higher than the DRY
foods; consequently, the insoluble fiber content of FPS was lower than DRY diets (Table 2).
Zinc content was higher in DRY foods than FPS; however, FPS had a higher concentration
of linoleic, arachidonic, and DHA acids (Table 3). The FPS diet had a higher concentration
of saturated and polyunsaturated fatty acids; however, the n-3 fatty acid concentration was
on average lower than the DRY foods (Table 3).
Analysis of 16S rRNA in groin identified a total of 627 OTUs that were aggregated
into 39 phyla and 421 genera. Similarly, ear analysis yielded 663 OTUs separated into 37
phyla and 435 genera, whereas in the paw 477 OTUS were aggregated into 32 phyla and
322 genera. Taxonomic composition bar plots were constructed to show the overall change
of the relative percentage of phyla and genera (Figure 1) for each body site between FPS
and DRY.
At the phyla level, DRY increased Actinobacteria,Bacteroidetes, and Proteobacteria and
decreased Planctomycetes, Firmicutes, and Chloroflexi populations compared to FPS (p< 0.05;
Figure 1A). When considering the 3 different skin sites, the groin had a higher population of
Firmicutes compared to the other sites and the paw had higher proportions of Cyanobacteria
and Planctomycetes (p< 0.05). The most common genera among the different skin sites and
diets were Staphylococcus, followed by Porphyromonas,Streptococcus,Corynebacterium, and
Conchiformibius (Figure 1B). The groin had higher proportions of Staphylococcus compared
to the ear and paw (p< 0.05).
Animals 2022,12, 1881 6 of 12
Animals 2022, 12, 1881 6 of 13
among diets, the soluble fiber content of FPS was between 2.1 and 3.8 times higher than
the DRY foods; consequently, the insoluble fiber content of FPS was lower than DRY diets
(Table 2). Zinc content was higher in DRY foods than FPS; however, FPS had a higher
concentration of linoleic, arachidonic, and DHA acids (Table 3). The FPS diet had a higher
concentration of saturated and polyunsaturated fatty acids; however, the n-3 fatty acid
concentration was on average lower than the DRY foods (Table 3).
Analysis of 16S rRNA in groin identified a total of 627 OTUs that were aggregated
into 39 phyla and 421 genera. Similarly, ear analysis yielded 663 OTUs separated into 37
phyla and 435 genera, whereas in the paw 477 OTUS were aggregated into 32 phyla and
322 genera. Taxonomic composition bar plots were constructed to show the overall change
of the relative percentage of phyla and genera (Figure 1) for each body site between FPS
and DRY.
Figure 1. Taxonomic composition changes between body sites and diets. (A) Change of taxonomic
composition of the skin microbial phyla and (B) genera for each body site between fresh (FPS) and
dry (DRY) dog foods. Figures created with BioRender.com (Accessed on 15 February 2022). Supple-
mentary Table S1 shows the relative percentages for each reported parameter.
At the phyla level, DRY increased Actinobacteria, Bacteroidetes, and Proteobacteria and
decreased Planctomycetes, Firmicutes, and Chloroflexi populations compared to FPS (p <
0.05; Figure 1A). When considering the 3 different skin sites, the groin had a higher pop-
ulation of Firmicutes compared to the other sites and the paw had higher proportions of
Cyanobacteria and Planctomycetes (p < 0.05). The most common genera among the different
skin sites and diets were Staphylococcus, followed by Porphyromonas, Streptococcus, Coryne-
bacterium, and Conchiformibius (Figure 1B). The groin had higher proportions of Staphylo-
coccus compared to the ear and paw (p < 0.05).
Figure 1.
Taxonomic composition changes between body sites and diets. (
A
) Change of taxonomic
composition of the skin microbial phyla and (
B
) genera for each body site between fresh (FPS)
and dry (DRY) dog foods. Figures created with BioRender.com (Accessed on 15 February 2022).
Supplementary Table S1 shows the relative percentages for each reported parameter.
There was an overall effect of diet in skin microbiome regardless of the area sampled
(PERMANOVA p
0.05), with a significant decrease of alpha diversity index Chao1 in
DRY compared to FPS (p0.05; Figure 2).
Animals 2022, 12, 1881 7 of 13
There was an overall effect of diet in skin microbiome regardless of the area sampled
(PERMANOVA p 0.05), with a significant decrease of alpha diversity index Chao1 in
DRY compared to FPS (p 0.05; Figure 2).
Figure 2. Skin microbiome alpha diversity of pet dogs fed fresh (FPS) versus dry (DRY) food. Ob-
served OTUs, Shannon, and Chao1 indices of alpha diversity at genus level in dogs fed FPS for 30
consecutive days, followed by DRY for an additional 30 consecutive days. Values were computed
using the core_diversity_analyses.py script in Quantitative Insights into Microbial Ecology. Group
differences were assessed by non-parametric permutational analysis of variance with protocol and
time as fixed effects, under a reduced model, 9999 permutations, and type III sum of squares.
Data from different swab areas were combined for further analyses. SIMPER analysis
yielded a 60.41% average dissimilarity between FPS and DRY, with 61 genera contributing
to 70% of differences between FPS and DRY (Figure 3).
