U.S. patent number RE39,436 [Application Number 10/807,554] was granted by the patent office on 2006-12-19 for interventions to mimic the effects of calorie restriction.
This patent grant is currently assigned to The Regents of the University of California. Invention is credited to Joseph M. Dhahbi, Stephen R. Spindler.
United States Patent |
RE39,436 |
Spindler , et al. |
December 19, 2006 |
Interventions to mimic the effects of calorie restriction
Abstract
Long term calorie restriction has the benefit of increasing life
span. Methods to screen interventions that mimic the effects of
calorie restriction are disclosed. Extensive analysis of genes for
which expression is statistically different between control and
calorie restricted animals has demonstrated that specific genes are
preferentially expressed during calorie restriction. Screening for
interventions which produce the same expression profile will
provide interventions that increase life span. In a further aspect,
it has been discovered that test animals on a calorie restricted
diet for a relatively short time have a similar gene expression
profile to test animals which have been on a long term calorie
restricted diet.
Inventors: |
Spindler; Stephen R.
(Riverside, CA), Dhahbi; Joseph M. (Alameda, CA) |
Assignee: |
The Regents of the University of
California (Oakland, CA)
|
Family
ID: |
27043357 |
Appl.
No.: |
10/807,554 |
Filed: |
March 22, 2004 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
Issue Date |
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09471224 |
Dec 23, 1999 |
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Reissue of: |
09648642 |
Aug 25, 2000 |
06406853 |
Jun 18, 2002 |
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Current U.S.
Class: |
435/6.11; 435/5;
435/91.2; 514/724; 514/693; 435/91.1; 424/9.2; 800/18 |
Current CPC
Class: |
A61P
3/10 (20180101); C12Q 1/6883 (20130101); A61P
35/00 (20180101); C12Q 2600/158 (20130101) |
Current International
Class: |
C12Q
1/68 (20060101) |
Field of
Search: |
;435/5,6,91.1,91.2
;514/693,724 ;119/15,18,54 |
References Cited
[Referenced By]
U.S. Patent Documents
Foreign Patent Documents
Other References
Walford et al., "Dietary restriction and aging: historical phases,
mechanisms and current directions," Journal of Nutrition vol. 117,
No. 10, pp. 1650-1654 (1987). cited by examiner .
Goyns et al., "Differential display analysis of gene expression
indicates that age-related changes are restricted to a small cohort
of genes," Mechanisms of Ageing and Development vol. 101, No. 1, 2,
pp. 73-90 (1998). cited by examiner .
Lane et al., "2-Deoxy-D-glucose feeding in rats mimics physiologic
effects of calorie restriction," Journal of Anti-Aging Medicine
vol. 1, No. 4, pp. 327-337 (1998). cited by examiner .
Weindruch et al., "Caloric Restriction Mimetics: Metabolic
Interventions," J. Gerontology: Series A, vol. 56A (Special Issue
1, pp. 20-33 (2001). cited by examiner .
Lee et al. Science, vol. 285, Aug. 1999, pp. 1390-1393. cited by
examiner .
Lee et al., Gene Expression Profile of Aging and Its Retardation by
Caloric .quadrature..quadrature.Restriction, (1999) Science
285:1390. cited by examiner .
Weindruch et al., Dietary Restriction in Mice Beginning at 1 Year
of Age: .quadrature..quadrature.Effect on Life-Span and Spontaneous
Cancer Incidence, (1982) Science 215-1415. cited by examiner .
Chu, K., et al., "Short-term caloric restriction augments
age-related decreases in gastrin content and release," Mechanisms
of Ageing and Development, 1996, vol. 87, pp. 25-33. cited by other
.
Mote, P., et al., "Influence of age and caloric restriction on
expression of hepatic genes for xenobiotic and oxygen metabolizing
enzymes in the mouse," Journal of Geronology: Biological Sciences,
1991, vol. 46, No. 3, pp. B95-B100. cited by other .
Tillman, J., et al., "Dietary calorie restriction in mice induces
carbamyl phosphate synthetase I gene transcription tissue
specifically," The Journal of Biological Chemistry, 1996, vol. 271,
No. 7, pp. 3500-3506. cited by other.
|
Primary Examiner: Wax; Robert A.
Attorney, Agent or Firm: Townsend and Townsend and Crew
LLP
Parent Case Text
This application is a continuation in part of U.S. application Ser.
No. 09/471,224, filed Dec. 23, 1999.
Claims
What is claimed is:
.[.1. A method of identifiing an intervention that mimics the
effects of caloric restriction in cells, comprising: obtaining a
biological sample; exposing said biological sample to an
intervention; waiting a specified period of time; assessing changes
in gene expression levels, levels of RNA, protein, or protein
activity levels related to one or more biomarkers of aging; and
identifying said intervention as one that mimics the effects of
caloric restriction if one or more changes in said levels also
occurs in caloric restriction..].
.[.2. The method of claim 1 , wherein said biological sample
comprises cells..].
.[.3. The method of claim 2, wherein said cells are obtained from a
mammal..].
.[.4. The method of claim 3, wherein said mammal is a mouse..].
.[.5. The method of claim 1, wherein said change in gene expression
levels, levels of RNA, protein, or protein activity levels
corresponds to a change in gene expression for a gene encoding a
chaperone protein..].
.[.6. The method of claim 5, wherein said gene encoding a chaperone
protein is GRP78..].
.[.7. The method of claim 1, wherein said biomarker is
apoptosis..].
.[.8. The method of claim 1, wherein said biomarker is
aging..].
.[.9. The method of claim 8, wherein said biomarker of aging is a
production of cancer cells..].
.[.10. The method of claim 1, wherein said changes in said gene
expression level, levels of RNA, protein, or protein activity
levels related to one or more biomarkers of aging occur in 6 weeks
or less..].
.[.11. The method of claim 10, wherein said changes in said gene
expression levels, levels of RNA, protein, or protein activity
levels related to one or more biomarkers of aging occur is four
weeks or less..].
.[.12. The method of claim 11, wherein said changes in said gene
expression levels, levels of RNA, protein, or protein activity
levels related to one or more biomarkers of aging occur in two
weeks or less..].
.[.13. The method of claim 12, wherein said changes in said gene
expression levels, levels of RNA, protein, or protein activity
levels related to one or more biomarkers of aging occur in about
two days or less..].
.[.14. A method according to claim 1 wherein changes in gene
expression are evaluated using a gene chip..].
.[.15. The method of claim 14, wherein the gene chip contains genes
for immune system activation..].
.[.16. The method of claim 14, wherein the gene chip contains genes
for DNA repair..].
.[.17. The method of claim 14, wherein the gene chip contains genes
associated with apoptosis..].
.[.18. The method of claim 14, wherein the gene chip contains genes
for the enteric nervous system..].
.[.19. The method of claim 1, wherein said biological sample is a
test animal..].
.[.20. The method of claim 19 additionally comprising determining
changes in said levels in a reference animal having identifying
characteristics of a long-term calorie-restricted animal wherein
the reference animal has been on a calorie restricted diet for less
than about 6 weeks and wherein said changes are used in said
identifying said intervention as one that mimics the effects of
calorie restriction..].
.[.21. The method of claim 20, wherein the reference animal has
been on a calorie restricted diet for less than about 4
weeks..].
.[.22. The method of claim 20, wherein the reference animal has
been on a calorie restricted diet for less than about 2
weeks..].
.[.23. The method of claim 19, wherein said test animal is a
mouse..].
.[.24. The method of claim 19, wherein changes in gene expression
are assessed in said test animal..].
.[.25. The method of claim 19 which further comprises: obtaining a
gene expression profile from a calorie-restricted reference animal;
comparing changes in gene expression for the test animal to the
gene expression profile of the calorie-restricted reference animal;
and identifying said intervention as one that mimics the effects of
calorie restriction if the gene expression profile of the test
animal is statistically similar to the gene expression profile of
the calorie restricted animal..].
.[.26. The method of claim 25, wherein the gene expression profile
of the test animal is determined to be statistically similar to the
gene expression of the calorie restricted animal by one-way ANOVA
followed by Fisher's test (P<0.05)..].
.Iadd.27. A method of identifying an intervention that mimics the
effects of caloric restriction in cells, comprising: obtaining a
biological sample; exposing the biological sample to an
intervention; waiting a specified period of time; assessing changes
in gene expression levels, levels of RNA, protein, or protein
activity levels related to one or more biomarkers of aging; and
identifying the intervention as one that mimics the effects of
caloric restriction if one or more changes in the levels also
occurs in a reference animal subjected to short term caloric
restriction..Iaddend.
.Iadd.28. The method of claim 27, wherein the short term caloric
restriction is about two to about six weeks..Iaddend.
.Iadd.29. The method of claim 27, wherein the short term caloric
restriction is about four weeks..Iaddend.
.Iadd.30. The method of claim 27, wherein the changes are
determined in a test animal..Iaddend.
.Iadd.31. The method of claim 30, wherein the test animal is a
mouse..Iaddend.
.Iadd.32. The method of claim 27, wherein the specified period of
time is six weeks or less..Iaddend.
.Iadd.33. The method of claim 27, wherein the specified period of
time is four weeks or less..Iaddend.
.Iadd.34. The method of claim 27, wherein the specified period of
time is two weeks or less..Iaddend.
.Iadd.35. The method of claim 27, wherein the specified period of
time is two days or less..Iaddend.
.Iadd.36. The method of claim 27, wherein the biomarker of aging is
a gene encoding a chaperone protein..Iaddend.
.Iadd.37. The method of claim 36, wherein the chaperone protein is
GRP78..Iaddend.
.Iadd.38. The method of claim 27, wherein the changes in gene
expression are evaluated using an oligonucleotide-based high
density array..Iaddend.
.Iadd.39. The method of claim 38, wherein the biomarker of aging is
a gene encoding a protein involved in immune system
activation..Iaddend.
.Iadd.40. The method of claim 38, wherein the biomarker of aging is
a gene encoding a protein involved in DNA repair..Iaddend.
.Iadd.41. The method of claim 38, wherein the biomarker of aging is
a gene encoding a protein involved in apoptosis..Iaddend.
.Iadd.42. The method of claim 38, wherein the biomarker of aging is
a gene encoding a protein involved in the enteric nervous
system..Iaddend.
Description
BACKGROUND OF THE INVENTION
1. Field of the Invention
For years, researchers have attempted to identify biomarkers of
aging to facilitate the identification of interventions that might
slow or reverse the aging process. Dietary calorie restriction (CR)
is the only well-documented method for extending life span in
homeothermic vertebrates, and is the most effective means known for
reducing cancer incidence. Although many of the physiological
consequences of CR were described 65 years ago, there is no
consensus regarding its mode of action. Consequently, there has
been no practical method of identifying interventions that might
mimic such calorie-restriction effects. Rather, a researcher would
have to wait the test animal's lifetime to determine whether a
particular intervention impacted life-span and/or cancer
incidence.
2. Description of the Related Art
Mammals seem to share a common set of genes, and yet they have
widely differing life spans. It is impossible to know at present
whether the differences in life spans are due to differences in the
sequence of specific genes, or to differences in their expression.
However, it is clear from many years of study in dozens of
laboratories that long term reduction in dietary calorie
consumption (CR) delays most age-related physiological changes, and
extends life span in all species tested, provided malnutrition is
avoided (Weindruch, et al. The Retardation of Aging and Disease by
Dietary Restriction (Charles C. Thomas, Springfield, Ill., 1988)).
These studies also have shown that CR is the most effective means
now known for reducing cancer incidence and increasing the mean age
of onset of age-related diseases and tumors in homeothermic
vertebrates (Weindruch et al. (1982) Science 215: 1415). Thus, it
seems clear that life spans can be extended through a relatively
simple dietary regimen. However, there are no studies on the
effects of short term calorie restriction on metabolism and gene
expression.
One report has been published of gene expression profiling in
muscle (Lee et al. (1999) Science 285: 1390) In these studies, many
age related changes in muscle gene expression appeared to be
prevented or reversed by CR. The expression profiles of 6500 genes
were compared among old, long-term CR and control mice, and young
control mice. Some age-related changes in muscle gene expression
appeared to be wholly or partially prevented by CR.
SUMMARY OF THE INVENTION
The present invention contemplates a method of identifying
interventions within a short time frame that mimic the effects of
calorie restriction. Such interventions will lead to increased life
span, reduce cancer incidence, and/or increase the ago of onset of
age-related diseases and tumors.
In a preferred embodiment a method of identifying an intervention
that mimics the effects of caloric restriction in cells is
disclosed, comprising the steps of: obtaining a biological sample;
exposing said biological sample to an intervention; waiting a
specified period of time; assessing changes in gene expression
levels, levels of RNA, protein, or protein activity levels related
to one or more biomarkers of aging; and identifying said
intervention as one that mimics the effects of caloric restriction
if one or more changes in said levels also occurs in caloric
restriction.
The biological sample may be either in vitro or in vivo. In a
preferred embodiment, the biological sample comprises cells. In a
more preferred embodiment, the cells are obtained from a mammal. In
an even more preferred embodiment, the mammal is a mouse.
In one embodiment, the change in gene expression levels, levels of
RNA, protein, or protein activity levels corresponds to a change in
gene expression for a gene encoding a chaperone protein. In a
preferred embodiment, the chaperone protein is GRP78.
In one embodiment, said biomarker is apoptosis. In another
preferred embodiment, said biomarker is aging. In another preferred
embodiment, said biomarker of aging is a production of cancer
cells.
In a preferred embodiment, the changes in said gene expression
level, levels of RNA, protein, or protein activity levels related
to one or more biomarkers of aging occur in 6 weeks or less. In a
more preferred embodiment, the changes in said gene expression
levels, levels of RNA, protein, or protein activity levels related
to one or more biomarkers of aging occur in four weeks or less. In
an even more preferred embodiment, the changes in said gene
expression levels, levels of RNA, protein, or protein activity
levels related to one or more biomarkers of aging occur in two
weeks or less. In a most preferred embodiment, the changes in said
gene expression levels, levels of RNA, protein, or protein activity
levels related to one or more biomarkers of aging occur in about
two days or less.
In a one embodiment, changes in gene expression are evaluated using
a gene chip. In a preferred embodiment, the gene chip contains
genes for immune system activation. In another preferred
embodiment, the gene chip contains genes for DNA repair. In another
preferred embodiment, the gene chip contains genes associated with
apoptosis. In another preferred embodiment, the gene chip contains
genes for the enteric nervous system.
In an alternate embodiment, the biological sample is a test animal.
In a preferred embodiment the disclosed method additionally
comprises determining changes in said levels in a reference animal
having identifying characteristics of a long-term
calorie-restricted animal wherein the reference animal has been on
a calorie restricted diet for less than about 6 weeks and wherein
said changes are used in said identifying said intervention as one
that mimics the effects of calorie restriction. In a more preferred
embodiment, the reference animal has been on a calorie restricted
diet for less than about 4 weeks. In an even more preferred
embodiment, the reference animal has been on a calorie restricted
diet for less than about 2 weeks.
In a preferred embodiment, the test animal is a mouse. In a
preferred embodiment, changes in gene expression are assessed in
the test animal.
In a more preferred embodiment, the disclosed method further
comprises: obtaining a gene expression profile from a
calorie-restricted reference animal; comparing changes in gene
expression for the test animal to the gene expression profile of
the calorie-restricted reference animal; and identifyng said
intervention as one that mimics the effects of calorie restriction
if the gene expression profile of the test animal is statistically
similar to the gene expression profile of the calorie restricted
animal.
In a more preferred embodiment, the gene expression profile of the
test animal is determined to be statistically similar to the gene
expression of the calorie restricted animal by one-way ANOVA
followed by Fisher's test (P<0.05).
In another aspect of the invention, a system is disclosed for
identifying an intervention that mimics the effects of calorie
restriction in a test animal comprising a test animal and a gene
chip comprising genes known to have altered expression during
calorie restriction. In a preferred embodiment, the gene chip
comprises genes selected from the group consisting of genes for
immune system activation, genes for DNA repair, genes associated
with apoptosis and genes for the enteric nervous system.
For purposes of summarizing the invention and the advantages
achieved over the prior art, certain objects and advantages of the
invention have been described above. Of course, it is to be
understood that not necessarily all such objects or advantages may
be achieved in accordance with any particular embodiment of the
invention. Thus, for example, those skilled in the art will
recognize that the invention may be embodied a carried out in a
manner that achieves or optimizes one advantage or group of
advantages as taught herein without necessarily achieving other
objects or advantages as may be taught or suggested herein.
Further aspects, features and advantages of this invention will
become apparent from the detailed description of the preferred
embodiments which follow.
BRIEF DESCRIPTION OF THE DRAWINGS
The file of this patent contains at least one drawing executed in
color. Copies of this patent with color drawing(s) will be provided
by the Patent and Trademark Office upon request and payment of the
necessary fee.
