The molecular age is upon us, creating exciting
opportunities in the pet food industry. Genome sequence
data, high-throughput functional genomics assays, and nanotools
have several applications to pet health and the pet food
industry. Such technology may be used to expand ingredient
options (e.g., items enriched in functional nutrients), for pet
food testing (e.g., contamination of microbes or toxins;
identify ingredient origin; detection of GMOs), or for
molecular-based animal research. Genomic biology may be
used to gain a better understanding of dog and cat physiology
and how nutrition contributes to health and disease.
Because this last point will arguably have the greatest impact
on pet health and the pet food industry, it will be the focus
herein.
Genomic tools have greatly changed the landscape of all
research fields pertaining to life sciences, including
nutrition. In pets, such tools are being used to study
microbial populations and gene expression changes in blood and
various tissues. In the past, the field of microbiology
was greatly limited by the methodology and inability to culture
the majority of gastrointestinal microbiota. DNA-based
techniques, which include quantitative polymerase chain
reaction that is very sensitive and used to quantify specific
microbial species, gel-based assays such as denaturing gradient
gel electrophoresis that allows for a broad view of the
population, and pyrosequencing that allows for widespread
characterization of phylogeny (who is present?) and
functional/metabolic capacity (what are they doing?), have many
scientific and practical advantages. Intestinal microbes
may be affected by host species, age, health status, and
location in gastrointestinal tract. Our laboratory and
others have begun using DNA-based sequencing techniques to
characterize the canine and feline gastrointestinal tracts
(Suchodolski
et al
., 2008; Middelbos
et al
., 2010; Swanson
et al
., 2010; Barry, unpublished data). These initial
experiments in healthy adult dogs and cats are providing a
strong foundation for future initiatives that may be aimed at
studying the microbial profile and metabolic pathways of
animals with different health status (e.g., healthy vs. IBD),
life stage (e.g., weanling vs. adult vs. geriatric), species
(e.g., dog vs. cat), or dietary regimen.
Genomic biology is also being used to advance our
understanding of nutrient-gene interactions within the dog and
cat. The field of 'nutrigenetics' is focused on
identifying how genetic background affects the response (e.g.,
absorption; metabolism; excretion; etc.) to a nutrient or
diet. In contrast, 'nutrigenomics' is focused on
measuring how a nutrient or diet affects gene expression.
Most mammalian genomes contain ~20,000-25,000 genes, all
interacting in complex ways. Identifying the genetic
basis for disease may be difficult, even for monogenic diseases
affected by a single mutation. One of the most popular
examples of nutrigenetics in dogs is that of copper toxicosis
in Bedlington Terriers (Klomp
et al
, 2003). In this example, dogs with a mutation in the
MURR1 gene accumulate copper in hepatic tissue over time,
eventually resulting in copper toxicosis. If undiagnosed
and fed a diet containing standard copper concentrations, these
dogs usually die between 3 and 7 years of age. A test is
now available to detect this mutation at birth so that dietary
management may be implemented long before clinical symptoms of
the disease appear. If diagnosed and fed a low-copper
diet, this population may live without complications.
Other monogenic diseases have been identified in dogs and cats,
but many are not directly related to diet. Moreover,
while mutations of several monogenic diseases have been
identified, the majority of diseases noted in pets are complex
in nature. Diseases such as obesity or hip dysplasia, for
example, are impacted by hundreds of genes and numerous
environmental factors, including diet. While this field
has enormous potential, we are many years away from devising a
personalized food for any given dog or cat based solely on a
blood (DNA) sample.
The field of nutrigenomics continues to enhance our
understanding of canine and feline metabolism and has broad
application to pet nutrition and health. Recently,
researchers have applied canine- and feline-specific functional
genomic assays to study adipose and skeletal muscle tissue
biology, various disease states, the normal effects of aging,
and diet-induced changes in gene expression. To lay the
foundation for future studies in diseased or aged dogs, our lab
initially focused on identifying gene expression differences in
cerebral cortex (Swanson
et al
., 2009b), skeletal muscle (Middelbos
et al
., 2009), adipose (Swanson
et al
., 2009a), colon (Kil
et al
., 2010), and liver (Kil, unpublished data) tissues of healthy
aged vs. young adult dogs. Biological systems highlighted
in these datasets (e.g., immune function, stress response, etc)
have provided targets of nutritional intervention in future
projects focused on improving tissue function and/or
longevity. Our lab and others have also used genomic
biology to identify molecular changes in adipose and skeletal
muscle tissues during weight gain/loss, after spay/neuter, or
in obese cats and dogs (Leray
et al
., 2008; Belsito
et al
. 2009; Vester
et al
., 2009a; Vester
et al
., 2009b). These studies have suggested the potential
role of specific nutrients or phytochemicals, such as
estrogenic-like compounds or green tea polyphenols, that may
aid in healthy weight maintenance and deserve more attention in
future research. Similarly, Brass
et al
. (2009) measured temporal gene expression patterns of skeletal
muscle in Alaskan sled dogs to identify novel regulatory
mechanisms and responses to exercise stimuli, which may lead to
dietary strategies with the ability to prolong bouts of
exercise or improve muscle recovery. Finally, other
researchers have identified key genes or pathways
differentially regulated in diseases such as atopic dermatitis
(Merryman-Simpson
et al
., 2008) and gastrointestinal diseases (Greger
et al
., 2006).