Figure 3. Cumulative genera percent dissimilarity of skin microbiome of pet dogs fed fresh (FPS)
vs. dry (DRY) food. Cumulative % contribution of genera to dissimilarity between FPS and DRY
(left Y axis), and their corresponding ratio of average dissimilarity to its standard deviation (right X
axis).
Staphylococcus, Porphyromonas, Streptococcus, Corynebacterium, Conchiformibius, and
Pseudomonas showed the largest percentage contribution to dissimilarity between FPS and
DRY, whereas Pedobacter, Porphyromonas, Hymenobacter, Spirosoma, Corynebacterium, and
Bacteroides were the best discriminators, as their ratio of average dissimilarity to its stand-
ard deviation were the highest (Figure 3). Compared with FPS, DRY increased (p 0.05)
average percentage relative counts of Hymenobacter, Acinetobacter, Neisseria, Stenotropho-
monas, and Janthinobacterium, and decreased (p 0.05) Actinomycetospora, Massilia, Bac-
teroides, Spirosoma, Mycoplasma, Jonesia, DA101, Sporosarcina, and Actinotelluria (Figure 4).
Figure 2.
Skin microbiome alpha diversity of pet dogs fed fresh (FPS) versus dry (DRY) food.
Observed OTUs, Shannon, and Chao1 indices of alpha diversity at genus level in dogs fed FPS
for 30 consecutive days
, followed by DRY for an additional 30 consecutive days. Values were com-
puted using the core_diversity_analyses.py script in Quantitative Insights into Microbial Ecology.
Group differences were assessed by non-parametric permutational analysis of variance with protocol
and time as fixed effects, under a reduced model, 9999 permutations, and type III sum of squares.
Animals 2022,12, 1881 7 of 12
Data from different swab areas were combined for further analyses. SIMPER analysis
yielded a 60.41% average dissimilarity between FPS and DRY, with 61 genera contributing
to 70% of differences between FPS and DRY (Figure 3).
Animals 2022, 12, 1881 7 of 13
There was an overall effect of diet in skin microbiome regardless of the area sampled
(PERMANOVA p 0.05), with a significant decrease of alpha diversity index Chao1 in
DRY compared to FPS (p 0.05; Figure 2).
Figure 2. Skin microbiome alpha diversity of pet dogs fed fresh (FPS) versus dry (DRY) food. Ob-
served OTUs, Shannon, and Chao1 indices of alpha diversity at genus level in dogs fed FPS for 30
consecutive days, followed by DRY for an additional 30 consecutive days. Values were computed
using the core_diversity_analyses.py script in Quantitative Insights into Microbial Ecology. Group
differences were assessed by non-parametric permutational analysis of variance with protocol and
time as fixed effects, under a reduced model, 9999 permutations, and type III sum of squares.
Data from different swab areas were combined for further analyses. SIMPER analysis
yielded a 60.41% average dissimilarity between FPS and DRY, with 61 genera contributing
to 70% of differences between FPS and DRY (Figure 3).
Figure 3. Cumulative genera percent dissimilarity of skin microbiome of pet dogs fed fresh (FPS)
vs. dry (DRY) food. Cumulative % contribution of genera to dissimilarity between FPS and DRY
(left Y axis), and their corresponding ratio of average dissimilarity to its standard deviation (right X
axis).
Staphylococcus, Porphyromonas, Streptococcus, Corynebacterium, Conchiformibius, and
Pseudomonas showed the largest percentage contribution to dissimilarity between FPS and
DRY, whereas Pedobacter, Porphyromonas, Hymenobacter, Spirosoma, Corynebacterium, and
Bacteroides were the best discriminators, as their ratio of average dissimilarity to its stand-
ard deviation were the highest (Figure 3). Compared with FPS, DRY increased (p 0.05)
average percentage relative counts of Hymenobacter, Acinetobacter, Neisseria, Stenotropho-
monas, and Janthinobacterium, and decreased (p 0.05) Actinomycetospora, Massilia, Bac-
teroides, Spirosoma, Mycoplasma, Jonesia, DA101, Sporosarcina, and Actinotelluria (Figure 4).
Figure 3.
Cumulative genera percent dissimilarity of skin microbiome of pet dogs fed fresh (FPS) vs.
dry (DRY) food. Cumulative % contribution of genera to dissimilarity between FPS and DRY (left Y
axis), and their corresponding ratio of average dissimilarity to its standard deviation (right X axis).
Staphylococcus,Porphyromonas,Streptococcus,Corynebacterium,Conchiformibius, and
Pseudomonas showed the largest percentage contribution to dissimilarity between FPS and
DRY, whereas Pedobacter,Porphyromonas,Hymenobacter,Spirosoma,Corynebacterium, and
Bacteroides were the best discriminators, as their ratio of average dissimilarity to its standard
deviation were the highest (Figure 3). Compared with FPS, DRY increased (p
0.05) aver-
age percentage relative counts of Hymenobacter,Acinetobacter,Neisseria,Stenotrophomonas,
and Janthinobacterium, and decreased (p
0.05) Actinomycetospora, Massilia, Bacteroides,
Spirosoma, Mycoplasma, Jonesia, DA101, Sporosarcina, and Actinotelluria (Figure 4).