These and other feature of this invention will now be described
with reference to the drawings of preferred embodiments which are
intended to illustrate and not to limit the invention.
FIG. 1. Effects of feeding on hepatic GRP78 and ERp72 mRNA. At 0,
1.5, 5 and 12 h following feeding, 5 mice from each dietary group
were killed. Their weights after 24 h of fasting were 22.96.+-.1.49
for CR and 37.12.+-.1.19 g for control mice. GRP78 mRNA (A) and
ERp72 mRNA (B) from control (closed circle) and CR (open circle)
mice were quantified using dot-blots. RNA loading and transfer were
normalized using data obtained from serial probings for 18S
ribosomal RNA and S-II mRNA. Similar results were obtained with
both control probes. CR and control mice, fed once daily for 30
days, were fasted for 24 hours and killed (n=5, 0 time point) or
refed and killed at the times specified (n=5 for each time point).
+ represents P<0.01 significance of difference between CR and
control at each time point. * represents P<0.01 significance of
difference from the 0 time point within each dietary group. The 0
and 24 hour times points are the same data set.
FIG. 2. The gene and tissue specificity of the chaperone feeding
response. A, The domain of chaperone genes responsive to feeding
was determined by quantifying hepatic chaperone mRNA abundance
using RNA from mice fasted for 48 hours (n=6; open bars) or from
mice fasted 48 hours, refed and killed) 1.5 h later (n=6; filled
bars). The mRNAs were quantified by dot-blotting and Northern
blotting. There was no significant difference in the results
obtained with either technique. The dot-blotting results are shown.
B, Liver, kidney, and muscle GRP78 mRNA from 24-hour fasted mice
(n=4), and from 24-hour fasted mice 1.5 hours after feeding (n=5).
These data were from different mice than used in panel A. The
statistical significance of the results are indicated (*,
P<0.05; **, P<0.01; ***, P<0.001).
FIG. 3. Effects of CR on hepatic pre-mRNA and GRP78 mRNA abundance.
A, RNase protection of pre-mRNA and mRNA in CR and control mice.
Hepatic RNA was purified from control and CR mice and hybridized
with an RNA probe for transcripts spanning the third intron and
fourth exon boundary of the GRP78 gene. The precursor mRNA
protected a 223 base region of the probe, labeled GRP78 pre-mRNA,
while the GRP78 mRNA protected a 113 base fragment, so labeled in
the figure. A probe for S-II mRNA coding sequences was included in
each reaction as an internal control. It protected a 185 base
fragment labeled S-II mRNA in the figure. Lane 1 shows the
protected fragments produced by the GRP78 probe and mouse liver
RNA. Lane 2 shows the fragments produced by the S-II probe
hybridized to yeast total RNA. Lane 3 shows the results produced by
the S-II probe hybridized to mouse liver RNA. Lanes 4, 6, and 8
show the results produced by hepatic RNA from control mice. Lanes
5, 7, and 9 show the results with RNA from CR mice. Quantification
of the abundance of the protected fragments representing the GRP78
mRNA (B) and pre-mRNA (C). Studies such as than shown above were
conducted using hepatic RNA from 6 CR and 6 control mice. The
intensity of the protected fragments was quantified with a
phosphorimager. The intensities of the pre-mRNA and mRNA fragments
were normalized to the intensity of the protected fragment
representing S-II mRNA. Statistical significance is indicated as in
the legend to FIG. 2.
FIG. 4. Effects of feeding on hepatic GRP78 mRNA and pre-mRNA
abundance. A, RNase protection of probes for hepatic GRP78 pre-mRNA
and mRNA in mice after 48 hours of fasting (n=5), or 1.5 h after
feeding of 48-hour fasted mice (n=5). RNA purified from liver was
hybridized either to a probe for primary transcripts containing the
exon 7 and intron 7 boundary of the GRP78 gene which produced a 257
base protected fragment (labeled S-II+GRP78; lanes 7-12), or to a
probe for primary transcripts spanning the exon 7 and intron 7
boundary, which protected a 200 nucleotide fragment (labeled
S-II+tGRP78, lanes 13-18), as indicated in the figure. GRP78 mRNA
produced a 143 nucleotide fragment representing GRP78 mRNA, as
indicated in the figure. A probe for S-II mRNA coding sequences was
included in each reaction as an internal control. With this probe,
S-II mRNA protected a 277 nucleotide fragment, labeled S-II mRNA in
the figure. Lane 1, RNA markers. Lanes 2-6, hybridization of the
indicated probes with yeast tRNA. Lanes 7-12, hybridization of the
GRP78 and S-II probes with RNA from fasted (lanes 7-9) and refed
(lanes 10-12) mice. Lanes 13-18, hybridization of tGRP78 and S-II
probes with RNA from fasted (lanes 13-15) and refed (lanes 16-18)
mice. Quantification of the abundance of the protected fragments
representing the GRP78 mRNA(B) and pre-mRNA (C). Studies such as
those shown above were conducted using hepatic RNA from 6 CR and 6
control mice. The intensity of the protected fragments was
quantified and normalized as described in FIG. 3 above. Statistical
significance is indicated as in the legend to FIG. 2.
FIG. 5. Effects of protein synthesis inhibitors on the feeding
response of GRP78 (A) and PEPCK (B) mRNA. Mice fasted for 48 h were
injected i.p. with vehicle and after 1 hour injected a second time
i.p with vehicle (Refed+Sham; n=6). Mice fasted for 48 hours were
injected i.p. with vehicle 30 min before and 30 min after feeding
(Refed+Sham, n=6). Mice fasted for 48 h were injected i.p. with
cycloheximide and after 1 hour injected a second time i.p with
cycloheximide (Fastest+Cycloheximide; n=6). Mice fasted for 48 h
were injected i.p. with cycloheximide 30 min before and 30 min
after feeding (Refed+Cycloheximide; n=6). Mice fasted for 48 h were
injected i.p. with puromycin and after 1 hour injected a second
time i.p with puromycin (Fasted+Puromycin; n=6). Mice fasted for 48
h were injected i.p. with puromycin 30 min before and 30 min after
feeding (Refed+Puromycin; n=6). GRP78 and PEPCK mRNA abundance were
determined using purified hepatic RNA. Bars without common
superscripts are significantly different (P<0.005).
FIG. 6. Regulation of the fasting-feeding response by insulin,
dibutyryl-cAMP, glucagon, and ingestion of mineral oil and
cellulose. A, Groups of six mice were fasted for 48 h and treated
as follows: Fasted+Sham mice were injected with vehicle and 1 h
later vehicle injected a second time; Fed+Sham mice were sham
injected with vehicle 30 min before and 30 min after feeding;
Fed+cAMP mine were injected with dibutyryl-cAMP and theophylline 30
min before and 30 min after feeding; Fed+glucagon mice were
injected with glucagon 30 min before and 30 min after feeding;
Fasted Diabetic+Sham mice, previously rendered diabetic with STZ,
were vehicle injected and 1 h later vehicle injected a second time;
Fed Diabetic+Sham, STZ-diabetic mice were sham injected with
vehicle 30 min before and 30 min after feeding; Fed Diabetic+cAMP,
diabetic mice were injected with dibutyryl-cAMP and theophylline 30
min before and 30 min after feeding. All mice were killed 1 h after
their last injection. Total RNA was isolated from the liver and
subjected to dot-blot analysis. Bars with no common superscripts
are significantly different (P<0.005). B, Effects of mineral oil
and cellulose ingestion on liver GRP78 mRNA abundance. Groups of
six mice were fasted for 48 h and treated as follows: Fasted, mice
were fasted for 48 h and killed; Fed, mice were fasted for 48 h,
fed, and killed 1.5 h later; Fasted+cellulose, mice fasted for 48 h
were fed a mixture of cellulose and mineral oil, and killed 1.5 h
later. Significance is indicated as in the legend to FIG. 5.
FIG. 7. Effects of adrenalectomy and dexamethasone administration
on the expression and regulation of hepatic GRP78 mRNA. Groups of
six mice were fasted for 48 h and treated as follows: Fasted+Sham,
sham-operated mice were injected with vehicle IP 7.5 h and 1.5 h
before they were killed; Fed+Sham, sham-operated mice were injected
with vehicle IP 6 hours before and 30 min after feeding, and mice
were killed 1 h after the last injection; Adx Fasted+Sham,
adrenalectomized mice were injected with vehicle IP 7.5 h and 1.5 h
before they were killed; Adx Fed+Sham, adrenalectomized mice were
injected with vehicle IP 6 hours before and 30 min after feeding,
and the mice killed 1 h later; Adx Fasted+Dex, adrenalectomized
mice were injected IP with dexamethasone 7.5 h and 1.5 h before
they were killed; Adx Fed+Dex, adrenalectomized mice were injected
IP with dexamethasone 6 hours before and 30 min after feeding, and
killed 1 h later. Significance is indicated as in the legend to
FIG. 5.
FIG. 8. The hepatic gene expression profiles of old control, old
CR, young control, and young CR mice. The mice weighed 37.2+1.9 g,
22.8+1.2 g, 26.0+2.8 g, and 19.4+1.6 g, respectively. The CR groups
consumed approximately 50% fewer calories than their control
counterparts post-weaning, as described. Levels of specific mRNA
were determined using the Mu11KsubA and Mu11KsubB .[.GeneChip.].
.Iadd.GeneChip.RTM. .Iaddend.arrays (Affymetrix, Santa Clara,
Calif.) containing targets for approximately 12,000 known mouse
genes and ESTs. The experiment tree function of GeneSpring 3.0
(Silicon Genetic, San Carlos. Calif.) was utilized to display the
results. The horizontal axis represents the position of each gene
assigned by the "gene tree" average-linkage hierarchical clustering
algorithms of the program. Below the position assigned to each gene
is a color-coded indication of its relative expression level, based
on a continuous scale. Bright blue indicates no detectable
expression, purple average expression, and bright red high
expression. The average expression of each gene in each group is
shown. The GeneSpring "experiment tree" clustering algorithm
calculated an average-linkage hierarchical clustering dendrogram of
the data for each group of mice, which is shown to the left of the
expression profiles.
FIG. 9. Schematic representation of the hypothesis that CR acts by
preventing age-related changes in gene expression. During aging,
some genes become over expressed or under-expressed relative to
their levels in young aninals (lower and upper lines). Unchanged
expression with age is represented by the horizontal line. These
deviations are assumed to be deleterious. The important genes
effected by CR, in this hypothesis, are the over- or
under-expressed genes returned to youthful levels of expression
(arrows). The numbers of genes and ESTs in each category are shown
at the ends of the lower and upper lines. The number of known genes
in each category returned to baseline expression by LT. and ST-CR
are given after the colons. Long-term and short-term CR both acted
to reverse or prevent 23 of the increases and 41 of the decreases.
Thus, long-term LT-CR actually prevented the increased expression
of only 30 genes and ESTs and the decreased expression of only 24
genes and ESTs.
FIG. 10. Avenge of pairwise comparison of the global gene
expression correlation coefficient for each possible pair of
mice
FIG. 11. The hepatic gene expression profiles of young CR, young
control and streptozotocin (STZ)-heated mice. Levels of specific
mRNA were determined using the Mu11KsubA and
Mu11KsubB.[.GeneChip.]. .Iadd.GeneChip.RTM. .Iaddend.arrays
(Affymetrix, Santa Clara, Calif.) containing targets for
approximately 12,000 known mouse genes and ESTs. The experiment
tree function of GeneSpring 3.0 (Silicon Genetic, San Carlos,
Calif.) was utilized to display the results. The horizontal axis
represents the position of each gene assigned by the "gene tree"
average-linkage hierarchical clustering algorithm of the program.
Below the position assigned to each gene is a color-coded
indication of its relative expression level, based on a continuous
scale. Bright blue indicates no detectable expression, purple
average expression, and bright red high expression. The average
expression of each gene in each group is shown. The GeneSpring
"experiment tree" clustering algorithm calculated an
average-linkage hierarchical clustering dendrogram of the data for
each group of mice, which is shown to the left of the expression
profiles.
FIG. 12. Average of pairwise comparison of the global gene
expression correlation coefficient for each possible pair of
mice.
FIG. 13. The hepatic gene expression profiles of old CR, old
control and aminoguanidine (AG)-treated mice. Levels of specific
mRNA were determined using the Mu11KsubA and
Mu11KsubB.[.GeneChip.]. .Iadd.GeneChip.RTM. .Iaddend.arrays
(Affymetrix, Santa Clara, Calif.) containing targets for
approximately 12,000 known mouse genes and ESTs. The experiment
tree function of GeneSpring 3.0 (Silicon Genetics, San Carlos,
Calif.) was utilized to display the results. The horizontal axis
represents the position of each gene assigned by the "gene tree"
average-linkage hierarchical clustering algorithm of the program.
Below the position assigned to each gene is a color-coded
indication of its relative expression level, based on a continuous
scale. Bright blue indicates no detectable expression, purple
average expression, and bright red high expression. The average
expression of each gene in each group is shown. The GeneSpring
"experiment treet" clustering algorithm calculated an
average-linkage hierarchical clustering dendrogram of the data for
each group of mice, which is shown to the left of the expression
profiles.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT
While the described embodiment represents the preferred embodiment
of the present invention, it is to be understood that modifications
will occur to those skilled in the art without departing from the
spirit of the invention. The scope of the invention is therefore to
be determined solely by the appended claims.
The effects of long term calorie restriction include increases in
the rate of clearance of serum proteins, including glucose damaged
serum proteins, from the blood as well as changes in gene
expression. For example, long term calorie restriction down
regulates the expression of certain chaperone genes, up regulates
the expression of certain transcription factors and homeobox genes,
increases expression of immune system genes, and increases genes
enhancing genetic stability and apoptosis. These changes in gene
expression correlate with an increase in apoptosis, reduced cancer
incidence and increase the turnover of damaged and toxic serum
proteins, reducing kidney and vascular damage with age or
diabetes.
Molecular chaperones assist in the biosynthesis, folding,
processing, and degradation of proteins. Many of the chaperone
genes are stress inducible. Subsets of chaperones are induced by
different physiological stressors. For example, the majority of the
known endoplasmic chaperones are induced by stresses that produce
malfolded or improperly glycosylated proteins in the ER. This
unfolded protein response pathway also may adjust the level of
protein trafficking through the ER to the level of ER chaperones.
Other chaperones, such as the abundant cytoplasmic chaperone HSC70
are normally thought of as constitutively expressed. The present
invention is based in part on the finding that certain chaperone
genes are down regulated by calorie restriction (such regulation is
thought to be mediated through the insulin and glucagon pathways).
The expression of Erp72, Erp57, GRP 170, GRP78, GRP94, HSC70,
Calnexin, and Calreticulin are particularly affected by calorie
restriction.
The fasting mRNA and protein levels of nearly every ER chaperone
studied were found to be significantly and consistently reduced in
the livers of CR mice chronically fed a low caloric diet. In the
case of GRP78, levels decreased by approximately 66%. Further, the
reduction in chaperone mRNA levels was proportional to the
reduction in calorie consumption. The fewer calories consumed, the
lower the level of chaperone mRNA. We subsequently found that
fasting chaperone mRNA levels changed over the course of 2 weeks in
response to different levels of chronic calorie consumption. The
more calories consumed per week, the higher the chaperone levels.
Chaperone mRNA levels respond more rapidly to calorie
consumption.
mRNA for most ER chaperones, and for the major cytoplasmic
chaperone, HSC70, are dynamically responsive (within 1.5 h) to each
meal, and to the number of calories consumed. Features of this
induction distinguish it from the unfolded protein response. The
feeding induction was observed in kidney and muscle tissue, as well
as in the liver. Postprandial changes in glucagon, in conjunction
with insulin, were found to be the key mediators of this
induction.
Chaperone mRNA abundance responds within 1.5 h to caloric intake.
Insulin and glucagon may be important for the response. This
feeding response is rapid. By 1.5 hours after feeding, ER chaperone
mRNAs were at or near their maximum level of induction. This
feeding-related induction is not limited to one strain of mouse or
to one species. Further, the response is found in tissues other
than liver. Thus, it is a response which is generally important to
the physiology of a variety of cell types in vivo.
Because many chaperones are relatively stable proteins, their
protein levels change more slowly in response to caloric intake
than their mnRNAs. For example, GRP78 protein has a half-life of
over 24 hours in cultured cells. We found that GRP78 protein levels
change only over a span of several days in response to changes in
average daily calorie consumption. In this way, many chaperones may
effectively integrate the rapid mRNA responses to feeding into
longer term changes in chaperone protein levels. Long term
differences in average calorie consumption do lead to differences
in the hepatic levels of both ER and some cytoplasmic
chaperones.