In addition to highlighting genes or pathways associated
with disease that may aid in developing preventative or
treatment strategies, such studies have suggested that genomic
tests may also be an effective diagnostic tool to distinguish
closely-related diseases from one another (Greger
et al
., 2006).
In summary, genomic biology is rapidly changing the research
environment, providing for new and exciting avenues of research
geared toward improving the health or longevity of pets.
Even though this field is in its infancy, initial publications
have shown great promise, highlighting dietary strategies for
further testing or inclusion in pet
foods.
- Belsito, K. R., B. M. Vester, T. Keel, T. K. Graves,
and K. S. Swanson. 2009. Impact of
ovariohysterectomy and food intake on body composition,
physical activity, and adipose gene expression in
cats.
J. Anim. Sci.
87:594-602.
- Brass, E. P., M. A. Peters, K. W. Hinchcliff, Y. D.
He, and R. G. Ulrich. 2009. Temporal pattern
of skeletal muscle gene expression following endurance
exercise in Alaskan sled dogs.
J. Appl. Physiol
. 107:605-612.
- Greger, D. L., F. Gropp, C. Morel, S. Sauter, and J.
W. Blum. 2006. Nuclear receptor and target
gene mRNA abundance in duodenum and colon of dogs with
chronic enteropathies.
Domest. Anim. Endocrinol.
31:327-339.
- Kil, D. Y., B. M. Vester, C. J. Apanavicius, L. B.
Schook, and K. S. Swanson. 2010. Age and diet
influence gene expression profiles of canine colonic
tissue.
Arch. Anim. Nutr.
(submitted).
- Klomp, A. E., B. van de Sluis, L. W. Klomp, and C.
Wijmenga. 2003. The ubiquitously expressed MURR1 protein
is absent in canine copper toxicosis.
J. Hepatol.
39:703-709.
- Leray, V., S. Serisier, S. Khosniat, L. Martin, H.
Dumon, and P. Nguyen. 2008. Adipose tissue gene
expression in obese dogs after weight loss.
J. Anim. Physiol. Anim. Nutr.
92:390-398.
- Merryman-Simpson, A. E., S. H. Wood, N. Fretwell, P.
G. Jones, W. M. McLaren, N. A. McEwan, D. N. Clements, S.
D. Carter, W. E. Ollier, and T. Nuttall.
2008. Gene (mRNA) expression in canine atopic
dermatitis: microarray analysis.
Vet. Dermatol.
19:59-66.
- Middelbos, I. S., B. M. Vester, L. K.
Karr-Lilienthal, L. B. Schook, and K. S. Swanson.
2009. Age and diet affect gene expression profile
in canine skeletal muscle.
PLoS ONE 4
:e4481. doi:10.1371/journal.pone.0004481.
- Middelbos, I. S., B. M. Vester Boler, A. Qu, B. A.
White, K. S. Swanson, and G. C. Fahey, Jr.
2010. Phylogenetic characterization of fecal
microbial communities of dogs fed diets with or without
supplemental dietary fiber using 454
pyrosequencing.
PLoS ONE 5
:e9768. Doi:10.1371/journal.pone.0009768.
- Suchodolski, J. S., J. Camacho, and J. M. Steiner.
2008. Analysis of bacterial diversity in the canine
duodenum, jejunum, ileum, and colon by comparative 16S
rRNA gene analysis.
FEMS Microbiol. Ecol.
66:567-578.
- Swanson, K. S., K. R. Belsito, B. M. Vester, and L.
B. Schook. 2009a. Adipose tissue gene
expression profiles of healthy young adult and geriatric
dogs.
Arch. Anim. Nutr.
63:160-171.
- Swanson, K. S., B. M. Vester, C. J. Apanavicius, N.
A. Kirby, and L. B. Schook. 2009b. Implications of
age and diet on canine cerebral cortex gene
transcription.
Neurobiol. Aging
30:1314-1326.
- Swanson, K. S., S. E. Dowd, J. S. Suchodolski, I. S.
Middelbos, B. M. Vester, K. A. Barry, K. E. Nelson, M.
Torralba, B. Henrissat, P. M. Coutinho, I. K. O. Cann, B.
A. White, and G. C. Fahey, Jr. 2010.
Phylogenetic and gene-centric metagenomics of the canine
gastrointestinal microbiome reveals similarities with
human and mouse gut metagenomes.
ISME J.
(submitted).
- Vester, B. M., S. M. Sutter, T. L. Keel, T. K.
Graves, and K. S. Swanson. 2009a.
Ovariohysterectomy alters body composition and adipose
and skeletal muscle gene expression in cats fed a
high-protein or moderate-protein diet.
Animal 3
:1287-1298.
- Vester, B. M., K. J. Liu, T. L. Keel, T. K. Graves,
and K. S. Swanson. 2009b. In utero and
postnatal exposure to a high-protein or high-carbohydrate
diet leads to differences in adipose tissue mRNA
expression and blood metabolites in kittens.
Brit. J. Nutr.
102:1136-1144.