Animals 2022, 12, 1881 8 of 13
Figure 4. Average percentage relative counts of genera selected by SIMPER expressed as fold
change. Dogs were fed FPS for 30 consecutive days, followed by their DRY for an additional 30
consecutive days. Data were analyzed by a one-way ANOVA that included diet as fixed effect. * p
0.05, ** p 0.01.
4. Discussion
The objective of this study was to investigate whether diet (fresh vs. dry food) would
have an impact on the skin microbiome of pet dogs. Because of the differences in the en-
vironment that pet vs. kennel dogs are subjected to and the effects of the environment on
microbiome, the results here presented are an attempt to generate data that would repre-
sent the housing conditions that most of the dogs in the US live in. Case in point, when
the nasal and oral microbiome of detection dogs of different locations were tested, there
was a difference in nasal Chaos1 diversity of dogs housed in different states in the United
States [33]. While the number of animals enrolled was a limitation of this work, the varia-
bility in the dry foods consumed by the selected pet dogs was chosen as an attempt to
mimic a real-life situation in which dog owners decided to change dog foods. No statistical
analyses were performed among the different dry foods to investigate if they would have
an influence in skin microbiome, as this was not the goal of this research and there were
not enough experimental units for such analyses. The dietary differences go beyond the
nutrient composition, but also the ingredient content, particularly the protein and the fat
sources of the diets. These differences in ingredients and processing methods likely af-
fected the nutrient availability of the diets. For example, the amino acid availability of
different chicken-based protein changed depending on how these proteins were pro-
cessed [23]. For the health of the skin, perhaps the fat of the diet might have a greater
impact than the protein, since the outer layer of the epidermis, the stratum corneum, is
mainly composed of different fat compounds [14]. Overall, FPS have a higher fat content
than DRY foods, thus this may have better supported the health of the skin. Of all the fatty
acids, linoleic acid has a key role in the formation of the stratum corneum, as it is bound
to cornified envelopes to create a scaffolding structure for free ceramides present among
the corneocytes [14]. The formation of these bonds is essential for the “brick and mortar
structure of the stratum corneum and the proper barrier function that the skin has [34].
Since the fat content of the skin can select different bacteria to grow on the surface of the
skin [13,14] and changes in dietary fat composition promote changes in the skin fat com-
position [10–12], perhaps when combined, these two factors might promote a change in
the skin microbiome.
There are two main factors that may have supported the compositional changes in
skin bacteria populations in this study: the type of the diet fed and changes in weather
Figure 4.
Average percentage relative counts of genera selected by SIMPER expressed as fold change.
Dogs were fed FPS for 30 consecutive days, followed by their DRY for an additional 30 consecutive
days. Data were analyzed by a one-way ANOVA that included diet as fixed effect. * p
0.05,
** p0.01.
4. Discussion
The objective of this study was to investigate whether diet (fresh vs. dry food) would
have an impact on the skin microbiome of pet dogs. Because of the differences in the
environment that pet vs. kennel dogs are subjected to and the effects of the environment
on microbiome, the results here presented are an attempt to generate data that would
Animals 2022,12, 1881 8 of 12
represent the housing conditions that most of the dogs in the US live in. Case in point,
when the nasal and oral microbiome of detection dogs of different locations were tested,
there was a difference in nasal Chaos1 diversity of dogs housed in different states in the
United States [
33
]. While the number of animals enrolled was a limitation of this work, the
variability in the dry foods consumed by the selected pet dogs was chosen as an attempt to
mimic a real-life situation in which dog owners decided to change dog foods. No statistical
analyses were performed among the different dry foods to investigate if they would have
an influence in skin microbiome, as this was not the goal of this research and there were
not enough experimental units for such analyses. The dietary differences go beyond the
nutrient composition, but also the ingredient content, particularly the protein and the fat
sources of the diets. These differences in ingredients and processing methods likely affected
the nutrient availability of the diets. For example, the amino acid availability of different
chicken-based protein changed depending on how these proteins were processed [
23
]. For
the health of the skin, perhaps the fat of the diet might have a greater impact than the
protein, since the outer layer of the epidermis, the stratum corneum, is mainly composed of
different fat compounds [
14
]. Overall, FPS have a higher fat content than DRY foods, thus
this may have better supported the health of the skin. Of all the fatty acids, linoleic acid has
a key role in the formation of the stratum corneum, as it is bound to cornified envelopes to
create a scaffolding structure for free ceramides present among the corneocytes [
14
]. The
formation of these bonds is essential for the “brick and mortar” structure of the stratum
corneum and the proper barrier function that the skin has [
34
]. Since the fat content of the
skin can select different bacteria to grow on the surface of the skin [
13
,
14
] and changes in
dietary fat composition promote changes in the skin fat composition [
10
12
], perhaps when
combined, these two factors might promote a change in the skin microbiome.