RNase protection assays indicate that GRP78 mRNA is
transcriptionally regulated in response to feeding. Similar RNase
protection results were obtained with hepatic RNA from chronically
CR mice. Thus, both feeding and CR transcriptionally alter the
expression of the chaperone genes.
Puromycin led to partial induction of GRP78 mRNA. It is unlikely
that induction of the mRNA by cycloheximide is due to stabilization
of the transcript by polysome aggregation. While cycloheximide
protects some mRNAs from inactivation and degradation in this way,
puromycin does not. Rather, it inhibits translation by polysome
dissociation. Thus, maintenance of low hepatic GRP78 mRNA levels
most likely requires the action of an unstable repressor of GRP78
gene expression in fasted mice. In the presence of inhibitors of
translation, this repressor may decay, releasing the gene from
repression.
Second, there was no augmentation of GRP78 mRNA induction when
feeding and inhibition of translation were combined. While partial
induction of the mRNA was found in puromycin treated mice, feeding
induced the mRNA to the same level found in the absence of the
inhibitor. Further, cycloheximide induced the mRNA to the same
extent. Without being bound to any particular mechanism, it is
suggested that the inhibitors and feeding may induce the gene
through a common pathway.
Third, since feeding fully induced GRP78 mRNA in puromycin treated
mice, de nova protein synthesis is not required for the feeding
response. Preexisting signaling and regulatory factors mediate the
response. Fourth, the feeding response cannot result from a
postprandial increase in protein trafficking through the ER.
Enhanced ER de novo protein trafficking an induce chaperone mRNA.
However, no such increase could have occurred in the presence of
puromycin.
Fifth, the unfolded protein and growth factor responses are not
involved in the induction of chaperones by feeding. Cycloheximide
blocks the unfolded protein and growth factor responses. We are
aware of only one manipulation besides feeding capable of inducing
ER chaperone mRNA in the presence of cycloheximide. GRP mRNAs are
induced by cellular hypoxia in culture, and this induction is
independent of cycloheximide treatment. Whether the feeding and
hypoxia response share common molecular pathways is unknown at
present.
Feeding is well-known to decrease glucagon and increase insulin
levels. Both glucagon and dibutyryl-cAMP blunted the feeding
induction of GRP78 mRNA. Thus, glucagon is a negative regulator of
GRP78 expression in vivo. The feeding induction of GRP78 mRNA was
significantly reduced in STZ-diabetic mice. Without being bound to
any particular mechanism, this result and the absence of a feeding
response in STZ-diabetic, dibutyryl-cAMP-treated mice indicate that
the action of both hormones is required for the response.
Other effectors which are known to respond to feeding were also
examined. Luminal stimuli can promote the release of
gastrointestinal hormones. For this reason, we determined whether
luminal filling with a non-digestible mixture of mineral oil and
cellulose could stimulate chaperone expression. A small but
significant response was found. However, insulin and glucagon have
a much stronger effect on chaperone mRNAs, indicating they are the
signals primarily responsible for the feeding response.
The feeding response was enhanced in adrenalectomized mice. These
results suggest that other adrenal hormones, perhaps
catecholamines, may partially blunt the chaperone mRNA response to
feeding. However, the mechanism by which these hormones stimulate
the feeding response is unknown at present.
Overall, feeling rapidly and strongly induced the mRNA for the
major cytoplasmic chaperone, HSC70, and most ER chaperones
examined. Feeding also induced BR chaperone mRNAs in at least three
different tissues. Feeding and CR regulated chaperone mRNA
abundance at the transcriptional level. Without being bound to any
particular mechanism, feeding appeared to release chaperone gene
expression from the effects of an unstable inhibitor. Insulin was
required, and glucagon and cAMP mediated the feeding response.
Post-prandial changes in glucagon levels may be the primary
mediator of the response. Gastrointestinal and adrenal hormones,
but not glucocorticoids also have a role in the feeding
response.
Surprisingly, changes in gene expression are also observed with
short-term calorie restriction. These changes is gene expression
are virtually identical to the changes observed in long-term CR.
Short-term calorie restriction occurs when switching a mature test
animal to a diet which is about 50% less than a control diet for
about 2-6 weeks. In a preferred embodiment, the test animal is a
mature mouse and the mature mouse is switched to a
calorie-restricted diet at about 31 months. Preferably, as
intermediate diet which is about 20-40% less than a control diet is
employed for about two weeks before switching to a CR diet for an
additional two weeks.
Both long term and short-term CR produces its profound effects on
mammalian physiology by affecting the expression of genes. To
identify as broadly as possible the effects of caloric restriction
on global patterns of gene expression, gene chip technology was
utilized to characterize the effects of long and short term CR on
the expression of approximately 11,000 mouse genes in the
liver.
Liver is an attractive organ for study, since it contains a number
of cell types, allowing assessment of the effects of CR on
hepatocytes, which are primarily responsible for the regulation of
metabolism and blood sugar, neurons of the enteric nervous system,
immune system cells in the blood, and vascular smooth muscle cells,
among others. In liver, by far the predominant effect of caloric
restriction is the activation of gene expression. In addition,
after only four weeks of caloric restriction, the gene expression
profile of old mature mice had been shifted from the profile
characteristic of fully fed "normo-aging" mice to the gene
expression profile of slow aging, long term CR mice. In both long
and short-term CR mice, changes were observed in gene expression of
immune system genes, genes enhancing genetic stability and
apoptosis, genes of the enteric nervous system and liver specific
genes.
The methods of the present invention include the identification of
interventions that mimic the effects of calorie restriction.
Particularly contemplated by the invention are methods of
identifying interventions that have as effect on life span, aging,
and/or the development of age-related diseases and cancer.
In certain embodiments, such methods comprise obtaining cells,
exposing them to an intervention, and observing whether the
intervention affects the gene expression profile, levels of RNA,
protein, or protein activity related to one or more biomarkers of
aging. Preferably, such changes in gene expression, RNA, protein,
or protein activity levels would occur within four weeks of the
intervention. More preferably, such changes would occur within two
weeks of the intervention, and most preferably, such changes occur
within two days of the intervention. Such methods permit the
identification of pharmacological or other means of achieving a
metabolic state similar to the profile observed with long and
short-term CR.
The methods of the present invention include the use of in vitro
assays (including gene chip assays) as well as animal assays.
Preferably, however, the methods are carried out in live mammals.
For example, transgenic mice having enhanced chaperone expression
may be used to measure an intervention's ability to reduce cancer,
apoptosis, and/or life span. Alternatively, the present methods may
be used to identify interventions that mimic calorie restriction
simply by measuring the intervention's ability to alter gene
expression for a particular gene or set of genes in live mammals.
Such methods allow identification of effective interventions in a
short period of time. Interventions identified by the methods of
the present invention may be pharmacological, surgical or
otherwise. Combinatorial chemistry may also be used in order to
screen a large number of pharmacological compounds. In general, the
interventions identified by the present invention should be
effective in the treatment of cancer, diabetes, age-related
diseases and/or the extension of life span.
While the described embodiment represents the preferred embodiment
of the present invention, it is to be understood that modifications
will occur to those skilled in the art without departing from the
spirit of the invention. The scope of the invention is therefore to
be determined solely by the appended claims.
EXAMPLES
Example 1
Long Term Calorie Restricted (LTCR) Animals and Treatments for
Chaperone Studies
Female, 28-month old mice of the long-lived F.sub.1 hybrid strain
C3B10RF.sub.1 have been described previously. Mice were weaned at
28 d, housed individually and subjected to one of two diets. The
control diet consisted of casein (high protein), 207.0 g/kg,
DL-methionine, 4.0 g/kg, dextrose monohydrate, 301.8 g/kg, corn
starch, 290.0 g/kg, cellulose, 702. g/kg, brewer's yeast, 8.0 g/kg,
Harlan Teklad Vitamin Mix #40060, 10.0 g/kg, Harlan Teklad AIN-76
Mineral Mix #170915, 35.0 g/kg, calcium carbonate (CaCO.sub.3), 3.0
g/kg, magnesium oxide (MgO), 1.0 g/kg, sodium fluoride (NaF), 2.3
mg/kg, sodium molybdate (Na2MoO.2H.sub.2O), 0.5 mg/kg. The 50%
restricted diet consisted of casein (high protein), 362.0 g/kg,
DL-methionine, 7.0 g/kg, dextrose monohydrate, 172.03 g/kg, corn
starch, 153.1 g/kg, cellulose, 83.6 g/kg, brewer's yeast, 14.0
g/kg, Harlan Teklad Vitamin Mix #40060, 17.5 g/kg, harlan Teklad
AIN-76 Mineral Mix #170915, 61.25 g/kg, calcium carbonate
(CaCO.sub.3), 5.25 g/kg, magnesium oxide (MgO), 1.75 g/kg, sodium
fluoride (NaF), 3.0 mg/kg, sodium molybdate (Na2MoO.2H.sub.2O), 0.9
mg/kg. From weaning, control mice were fed 4.8 g of the control
diet on Monday through Thursday. On Friday they were fed 13.8 g of
control diet. This feeding regimen provided 450 kJ/wk. From
weaning, the 50% calorie restricted (CR) mice were fed 4.6 g of the
restricted diet on Monday and Wednesday, and 6.9 g on Friday. This
regimen provided 225 kJ/wk. Each dietary group received
approximately equal amounts of protein, corn oil, minerals and
vitamins per gram body weight. The amount of carbohydrates consumed
varied between groups. Beginning 30 d before these studies, the
control mice were fed 4.1 g (54.44 kJ) control diet daily at 0900
h. The 50% restricted mice were fed 2.3 g of restricted diet (32
kJ) daily at 0900 h. During this 30 d period, the control and
restricted mice received approximately 15% and 50% less dietary
energy than normally thought to be required for a typical mouse
{Subcommittee on Laboratory Animal Nutrition & Committee on
Animal Nutrition 1978 ID: 5480} All food was routinely consumed
within 30 min.
Retired male Swiss-Webster breeder mice were purchased from Jackson
Laboratories. Beginning 30 days before the studies, the mice were
fed Monday and Wednesday 11 g and Friday 16.6 g of the control diet
daily at 0900 h. In fasting-feeding studies, mice were deprived of
food for 48 h, fed 5.5 g of the control diet at 0900 h, and killed
90 min later. The food was consumed within 30 min. Diabetes was
induced by three weekly intraperitoneal injections of
streptozotocin [10 mg/100 g body weight (b.w.)] in 50 mM sodium
citrate, pH 4.5. Mice were diabetic one week after the last
injection. Only mice with blood glucose level higher than 3 mg/ml
were used. Mice injected with equivalent volumes of sodium citrate
served as controls for the STZ-diabetic mice. Adrenalectomized and
sham-operated mice were purchased from Jackson Laboratories.
Dibutyryl cAMP (Sigma; 18 mg. 100 g b.w.), and theophylline (Sigma;
3 mg/100 g b.w.), glucagon (Sigma; 300 .mu.g/100 g b.w.),
dexamethasone (Sigma; 125 .mu.g/100 g b.w), cycloheximide (Sigma; 4
mg. 100 g b.w.), and puromycin (Sigma; 10 mg.100 g b.w.), were
administered intraperitonealy to mice as specified in the figure
legends. Mice received two doses of each drug or drug combination.
The first injection was administered 30 min before feeding, and the
second injection was administered 30 min after feeding. Mice were
killed 1.5 h after the start of feeding. Drug-injected mice
consumed similar amounts of food as control animals during the
feeding period. All animal use protocols were approved by the
institutional animal use committee of the University of California,
Riverside.
Example 2
RNA Isolation and Quantification for Chaperone Studies
Mice were killed and the livers, kidneys, and muscle were removed.
Muscle from the hind legs and back was removed and pooled for each
animal. Tissues were flash frozen in liquid nitrogen. Approximately
0.2 g of frozen tissue was homogenized for 40 s in 4 ml of TRl
Reagent (Molecular Research Center, Cincinnati, Ohio) using a
Tekmar Tissuemizer (Tekmar, Cincinnait, Ohio) at a setting of 55.
RNA was isolated as described by the TRI Reagent supplier. RNA was
resuspended in FORMAzol (Molecular Research Center) and Northern
and dot blots were performed using 20 and 10 .mu.g of RNA
respectively. The RNA was analyzed using Northern blots to verify
its integrity. Dot blots were used to quantify mRNA levels (24;
27). Specific mRNA levels were normalized to the level of total RNA
and/or mRNA present in each sample using hybridization with
radiolabeled complementary DNA to 18S rRNA and/or transcription
factor S-II, as indicated in the figure legends (12; 27). The
murine ERp72 2.5 kb cDNA was excised with BamHI from pcD72-1 (19).
The 1235 bp murine GRP75 coding fragment was excised with HindIII
from pG7z-PBP1.8 (6). A 1.5 kb coding fragment of GRP78 cDNA was
produced by digestion of p3C5 with EcoRI and PstI (15). A 1.4 kb
hamster GRP94 coding fragment was produced by EcoRI and Sa/K
digestion of p4A3 (15). A 664 bp coding fragment of rat
calreticulin (nucleotides 148 to 812) was produced by PCR from
GT10.U1 (23). The entire 2.4 kb cDNA of murine PDI was excised from
pGEM59.4 with Sacl and BamHII (19). A 1 kb coding fragment of
hamster GRP170 cDNA was excised with EcoRI and XhoI from pCRmII
(16). The 1.9 kb cDNA of murine ERp57 was excised with HindIII and
Sstl from pERp61 (18). The 1 kb cDNA of murine HSC70 was excised
with PstI from phsc1.5 (9). The 1.3 kb PEPCK coding fragment was
produced by SphI followed by SalI digestions of pGEM5ZEP (a gift
from Dr. Ganner D. K. Vanderbilt University School of Medicine,
Nashville, Tenn.). The fragments were isolated by agarose gel
electrophoresis and radioactively labeled using a "QuickPrime Kit
(Pharmacia) according to the manufacturer's instructions.
Example 3
RNase Protection Assays for Chaperone Studies
A 223 base pair (bp) DNA fragment made up of 110 bases of intron 3
and all 113 bases of exon 4 of the mouse GRP78 gene was synthesized
by PCR using genomic DNA as template and inserted into pT7/T3
(Ambion, Austin, Texas). Two probes of the junction region of
intron 7 and exon 7 of the GRP78 gene were produced by PCR using
mouse genomic DNA as template. A 257-base fragment including all of
exon 7 and the first 113 bases of intron 7 was produced. A 200-base
fragment including all of exon 7 and the first 56 bases of intron 7
also was produced. The T7 RNA polymerase promoter was ligated to
these PCR fragments using a Lig'nScribe kit as described by the
supplier (Ambion). These constructs were used as template for the
synthesis of [.sup.32P]-labeled antisense RNA probes using a
MAXIScript kit as described by the supplier (Ambion). RNase
protection assays were performed using an RPA II kit as described
by the supplier (Ambion). Hybridization of the 257-base RNA probe
with GRP78 pre-mRNA protected all 257-bases corresponding to exon 7
and the first 113 bases of intron 7. Hybridization of the 200-base
RNA probe to pre-mRNA protected 200-bases corresponding to all of
exon 7 and the first 56 bases of intron 7. Hybridization of either
probe to GRP78 mRNA protects the 143-bases complementary to exon 7.
A 185- and a 277-bp cDNA fragment of S-II cDNA was synthesized and
subcloned into pT7/T3 (12). [.sup.32P]-labeled RNA probes for the
sense and antisense transcripts were synthesized in vitro and RNase
protection assays performed. Hybridization with S-II mRNA protected
the entire 185- or 277-base region of the probes. Protection of
only the sense strand probes was detected. Quantitation of the
hybridized fragments was determined with ImageQuaNT (Molecular
Dynamics, Sunnyvale, Calif.).
Example 4
Plasma Glucose and Insulin for Chaperone Studies
Plasma glucose, insulin, and glucagon concentrations were
determined using Glucose [HK] 10 (Sigma, St. Louis, Mo.), Rat
Insulin RIA and Glucagon RIA kits (Linco Research, St. Charles,
Mo.), as described by the suppliers.
Example 5
Statistical Analysis for Chaperone Studies
The data shown in FIG. 1 are expressed as means.+-.SD for 5 mice at
each time point. The effects of food deprivation and subsequent
feeding on mice of each dietary group were analyzed using a one-way
ANOVA followed by Fisher's test. The analysis determined whether
individual time point means differed from time 0 means within each
dietary group. It also determined the differences between the means
of the control and CR groups at each time point. Differences of
P<0.05 were considered significant. Values are expressed as
means.+-.SD. Significance was determined with either Student's
unpaired t-test (P<0.95) or a one-way ANOVA followed by Fisher's
or Tukey's tests (P<0.01). All statistical analyses were
performed with Minitab Statistical Software (Minitah, State
College, Pa.).
Example 6
Chronic and Acute Effects of Calorie Consumption on Hepatic
Chaperone mRNA
Feeding of the fasted mice rapidly induced the abundance of GRP78
and ERp72 mRNA (FIGS. 1A and 1B). A large increase in chaperone
mRNA was detected by 1.5 h after feeding, the first time point
studied. The 24-h fasting levels (0 time) of GRP78 and ERp72 mRNA
were lower in the CR mice. The response to feeding was kinetically
different in control and CR mice. Thus, the amount of food consumed
affects the kinetics of the response. The integrated level of GRP78
and ERp72 mRNA over the entire 24-hour period was also less in the
CR than in control mice. Similar results were obtained when the
effects of feeding on HSC70, ERp57, and calreticulin mRNA were
determined (data not shown). Thus, this represents a common
response of chaperone gene expression to feeding.
Example 7
Fasting-Feeding Induced Multiple Chaperone mRNAs in Multiple
Tissues
Mice were fasted for 48 hours and refed for 1.5 hours. Hepatic
GRP78 mRNA was induced approximately 3-fold after this time (FIG.
2A). The mRNA for the other ER chaperones investigated, ERp57,
ERp72, GRP94, GRP170, PDI, and calreticulin, and for the most
abundant cytoplasmic chaperone, HSC70, also were induced by feeding
(FIG. 2A). HSC70 was induced by nearly 3-fold. No changes in the
mitochondrial chaperone GRP75 was detected in this study. By
examining chaperone levels in other tissues of fasted and fed mice,
we found that the feeding-related chaperone induction extends to at
least kidney and muscle (FIG. 2B). GRP78 mRNA induction is shown in
the figure (FIG. 2B). HSC70 mRNA was also induced in these tissues
(data not shown). In studies not shown, we have found that a
similar induction of hepatic chaperone mRNAs occurs in rat. Thus,
the response is shared by other species.
Example 8
CR Reduces the Abundance of the GRP78 Primary Transcript
RNase protection studies were used to investigate the
responsiveness of the GRP78 mRNA and primary transcript to chronic
differences in dietary calorie consumption. A probe was utilized
for these studies designed so that the GRP78 primary transcript
protected a 223 base RNA fragment representing the third
intron-fourth exon boundary of the transcript (FIG. 3A lane 1,
upper band). The mRNA protected a 113 base fragment of the probe
which represents the fourth exon of the gene (FIG. 3A , lane 1,
lower band). Much less of the 223 and 113 base GRP78 precursor and
mRNA probes were protected by RNA from CR mice (FIG. 3A , lanes
4-9). A probe for 185 bases of S-II mRNA was included in each
sample as an internal control (FIG. 3A, lane 3). S-II mRNA is
unresponsive to CR or fasting-feeding (25). The unlabeled bands in
FIG. 3 represent RNase-resistant artifacts of the S-II probe (FIG.
3A , lane 2).
When the amount of protected probe was quantified and normalized to
the signal obtained from the S-II probe, it became clear that the
abundance of the chaperone precursor and mRNA were decreased to the
same extent in the CR mice (FIG. 3B). The same conclusion was
reached using a probe for the boundary regions of intron 7 and exon
7. Consequently, CR decreases either the rate of GRP78 gene
transcription or the stability of the GRP78 primary transcript. The
data are not consistent with blocked or paused GRP78 gene
transcription or changes in the stability of the mRNA in CR
mice.
Example 9
Fasting-feeding Induction of the GRP78 Primary Transcript
RNase protection studies also were used to investigate the
fasting-feeding response. RNA isolated 1.5 h after feeding
protected much more of a 257 base fragment representing the exon
7-intron 7 boundary of the primary transcript than RNA isolated
from fasted mice (compare FIG. 4A, lanes 10-12 to lane 7-9).
Similar results were obtained with a probe in which 200 bases
representing the exon 7-intron 7 boundary were protected (compare
FIG. 4A , lanes 16-18 to lanes 13-15). In each case, RNA from refed
mice also protected more of the 143 base fragment representing the
exon 7 region of the mRNA (FIG. 4A). A probe for 277 bp of the S-II
mRNA was present in each assay for use as an internal control.
Quantification of these data, and normalization of the S-II
internal control demonstrated that the mRNA and the precursor RNA
were induced by feeding to essentially the same extent (FIGS. 4B
and 4C). Similar results were obtained using the probe described
earlier for the third intron-fourth exon boundary of the gene (data
not shown). Without being bound to a specific mechanism, these data
suggest the same molecular step is responsible for regulating the
genetic responsiveness of chaperones to both acute and chronic
changes in calorie consumption. This mechanism appears to involve
changes in either the transcription or the stability of the primary
transcript.
Example 10
Inhibitors of Protein Synthesis
To investigate the physiological basis for the fasting-feeding
response, studies were performed using inhibitors of protein
synthesis. Fasted mice were treated with a dose of cycloheximide or
puromycin sufficient to inhibit greater than 95% of protein
synthesis in the liver. Treatment with cycloheximide strongly
induced GRP78 mRNA in fasted mice (FIG. 5A). GRF78 mRNA also was
strongly induced in cycloheximide-treated, refed mice. Puromycin
treatment modestly induced GRP78 mRNA in fasted mice (FIG. 5A).
Feeding of puromycin treated mice fully induced the mRNA. Thus,
induction by feeding does not appear to require de novo protein
synthesis. Further, these results suggest that the lower chaperone
mRNA levels in fasted mice may involve the action of a rapidly
turning over factor.
The effects of the protein synthesis inhibitors on PEPCK mRNA also
was determined as a positive control. The effects of
fasting-feeding and cycloheximide treatment on this mRNA are well
known. Fasting induced, and feeding repressed PEPCK mRNA, as
expected (FIG. 5B). Also, as expected from published data,
cycloheximide increased PEPCK mRNA in both fasted and refed mice
through its effects on PEPCK mRNA stability. The effects of the
inhibitors on PEPCK mRNA levels indicate the inhibitors were
efficacious in these studies.
Example 11
Pancreatic Hormones and Glucose
The physiological hallmarks of the fasting-feeding transition are
increased circulating insulin and decreased circulating glucagon.
In the studies shown in FIG. 6, fasted and refed sham-injected mice
had serum glucose concentrations of 84.4.+-.5.1 and 1.21.+-.8.0
mg/dl, serum insulin concentrations of 0.491.+-.0.203 and
1.3.+-.0.256 pmol/ml, and serum glucagon concentrations of
143.+-.22.4 and 81.4.+-.13.2 pg/ml, respectively.
To investigate whether these hormones an: involved in the
postprandial induction of GRP78 mRNA, the effects of cAMP,
glucagon, and STZ-induced diabetes on the response were examined.
Administration of either dibutyryl cAMP or glucagon reduced the
response of GRP78 mRNA to feeding (FIG. 6A). Vehicle alone had no
effect. Likewise, STZ-induced diabetes resulted in a blunted
response to feeding although it did not modify the fasting level of
GRP78 mRNA. When STZ-induced diabetes was combined with cAMP
administration, the postprandial induction of GRP78 mRNA was
obliterated. The mRNA remained at fasting levels Without being
bound to any particular mechanism, these results suggest that
glucagon, acting to increase intracellular cAMP levels, suppresses
chaperone gene transcription, or possibly GRP78 pre-RNA stability.
Further, they suggest that insulin is required for full
responsiveness of the chaperone genes to decreased intracellular
cAMP.
Example 12
Luminal Filling
Luminal filling can lead to the release of some gastrointestinal
polypeptide. For this reason, we investigated the role of luminal
stimuli on the chaperone mRNA response. Fasted mice were refed a
nonnutritive paste of cellulose (a normal component of their
regular diet) and mineral oil. The mice initially consumed the
mixture enthusiastically. Stomach filling was confirmed for each
mouse by postmortem examination. Cellulose-mineral oil consumption
produced a minor but significant increase in GRP78 mRNA (FIG. 6B),
without producing a change in plasma glucose, insulin, or glucagon
concentrations.
Example 13
Adrenal Hormones
To investigate the role of adrenal hormones in the post-prandial
induction of GRP78 mRNA, we examined the effects of feeding in
adrenalectomized mice (FIG. 7). Neither adrenalectomy nor sham
surgery had any effect on the fasting levels of GRP78 mRNA.
However, adrenalectomy increased the magnitude of the postprandial
induction of the mRNA by approximately 2-fold over that found is
refed, sham-operated mice. The feeding response of GRP94, ERp72,
and GRP170 were also enhanced in the adrenalectomized mice (data
not shown). Thus, the increase is a generalized ER chaperone
response. Administration of dexamethasone to adrenalectomized mice
increased the basal level of GRP78 mRNA during starvation, although
not significantly (FIG. 7). However, dexamethasone administration
had no effect on the feeding induction of the gene, suggesting its
absence from adrenalectomized mice is not responsible for the
enhancement of the feeding response.
Example 14
Preparation of Test Groups for Short-term CR Studies
Three groups of 30 month old mice were utilized for these studies.
Male B6 C3F.sub.1 mice were maintained as described (Dhahbi et al.
(1998) J. Gerontol 53A: B180). Mice were weaned at 28 days and
housed individually. The composition of the defined diets used have
been described. They are formulated so that only the amount of
carbohydrate consumed varied between the CR and control mice. A
group of control mice was fed a purified, semi-defined diet from 6
weeks of age. Control mice consumed approximately 105 kcal per week
from weaning. This is approximately 10% less than the amount of
food thought to support optimal growth, fertility and fecundity in
mice {Subcommittee on Laboratory Animal Nutrition & Committee
on Animal Nutrition 1978 ID: 5480}. Subjectively, these mice
appeared neither fat or lean. A group of calorically restricted
mice (CR mice) were fed a diet reduced in dietary carbohydrate such
that the mice consumed approximately 40% fewer calories than
control mice. The long term CR mice consumed approximately 55 kcal
per week from weaning. The short term CR mice were fed 105 kcal
until the age of 29 months. They were then fed 80 kcal of control
diet for 2 weeks, followed by 55 kcal of CR diet for two weeks. The
mice were fed daily at 0900 hours. They had free access to water.
For the studies, mice were fed a normal allotment of food Monday
morning, and all the food was eaten within 45 minutes. They were
fasted for 24 hours, and killed on Tuesday morning. At the time of
use, the long term CR, short term CR and control mice weighed
22.8.+-.1.4, 25.22.+-.0.3 and 37.2.+-.2.4 g, respectively. The mice
were approximately 30 months old when killed.
Mice were killed by cervical dislocation and the liver rapidly
removed and flash frozen in liquid nitrogen. Approximately 0.2 g of
frozen liver was homogenized for 40 s in 4 ml of TRI Reagent
(Molecular Research Center, Inc., Cincinnati, Ohio) using a Tekinar
Tissuemizer (Tekmar Co., Cincinnati, Ohio) at a setting of 55. RNA
was isolated as described by the supplier.
.[.GeneChip o.]. .Iadd.O.Iaddend.ligonucleotide-based high-density
array RNA expression assays were performed according to the
standard Affrymetrix protocol. The biotinylated, fragmented cRNA
was hybridized to the Mu11KsubA and Mu11KsubB.[.GeneChip.].
.Iadd.GeneChip.RTM. .Iaddend.arrays (Affymetrix, Santa Clara,
Calif.), which contain targets for more than 11,000 known mouse
genes and ESTs. The arrays were washed, stained and scanned.
Scanned image analysis and data quantification were performed using
the Affymetrix .[.GeneChip.]. .Iadd.GeneChip.RTM. .Iaddend.analysis
suite v3.2 at default parameter settings. Resultant data were
normalized by global scaling.
Data analysis. Data sets were normalized furher using GeneSpring
3.0 (Silicon Genetics, San Carlos, Calif.). Negative expression
levels were forced to zero, and the expression data for each animal
divided by the median of all experimental values for that chip
above an expression level of 10. This step reduced cliip-to-chip
signal variation. Fold change in expression was calculated by
dividing the mean of the expression levels in the CR groups by the
mean of the expression levels in the control group.
Statistical analysis. To test for significance of the effect of
diet on gene expression, one-way ANOVA was followed by Fisher's
test (P<0.05). Genes were placed in expression pattern groups
(Table 2) for which they passed both tests. All statistical
analyses were performed using Minitab Statistical Software.
Example 15
Gene Expression in Long and Short Term CR Mice
The global patterns of hepatic gene expression in the three groups
of mice as displayed by GeneSpring 3.0, are shown in FIG. 8. The
11,000 genes assayed in the study are grouped according to both
structure and function by the GeneSpring gene clustering algorithm
across the horizontal axes of the figure. While this representation
of the data cannot be subjected to statistical tests, subjective
examination of this color coded representation of the data obtained
immediately suggests that striking similarities exist in the gene
expression profile of long and short term CR mice. Likewise,
examination of the figure suggests that both CR expression profiles
are very different than the profile of control mice. An
average-linkage hierarchical clustering dendrogram calculated from
the data by the GeneSpring clustering algorithm is shown to the
left of the expression profiles. The dendrogram shows that the
algorithm clustered the short- and long-term CR groups together,
separated from the control group. This analysis agrees with our
subjective interpretation of the expression profile.
Another aspect of this representation of the data was of interest.
Significantly larger areas of blue were found in the expression
profile of the control mice. These areas represent genes for which
expression was not detectable. In both groups of CR mice, many of
these regions were red, indicating higher levels of expression.
Thus, a major effect of CR was the activation of specific gene
expression.
To quantify the similarities in gene expression among groups of
mice, a global expression correlation coefficient was calculated
for each possible pair of mice. Table 1 shows the nine by nine
matrix of these pairwise comparisons. The values are a measure of
the similarities in gene expression between pairs of mice. Because
the mice were genetically identical, the intra-group values provide
a measure of the maximum correlations attainable. The inter-group
correlations of the short- and long-term CR mice were similar to
their intra-group correlations, indicating that gene expression in
all CR mice was similar. In contrast, the control mice have little
correlation with the mice in either CR group. This analysis
suggests that short- and long-term CR had highly similar effects on
overall patterns of specific gene expression.
TABLE-US-00001 TABLE 1 Pairwise comparisons of the global gene
expression correlation coefficient calculated for each possible
pair of mice. CR CONTROL SWITCHED CR 1.00* 0.25 0.32 0.01 0.04
-0.04 0.16 0.17 0.18 1.0 0.27 -0.03 0.03 -0.01 0.13 0.12 0.18 1.00
0.02 0.02 -0.02 0.18 0.14 0.21 CONTROL 1.00 0.29 0.42 0.0 0.03 0.07
1.00 0.28 0.07 0.10 0.01 1.00 -0.02 0.02 0.05 SWITCHED 1.00 0.24
0.18 1.0 0.16 1.00
Example 16
Long- and Short-term CR Induced Expression of the Same Genes
The pseudogene function of GeneSpring 3.0, and statistical analysis
of the data were utilized to sort the genes into one of seven
possible categories of relative gene expression. These groups were:
expression not different among groups; expression high in long-term
CR, low in control, and high in short-term CR (termed,
high-low-high) (Appendix A); expression low in long-term CR, high
in control, and low in short-term CR (low-high-low) (Appendix B);
expression low in long-term CR and control, but high in short-term
CR (low-low-high) (Appendix C); expression high in long-term CR and
control, and low in short-term CR (high-high-low) (Appendix D);
expression high in long-term CR, and low in control and short-term
CR (high-low-low) (Appendix E); and expression low in long-term CR
and high in control and short-term CR (low-high-high) (Appendix F).
The vast majority of the genes were not different among groups, and
will not be discussed further.
Table 2 shows the number of genes and expressed sequence tags
(ESTs) in each of the other groups. Ninety percent or these genes
and ESTs were in the high-low-high and low-high-low groups. In
these groups, the short- and long-term CR expression patterns are
most similar. The other 4 groups accounted for only 10% of the
remaining genes ans ESTs. These data indicate that short- and
long-term CR produced remarkably similar effects on the expression
of more than 11,000 hepatic genes and ESTs. A complete listing of
the expression data for the genes and ESTs in each group is
available
.[.(http://wwwbiochemistry.ucr.edu/faculty/spindler.html/GeneCh-
ipData) (This URL will be activated upon allowance of this
application).]. .Iadd.on the internet.Iaddend..
By far the most common response to short- and long-term CR was the
high-low-high expression pattern. It accounted for nearly 86% of
the genes and ESTs in the groups. Thus, the most common effect of
short- and long-term CR was the activation of gene expression. To
determine whether short- and long-term CR induced expression to the
same degree in the high-low-high group, we tabulated the number of
known genes for which expression was statistically the same in the
two groups. In high-low-high, 303 of 340 known genes (89%) were
expressed at the same level in the short- and long-term CR groups.