There are two main factors that may have supported the compositional changes in
skin bacteria populations in this study: the type of the diet fed and changes in weather
conditions. Because the trial was performed from September through November 2020, there
were seasonal changes that might have affected the skin microbiome, since environmental
conditions are a known factor that impacts skin microbiome [
35
,
36
]. However, because
all dogs enrolled in the trial were indoor dogs with limited access to outdoors (occasional
walks and visits to the dog park), most likely the environmental conditions had limited
effects on the changes reported here, as the dogs would spend most of their time indoors
under controlled conditions. Thus, the diet change might be the main factor contributing
to the changes in microbial diversity, with seasonal environmental conditions playing a
smaller role. In a study that evaluated the skin microbiome of healthy and allergic dogs [
4
],
the diversity of the bacterial population was lower in allergic dogs compared to healthy
dogs. However, it is not known if the change is a cause or an effect of the disease. In
addition, the skin microbiome of dogs with atopic dermatitis was reported to have less
diversity and higher relative concentrations of Staphylococcus (especially S. pseudintermedius)
and Corynebacterium compared to healthy dogs [
5
]. Therefore, improving skin microbiome
could be beneficial in preventing or waning some of these illnesses. In this study, there
was a decrease in diversity when dogs were fed DRY compared to FPS. Moreover, the
abundance of Corynebacterium was higher in dogs fed DRY; however, the abundance of
Staphylococcus was lower compared to dogs fed FPS. Although these results are conflicting,
it is important to determine the species of the bacteria on the skin, as some specific species
are related to certain conditions [
37
]. For example, while the increased abundance of
Staphylococcus when dogs were fed FPS could be concerning, there is the need to further
investigate what species was increased. For example, in humans, Staphylococcus epidermidis
can prevent the colonization of Staphylococcus aureus [
38
]. While this has not been proven
true for dogs, it would be prudent to assume that the increase of Staphylococcus abundance
would be detrimental for the dog’s health. From research done with human subjects, it
is known that different skin sites have different concentrations of sebum and bacteria
populations [
13
,
39
]. The present research reported differences in bacteria composition in
Animals 2022,12, 1881 9 of 12
the different sites analyzed; however, the skin sebum content was not evaluated, and it
should be addressed in future research.
Although this study was not designed to investigate specific components in the
diet, differences in nutrient composition between FPS and DRY foods may have partially
contributed to the observed differences in skin microbial population. Diet nutrients (such
as zinc, higher fat content, and specific fatty acids) are known to impact the composition
of the skin [
11
,
21
]. Zinc is involved as a cofactor for RNA and DNA polymerases and in
the activation of delta-6-desaturase, an enzyme that converts linoleic acid into arachidonic
acid. Zinc concentration and availability are of particular interest for the health of the skin,
due to skin’s constant cell divisions to replenish the cells lost by desquamation. There were
different sources of zinc used in the experimental diets, such as zinc oxide, zinc proteinate,
and zinc sulfate. While all these zinc sources are recognized by AAFCO, zinc proteinate was
reported to be more bioavailable than zinc oxide and zinc sulfate [
40
,
41
]. A more available
zinc source would possibly contribute to the health of the skin. As reported previously
elsewhere [
41
], the diet with zinc proteinate increased the hair brightness of different areas
of the dog’s body, which the authors considered as a healthier coat. These same authors
also reported that dogs fed zinc proteinate had an immune response that persisted longer
than dogs fed zinc oxide. This persistent immune response could be beneficial for dogs in
controlling pathogenic bacteria colonization on the surface of the skin.
Another major difference among these diets is the soluble fiber content (Table 2). Solu-
ble fibers are known to change the gut microbiome composition [
42
44
]. Fiber fermentation
is beneficial to the host with the provision of short-chain fatty acids, specifically butyrate,
which has been shown to regulate some of the host’s physiology [
45
]. Moreover, there is
novel research showing a relationship between the gut and skin [20,36]. While the mecha-
nisms behind the gut–skin axis are not well understood to date, the gut microbiome can
indirectly influence the skin microbiome by modulating the host immune system. Due to
the novelty of gut–skin axis, even for human research, any associations with a dog model
must be approached carefully, although it would be safe to assume that the higher propor-
tions of soluble fibers in FPS would stimulate fermentation and bacterial growth in the
colon when dogs were fed this diet. This increase in bacteria populations and production of
fermentation products could stimulate the immune system and promote changes on how
the skin would react to different bacteria. However, neither the gut microbiome nor the
fermentation products were measured in the feces of the dogs enrolled in the trial. Since the
gut bacteria can modulate the immune system, it would be prudent to consider different
measurements of the immune system in future studies.
Finally, the water content of FPS was much higher than the DRY foods. However,
dogs are known to regulate water intake regardless of the amount of water present in the
food to maintain water balance [
46
,
47
]. Furthermore, the evaluation of the water balance
was not the intent this study. In humans it was reported that drinking 1 L more than their
baseline water intake [
48
] improved skin hydration status; however, the microbiome of
the skin was not evaluated. Moreover, Mukherjee and co-workers [
49
] reported that there
are differences in bacterial distribution on the face of women depending on the sebum or
hydration of the skin, although it is necessary to mention that the water intake was not
evaluated in that publication [
49
]. It is unknown if this is relevant for dogs, since humans
can willingly increase water intake to a certain level to meet research protocols and dogs
most likely would not voluntarily drink more.
As mentioned previously, the preset study has limitations. The small number of
animals, the use of different dry pet foods, and the change of environmental conditions
as the trial progressed are the main limitations. Future studies should take these into
consideration when designing new trials.
5. Conclusions
In conclusion, changing FPS diet to DRY promoted a decrease in skin microbiome rela-
tive abundance in dogs. Nevertheless, future research should evaluate the water balance,
Animals 2022,12, 1881 10 of 12
the colonic microbiome, and the immune system when analyzing the skin microbiome,
since these factors may have an impact the skin bacteria populations.
Supplementary Materials:
The following supporting information can be downloaded at: https:
//www.mdpi.com/article/10.3390/ani12151881/s1, Table S1: Relative percentages of the most
common Phyla and genera of dogs fed FPS and DRY foods.
Author Contributions:
K.L., G.P.-C., E.L. and D.V.; methodology, K.L., E.L., R.M., T.M.S.-R.; formal
analysis, R.M. and T.M.S.-R.; writing—original draft preparation, R.D. and R.M.; writing—review
and editing, R.D., R.M., G.P.-C. and K.L.; supervision, G.P.-C.; project administration, G.P.-C., K.L.,
E.L. and D.V.; funding acquisition, G.P.-C. All authors have read and agreed to the published version
of the manuscript.
Funding: This research received no external funding.
Institutional Review Board Statement:
Approval for all experimental procedures was obtained
from the Institutional Animal Care and Use Committee of the California State University (#2208),
and all procedures were in compliance with the National Research Council Guide for the Care and
Use of Laboratory Animals.
Informed Consent Statement:
This study was carried out in strict accordance with the recommenda-
tions in the Guide for the Care and Use of Laboratory Animals of the National Institute of Health.
The research protocol was explained to dog owners, and their consent was required for the inclusion
of the animals in the trial. Dog owners were aware that they could re-move their pets from the trial at
any time if they desired to do so.
Data Availability Statement:
The data presented in this study are available on request from the
corresponding author.
Acknowledgments:
We thank Antino Allen at the University of Arkansas for Medical Sciences for
allowing us to process our samples in his lab. We thank Alexandria DeCandia at the Smithsonian
Institution for her assistance and feedback throughout the lab analysis process. We would also like to
thank Wei Wang and Jessica Wiggins at Princeton University for their support during library prepara-
tion, sequencing, data processing and analysis, Amanda N. Dainton for reviewing the manuscript
before submission.
Conflicts of Interest:
This research was sponsored by Freshpet, the manufacturer of the Freshpet
Select Sensitive Stomach and Skin roll; E.L., D.V., R.D. and G.P.C. are employed by Freshpet. During
the feeding trial K.L. was an intern at Freshpet.
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[CrossRef]
... To date, studies of the canine skin microbiota have focused on 16S rRNA high-throughput sequencing to describe the taxonomic profile of healthy dogs and those with skin conditions, such as atopic dermatitis 1,[8][9][10][11][12][13][14][15][16][17][18][19] . Across these studies, the most dominant phyla observed across different skin sites are the Proteobacteria, with Firmicutes, Actinobacteria and Bacteroidota observed to a lesser extent. ...
... Seasonal changes and cohabitation with other dogs have been shown to significantly alter skin bacterial communities with dogs living together, in the same household, having a more similar bacterial profile than that of dogs living separately 1 . In addition, geographical origin, hygiene status of living environment, access to outdoor environments, life stage 20 and diet 19 have been shown to shape the skin microbiota of dogs 19,20 . ...
... Previous studies into the canine skin microbiome have generally utilised 16S sequencing approaches where the hypervariable region of the 16S gene studied can bias the reported microbial composition 1,[8][9][10][11][12][13][14][15][16][17][18][19] . There is only one study published to date utilising shotgun sequencing for a small number of canine skin samples (n = 11) 17 . ...
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Furthering our knowledge of the skin microbiome is essential to understand health and disease in canines. To date, studies into the canine skin microbiome have focused on 16S rRNA high throughput sequencing however, these lack the granularity of species and strain level taxonomic characterisation and their associated functions. The aim of this study was to provide a comprehensive assessment of the skin microbiome by analysing the skin microbiome of 72 healthy adult colony dogs, across four distinct skin sites and four breeds, using metagenomic sequencing. Our analysis revealed that breed and skin site are drivers of variation, and a core group of taxa and genes are present within the skin microbiome of healthy dogs, comprising 230 taxa and 1219 gene families. We identified 15 species within the core microbiome that are represented by more than one strain. The biosynthesis of secondary metabolites pathway was enriched in the core microbiome suggesting the skin microbiome may play a role in colonisation resistance and protection from invading pathogens. Additionally, we uncovered the novelty of the canine skin microbiome and show that further investigation is required to increase the suitability of current databases for metagenomic sequencing of canine skin samples.
... Two 11,14 did not report any taxa recovered in low numbers, but they did recover the species in their studies (personal communications). One study 21 found Sphingomonas spp on the same dogs at both sampling times, 30 days apart, although the species recovered were not reported. All are to median count cm −2 with IQR. ...
... Our data, and that reported in other studies, of the canine microbiome, 11,[13][14][15][16][17][18][19][20][21][22][23] suggest that the canine cutaneous flora is very broad and very variable. Torres et al 23 suggested that a core community of cutaneous bacteria might be identified across a broad group of animals. ...