For 26 of these genes (8%), expression in the long-term CR mice was
statistically greater. For 11 genes (3%), expression was greater in
the short-term CR group. Thus, short- and long-term CR induced the
expression of the vast majority of these genes to the same
levels.
Of the genes in the high-low-high group, 146 of 340 genes were
activated from undetectable levels in the control mice to much
higher, but very similar levels in both CR groups. Expression of
these genes averaged 1.25.+-.0.25 and 1.23.+-.0.23, in the short-
and long-term CR groups, respectively. These observations reinforce
the idea that short- and long-term CR have highly homologous
effects on the expression of genes.
To further understand the genomnic effects of CR, we identified the
genes in the high-low-high group described above.
TABLE-US-00002 TABLE 2 GENES WHICH DIFFER FROM CONTROL IN RESPONSE
TO CR LT CR* CONTROL ST CR** GENES ESTs PERCENT High Low High 340
860 85.7 Low High Low 23 37 4.3 High High Low 4 9 0.9 Low Low High
13 19 2.3 High Low Low 26 55 5.8 Low High High 9 6 1.1 *Long-term
CR **Short-term CR
Example 17
Immune System Activation: The Immune Theory of Aging
Many of the genes which were induced by CR in the long and short
term CR group were genes involved with immune system activation.
Without being limited to any specific mechanism, this result
provides support for the theory that the immune system plays a
central role in the rate and many of the pathologies of aging.
Slightly more than 130 T-cell receptor, IgG, IgA, IgD, IgK, and
IgM, genes were present in the high-low-high group. The average
fold relative expression of these mRNAs in the long and short term
CR groups was 1.24.+-.0.86 and 1.23.+-.0.25, verses 0.16.+-.0.16 in
the control group. Thus, CR increased immunoglobulin and T-cell
receptor expression more then 10-fold. It is highly unlikely that
this increase was due to an increase in the amount of blood in the
CR livers. The level of globin mRNA found in these mRNA samples was
actually reduced by about 20% in the long and short term CR groups.
No statistically significant difference was found in the globin
mRNA concentration in the blood of these animals.
Other changes in gene expression indicate that CR activates the
immune system (Table 3). As can be seen in the table, both long and
short term CR induced the expression of hemopoietic and
lymphopoetic cytokines, hormones, signal transduction proteins,
protein kinase modulators of the cell cycle and signal
transduction, cell-surface receptors, and transcription factors.
Not shown are a group of 20 immune cell specific genes known to be
involved in endocytosis, cell adhesion, phagocytosis, potassium
channels, lymphocyte activation, VDJ recombination, and immune cell
activation which were strongly and significantly induced by CR (3-
to 40-fold; P.ltoreq.0.037). Together, these data evidence that CR
enhances the activity of the immune system.
TABLE-US-00003 TABLE 3 Immune system genes activated by short- and
long-term CR LTCR* STCR* P GENE Hormones/Cytokines/Chemokines 4 4
0.003 Antigen, B cell receptor, L43567 53 55 <0.001
Calcium/calmodulin-dependent protein kinase IV (Camk4);
multifunctional serine-threonine protein kinase; T cells; X58995
>100 >100 <0.001 Chemokine (C--C) receptor 1 (Cmkbr1);
growth inhibitory effects; liver and spleen; U28404 13 17 <0.001
Chemokine (C--C) receptor 5 (Cmkbr5); induces mobilization of
intercellular calcium; beta-chemokine; leucocyte cheatoallractant;
liver, thymus, spleen, elsewhere: LT62976 >100 >100 0.003
Chemokine (C-X-C) receptor 4 (Cmkbr4); integral membrane G-
protein-coupled receptor; chemotaxis and calcium flux; directs
monocytes and lymphocytes to their target tissues; thymus, T cells,
and monocytes; ET62920 19 21 0.002 Colo9ny stimulating factor 1
(macrophage) (Caf1); receptor; liver; X06368 10 8 0.016 Complement
receptor 2 (Cr2); Late pre-B cells; M35684 3 2 0.015 Interferon
beta type 1; growth factor; T helper cell differentiation factor;
antiviral; modulated immune response to foreign and self-
antigenes; immune system cells, others; V00755 11 10 <0.001
Interferon-related developmental regulator (Ifrd1); T cells; V00756
9 6 0.044 Interleukin 2 (Il2); stimulated proliferation of
activated T lymphocytes; M16762 >100 >100 0.015 Interleukin 2
receptor (Il2r); T cells; M26271 2 2 0.014 Interleukin 6 (Il6);
promoter B cell maturation to tg-secreting cells; activation of T
cells; some helper T cells and macrophages; X54542 5 6 0.004
Interleukin 7 (Il7); growth factor, B cell progenitors; X07962 4 3
0.046 Killer cell lectin-like receptor, subfamily A, member 3
(Klra3); Ly- 49C; involved in graft rejections; subpopulation of
natural killer cell; U49866 >100 >100 0.034 Killer cell
lectin-like receptor, subfamily A, member 6 (Klra6); Ly- 49F; NK
cell surface antigen; determinant of IL-2-activated NK cell
proteins; NK cells, U10092 13 11 <0.001 Lymphocyte antigen 84
(Ly84); signal transduction protein 2; T cells; D13695 5 6 0.007
Mast cell protease 7 (Mcpt7); released when mast cells are
activated; mast cells; ET61471 3 2 0.037 Myc box dependent
interacting protein 1 (Bin1); endocytosis and signal transduction;
recycling synaptic vesicle components; macrophages, neurons,
endocrine cells; U86405 >100 >100 <0.001 Paired-Ig-like
receptor A1 (Pira1); activates B lymphocytes, dendritic and
mycloid-linage cells; ET62839 5 4 0.027 Paired-Ig-like-receptor A6
(Pira6); appears to activate immunoglobulin-related receptor; H
lymphocytes, myeloid lineage cells; ET62844 3 4 0.038
Preprosomatostatia (Stnst); regulates T cell IFN-gamma production;
macrophages, nervous system; X51468 >100 >100 <0.001
Protein tyrosine phosphatase, receptor type B (Ptpre);
transmembranal, receptor-like form and a cytoplasmic, non-receptor
form; hematopoietic tissues; ET61424 23 41 0.010 Proviral
integration site (Pim2); serine/threonine kinase 2; cell
proliferation; mitogen stimulated; long-term potentiation in
hippocampus; immune and epithelial cells, CNS; L41495
Receptors/Signal Transduction Proteins 11 8 0.001 Small inducible
cytokine subfamily, member 2 (Scyb2); small inducible cytokine;
macrophages; X5379H 8 8 0.002 Son of sevenless 1, homologue 1
(Drosophila) (Sos1); Ras-specific exchange factor; T cells; Z11574
>100 >100 <0.001 Son of sevenless 2 homologue 2
(Drosophila) (Sos2); Ras-specific exchange factor; T cells; Z11664
>100 >100 0.002 Spleen protein kinase (Syk); signal
transduction; lymphopoietic and haematopoietic cells, plateleta,
anacrophages and neutrophils; ET61263 >100 >100 0.048 Tbel;
domains homologous to tre-2 oncogene and yeast mitosis regulators
BUB2 and cdc16; nuclear localization; B lymphocytes; deadritic
cells, myeloid-linage cells; U33005 2 2 0.044 Thrombin receptor;
transmembrane G-protein-coupled receptor; activated by serine
protease cleavage; mitogen and apoptosis inducer following vessel
injury; plateleta, monocytes, endothelial cells, neuronal and glial
cells; U36757 >100 >100 0.002 Weel homologue (S. pombe)
(Weel); inhibits entry into mitosis by phosphorylatios of the Cdc2
kinase; lymphocytes; D30743 Transcription Factors 38 35 <0.001
Abelson nurine leukemia oncogene (Abl); nonreceptor tyrosine
kinase; role in cell progression, cell proliferation and
differentiation; liver, B cells, others; X07540 >100 >100
0.047 Homeo box A4 (Hoxa4); transcription factor; embryonic spinal
cord and adult testis; X13538 4 7 0.026 Homeo box B4 (Hoxb4);
transcription factor; embryonic development; haematopoiesis; NK
cells; M36654 6 10 0.029 Homeo box B7 (Hoxb7); transcription
factor; embryonic development; haematopoiesis; developing embryo;
blood, bone marrow, natural killer cells; X06762 8 9 <0.001
Homeo box C6 (Hoxc6); transcription factor; embryogenesis;
haematopoiesis; lliver and many other tissues; X16510 40 36 0.001
Homeo box D1 (Hoxd1); transcription factor; neurogenesis;
developing CNS and forelimb bud; X60034 >100 >100 <0.001
Nuclear factor of activated T cells, cytoplasmic 2 (Nfatc2); T cell
transcription factor isoform B; T cells; U36575 5 5 0.001 SRY-box
containing gene 4 (Sox4); Sox gene family transcription factor;
thymus, bone marrow, gonads; ET62444 2 2 0.012 Zinc finger protein
79 (Zfp79); Kruppel type zinc finger putative transcriptional
repressor; associates with RB in vitro; haematopoietic cells,
perhaps others; U29513 Primary Response Genes >100 >100 0.005
Fos-like antigen-1 (Fosl1); spleenocytes; U34245 >100 >100
<0.001 Immunity associated protein, 38 kDa (Imap38);
spleenocytes; Y08026 >100 >100 <0.001 Immunorespossive
gene 1 (Irg1); activated by bacterial LPS treatment; macrophages;
L38281 >100 >100 <0.001 Prostaglandin-endoperoxide
synthase (Ptgs2); putative mediator of inflammation; induced by
growth factors and cytokines; monocytes and fibroblasts; M88242 388
353 0.001 T-cell actue lymphocytic leukemia 2 (Ts12); putative
basic helix- loop-helix transcription factor activated in T-cell
acute lymphoblastic leukemia; T cells; M81077 >100 >100
<0.001 Tumor necrosis factor inducted protein 3 (Tnfip3);
putative helix- loop-helix transcription factor activated in T-cell
acute lymphoblastic leukemia; lymphocytes; U19463 Cell
Adhesion/Membrane Components >100 >100 0.002
ADP-ribosyltransferase 2s (Art2s); homologue of the rat T cell
differentiation marker RT6; cell-cell signaling; cytotoxic T
lymphocytes; X52991 9 9 0.013 Cadherin 9 (Cdh9); calcium-binding
membrane glycoprotein; cell adhesion molecule; thymocytes; U69136 6
5 0.015 CD22 antigen (Cd22); mediated B cell interactions with
endothelial cells; B cells; L16928 7 7 0.002 CD53 antigen (Cd53);
pan-leukocyte antigen; cell membrane glycoprotein; thymocytes;
X97227 40 36 <0.001 Erythrocyte protein bond 7.2 (Epb7.2);
involved in Na+/K+ permeability of cells; spleen, lung, testis;
X91043 8 8 0.006 Integria alpha 4 (Iiga4); cell adhesion;
lymphocytes; X53176 >100 >100 <0.001 Mannose receptor, C
type 2 (Mrc2); cell adhesion; antigen presentation; widespread
tissue distribution, fetal liver, U56734 Immune Cell Function 38 44
<0.001 Cytochrome b-245, beta polypeptide (Cybb); gp91phox;
flavocytochrome mediating electron transfer from NADPH to molecular
oxygen in the respiratory burst oxidase; phagocytes; U43384 8 8
<0.001 Cytotoxic T lymphocyte-associated protein 2 beta
(Ctla2b); homologue of cysteine protease proregion, T cells; X15592
>100 >100 <0.001 GraezyineG (Gzng); CTL serine protease 3;
may play a role in cytolytic lymphocyte activation; T lymphocytes;
X14092 >100 >100 0.007 Helicase, lymphoid specific (Hells);
replication, repair, recombination and transcription; T and B
cells; U25691 >100 >100 0.001 Mast cell protease 4 (Mcpt4);
secretory granule serine protease; peritoneal and most connective
tissue mast cells; M55617 5 6 0.007 Mast cell protease 7 (Mcpt7);
released when mast cells are activated; mast cells; ET61471 8 8
0.005 Potassium voltage gated channel, shaker related subfamily,
member 2 (Kena2); T cells, myelinating Schwann cells; M30440 3 3
0.003 Terminal deoxynucleotidyl transferase (Tdt); VDJ assembly;
recombination; earliest stage B and T cells; X04123 *Fold of
control
Further support for this view was found in the liver specific genes
which were strongly induced in expression by CR (Table 4). Long and
short-term CR significantly enhanced the expression of the CD44
hyaluronan receptor gene, which has a role in lymphocyte homing and
activation. Likewise, CR activated the mRNA abundance of the
chemokine receptor 4, which is also involved in stimulating growth
of pre-B cells; the mannose receptor, C type 2, which is involved
in antigen presentation; colony stimulating factor 1, which is a
macrophage growth factor; and proteaseome 3, which enhances the
generation of class I binding peptides.
TABLE-US-00004 TABLE 4 Liver specific and ubiquitous genes LTCR*
STCR* P GENE Cytokines/Growth Factors 12 7 0.003 C-Fow induced
growth factor (Fief); secreted growth factor; mitogenic and
morphogenic activity; endothelial cells of liver during embryonic
development; X99572 2 2 0.002 Fibroblast growth factor 2 (Fgf2);
mitogen, differentiation and survival factor, angiogenic factor;
stimulates hepatocyte >100 >100 0.001 Fibroblast growth
factor 3 (Ffg3); liver epithelial cells; Y00648 3 3 0.012
Fibroblast growth factor 7 (Ffg7); liver epithelial cells; ET62118
>100 >100 0.001 Follistatis (Fst); binds and inactivates
activia; control of the inflammatory cascase; liver; Z29532 >100
>100 0.005 Inhibin beta B (Iabbb); transforming growth factor
beta (TGF- beta) superfamily member; liver and elsewhere; X69620
>100 >100 0.001 Inhibin beta E (Iabbe); transforming growth
factor beta (TGF- beta) superfamily member; liver and elsewhere;
U96386 13 9 0.000 Interferon alpha gene family leukocyte (Iafa);
inhibition of cell proliferation; ubiquitous; M28587 3 2 0.015
Interferon beta type 1; growth factor; T helper cell
differentiation factor; antiviral; modulates immune responses to
foreign and self- antigens; ubiquitous; V00755 11 11 0.001
Interferon-beta (Ifnb); inhibitor of inflammations; liver and other
cells; J00424 13 13 <0.001 Neurotrophin 3 (Ntf3); secreted
protein; binds high affinity receptor trk C; may be involved in
postestial development; liver parenchymal cells, cerebellu, thymus,
other; X53257 4 5 0.003 Preproendothelin 1 (Edn1); activates p38
MAP kinase and JNK; portal vein contriction; hepatic stellate
cells, liver and arterial smooth muscle cells, others; U07982 10 15
0.003 Transforming growth factor beta 2 (Tgfb2); cell
proliferation; liver stellate cells; X57413 Cell Surface Receptors
>100 >100 0.020 Bradykinin receptor beta (Bdkrb);
G-protein-coupled membrane bouad; T-kininogen modulation during
acute phase protein synthesis; liver (ubiquitous); ET61559 2 2
0.017 CD44 antigen (Cd44); receptor for hyaluronan; cell surface
glycoprotein; hyaluronan clearance from the blood; lymphocyte
homing and activation; liver, CNS, other; U57612 >100 >100
<0.001 Chemokine (C--C) receptor 1 (Cmkbr1); mediates growth
inhibitory effects of the chemokine; liver and spleen; U28404 12 8
0.013 Chemokine (C-X-C) receptor 4 (Cmkar4); primary receptor
stromal cell-derived factor/pre-B growth stimulating factor; seven
transmembrane domain receptor; liver and bone marrow; X99581
>100 >100 <0.001 Fibroblast growth factor receptor 2
(Fgfr2); membrane;spanning tyrosine kinase; activated by three
members of the FGF family; liver development; liver parenchymal
cells and others; M86441 4 3 0.001 Leptin receptor (Lepr);
transmembrane receptor; liver, lung, muscle, brain, other; ET61693
4 3 0.027 Melanocortin 5 receptor (Mc5r); G-protein-coupled
receptor, stimulates adenylyl cyclase; widely expressed; X76295 3 4
0.029 Pancreatic polypeptide receptor 1 (Ppyr1); aeuropeptide Y;
peptide YY receptor; O-protein-coupled; liver; U40189 >100
>100 <0.001 Proteaseome 3 (Psme3); Ki antigen; cell
proliferation; enchances generation of class I binding peptides;
liver, broad tissue distribution; U60330 >100 >100 <0.001
Purinergic receptor P2X, ligand-gated ion channel 1 (P2rx1);
mediated Ca(2+) influx; liver, ubiquitous; X84896 64 68 0.001
Ryasodine receptor 2 (Ryr2); endoplasmic reticulon membrane Ca2+
channels; controls cytosolic calcium levels; liver, cardiac muscle,
neurons, most excitable cells; X83933 >100 >100 0.003
Transferrin receptor (Trfr); cell surface glycoprotein; cell
growth; iron uptake; liver; X57349 Signal Transduction/Cell
Cycle/Cell Growth 38 35 <0.001 Abelson murine leukemia oncogene
(Abl); nonreceptor tyrosine kinase; role in cell proliferation and
differentiation; liver, B cells; X07540 >100 >100 0.006
Cyclin-dependent kinase inhibitor 1B (P27) (Cdkn1b); cell cycle;
ubiquitous; U10440 35 40 0.003 Gusnine nucleotide binding protein,
alpha inhibiting 1 (Gnail); liver, cerebral cortex, others; U38501
>100 >100 0.013 Gusnine nucleotide binding protein beta 4
(Gab4); liver, brain, blood cell; M63658 >100 >100 0.001
Histamine recepotr H1 (Hrb1); coupled to phosphoinositide
turnover-calcium mobilization signaling pathway; regulates IOF-1
expression and cell proliferation; regulates thyroxine transport
into hepatocytes; liver, brain, spleen (ubiquitous); D50095 >100
>100 0.002 Interferon-activated gene 204 (Ifi204); mediates
antimicrobial, immunomodulary and cell growth-regulatory activities
of interferons; nucleoli; M31419 4 4 0.004 Kinase interacting with
leukemia-associated gene (Kis); cytosolic phosphoprotein;
integration of intracellular proliferation and differentiation
signaling; ubiquitous; X82320 9 8 0.004 MAD homologue 5 (Madh5);
downstream component in the TGF-beta family signaling cascase;
liver development angiogenesis; liver; ET62570 >100 >100
0.002 MAP kinase kinase kinase (Map3k1), serine-threonine kinase;
regulates sequential protein phosphorylation pathways involving
mitogen-activated protein kinase (MAPKs); ubiquitous; ET61257
>100 >100 0.002 Mitogen activated protein kinase 1 (Mapk1);
signal transduction; cell proliferation, differentiation, and
apopiosis; liver, ubiquitous; U85608 >100 >100 0.004
NIMA-related expressed kinase (Nek1); ubiquitous; S45828 3 3 0.041
Neuroblastoma ras oncogene (Nras); key component of growth
signaling pathways; liver, wide tissue distribution; X13664 >100
>100 <0.001 Phosphatidylinositol 3-kinase regulatory subunit,
polypeptide 1 (p85alpha) (Pik3r1); role in cell growth,
differentiation, survival, and vesicular transport; liver; ET61628
>100 >100 0.003 Phospholipase C, gamma 1 (Pleg1); produces
second messengers of signal transduction pathways related to cell
proliferation; ubiquitous; ET63005 >100 >100 <0.001
Proteasome 3 (Psme3); Ki antigen; cell proliferation; enchances the
generation of class I binding peptides by altering the cleavage
pattern of the proteosome; liver, neurons, broad tissue
distribution; U60330 3 2 0.002 Protein tyrosine phosphatase,
non-receptor type 16 (Ptpn16); growth factor-induced immediate
early gene; dephosphorylates MAP kinase; liver parenchyenal and
vascular smooth muscle cells, others; X61940 11 12 0.001
Ras-GTPase-activating protein SH3-domain binding protein 2
(G3bp2-pending); essential for Ras signaling; ubiquitous; U65313 2
2 0.001 Rhodopsin kinase (Rhok); small GTPase and serine/threonine
protein kinase; regulates actia cytoskeletal reorganization;
enhances secretion; ubiquitous except for brain and muscle; U58513
15 14 0.016 Ros 1 proto-oncogene (Ros1); embryonic develoopment;
tyrosine kinase catalytic domains; expressed in neoplastic and
fetal tissues; neoplastic and fetal tissues; U15443 6 4 0.010
SUMO-1 activating enzyme subunit 1; conjugates SUMO-1 (a small
ubiquitin-like protein) to other proteins; modification of I Kappy
B alpha blocks NF kappa B-dependent transcriptional activation;
ubiquitous; AA162130 >100 >100 <0.001 Wingless related
MMTV integration site 10b (Wat10b); development regulation of cell
growth and differentiation; ET62229 Nuclear Receptors 19 17 0.016
Thyroid hormone receptor alpha (Thra); energy balance,
thermoregulation, substrate uptake; liver; X07751 10 9 0.003
Glucocorticoid receptor 1 (Gd1); energy balance; substrate uptake;
liver; X04435 45 42 <0.001 Nuclear receptor subfamily 2, group P
member 1 (Nr2f1); COUP- TF1; orphan steroid hormone receptor,
transcription factor; liver, X74134 >100 >100 0.010 Nuclear
receptor subfamily 2, group F member 2 (Nr2(2); apolipoprotein
regulatory protein 1; member of the COUP-family of steroid hormone
orphan reception; liver, lung, kidney; X76653 Transcription Factors
4 3 0.016 Sine oculis-related homeobox 1 homologue (Drosophila)
(Six1); AREC3; expressed in many cell-types during development;
ET61028 9 7 0.003 cAMP responsive element binding protein 1
(Creb1); a mediator of cAMP responsive transcriptional regulation;
ubiquitous; X67719 >100 >100 <0.001 Reticuloendotheliosis
(Rel); c-rel; member of the ReVauclear factor (NF)-kappa B family
of transcriptional factors; ubiquitous; X15842 >100 >100
<0.001 E4F transcription factor 1 (E4f1); DNA binding
transcription factor; ubiquitous; X76858 4 4 0.026 Forkhead box C2
(Foxc2); transcription factor; hepatocytes; X74040 11 11 0.001
Homeo box A9 (Hoxa9); transcription factor; embryogenesis; M28449
>100 >100 0.003 Homeo box msh-like 1 (Max1); transcription
factor; early stage of eye developmental regulation in embryo;
embryogenesis; X59251 2 3 0.003 Inhibitor of DNA binding 4 (Idb4);
domineer negative regulator of bHLH transcription factors;
myogenesis, neurogenesis D83 and haematopoiesis; liver and
elsewhere; X75018 >100 >100 0.010 Myogen factor 5 (Myf5);
transcription factor, embryonic liver and heart; X56182 6 8 0.003
Nuclear transcription factor-Y alpha (Nfye); CAAT-box DNA binding
protein subunit A; involved in activation of many hepatic genes;
ubiquitous; X55315 3 3 0.018 Paired box gene 2 (Pax2); Pax2
transcription factor; developing embryo excretory and CNS; X55781
12 13 0.003 RE2-silencing transcription factor (Rest);
transcription factor; represses expression of neuronal genes; many
noancuronal cells and tissues; U13878 >100 >100 0.002 Sine
oculia-related homeobox 1 homolog (Drosophila) (Six1); homeobox;
development of limb teadons; skeletal and smooth muscle cells;
X80339 >100 >100 0.005 SRY-box containing gene 12 (Sox12);
transcription factor; Sox family plays important role in
development; developing embryos; ET62446 2 3 0.032 T-box 4 (Tbx4);
DNA binding domain putative transcription factor; putative roll in
inductive interactions during embryogenesis; embryonic development;
ET62078 >100 >100 0.009 Trans-acting transcription factor 1
(Sp1); transcription factor; component of some hepatic glucose
response elements, ubiquitous; X60136 >100 >100 0.024
Transcription elongation factor A 1 (Tcea1); transcription
elongation factor; liver; D00925 14 12 <0.001 Yes-associated
protein, 65 kDa (Yap); transcription activator, ubiquitous; X80508
10 10 <0.001 Zinc finger protein 37 (Zfp37); putative
transcription factor; peroxisome proliferator responsive; liver;
X89264 >100 >100 0.009 Zinc finger protein 61 (Zfp61);
putative transcription factor, liver, elsewhere; L28167
Translation/Splicing/Rna Processing Factors 7 7 0.001 Cytoplasmic
polyadenylatice element binding protein (Cpeb); RNA binding protein
that promotes polyadenylation and translational activation;
ubiquitous; Y08260 4 4 0.011 Eukayotic translation initiation
factor 1A (Eif1a); ubiquitous; U28419 >100 >100 <0.001
Ribosomal protein L32, pseudogene (Rp132ps); ubiquitous; X02060
>100 >100 0.000 Ribosomal protein L7 (Rp17); incorporated
into 60 S subunit; ubiquitous; X57960 18 13 0.001 Signal
recognition particle 9 kDa (Srp9); synthesis and translocation of
membrane and secreted proteins into the endoplasmic reticulum;
ubiquitous; X78304
>100 >100 0.004 Splicing factor arginine/serine-rich 3
(Sfrs3); splicing factor belonging to the highly conserved family
of SR proteins; regulation of constitutive and alternative
splicing; ubiquitous; X91656 Chromatin Structure 4 5 0.009
Chromobox homologue (Drosophila HP1beta) (Cbx); modifs chromatin
heritably activating or silencing genes; ubiquitous during
development; X56690 >100 >100 0.026 Histone H1 subtype e
(Hle); chromatin structure; ubiquitous; L04141 >100 >100
<0.001 Histone H1; chromatin structure; ubiquitous; J03482 109
70 <0.001 Histone H1b; chromatin structure; ubiquitous; ET62262
>100 >100 0.024 Histone H2A; chromatin structure; ubiquitous;
X16495 4 3 0.030 Histone H2B; chromatin structure; ubiquitous;
ET62908 7 8 0.006 Histone H3; 1-D (H3-D) and histone H4-D (H4-D);
chromatin structure; ubiquitous; U62672. >100 >100 <0.001
Histone H3.2-F (H3-F), histone H2a.1-F (H2a-F), histone H2b-F
(H2b-F); chromatin structure; ubiquitous; U62669 4 4 0.034 HpaH
tiny fragments locus 9c (Htf9c); structural similarity with yeast
mucleic acid-modifying enzymes; activated at the G1/S transition,
and S phase; down-regulated in growth arrested cells; liver
(ubiquitous); X56044 *Fold of control
Example 18
CR Stimulates the Expression of Genes Enhancing Genetic Stability
and Apoptosis
The accumulation of genetic damage has been postulated to be a
cause of aging. Without being limited to any specific mechanism, CR
has been postulated to either reduce the rate of accumulation of
genetic damage, or to enhance its rate of repair. Both long and
short term CR enhanced the expression of numerous genes associated
with DNA repair (Table 5). These genes included Xpa, which is
involved in nucleotide excision DNA repair; and the Brca2 gene,
which is important in DNA double-strand break repair and DNA
damage-induced cell-cycle checkpoint activation.
A theory of aging closely related to the DNA damage theory proposes
that the reduction of apoptosis with age, and its restoration with
CR plays and important role in aging. This hypothesis purposes that
the accumulation of damaged cells with age contributes to aging
itself and to the onset of the diseases of aging. Long and short
term CR greatly enhanced the expression of a number of genes which
choreograph the progression of a cell through the apoptotic pathway
(Table 5). These genes included Casp1, Casp3, Bax, and Bcl2 which
code for key components of the apoptotic pathway.
TABLE-US-00005 TABLE 5 Genetic stability and apoptosis LTCR* STCR*
P GENE DNA Replication/Repair 9 8 <0.001 Antigenic determinant
of rec-A protein (Kia); Kia17; DNA- binding nuclear protein
upregulated in response to UV and ionizing radiation; accomulated
in the nucleus of proliferating cells; ubiquitious; X58472 >100
>100 0.001 Breast cancer 2 (brc32); DNA double-strand break
repair and DNA damage-induced cell-cycle checkpoint activation;
ubiquitous; ET62746 3 3 0.029 DNA primase p49 subunit (Prim); DNA
replication; liver (ubiquitdus); X74351 6 5 0.009 Mut L. homologue
1 (E. Coli(M1h1); treanscription-coupled nucleotide excision
repair; cell cycle checkpoint control; ubiquitous; ET63479 3 3
0.025 Xeroderina pigmentosum complementation group A (Xpa);
nucleotide excisine DNA repair; ubiquitous; X7435 Apoptosis >100
>100 0.001 B-cell leukemia/lymphoma 2 (Bcl2); suppresses
apoptosis by controlling mitochondrial membrane permeability; many
cells and tissues; L31532 >100 >100 <0.001 Bcl2-associated
X protein (Bax); pro-apoptotic activity; can form channels in lipid
membranes; many cells and tissues; L22472 5 4 0.033 Caspase 1
(casp1); cysteiac protease mediator of apoptosis; ubiquitous;
U04269 2 3 0.000 Caspase 3 (Casp3); cysteine protease mediator of
apoptosis; ubiquitous; ET63241 3 4 0.005 Cyclin G (Ccng); augments
apoptosis; target gene of P53; liver, elsewhere; Z37110 >100
>100 <0.001 Fused toca (Fta); a gene related to
ubiquitin-conjugating enzymes; suggested role in apoptosis during
development; expression distribution poorly defined; X71978 22 21
<0.001 P53 specific ubiquitin ligase 2 (Mdm2); promotes
ubiquitination and proteaesome degradation of p53; inactivation by
stress causes cell cycle arrest and apoptosis; liver, elsewhere;
X58876 >100 >100 <0.001 RNA-dependent EIF-2 alpha kinase;
double-stranded RNA- dependent protein kinase; key mediator of
antiviral effects of interferon; ubiquitous; ET61211 >100
>100 0.009 Tumor necrosis factor (Tnf); Proapoptotic factor in
liver; X02611 *Fold of control
Example 19
CR Activation of Genes of the Enteric Nervous System
The liver is a highly innervated organ. This innervation includes
elements of the enteric nervous system, as well as sympathetic
innervation in the small arteries of the hepatic mesentery. This
nervous innervation is essential to the activity of the liver.
Nervous innervation has a role in the release of glucose by
hepatocytes in response to insulin. As shown in Table 6, long and
short term CR activated the expression of a large number of genes
associated with the membrane receptor signaling, including membrane
receptors for protein and small molecule neurotransmitters, and for
cell growth and maintenance factors. CR induced the expression of
genes for both phosphatases and kinases involved in signaling by
these receptors. CR also induced the expression of four neuronal
tissue specific transcription factors (Table 6).
CR enhanced the ability of liver neurons to transduce and respond
to nervous system signaling. Eight genes for membrane channels were
induced, including genes for sodium, potassium, and water channels
(Table 6). Also induced were a number of integral membrane proteins
such as proteolipid protein and cadherin 8, as well as the products
of 5 genes for molecular motors which are probably involved in
neural plasticity and remodeling. These proteins included 4 members
of the dynein, axon, heavy chain family. Our results are consistent
with the idea that CR increases the remodeling and activity of
hepatic nerves after only 4 weeks.