... Identifying a core member of the microbiome is difficult as individual dogs have their own microbiome, which is similar across all body sites. 13,15,23 We suggest that Sphingomonas species might be considered candidates as part of the core gram-negative bacteria flora on normal dogs not just on the basis of its prevalence in the various studies but also because Leverett et al 21 found Sphingomonas spp on the same dogs, 30 days apart. ...
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OBJECTIVE To report the density, and the major constituents, of the bacteria on the skin surface of healthy dogs and to assess if scraping the skin before sampling was necessary. ANIMALS 20 healthy dogs were recruited for the study, with informed consent in all cases. METHODS Flocked swabs were used to sample the skin surface and to sample the skin surface after superficial scraping with a blunted spatula. Both samples were taken within a brass guide of 3.5 cm ⁻² area. Next-generation 16S rRNA sequencing was used to identify and quantify components of the bacterial microbiome. RESULTS The median density of the bacterial microbiome on the ventral abdomen of 20 healthy dogs was approximately 1.1 X 10 ⁵ cm ⁻² (IQR 1.22 X 10 ⁴ , 1.6 X 10 ⁵ cm ⁻² ). Sphingomonas species were isolated on 17 of the 20 dogs and Corynebacterium kroppstedtii from 15. CLINICAL RELEVANCE This is the first study to report the density of the canine skin microbiome. Superficial scraping of the skin before swabbing does not affect the result of sampling the microbiome in healthy dogs. These results will increase our understanding of the biology of canine skin.
... Our findings indicated that the distinction between dogs kept predominantly outdoors versus a combination of both indoors and outdoors did noticeably impact the bacterial or fungal diversity in our samples, similar to what has previously been described [54,57,59,60]. However, additional factors could modify the microbiome composition such as skin barrier alterations, immune response, genetic background, cohabitation with other animals and/or humans, and diet, among others [57,59,60,[62][63][64][65][66][67]. ...
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Photobiomodulation (PBM) is a newly adopted consensus term to replace the therapeutic application of low-level laser therapy. It has been suggested that PMB influences the microbiome which, in turn, has increasingly been shown to be linked with health and disease. Even though the use of PBM has also grown dramatically in veterinary medicine, there is still a lack of evidence supporting its effect in vivo. Our objective was to investigate the impact of a dual-wavelength near-infrared laser source (Multiwavelength Locked Laser System, MLS®) on the skin microbiome in atopic dogs. Twenty adult-client-owned atopic dogs were enrolled in the study. The dogs were treated with MLS® laser therapy on one half of the abdominal region, whereas the contralateral side was left untreated and served as a control. Skin microbiome samples were collected before and after MLS® treatments, and then subjected to NGS-based ITS and 16S rRNA analysis. The results showed that while microbiome composition and diversity were not significantly affected, PBM could play a role in modulating the abundance of specific bacterial species, in particular Staphylococcus, that represent a major skin pathogenic strain. To the best of the authors’ knowledge, this is the first study to investigate the potential impact of MLS® laser therapy on the skin microbiome in atopic dogs.
... Other factors include anatomical location of sample and breed. In addition, dietary influence has also been identified as a source of potential impact on dermal microbiota (6). Other factors that may be disruptive to dermal microbiota include topical treatments such as the use of cleansers or detergents. ...
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Introduction Working dogs routinely operate in environmental conditions which may necessitate daily bathing to remove contaminants or soilage. The impacts of frequent or repeated bathing on the canine dermal microbiota are unknown. The objective of this study was to characterize changes in canine dermal microbial populations following repeated daily bathing. Methods Labrador retrievers (n = 16) were bathed daily using a dilute dish detergent solution (1.6% detergent solution) over the course of 14 days. Dermal microbial DNA was collected via sterile swabs (n = 142) taken at days 0, 7, 14, 16, 21, 28, 35, 42, and 49 and analyzed for alpha diversity, beta diversity and relative abundance to assess changes in the dermal microbiota via 16 s sequencing. Results Results indicate that daily bathing significantly increased Shannon diversity, Chao1, and several rare amplicon sequence variants. Although typically reported in highest abundance, relative abundance was decreased in the phyla Actinobacteria, Firmicutes, and Proteobacteria (p < 0.05). Conclusion Repeated daily bathing with dilute dish detergent significantly reduced normal healthy dermal microbial taxa and created significant changes in the dermal microbiota of canines. Disruption to the canine dermal microbiota may cause negative impacts to canine dermal health and require further investigation.
... Some of this work is already happening as it pertains to the feline gastrointestinal and oral microbiomes; 54,55 however, thus far, changes in the cutaneous microbiota in relation to applied therapy have only started to be evaluated in dogs. 56,57 Additionally, the cutaneous metabolome itself needs to be further investigated in the feline patient. Various disease states not only impact the microbial communities on the skin, they also impact the metabolites and products generated by those organisms. ...
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... 12 A recent study suggested that diet can influence the diversity of the skin's bacterial microbiota as well. 13 Future studies in larger populations are needed to validate this result. ...
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Review article of the canine skin microbiome. https://todaysveterinarypractice.com/dermatology/the-canine-skin-and-ear-bacterial-microbiota/
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Since the 1960s, more than 350,000 new chemicals have been introduced into the lives of humans and domestic animals. Many of them have become part of modern life and some are affecting nature as pollutants. Yet, our comprehension of their potential health risks for both humans and animals remains partial. The “epithelial barrier theory” suggests that genetic predisposition and exposure to diverse factors damaging the epithelial barriers contribute to the emergence of allergic and autoimmune conditions. Impaired epithelial barriers, microbial dysbiosis, and tissue inflammation have been observed in a high number of mucosal inflammatory, autoimmune and neuropsychiatric diseases, many of which showed increased prevalence in the last decades. Pets, especially cats and dogs, share living spaces with humans and are exposed to household cleaners, personal care products, air pollutants, and microplastics. The utilisation of cosmetic products and food additives for pets is on the rise, unfortunately, accompanied by less rigorous safety regulations than those governing human products. In this review, we explore the implications of disruptions in epithelial barriers on the well‐being of companion animals, drawing comparisons with humans, and endeavour to elucidate the spectrum of diseases that afflict them. In addition, future research areas with the interconnectedness of human, animal, and environmental well‐being are highlighted in line with the “One Health” concept.
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OBJECTIVE To report the density, and constituents, of the mycobiome on the skin surface of normal dogs. ANIMALS 20 normal dogs were recruited for this study, with informed consent in all cases. METHODS Flocked swabs were used to sample the skin surface and to sample the skin surface after superficial scraping with a blunted scapula. Both samples were taken within a brass guide with an internal area of 3.5 cm ⁻² . Next-generation DNA sequencing was used to identify and quantify components of the mycobiome. RESULTS The median density of the mycobiome was 1.1 X 10 ⁵ cm ⁻² (IQR, 27,561, 409,572). Cladosporium spp and Vishniacozyma victoriae were found on all 20 dogs. CLINICAL RELEVANCE Knowledge of the density and the composition of the cutaneous mycobiome will increase our understanding of skin biology and may have relevance to future therapeutic trials.
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The skin is the largest organ of the human body and it protects the body from the external environment. It has become the topic of interest of researchers from various scientific fields. Microorganisms ensure the proper functioning of the skin. Of great importance, are the mutual relations between such microorganisms and their responses to environmental impacts, as dysbiosis may contribute to serious skin diseases. Molecular methods, used for microorganism identification, allow us to gain a better understanding of the skin microbiome. The presented article contains the latest reports on the skin microbiota in health and disease. The review discusses the relationship between a properly functioning microbiome and the body’s immune system, as well as the impact of internal and external factors on the human skin microbiome.
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The gastrointestinal (GI) microbiome of cats and dogs is increasingly recognized as a metabolically active organ inextricably linked to pet health. Food serves as a substrate for the GI microbiome of cats and dogs and plays a significant role in defining the composition and metabolism of the GI microbiome. The microbiome, in turn, facilitates the host’s nutrient digestion and the production of postbiotics, which are bacterially derived compounds that can influence pet health. Consequently, pet owners have a role in shaping the microbiome of cats and dogs through the food they choose to provide. Yet, a clear understanding of the impact these food choices have on the microbiome, and thus on the overall health of the pet, is lacking. Pet foods are formulated to contain the typical nutritional building blocks of carbohydrates, proteins, and fats, but increasingly include microbiome-targeted ingredients, such as prebiotics and probiotics. Each of these categories, as well as their relative proportions in food, can affect the composition and/or function of the microbiome. Accumulating evidence suggests that dietary components may impact not only GI disease, but also allergies, oral health, weight management, diabetes, and kidney disease through changes in the GI microbiome. Until recently, the focus of microbiome research was to characterize alterations in microbiome composition in disease states, while less research effort has been devoted to understanding how changes in nutrition can influence pet health by modifying the microbiome function. This review summarizes the impact of pet food nutritional components on the composition and function of the microbiome and examines evidence for the role of nutrition in impacting host health through the microbiome in a variety of disease states. Understanding how nutrition can modulate GI microbiome composition and function may reveal new avenues for enhancing the health and resilience of cats and dogs.
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Background: Sarcoptic mange is a highly contagious skin disease caused by the ectoparasitic mite Sarcoptes scabiei. Although it afflicts over 100 mammal species worldwide, sarcoptic mange remains a disease obscured by variability at the individual, population and species levels. Amid this variability, it is critical to identify consistent drivers of morbidity, particularly at the skin barrier. Methods: Using culture-independent next generation sequencing, we characterized the skin microbiome of three species of North American canids: coyotes (Canis latrans), red foxes (Vulpes vulpes) and gray foxes (Urocyon cinereoargenteus). We compared alpha and beta diversity between mange-infected and uninfected canids using the Kruskal-Wallis test and multivariate analysis of variance with permutation. We used analysis of composition of microbes and gneiss balances to perform differential abundance testing between infection groups. Results: We found remarkably consistent signatures of microbial dysbiosis associated with mange infection. Across genera, mange-infected canids exhibited reduced microbial diversity, altered community composition and increased abundance of opportunistic pathogens. The primary bacteria comprising secondary infections were Staphylococcus pseudintermedius, previously associated with canid ear and skin infections, and Corynebacterium spp., previously found among the gut flora of S. scabiei mites and hematophagous arthropods. Conclusions: This evidence suggests that sarcoptic mange infection consistently alters the canid skin microbiome and facilitates secondary bacterial infection, as seen in humans and other mammals infected with S. scabiei mites. These results provide valuable insights into the pathogenesis of mange at the skin barrier of North American canids and can inspire novel treatment strategies. By adopting a "One Health" framework that considers mites, microbes and the potential for interspecies transmission, we can better elucidate the patterns and processes underlying this ubiquitous and enigmatic disease.