TABLE-US-00006 TABLE 6 Neuromal Cell Specific Genes LTCR* STCR* P
GENE Signal Transduction 19 18 0.001 5-hydroxytryptamine
(serotonin) receptor 1E beta (Htrieb); G- protein-coupled receptor;
CNS; Z14224 >100 >100 <0.001 Activia A receptor, type 1B
(Acvt1b); limb development; embryo brain, dorsal rool ganglin,
spinal cord, vibrisae, elsewhere; Z31663 5 5 0.005 Ankynin 3
(Ank3); implicated in Na(+) channel clustering and activity;
neurosal axons, wide distribution; ET62740 3 3 0.022 Bone
morphogenetic protein receptor, type 1B (Bmpr1b); activin
receptor-like kinase-6; serine-threonine kinase; CNS, muscle, blood
vessels, others; Z23143 5 6 0.004 Discs, large homologue 1
(Drosophila) (Digh1); role in localization and function of
glutamate receptors and K(+) channels; neurons, epithelial cells;
ET61665 67 70 0.001 Eph receptor A7 (Epo7); developmental kinase 1;
member of receptor tyrosine kinase family; brain, testes and
spleen; X79082 >100 >100 0.001 Fibroblast growth factor 9
(Fgf9); autocrine/paracrine growth factor; embryonic acural cell
differentiation; adult and developing acuronal cells, epithelial
cells, others; U33535 14 15 <0.001 Fibroblast growth factor
homologous factor 1 (Fgf1); nervous system development and
function; highest in brain and skeletal muscle; U66201 17 19 0.003
G-protein-coupled receptor, family C, group 1, member H (Gprc1b);
glutamate receptor, metabotropic 8, CNS, glial cells, retina,
olfactory bulb, stellate/basket cells; U17152 28 29 <0.001
Gamma-aminobutyric acid (GABA-A) receptor, subunit beta 3 (Gabrb3);
links binding of GABA to inhibitory chloride flux; CNS; U14420 12
11 <0.001 Glutamic receptor, iosotropic, kainate 1 (Grik1); CNS;
X66118 >100 >100 0.007 Gosadotropia releasing hormone
recepotr (Garbr); G-protein- coupled receptor; activates MAPK
cascases; brain, anterior pituitary, reproductive organs; L28756 4
3 0.018 H6 homeo box 2 (hmx2); specification of neuronal cells;
developing CNS; S80989 >100 >100 0.001 Histamine receptor H1
(Hrb1); coupled to phosphoisositide turnover-calcium mobilization
signaling; regulates IGF-I expression, cell proliferation, several
function; neurons, liver, elsewhere; D50095 64 73 <0.001
Neuropeptide Y receptor Y6 (Npy6r); regulates energy balance
through its oranigenic, antithermogenic, and insulin secretagogue
actions, neurons, vascular smooth muscle cells; U58367 >100
>100 <0.001 Paired-Ig-like receptor A1 (Pira1); activating
receptor on B lymphocytes, deadritic and myeloid-linage cells;
ET62839 4 4 0.003 Preproglucagon (Ocg); glucagon-like peptides I
and II; neuropeptide; CNS, pancreatic alpha cells, ileum, Z46845
>100 >100 0.013 Protein kinase, cGMP-dependent, type II
(Prkg2); signal transductions; brain, kidney, small intestine,
colon; L12460 >100 >100 0.001 Protein tyrosine phosphatase,
receptor type, M (Ptprm); expressed in capillaries in developing
neural tissue, lung; X58287 >100 >100 <0.001 Reluxin
precursor (Rln); insulin gene family; remodeling of collagen;
brain, uterus, prostate, pancrease and kidney; Z27088 >100
>100 <0.001 Ryanodine receptor 3 (Ryr3); intracellular Ca2+
channels; neurons, skeletal and smooth muscle; ET61090 Neuronal
Tissue Specific Transcription Factors >100 >100 <0.001
Atonal homologue 5 (Drosophila) (Aloh 5); neurogeain 3;
transcription factor; neuroD-related bHLH protein; CNS; U76208 19
18 0.003 Embigin (Emb); DNA-binding transcription factor; class Vt
POU domain; CNS; D13801 >100 >100 0.026 Paired box gene 6
(Pax6); transcription factor; development of CNS, eye; X63963
>100 >100 <0.001 Zinc finger protein 2 (Zfp2); Mkr-2;
differentiation and/or maintenance of neurons; central and
peripheral neurons; Y00850 Channels 4 3 0.007 Aquaporia 4 (Aqp4);
allows water and small solutes through plasma membrane; brain and
other tissues; U48397 5 6 0.004 Discs, large homologue 1
(Drosophila) (Dlgh1); localization and function of glutamate
receptors and K(+) channels; neural sysapacs; ET61665 22 25 0.001
Gap junction membrane channel protein beta 6 (Gjb6); connexin 30;
forms transmembranous gap junction channels between adjacent cells;
brain, skin; ET63385 11 11 0.001 K+ channel beta-subunit; ion
channel; brain and kidney; X97281 14 16 0.001 Potassium
inwardly-rectifying channel, subfamily J, member 6 (Kcnj6);
neurons; ET61642 8 8 0.005 Potassium, voltage gated channel, shaker
related subfamily, member 2 (Kena2); T cells, myelinating Schwann
cells; M30440 27 28 <0.001 Sodium channel 27; brain; L22340 11
11 <0.001 Sodium channel, type X, alpha polypeptide (Scn10a);
brain unmyelinated axons; Y09108 Molecular Motors 2 2 0.004 Dilute
lethal-20J; Class-V myosin; vesicular membrane trafficking;
transport of endoplasmic reticulum vesicles in neurons; M33467 7 8
0.001 Dynein, axon, heavy chain 1 (Dashe1)k dyneins are molecular
motors that drive the beating of cilis and flagella; brain,
trachea, testis; ET63395 >100 >100 <0.001 Dynein, axon,
heavy chain 3 (Dnahc3); brain, trachea, testis; ET63399 5 6 0.013
Dynein, axon, heavy chain 6 (Dnahc6); brain, trachea, testis;
ET63402 4 5 0.002 Dynein, axon, heavy chain 9 (Dnahc9); brain,
trachea, testis; ET63405 Cell Surface and Secreted Proteins >100
>100 0.001 Cadherin 9 (Cdh8); adhesion molecule; subdivisions of
the early CNS and thymus; ET63017 37 36 <0.001 Glutamic acid
decarboxylase, 67 kD; responsible for gamma- aminobutyric acid
synthesis; brain, islets; Y12257 2 2 0.011 Glypius 4 (Gpc4); cell
surface heparis sulfate proteoglycan; role in regulation of neural
cell transition from proliferation to differentiation; neurons;
X83577 19 20 <0.001 Neurexophilin 2 (Nxph2); neuronal
glycoprotein; binds to alpha- neurexine; brain; U56650 13 13
<0.001 Neurotrophin 3 (Ntf3); secreted protein; resistenance and
plasticity of neurons; enteric neurons, others; X53257 43 41 0.001
Proteolipid protein (Plp), main integral protein of myelin; CNS;
X07215 4 4 0.043 Sema domain, immunglobulin domain (lg), short
basic domain, secreted, (serinaphonin) 3E (Sema3e); glycoprotein
involved in embryonic development; developing neural tubes, lungs,
skeletal elements; ET63410 >100 >100 <0.001 Sema domain,
seven thrombospondin repeats (type 1 and type 1- like) (Sema5a);
axonal guidance; early embryogenesis; X97817 Other Genes 6 7 0.015
Disabled homolog 1 (Drosophila) (Dah1); adaptor molecule in neural
development; neuronal and hematopoietic cells; ET63156 23 24
<0.001 Galanin (Gal); neuropeptide; enhances hepatic glucose
production: hepatic nerves and elsewhere; L38580 3 4 0.006 Netrin 1
(Nta1); axon outgrowth-promoting protein; guidance molecule; guides
growing axons in development; CNS; U65418 127 129 <0.001
Nucleosome assembly protein 1-like 2 (Nap12); Bpx; brain; X92352
>100 >100 <0.001 Proteasecome 3 (Ptne3); Ki antigen; cell
proliferation; enhances generation of class I binding peptides;
liver, neurons, elsewhere; U60330 58 58 <0.001
UDP-glucoronosyltransferase 8 (Ugt8); cerebroside and sulfatide
biosynthesis; CNS and peripheral nervous system; X92122 *Fold of
control
Example 20
Induction of Other Liver Specific Genes by CR
Of the approximately 200 genes reported to be expressed either
liver specifically or ubiquitously, 13 code for cytokines or growth
factors; 12 for cell surface receptors; 21 for signal transduction,
cell cycle or cell growth related proteins; 4 for nuclear
receptors, 20 for transcription factors; 6 for translation,
splicing, or RNA processing related factors; and 9 for chromatin
structure related genes (Table 4). The overall pattern of genes
induced in this group of genes suggests that CR stimulates the
growth, remodeling and responsiveness of liver cells to signaling
systems. These results are consistent with those found for neuronal
genes, discussed above.
Both long and short term CR induced the expression of the cell
growth factors Tgfb2, Fgf1, Fgf2, Fgf3, Fgf7, Fgf9, Figf, Inhbb,
Inhbe, and 3 interferon-related genes. Likewise, a large number of
genes coding for cell cycle regulation were induced by CR. These
genes included Ptpn16, Nck1, Plcg1, Map3k1, Mapk1, Madb5, Wnt10b ,
Ab1, and others. Without being limited to any specific mechanism,
the hypothesis that CR induces cell remodeling and growth of liver
cells is further supported by the observation that both long and
short term CR very strongly induced the expression of 7 histone
genes. In 6 cases, these mRNA levels were induced from
undetectable, or nearly undetectable levels. Two other genes which
appear to be associated with chromatin structural modification were
also strongly induced by CR (Htf9c and homologous to Drosphila Hp1;
Table 4). Further evidence that CR enhance cell division and
remodeling is the up regulation of the mRNA for the transferrin
receptor, which mediates cellular iron uptake, a process essential
for cell growth and division.
Three receptor mRNAs associated with energy balance were induced by
CR. Two of these were for neuropeptide Y receptor Y6 (Table 6) and
pancreatic polypeptide receptor 1, and one was for the leptin
receptor (Table 4).
Example 21
Global Hepatic Gene Expression Profile
We have tested the hypotheses that CR produces similar effects on
gene expression early and late in life by examining the effects of
aging and caloric intake on the expression of approximately 12,000
genes and ESTs in the liver of old (27-month-old) and young
(7-month-old), control and CR mice, using .[.GeneChip.].
.Iadd.oligonucleotide based high-density .Iaddend.microarrays. We
found that CR produced a massive reprogramming of gene expression
early and late in life. The patterns of expression induced by CR in
young and old mice were highly homologous. Comparison of gene
expression in the groups of mice indicated that CR only prevented
age-related changes in the expression of a few genes. Examination
of the genes involved does not support the idea that they have a
principle role in the age-retarding effects of CR. Together, the
results do not support the idea that CR acts principally to prevent
deleterious age-related changes in gene expression. Instead, CR
induces a highly-homologous, major reprogramming of gene expression
in animals of all ages.
The average global hepatic gene expression profile for each group
of mice, displayed using GeneSpring 3.0 (Silicon Genetics, San
Carlos, Calif), is shown in FIG. 8. The GeneSpring experiment tree
algorithm clustered gene expression in the young and old CR mice
together, and separately clustered expression in the young and old
control mice together. These results indicate that that the effects
of the CR diet on gene expression was significantly greater than
the effect of age. Further, these data indicate that CR produced
homologous effects on gene expression in the young and old
mice.
TABLE-US-00007 TABLE 7 Pairwise comparisons of the global gene
expression correlation coefficients for each possible pair of mice.
Young- Old-CR Old-Control Young-CR Control Old-CR 0.53 .+-. 0.02*
-0.09 .+-. 0.02 0.41 .+-. 0.04 -0.10 .+-. 0.03 Old-Control 0.28
.+-. 0.06 -0.11 .+-. 0.03 0.23 .+-. 0.02 Young-CR 0.41 .+-. 0.01
-0.06 .+-. 0.02 Young- 0.22 .+-. 0.02 Control *All values average
values, .+-. SD are calculated as the Log (1+ the mRNA level)
These conclusions are supported by comparison of the correlation
coefficients calculated from the expression data for each possible
pair of mice in the study (Table 7). Because the mice were
genetically identical, infra-group values provide a measure of the
maximum correlations attainable. Inter-group values measure the
similarity between groups. Inter-group comparisons between young
and old CR and control mice indicated that gene expression in all
CR mice was highly homologous, regardless of the age of the
animals. Likewise, regardless of age, the intra-group expression
patterns of the control mice were highly homologous. In contrast,
there was no intra-group correlation between mice in different
dietary groups, regardless of age. These data indicate that the
number of calories consumed, but not age was the major influence in
determining the global patterns of gene expression in these mice.
This novel result is fuirther supported by the analysis described
below.
The patterns of gene expression in the mice were further evaluated
by successive application of the Venn Diagram Function of
GeneSpring 3.0, one-way ANOVA, and Fisher's test (P<0.05) to the
levels of expression of each gene and expressed sequence tag (EST)
in the 4 groups of mice. These operations sorted the genes and ESTs
into one of 9 possible categories (Tables 8A and B). Only
statistically significant differences of 2-fold or more are shown.
The expression of most genes and ESTs were not affected by either
CR (-80% unchanged) or aging (95% unchanged). Of the genes and ESTs
which did changed expression among the groups, 5-times as many
genes and ESTs changed expression level in response to CR (2456) as
changed in response to age (561). Of the genes and ESTs responsive
to CR, most (40%) were upregulated in both young and old mice. Two
other groups of genes and ESTs were upregulated either in old mice
only (28% of the genes that changed expression), or in young mice
only (19% of the genes that changed expression). An even smaller
number of genes and ESTs were down regulated by the CR diet in
young or old mice (13% of the genes that changed expression).
TABLE-US-00008 TABLE 8 The effects of age and diet on gene
expression a. Diet Effect Young Old (CR/Control)* (CR/Control)*
Up** Unchanged Down** Total Up** 975 (8.1%**) 473 (3.9%) 0 1448
Unchanged 685 (5.7%) 9587 172 (1.4%) (79.6%) Down** 0 105 (0.9%) 46
(0.4%) 151 Total 1660 218 b. Age Effect Control CR (Old/Young)*
(Old/Young)* Up** Unchanged Down** Total Up** 6 (0.05%***) 136 2
(0%) 144 (1.1%) Unchanged 186 (1.5%) 11482 (95%) 112 (0.9%) Down**
1 (0%) 113 6 (0.4%) 119 (0.9%) Total 193 119
Example 22
208 Genes Greater in CR in Both Young and Old
Three novel conclusions can be drawn from these data. First, CR
induced a substantial age-independent reprogramming of gene
expression. A large number of genes and ESTs (975) were up
regulated by CR in both young and old mice (Table 8A). In this
group, 208 were known genes (See Appendix G) All of these known
genes were among the group of 340 genes induced in 30 month old
mice by both long-term CR (LT-CR; life-long) and short-term CR
(ST-CR; only 4 weeks of CR). This highly reproducible,
age-independent, responsiveness to CR suggests to us that these
genes and ESTs are likely to mediate the life- and health-span
extending effects of CR. At a minimum, the dietary responsiveness
of these genes can be used as a gauge of the effectiveness of other
treatments in reproducing the effects of CR on global patterns of
gene expression. Further, because 90% of the genes and ESTs induced
by lifelong CR (which includes the age-independent and
age-dependent genes and ESTs) can be induced after only 4 weeks of
CR, the vast majority of the genetic reprogramming induced by CR
can be reproduced rapidly.
Example 23
142 Genes Up in Young CR But Not in Old CR
There is a second novel conclusion which can be drawn from the
results in Table 8A . CR produced some "age-dependent"
reprogramming of gene expression in both young and old mice. Of the
473 genes and ESTs induced by CR only in young mice, 142 are known
genes (Appendix H) These results indicate that this subset of genes
was also CR responsive in old mice, but not to sufficient levels
that they were distinguished statistically from control expression
levels in these studies. Thus, Table 8A overestimates the number of
young-specific induced genes by approximately 25%. Of the
young-specific genes, 8% are involved in transcriptional
regulation; 5% are growth factors, cytokines or hormones; 18% are
involved in signal transduction or cell cycle regulation; 14% are
involved in embryogenesis and development; 14% are involved in
cellular adhesion, or are components of the extracellular matrix or
membrane; 7% are channels or ion pumps; 3% are involved in
extracellular transport or secretion; 3% are involved in
metabolism; 3% in DNA replication, repair or apoptosis; 3% in
chromatin structure; 9% in immune function or in the primary
response; and 15% are involved in other functions.
Example 24
200 Known Genes Greater in Old CR But Not in Young CR
Or the 685 genes and ESTs induced by CR in old mice, the identity
of 200 are known (Table 8A); (Appendix I). Of these, 122 (61%)
previously were shown to be induced by ST-CR in old mice. Thus, the
majority are rapidly responsive to CR. Of the remaining 78 genes,
approximately 12% are transcriptional regulators; 8% are growth
factor, cytokines or hormones; 13% are involved in signal
transduction or cell cycle regulation; 11% are involved in
embryogenesis and development; 10% are involved in cellular
adhesion, or are components of the extracellular matrix or
membrane; 4% are channels or ion pumps; 4% are involved in
extracellular transport or secretion; 3% are involved in
metabolism; 3% in DNA replication, repair or apoptosis; 2% in
chromatin structure; 3% in immune function or in the primary
response; 2% in translation, splicing or RNA processing; 2% are
cell surface receptors; and 23% are involved in other
functions.
The proportion of genes involved in each functional category above
are remarkably similar. Further, many of the genes induced by CR in
young mice were members of similar gene families or were
structurally or functionally related to genes induced only in old
mice. These similarities suggest that CR has highly homologous
age-specific effects. It is less likely that the relative
proportion of genes falling into each category, and the identity of
these genes is an artifact of the probes present on the chip.
Firstly, all of the results are statistically significant. Second,
the genomic profiles produced in several drug studies were
strikingly different from those found here as to the identity of
the genes affected, and their functional categories (data not
shown). Together, these results indicate that CR has a robust,
pervasive, and highly homologous effect in both young and old mice.
It induced the expression of a substantial group of genes involved
in a wide variety of cellular functions.