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Canine atopic dermatitis is a genetically predisposed inflammatory and pruritic allergic skin disease that is often complicated by (secondary) bacterial and fungal (yeast) infections. High-throughput DNA sequencing was used to characterize the composition of the microbiome (bacteria and fungi) inhabiting specific sites of skin in healthy dogs and dogs with atopic dermatitis (AD) before and after topical antimicrobial treatment. Skin microbiome samples were collected from six healthy control dogs and three dogs spontaneously affected by AD by swabbing at (non-) predilection sites before, during and after treatment. Bacteria and fungi were profiled by Illumina sequencing of the 16S ribosomal RNA gene of bacteria (16S) and the internally transcribed spacer of the ribosomal gene cassette in fungi (ITS). The total cohort of dogs showed a high diversity of microbes on skin with a strong individual variability of both 16S and ITS profiles. The genera of Staphylococcus and Porphyromonas were dominantly present both on atopic and healthy skin and across all skin sites studied. In addition, bacterial and fungal alpha diversity were similar at the different skin sites. The topical antimicrobial treatment increased the diversity of bacterial and fungal compositions in course of time on both AD and healthy skin.
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Chicken-based ingredients are commonly used in pet food products, but vary greatly in nutrient composition and processing conditions that may affect their protein quality and digestibility. Testing the quality of protein sources undergoing different processing conditions provides important information to pet food producers. The objective of this study was to determine the chemical composition, nutrient digestibility, protein, and amino acid (AA) digestibility scores, and nitrogen-corrected true metabolizable energy (TMEn) of chicken-based ingredients that had undergone different processing conditions (i.e., chicken meal, raw chicken, retorted chicken, and steamed chicken) using the precision-fed cecectomized rooster assay. True nutrient digestibility was variable among the protein sources (60 to 76% of DM, 66 to 81% of OM, 83 to 90% of AHF, 48 to 59% of N, 50 to 95% of AA and 73 to 85% of TMEn/GE). In general, the chicken meal had a lower (P<0.05) nutrient digestibility than other ingredients tested, including DM, OM, and most indispensable and dispensable AA, with most having a true digestibility between 75 to 85%. The steamed chicken had the highest indispensable AA digestibilities, with all having a true digestibility greater than 88% and most being over 90%. TMEn value and digestible indispensable amino acid scores (DIAAS)-like values were higher (P < 0.0001) in the less processed chicken-based ingredients in comparison to chicken meal. Although animal proteins are often considered to be complete proteins, DIAAS-like values less than 100% suggest that ingredients like chicken meal may not provide all indispensable AA when included at levels to the meet minimal crude protein recommendation. Although raw protein sources are often touted as being the most digestible and of the highest quality, the steamed chicken had the highest (P < 0.0001) DIAAS-like values in this study. This study demonstrates the considerable variability exists, not only in the chemical composition but also in the true nutrient digestibility among chicken-based ingredients undergoing different processing conditions. These data justify more in vivo testing and the use of DIAAS-like values that consider AA profile, in vivo digestibility, and species-specific recommendations, to evaluate protein-based ingredients intended for use in dog and cat foods.
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Purpose of review: The skin is home to a diverse milieu of bacteria, fungi, viruses, bacteriophages, and archaeal communities. The application of culture-independent approaches has revolutionized the characterization of the skin microbiome and have revealed a previously underappreciated phylogenetic and functional granularity of skin-associated microbes in both health and disease states. Recent findings: The physiology of a given skin-niche drives the site-specific differences in bacterial phyla composition of healthy skin. Changes in the skin microbiome have consistently been associated with atopic dermatitis. In particular, Staphylococcus aureus overgrowth with concomitant decline in Staphylococcus epidermidis is a general feature associated with atopic dermatitis and is not restricted to eczematous lesions. Changes in fungal species are now also being described. Changes in the composition and metabolic activity of the gut microbiota are associated with skin health. Summary: We are now beginning to appreciate the intimate and intricate interactions between microbes and skin health. Multiple studies are currently focused on the manipulation of the skin or gut microbiome to explore their therapeutic potential in the prevention and treatment of skin inflammation.
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Recent advances in genomics, spectroscopy, and immunology have increased our understanding of the skin barrier. A new model of barrier lipid organization has emerged owing to the application of advanced modeling and microscopy techniques. The contribution of filaggrin gene mutations to atopic dermatitis has increased our appreciation of the role barrier perturbations play in inflammatory dermatoses. Next generation sequencing techniques have led to a greater understanding of the diversity of resident skin microorganisms and the close association between microbes and the host immune system. This paper reviews the basics of stratum corneum structure and function, with an emphasis on recent advances in our understanding of barrier perturbations and their effect on skin health. J Drugs Dermatol. 2019;18(1 Suppl):s63-67