A commonly expressed view in the literature of CR and aging assumes
tacitly or explicitly that CR acts by preventing deleterious,
age-related changes in gene expression. This view is shown
schematically in FIG. 9. This hypothesis assumes that prevention of
age related changes in gene expression underlies the health- and
life-span extending effects of CR. During aging, some genes become
over expressed or under-expressed relative to their levels in young
animals (lower and upper lines, FIG. 9). Some of these deviations
are assumed to be deleterious. Preferably, no changes would change
with time, and aging would either not occur or occur more slowly
(center line, FIG. 9). In this view, CR should wholly or partially
return over- or under-expressed genes to their youthful levels
(arrows, FIG. 9). Although the reasoning is circular, some have
said that if CR changes the expression of a gene toward the center
line in the figure, it restored youthful levels of expression. We
have analyzed the results of the studies reported here to evaluate
this hypothesis further.
Of the approximately 12,000 genes and ESTs examined, aging of
control mice increased the expression of 257 genes and ESTs, and
decreased expression of 191 genes and ESTs (FIG. 9). Long-term CR
wholly or partially, reversed or prevented 55 of the increases and
70 of the decreases. Short-term CR reversed 45 of the increases and
59 of the decreases in gene expression. Long-term and short-term CR
both acted to reverse or prevent 23 of the increases and 41 of the
decreases. Thus, long-term CR actually prevented the increased
expression of only 32 genes and ESTs and the decreased expression
of only 29 genes and ESTs. It is likely that the number of ESTs in
each class overestimates the number of authentic genes in each
category. First, the genes and ESTs which responded to CR in only 4
weeks are likely a subset of the genes and ESTs which respond
acutely to CR. We have not yet examined longer times on the domain
of genes responsive to acute CR. Some genes may be "slow changers"
in response to acute CR. Second, we have found that many of the
known genes present on these chips are redundant (e.g., multiple
immunoglobulin genes of each class and T cell receptor genes,
cloned chromosome break-points representing parts of two genes,
uncharacterized chromosome regions, uninvestigated, unpublished
cDNA sequences, etc.). For example, of the 23 genes and ESTs
reduced to baseline expression levels only by LT-CR, 12 were known
genes (Table 9). Of the 27 genes and ESTs which were decreased in
expression by age and returned to baseline expression only by
LT-CR, only 13 were from known genes (Table 10).
Of the 12 genes prevented from increasing with age by CR, few are
involved in signal transduction. Rather, 6 are involved in immune
system function, particularly in macrophage differentiation,
proliferation, apoptosis, and activity. Of these,
platelet-activating factor acetylhydrolase activity reduces plasma
platelet activating factor mRNA levels. Platelet activating factor
is a potent pro-inflammatory autacoid with diverse physiological
and pathological actions. It does not seem likely that the return
of these genes to baseline expression levels is due to a general
reduction in inflammation, stress, or immune activity. In a
previous study, we found that 61 immune system genes, including 6
primary response genes, and an additional 9 apoptotic genes were up
regulated by both LT- and ST-CR in the liver of mice. Similar
considerations apply to the other 6 genes in this group, and to the
genes prevented from decreasing with age (Table 10). One can
speculate about why reduction in the expression of the relatively
few immune system specific, acute phase response genes and other
genes listed in Table 9, or enhanced expression of the 13 immune
system, and neuron or liver specific genes in Table 10 might be
important in reducing the rate of aging. However, with few
exceptions, very similar genes, and in some cases closely related
family members of the genes in these lists are present in the group
of 340 known genes induced by both LT- and ST-CR. Thus, it seems
intuitively and statistically much more likely that the massive
reprogramming of gene expression induced by CR (Tables 9 and 10) is
responsible for the increase in life- and health-span induced by
CR. The genes prevented from increasing and decreasing with age
(Tables 9 and 10) seem much more likely to be the result, rather
than the cause of these effects.
In summary, the studies presented here show that a major effect of
CR is to massively (more than 10% of the genes and ESTs
investigated) reprogram gene expression to a new pattern associated
with slower aging and delayed onset of age-related diseases. This
reprogramming includes age-independent induction of a relatively
large group of genes and ESTs, as well as induction of smaller
groups of genes age-dependently. Further, we found that age-related
changes in gene expression are relatively rare. Even rarer are
instances in which life-long CR prevents these changes. The rarity
of such genes, and their identity suggest to as that they do not
play a major role in the physiological effects of CR. The large and
rapid response induced by CR on total liver gene expression
suggests that major, systemic regulators of gene expression are
altered by CR. Study of the regulation of a number of these genes
should yield the identity of the regulators, and reveal how they
are influenced by CR.
TABLE-US-00009 TABLE 9 mRNAs increased by age and returned to
control levels by LT-CB GenBank Phenotype Immune System AF018268
Apoptosis inhibitory 6 (Api6); a member of macrophage scavenger
receptor cysteine- rich domain superfamily; inhibits apoptosis of a
variety of cell types; secreted specifically by macrophages M13018
Cysteine rich intestinal protein (Crip); double zinc finger
protein; expression changes with acute liver injury (cellular
change); may function in cell proliferation, differentiation or
turnover; high expression in immune cells, low in liver J04596 GRO1
oncogene (Gro1); encodes a cytokine; mediator of inflammatory and
immune responses; also called melanoma growth-stimulatory activity;
cell cycle regulator; platelets L20315 Macrophage expressed gene 1
(Mpeg1 or Mpg-1); increased when murine fetal liver hematopoietic
progenitor cells induced to differentiate into macrophages; high
levels in macrophages, moderate levels in certain myelomonocytic
cell lines U34277 Phospholipase A2 group VII, platelet-activating
factor acetylhydrolase, plasma (Pln2g7); secreted phopholipase A1
which modifies the pre-inflammatory platelet- activating factor
(PAF) to yield the biologically inactive lyo-PAF; regulates
baseline circulating PAF levels and may be critical in resolving
inflammation; high PAF is a predictor of heart disease; liver
macrophages L27990 Sjogren syndrome antigen A1 (Seal); Ho52; stress
response gene; ribonucleoprotein; macrophages Ubiquitous D86729
Heterogeneous nuclear ribonucleoprotein A1 (Hnrpa1);
ribonucleoprotein, RNA processing; early down-regulation of this
gene contributes to the cytotoxicity of the topoisomerase
inhibitors that induce DNA cleavage; ubiquitous U50850
Retinoblastoma-like 2 (Rbl2); p130; transcriptional cell cycle
repression through G1 phase (controls cyclia A, cdc 25G and cdc2
genes); tumor suppressor gene; expressed independently of
retinoblastoma gene; expressed in embryo and ubiquitously in adult
U34042 Tolloid-like (Tl1), an alternatively spliced product of the
bone morphogenic protein-1 gene; metalloprotease purified from
extracts capable of inducing ectopic bone formation; ubiquitous
Liver Specific U60438 Serum amyloid A protein isoform 2 (Saa2);
encodes an acute-phase reactant serum protein; liver Not Reported
in Liver M27501 Protamine 2 (Prm2); compacting chromatin; expressed
in posimiotic male germ cells during late stages of spermatogenesis
U52433 Tubby (Tub); mutation is the tub gene causes maturity-onset
obesity; adipocyte fat storage increased by 5-6 fold, insulin
resistance; mutant mice have retinal and cochlear degeneration;
gene function unknown; brain, hypothalamus, cochlea, retina
TABLE-US-00010 TABLE 10 mRNAs decreased by age and returned to
control levels by LT-CB GenBank Phenotype Immune System M30903 B
lymphocyte kinase (Blk); sac-family protein tyrosine kinase; plays
important role in B-cell development/activities and immune
responses; B-lineage cells U43384 Cytochrome b-245, beta
polypeptide (Cybb, cytochrome b558); integral component of the
microbicidal oxidase electron transport chain of phagocytic cells,
respiratory burst oxidase; phagocytes U10871 Mitogen activated
protein kinase 14 (Mapk14); signal transduction, stimulate
phosphorytation of transcription factors; major upstream activator
of MAPKAP kinas 2; hematopoietic stem cells Z22649
Myeloproliferative leukemia virus oncogene (Mp1); Member of
hematopoietic cytokine receptor family, cell cycle regulator,
induces proliferation and differentiation of hematopoietic cell
lines; hematopoietic precursor cells, platelets and megakaryocytes
Y07521 Potassium voltage gated channel, Show-related subfamily
member 1 (Kene1) potassium channels with properties of delayed
rectifiers; nervous system, skeletal system, T lymphocytes U87456
Flavin-containing monooxygenase 1 (Fmo1); xenobiotic metabolism;
highly expressed in liver, lung, kidney, lower expressed in heart,
spleen, testis, brain U40189 Pancreatic polypeptide receptor 1
(Ppyr1), neuropeptide Y receptor, peptide Y receptor;
G-protein-coupled receptor; liver, gastrointestinal tract,
prostate, aeurosa endocrine cells Neuron Specific U16297 Cytochrome
b-561 (Cyb561); electron transfer protein unique to aeuroendocrine
secretory vesicles; vectoral transmembrane electron transport;
brain D50032 Trans-golgi network protein 2 (Tiga2); integral
membrane protein localized to the Trans-Golgi network; involved in
the budding of exocytic transport vesicles; brain neurons Liver
Specific/Ubiquitous D82019 Basigin (Bag), CD147, neurothelin;
membrane glycoprotein, immunoglobulin superfamily, homology to
MIICs, acts as an adhesion molecule or a receptor, neural network
formation and tumor progression; embryo, liver and other organs
U38990 Glucokinase (Gk), key glycolytic enzyme; liver U50631
Heat-responsive protein 12 (Hrp12); heat-responsive, phosphorylated
protein sequence simularity to Hbp20; liver, kidney U39818 Tuberous
sclerosis 2 (Tsc2); mutationally inactivated in some families with
tuberous sclerosis; encodes a large, membrane-associated GTPase
activating protein (GAP tuberlin); may have a key role in the
regulation of cellular growth; ubiquitous
Gene Expression in STZ-diabetic Mice
Streptozotocin (STZ) induces diabetes. Mice receiving three
treatments with STZ were diabetic for about 4 weeks. Diabetes
reduces insulin levels to almost zero. CR has a similar effect in
that it lowers insulin levels, although not as low as in
STZ-treated animals. Also, while CR lengthens life span, STZ has
the opposite effect and shortens life span.
FIG. 10 shows pairwise comparison of global gene expression
correlation coefficients for each possible mouse pair. The results
indicate that hepatic gene expression is very different between
young CR, young control and STZ-diabetic mice. FIG. 11 presents a
visual profile which shows that the pattern of gene expression in
the three groups is dissimilar. In conclusion, lowering insulin in
the pathological way found in serious diabetes is insufficient to
produce the gene expression profile or the life-span effects
observed with CR.
Example 26
Gene Expression in Aminoguanidine Treated Mice
Aminoguanidine is believed to retard aging by preventing
cross-linking of protein initiated by the aldehyde form of glucose.
However, mice fed aminoguanidine exhibited little or no effect on
life span. However, a large effect on gene expression was observed
(FIG. 12). Gene expression for aminoguanidine-treated mice did not
correlate with either old CR or old control. A visual
representation of this finding is shown in FIG. 13. In conclusion,
although aminoguanidine has little effect on aging in mice, major
differences in gene expression are observed. These effects are not
like those of CR, and this is consistent with the absence of a
strong effect on the life-span of mice.
Example 27
To determine whether certain interventions mimic calorie
restriction in mice, the following groups of mice are prepared.
Group 1: Controls
Group 2: Troglitazone (synthetic proposed calorie restriction
mimetic drug that lowers insulin levels in rats and mice, lowers
blood pressure and triglycerides, inhibits free radicals, increases
mitochondrial mass, and doesn't seem to change food intake in
rodents): treatment starts at 10 months
Group 3: IGF-1 (natural proposed calorie restriction mimetic
hormone that lowers both insulin and glucose levels and which may
be directly involved in the basic mechanisms of aging; has
rejuvenating effects on immune, muscular, and other systems):
treatment starts at 12 months
Group 4: ALT-711 (or other AGE breaking agent: proposed calorie
restriction mimetic that acts by reversing the effects of elevated
glucose levels as they occur or after they occur, rather than by
reducing glucose levels): treatment starts at 18 months.
Animals in all groups will receive the same, known amount of food
throughout the study.
Troglitazone and IGF-1 doses will be chosen to set glucose and
insulin levels in the range for young or preferably
calorie-restricted animals. Glucose and insulin will be measured
but not controlled in the control and ALT-711 groups. Troglitazone
will be supplied at a dose of .about.0.2% of the diet (standard for
troglitazone studies for other purposes). Similarly, ALT-711 will
be incorporated into the diet. A low (two-toxic) level of ALT-711
is used that will remain constant over time.
It is assumed that IGF-1 will be supplied by injection (3 times per
week, minimum) unless a continuous delivery method can be arranged.
The preferred dosage method is implantation of non-dividing
IGF-1-secreting cells, to attain steady IGF-1 levels, and if
possible, this will be done. If this is not possible, IGF-1 will be
obtained as a gift from Genentech or another manufacturer. Other
possible alternatives to injection are: osmotic minipump; injection
of IGF-1 into subcutaneous slow-release reservoirs; infusion by
means of minipumps used by Celtrix; use of skin patches that allow
slow-release to the body.
There will be 60 animals in each longevity-testing group (LTG).
Each LTG will be accompanied by another set of, on average, 40
similarly-treated animals, which will be set aside for sacrifice to
permit biochemical assays and histological documentation of the
condition of the animals at fixed ages (sacrifice group, SG). In
the case of the IGF-1 and troglitazone groups, some animals will be
earmarked for pilot dose-finding experiments in a manner that will
allow the average SG size to remain at 40, as described below. The
groups earmarked for dose-verification will be referred to as the
pilot dose groups, or PDGs.
For troglitazone, about a 2-month supply of each of three
troglitazone diets (containing 0.1%, 0.2%, or 0.3% troglitazone)
will be initially ordered. The main 0.2% troglitazone dose will be
tested on a small pilot mouse population before committing the
troglitazone group proper to this dose. If 0.2% troglitazone is not
found to yield the expected changes in circulating insulin after 2
weeks on the 0.2% troglitazone, the diet will be changed to the
more appropriate dose diet at that time and verified on a second
small pilot mouse population.
Similarly, some animals will be used for IGP-1 injection pilot
experiments to determine the proper starting dose.
At age 12 months: Sacrifice 3 animals/SG to obtain common baseline
group of 12 animals to be compared to all subsequent results. This
is the middle-aged universal control group. All subsequent data can
be compared to the results for this pooled group.
At age 12.5 months: Begin the IGF-1 PDG with 7 mice given the best
estimated dose of IGF-1. Sacrifice two weeks later for
determination of insulin and glucose levels. Begin a
verification/second trial dose of IGF-1 at 13 months, 1 week of
ago, and sacrifice this second PDG at 13 months, 3 weeks of age.
Assuming the assays for insulin and glucose can be completed in 1
week, this regimen will allow the final dose for the LTG to be
determined prior to age 14 months. Similarly, at 12.5 months, place
7 mice on the 0.2% troglitazone diet. Two weeks later, sacrifice
and assay for insulin and glucose. Begin adjusted-dose or
verification dose group at 13 months, 1 week and sacrifice after
two weeks.
At age 14 months: Begin troglitazone and IGF-1 at the
experimentally-determined or estimated optimal doses for each.
At age 15 months: Sacrifice six animals from the IGF-1 and
troglitazone SGs for determinations of glucose, insulin, and all
other endpoints involved in the study. If necessary, adjust the
IGF-1 dose again (both in the LTG and the untapped portion of the
IGF-1 SG) and/or order diet with a modified troglitazone content.
Sacrifice three animals each from the SGs for the controls and the
ALT-11 groups and pool to create a common group of six animals for
comparison to the IGF-1 and troglitazone groups.
At age 18 months: same as at 15 months, but use 7 mice/SG for IGF-1
and troglitazone and 4 mice/SG for the control and for the ALT-711
group. Begin the ALT-711 groups on ALT-711 immediately after this
sampling.
At around 27 months (.about.24-30 months): Sample all remaining
surviving SG mice.
If the total initial numbers of mice in the sacrifice groups for
treatments 1, 2, 3, and 4 are 30, 50, 50, and 30, respectively,
then if there were no mortality in any of these groups, there would
be 20 animals left in each SG at the time of final sampling. But if
we assume that only 1/3 of this number will be alive, then about 7
animals will remain to be sampled at the final sample time, or
about the minimum required for statistical significance. It the
mean survival rate at 27 month is over 73%, the 27 month end point
may be postponed to a greater age.
In addition to other biochemical markers, assays may include: heart
and thymus volume and histology; autoantibody titer, T and B cell
characteristics; protein or albumin concentration in bladder urine
at sacrifice; molecular glycation indices; protein carbonyl content
or other free radical/oxidation indices; and incidence of
neoplasia, esp. of prostate and breast.
* * * * *
References